Revert "remove function closure"

This reverts commit 55d48c6ed17abe42e7a122e69d603ef0c1506787.

path/to/venv/bin/Activate.ps1

@@ -1,247 +0,0 @@
-<#
-.Synopsis
-Activate a Python virtual environment for the current PowerShell session.
-
-.Description
-Pushes the python executable for a virtual environment to the front of the
-$Env:PATH environment variable and sets the prompt to signify that you are
-in a Python virtual environment. Makes use of the command line switches as
-well as the `pyvenv.cfg` file values present in the virtual environment.
-
-.Parameter VenvDir
-Path to the directory that contains the virtual environment to activate. The
-default value for this is the parent of the directory that the Activate.ps1
-script is located within.
-
-.Parameter Prompt
-The prompt prefix to display when this virtual environment is activated. By
-default, this prompt is the name of the virtual environment folder (VenvDir)
-surrounded by parentheses and followed by a single space (ie. '(.venv) ').
-
-.Example
-Activate.ps1
-Activates the Python virtual environment that contains the Activate.ps1 script.
-
-.Example
-Activate.ps1 -Verbose
-Activates the Python virtual environment that contains the Activate.ps1 script,
-and shows extra information about the activation as it executes.
-
-.Example
-Activate.ps1 -VenvDir C:\Users\MyUser\Common\.venv
-Activates the Python virtual environment located in the specified location.
-
-.Example
-Activate.ps1 -Prompt "MyPython"
-Activates the Python virtual environment that contains the Activate.ps1 script,
-and prefixes the current prompt with the specified string (surrounded in
-parentheses) while the virtual environment is active.
-
-.Notes
-On Windows, it may be required to enable this Activate.ps1 script by setting the
-execution policy for the user. You can do this by issuing the following PowerShell
-command:
-
-PS C:\> Set-ExecutionPolicy -ExecutionPolicy RemoteSigned -Scope CurrentUser
-
-For more information on Execution Policies: 
-https://go.microsoft.com/fwlink/?LinkID=135170
-
-#>
-Param(
-    [Parameter(Mandatory = $false)]
-    [String]
-    $VenvDir,
-    [Parameter(Mandatory = $false)]
-    [String]
-    $Prompt
-)
-
-<# Function declarations --------------------------------------------------- #>
-
-<#
-.Synopsis
-Remove all shell session elements added by the Activate script, including the
-addition of the virtual environment's Python executable from the beginning of
-the PATH variable.
-
-.Parameter NonDestructive
-If present, do not remove this function from the global namespace for the
-session.
-
-#>
-function global:deactivate ([switch]$NonDestructive) {
-    # Revert to original values
-
-    # The prior prompt:
-    if (Test-Path -Path Function:_OLD_VIRTUAL_PROMPT) {
-        Copy-Item -Path Function:_OLD_VIRTUAL_PROMPT -Destination Function:prompt
-        Remove-Item -Path Function:_OLD_VIRTUAL_PROMPT
-    }
-
-    # The prior PYTHONHOME:
-    if (Test-Path -Path Env:_OLD_VIRTUAL_PYTHONHOME) {
-        Copy-Item -Path Env:_OLD_VIRTUAL_PYTHONHOME -Destination Env:PYTHONHOME
-        Remove-Item -Path Env:_OLD_VIRTUAL_PYTHONHOME
-    }
-
-    # The prior PATH:
-    if (Test-Path -Path Env:_OLD_VIRTUAL_PATH) {
-        Copy-Item -Path Env:_OLD_VIRTUAL_PATH -Destination Env:PATH
-        Remove-Item -Path Env:_OLD_VIRTUAL_PATH
-    }
-
-    # Just remove the VIRTUAL_ENV altogether:
-    if (Test-Path -Path Env:VIRTUAL_ENV) {
-        Remove-Item -Path env:VIRTUAL_ENV
-    }
-
-    # Just remove VIRTUAL_ENV_PROMPT altogether.
-    if (Test-Path -Path Env:VIRTUAL_ENV_PROMPT) {
-        Remove-Item -Path env:VIRTUAL_ENV_PROMPT
-    }
-
-    # Just remove the _PYTHON_VENV_PROMPT_PREFIX altogether:
-    if (Get-Variable -Name "_PYTHON_VENV_PROMPT_PREFIX" -ErrorAction SilentlyContinue) {
-        Remove-Variable -Name _PYTHON_VENV_PROMPT_PREFIX -Scope Global -Force
-    }
-
-    # Leave deactivate function in the global namespace if requested:
-    if (-not $NonDestructive) {
-        Remove-Item -Path function:deactivate
-    }
-}
-
-<#
-.Description
-Get-PyVenvConfig parses the values from the pyvenv.cfg file located in the
-given folder, and returns them in a map.
-
-For each line in the pyvenv.cfg file, if that line can be parsed into exactly
-two strings separated by `=` (with any amount of whitespace surrounding the =)
-then it is considered a `key = value` line. The left hand string is the key,
-the right hand is the value.
-
-If the value starts with a `'` or a `"` then the first and last character is
-stripped from the value before being captured.
-
-.Parameter ConfigDir
-Path to the directory that contains the `pyvenv.cfg` file.
-#>
-function Get-PyVenvConfig(
-    [String]
-    $ConfigDir
-) {
-    Write-Verbose "Given ConfigDir=$ConfigDir, obtain values in pyvenv.cfg"
-
-    # Ensure the file exists, and issue a warning if it doesn't (but still allow the function to continue).
-    $pyvenvConfigPath = Join-Path -Resolve -Path $ConfigDir -ChildPath 'pyvenv.cfg' -ErrorAction Continue
-
-    # An empty map will be returned if no config file is found.
-    $pyvenvConfig = @{ }
-
-    if ($pyvenvConfigPath) {
-
-        Write-Verbose "File exists, parse `key = value` lines"
-        $pyvenvConfigContent = Get-Content -Path $pyvenvConfigPath
-
-        $pyvenvConfigContent | ForEach-Object {
-            $keyval = $PSItem -split "\s*=\s*", 2
-            if ($keyval[0] -and $keyval[1]) {
-                $val = $keyval[1]
-
-                # Remove extraneous quotations around a string value.
-                if ("'""".Contains($val.Substring(0, 1))) {
-                    $val = $val.Substring(1, $val.Length - 2)
-                }
-
-                $pyvenvConfig[$keyval[0]] = $val
-                Write-Verbose "Adding Key: '$($keyval[0])'='$val'"
-            }
-        }
-    }
-    return $pyvenvConfig
-}
-
-
-<# Begin Activate script --------------------------------------------------- #>
-
-# Determine the containing directory of this script
-$VenvExecPath = Split-Path -Parent $MyInvocation.MyCommand.Definition
-$VenvExecDir = Get-Item -Path $VenvExecPath
-
-Write-Verbose "Activation script is located in path: '$VenvExecPath'"
-Write-Verbose "VenvExecDir Fullname: '$($VenvExecDir.FullName)"
-Write-Verbose "VenvExecDir Name: '$($VenvExecDir.Name)"
-
-# Set values required in priority: CmdLine, ConfigFile, Default
-# First, get the location of the virtual environment, it might not be
-# VenvExecDir if specified on the command line.
-if ($VenvDir) {
-    Write-Verbose "VenvDir given as parameter, using '$VenvDir' to determine values"
-}
-else {
-    Write-Verbose "VenvDir not given as a parameter, using parent directory name as VenvDir."
-    $VenvDir = $VenvExecDir.Parent.FullName.TrimEnd("\\/")
-    Write-Verbose "VenvDir=$VenvDir"
-}
-
-# Next, read the `pyvenv.cfg` file to determine any required value such
-# as `prompt`.
-$pyvenvCfg = Get-PyVenvConfig -ConfigDir $VenvDir
-
-# Next, set the prompt from the command line, or the config file, or
-# just use the name of the virtual environment folder.
-if ($Prompt) {
-    Write-Verbose "Prompt specified as argument, using '$Prompt'"
-}
-else {
-    Write-Verbose "Prompt not specified as argument to script, checking pyvenv.cfg value"
-    if ($pyvenvCfg -and $pyvenvCfg['prompt']) {
-        Write-Verbose "  Setting based on value in pyvenv.cfg='$($pyvenvCfg['prompt'])'"
-        $Prompt = $pyvenvCfg['prompt'];
-    }
-    else {
-        Write-Verbose "  Setting prompt based on parent's directory's name. (Is the directory name passed to venv module when creating the virtual environment)"
-        Write-Verbose "  Got leaf-name of $VenvDir='$(Split-Path -Path $venvDir -Leaf)'"
-        $Prompt = Split-Path -Path $venvDir -Leaf
-    }
-}
-
-Write-Verbose "Prompt = '$Prompt'"
-Write-Verbose "VenvDir='$VenvDir'"
-
-# Deactivate any currently active virtual environment, but leave the
-# deactivate function in place.
-deactivate -nondestructive
-
-# Now set the environment variable VIRTUAL_ENV, used by many tools to determine
-# that there is an activated venv.
-$env:VIRTUAL_ENV = $VenvDir
-
-if (-not $Env:VIRTUAL_ENV_DISABLE_PROMPT) {
-
-    Write-Verbose "Setting prompt to '$Prompt'"
-
-    # Set the prompt to include the env name
-    # Make sure _OLD_VIRTUAL_PROMPT is global
-    function global:_OLD_VIRTUAL_PROMPT { "" }
-    Copy-Item -Path function:prompt -Destination function:_OLD_VIRTUAL_PROMPT
-    New-Variable -Name _PYTHON_VENV_PROMPT_PREFIX -Description "Python virtual environment prompt prefix" -Scope Global -Option ReadOnly -Visibility Public -Value $Prompt
-
-    function global:prompt {
-        Write-Host -NoNewline -ForegroundColor Green "($_PYTHON_VENV_PROMPT_PREFIX) "
-        _OLD_VIRTUAL_PROMPT
-    }
-    $env:VIRTUAL_ENV_PROMPT = $Prompt
-}
-
-# Clear PYTHONHOME
-if (Test-Path -Path Env:PYTHONHOME) {
-    Copy-Item -Path Env:PYTHONHOME -Destination Env:_OLD_VIRTUAL_PYTHONHOME
-    Remove-Item -Path Env:PYTHONHOME
-}
-
-# Add the venv to the PATH
-Copy-Item -Path Env:PATH -Destination Env:_OLD_VIRTUAL_PATH
-$Env:PATH = "$VenvExecDir$([System.IO.Path]::PathSeparator)$Env:PATH"

path/to/venv/bin/activate

@@ -1,70 +0,0 @@
-# This file must be used with "source bin/activate" *from bash*
-# You cannot run it directly
-
-deactivate () {
-    # reset old environment variables
-    if [ -n "${_OLD_VIRTUAL_PATH:-}" ] ; then
-        PATH="${_OLD_VIRTUAL_PATH:-}"
-        export PATH
-        unset _OLD_VIRTUAL_PATH
-    fi
-    if [ -n "${_OLD_VIRTUAL_PYTHONHOME:-}" ] ; then
-        PYTHONHOME="${_OLD_VIRTUAL_PYTHONHOME:-}"
-        export PYTHONHOME
-        unset _OLD_VIRTUAL_PYTHONHOME
-    fi
-
-    # Call hash to forget past commands. Without forgetting
-    # past commands the $PATH changes we made may not be respected
-    hash -r 2> /dev/null
-
-    if [ -n "${_OLD_VIRTUAL_PS1:-}" ] ; then
-        PS1="${_OLD_VIRTUAL_PS1:-}"
-        export PS1
-        unset _OLD_VIRTUAL_PS1
-    fi
-
-    unset VIRTUAL_ENV
-    unset VIRTUAL_ENV_PROMPT
-    if [ ! "${1:-}" = "nondestructive" ] ; then
-    # Self destruct!
-        unset -f deactivate
-    fi
-}
-
-# unset irrelevant variables
-deactivate nondestructive
-
-# on Windows, a path can contain colons and backslashes and has to be converted:
-if [ "${OSTYPE:-}" = "cygwin" ] || [ "${OSTYPE:-}" = "msys" ] ; then
-    # transform D:\path\to\venv to /d/path/to/venv on MSYS
-    # and to /cygdrive/d/path/to/venv on Cygwin
-    export VIRTUAL_ENV=$(cygpath "/Users/royhan-ollama/ollama/path/to/venv")
-else
-    # use the path as-is
-    export VIRTUAL_ENV="/Users/royhan-ollama/ollama/path/to/venv"
-fi
-
-_OLD_VIRTUAL_PATH="$PATH"
-PATH="$VIRTUAL_ENV/bin:$PATH"
-export PATH
-
-# unset PYTHONHOME if set
-# this will fail if PYTHONHOME is set to the empty string (which is bad anyway)
-# could use `if (set -u; : $PYTHONHOME) ;` in bash
-if [ -n "${PYTHONHOME:-}" ] ; then
-    _OLD_VIRTUAL_PYTHONHOME="${PYTHONHOME:-}"
-    unset PYTHONHOME
-fi
-
-if [ -z "${VIRTUAL_ENV_DISABLE_PROMPT:-}" ] ; then
-    _OLD_VIRTUAL_PS1="${PS1:-}"
-    PS1="(venv) ${PS1:-}"
-    export PS1
-    VIRTUAL_ENV_PROMPT="(venv) "
-    export VIRTUAL_ENV_PROMPT
-fi
-
-# Call hash to forget past commands. Without forgetting
-# past commands the $PATH changes we made may not be respected
-hash -r 2> /dev/null

path/to/venv/bin/activate.csh

@@ -1,27 +0,0 @@
-# This file must be used with "source bin/activate.csh" *from csh*.
-# You cannot run it directly.
-
-# Created by Davide Di Blasi <davidedb@gmail.com>.
-# Ported to Python 3.3 venv by Andrew Svetlov <andrew.svetlov@gmail.com>
-
-alias deactivate 'test $?_OLD_VIRTUAL_PATH != 0 && setenv PATH "$_OLD_VIRTUAL_PATH" && unset _OLD_VIRTUAL_PATH; rehash; test $?_OLD_VIRTUAL_PROMPT != 0 && set prompt="$_OLD_VIRTUAL_PROMPT" && unset _OLD_VIRTUAL_PROMPT; unsetenv VIRTUAL_ENV; unsetenv VIRTUAL_ENV_PROMPT; test "\!:*" != "nondestructive" && unalias deactivate'
-
-# Unset irrelevant variables.
-deactivate nondestructive
-
-setenv VIRTUAL_ENV "/Users/royhan-ollama/ollama/path/to/venv"
-
-set _OLD_VIRTUAL_PATH="$PATH"
-setenv PATH "$VIRTUAL_ENV/bin:$PATH"
-
-
-set _OLD_VIRTUAL_PROMPT="$prompt"
-
-if (! "$?VIRTUAL_ENV_DISABLE_PROMPT") then
-    set prompt = "(venv) $prompt"
-    setenv VIRTUAL_ENV_PROMPT "(venv) "
-endif
-
-alias pydoc python -m pydoc
-
-rehash

path/to/venv/bin/activate.fish

@@ -1,69 +0,0 @@
-# This file must be used with "source <venv>/bin/activate.fish" *from fish*
-# (https://fishshell.com/). You cannot run it directly.
-
-function deactivate  -d "Exit virtual environment and return to normal shell environment"
-    # reset old environment variables
-    if test -n "$_OLD_VIRTUAL_PATH"
-        set -gx PATH $_OLD_VIRTUAL_PATH
-        set -e _OLD_VIRTUAL_PATH
-    end
-    if test -n "$_OLD_VIRTUAL_PYTHONHOME"
-        set -gx PYTHONHOME $_OLD_VIRTUAL_PYTHONHOME
-        set -e _OLD_VIRTUAL_PYTHONHOME
-    end
-
-    if test -n "$_OLD_FISH_PROMPT_OVERRIDE"
-        set -e _OLD_FISH_PROMPT_OVERRIDE
-        # prevents error when using nested fish instances (Issue #93858)
-        if functions -q _old_fish_prompt
-            functions -e fish_prompt
-            functions -c _old_fish_prompt fish_prompt
-            functions -e _old_fish_prompt
-        end
-    end
-
-    set -e VIRTUAL_ENV
-    set -e VIRTUAL_ENV_PROMPT
-    if test "$argv[1]" != "nondestructive"
-        # Self-destruct!
-        functions -e deactivate
-    end
-end
-
-# Unset irrelevant variables.
-deactivate nondestructive
-
-set -gx VIRTUAL_ENV "/Users/royhan-ollama/ollama/path/to/venv"
-
-set -gx _OLD_VIRTUAL_PATH $PATH
-set -gx PATH "$VIRTUAL_ENV/bin" $PATH
-
-# Unset PYTHONHOME if set.
-if set -q PYTHONHOME
-    set -gx _OLD_VIRTUAL_PYTHONHOME $PYTHONHOME
-    set -e PYTHONHOME
-end
-
-if test -z "$VIRTUAL_ENV_DISABLE_PROMPT"
-    # fish uses a function instead of an env var to generate the prompt.
-
-    # Save the current fish_prompt function as the function _old_fish_prompt.
-    functions -c fish_prompt _old_fish_prompt
-
-    # With the original prompt function renamed, we can override with our own.
-    function fish_prompt
-        # Save the return status of the last command.
-        set -l old_status $status
-
-        # Output the venv prompt; color taken from the blue of the Python logo.
-        printf "%s%s%s" (set_color 4B8BBE) "(venv) " (set_color normal)
-
-        # Restore the return status of the previous command.
-        echo "exit $old_status" | .
-        # Output the original/"old" prompt.
-        _old_fish_prompt
-    end
-
-    set -gx _OLD_FISH_PROMPT_OVERRIDE "$VIRTUAL_ENV"
-    set -gx VIRTUAL_ENV_PROMPT "(venv) "
-end

path/to/venv/bin/normalizer

@@ -1,8 +0,0 @@
-#!/Users/royhan-ollama/ollama/path/to/venv/bin/python3.12
-# -*- coding: utf-8 -*-
-import re
-import sys
-from charset_normalizer.cli import cli_detect
-if __name__ == '__main__':
-    sys.argv[0] = re.sub(r'(-script\.pyw|\.exe)?$', '', sys.argv[0])
-    sys.exit(cli_detect())

path/to/venv/bin/pip

@@ -1,8 +0,0 @@
-#!/Users/royhan-ollama/ollama/path/to/venv/bin/python3.12
-# -*- coding: utf-8 -*-
-import re
-import sys
-from pip._internal.cli.main import main
-if __name__ == '__main__':
-    sys.argv[0] = re.sub(r'(-script\.pyw|\.exe)?$', '', sys.argv[0])
-    sys.exit(main())

path/to/venv/bin/pip3

@@ -1,8 +0,0 @@
-#!/Users/royhan-ollama/ollama/path/to/venv/bin/python3.12
-# -*- coding: utf-8 -*-
-import re
-import sys
-from pip._internal.cli.main import main
-if __name__ == '__main__':
-    sys.argv[0] = re.sub(r'(-script\.pyw|\.exe)?$', '', sys.argv[0])
-    sys.exit(main())

path/to/venv/bin/pip3.12

@@ -1,8 +0,0 @@
-#!/Users/royhan-ollama/ollama/path/to/venv/bin/python3.12
-# -*- coding: utf-8 -*-
-import re
-import sys
-from pip._internal.cli.main import main
-if __name__ == '__main__':
-    sys.argv[0] = re.sub(r'(-script\.pyw|\.exe)?$', '', sys.argv[0])
-    sys.exit(main())

path/to/venv/bin/python

@@ -1 +0,0 @@
-python3.12

path/to/venv/bin/python3

@@ -1 +0,0 @@
-python3.12

path/to/venv/bin/python3.12

@@ -1 +0,0 @@
-/opt/homebrew/opt/python@3.12/bin/python3.12

path/to/venv/lib/python3.12/site-packages/certifi-2024.7.4.dist-info/INSTALLER

@@ -1 +0,0 @@
-pip

path/to/venv/lib/python3.12/site-packages/certifi-2024.7.4.dist-info/LICENSE

@@ -1,20 +0,0 @@
-This package contains a modified version of ca-bundle.crt:
-
-ca-bundle.crt -- Bundle of CA Root Certificates
-
-This is a bundle of X.509 certificates of public Certificate Authorities
-(CA). These were automatically extracted from Mozilla's root certificates
-file (certdata.txt).  This file can be found in the mozilla source tree:
-https://hg.mozilla.org/mozilla-central/file/tip/security/nss/lib/ckfw/builtins/certdata.txt
-It contains the certificates in PEM format and therefore
-can be directly used with curl / libcurl / php_curl, or with
-an Apache+mod_ssl webserver for SSL client authentication.
-Just configure this file as the SSLCACertificateFile.#
-
-***** BEGIN LICENSE BLOCK *****
-This Source Code Form is subject to the terms of the Mozilla Public License,
-v. 2.0. If a copy of the MPL was not distributed with this file, You can obtain
-one at http://mozilla.org/MPL/2.0/.
-
-***** END LICENSE BLOCK *****
-@(#) $RCSfile: certdata.txt,v $ $Revision: 1.80 $ $Date: 2011/11/03 15:11:58 $

path/to/venv/lib/python3.12/site-packages/certifi-2024.7.4.dist-info/METADATA

@@ -1,67 +0,0 @@
-Metadata-Version: 2.1
-Name: certifi
-Version: 2024.7.4
-Summary: Python package for providing Mozilla's CA Bundle.
-Home-page: https://github.com/certifi/python-certifi
-Author: Kenneth Reitz
-Author-email: me@kennethreitz.com
-License: MPL-2.0
-Project-URL: Source, https://github.com/certifi/python-certifi
-Classifier: Development Status :: 5 - Production/Stable
-Classifier: Intended Audience :: Developers
-Classifier: License :: OSI Approved :: Mozilla Public License 2.0 (MPL 2.0)
-Classifier: Natural Language :: English
-Classifier: Programming Language :: Python
-Classifier: Programming Language :: Python :: 3
-Classifier: Programming Language :: Python :: 3 :: Only
-Classifier: Programming Language :: Python :: 3.6
-Classifier: Programming Language :: Python :: 3.7
-Classifier: Programming Language :: Python :: 3.8
-Classifier: Programming Language :: Python :: 3.9
-Classifier: Programming Language :: Python :: 3.10
-Classifier: Programming Language :: Python :: 3.11
-Classifier: Programming Language :: Python :: 3.12
-Requires-Python: >=3.6
-License-File: LICENSE
-
-Certifi: Python SSL Certificates
-================================
-
-Certifi provides Mozilla's carefully curated collection of Root Certificates for
-validating the trustworthiness of SSL certificates while verifying the identity
-of TLS hosts. It has been extracted from the `Requests`_ project.
-
-Installation
-------------
-
-``certifi`` is available on PyPI. Simply install it with ``pip``::
-
-    $ pip install certifi
-
-Usage
------
-
-To reference the installed certificate authority (CA) bundle, you can use the
-built-in function::
-
-    >>> import certifi
-
-    >>> certifi.where()
-    '/usr/local/lib/python3.7/site-packages/certifi/cacert.pem'
-
-Or from the command line::
-
-    $ python -m certifi
-    /usr/local/lib/python3.7/site-packages/certifi/cacert.pem
-
-Enjoy!
-
-.. _`Requests`: https://requests.readthedocs.io/en/master/
-
-Addition/Removal of Certificates
---------------------------------
-
-Certifi does not support any addition/removal or other modification of the
-CA trust store content. This project is intended to provide a reliable and
-highly portable root of trust to python deployments. Look to upstream projects
-for methods to use alternate trust.

path/to/venv/lib/python3.12/site-packages/certifi-2024.7.4.dist-info/RECORD

@@ -1,14 +0,0 @@
-certifi-2024.7.4.dist-info/INSTALLER,sha256=zuuue4knoyJ-UwPPXg8fezS7VCrXJQrAP7zeNuwvFQg,4
-certifi-2024.7.4.dist-info/LICENSE,sha256=6TcW2mucDVpKHfYP5pWzcPBpVgPSH2-D8FPkLPwQyvc,989
-certifi-2024.7.4.dist-info/METADATA,sha256=L9_EuPoQQvHFzxu03_ctaEZxhEty7inz569jGWjlLGo,2221
-certifi-2024.7.4.dist-info/RECORD,,
-certifi-2024.7.4.dist-info/WHEEL,sha256=y4mX-SOX4fYIkonsAGA5N0Oy-8_gI4FXw5HNI1xqvWg,91
-certifi-2024.7.4.dist-info/top_level.txt,sha256=KMu4vUCfsjLrkPbSNdgdekS-pVJzBAJFO__nI8NF6-U,8
-certifi/__init__.py,sha256=LHXz7E80YJYBzCBv6ZyidQ5-ciYSkSebpY2E5OM0l7o,94
-certifi/__main__.py,sha256=xBBoj905TUWBLRGANOcf7oi6e-3dMP4cEoG9OyMs11g,243
-certifi/__pycache__/__init__.cpython-312.pyc,,
-certifi/__pycache__/__main__.cpython-312.pyc,,
-certifi/__pycache__/core.cpython-312.pyc,,
-certifi/cacert.pem,sha256=SIupYGAr8HzGP073rsEIaS_sQYIPwzKKjj894DgUmu4,291528
-certifi/core.py,sha256=qRDDFyXVJwTB_EmoGppaXU_R9qCZvhl-EzxPMuV3nTA,4426
-certifi/py.typed,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0

path/to/venv/lib/python3.12/site-packages/certifi-2024.7.4.dist-info/WHEEL

@@ -1,5 +0,0 @@
-Wheel-Version: 1.0
-Generator: setuptools (70.2.0)
-Root-Is-Purelib: true
-Tag: py3-none-any
-

path/to/venv/lib/python3.12/site-packages/certifi-2024.7.4.dist-info/top_level.txt

@@ -1 +0,0 @@
-certifi

path/to/venv/lib/python3.12/site-packages/certifi/__init__.py

@@ -1,4 +0,0 @@
-from .core import contents, where
-
-__all__ = ["contents", "where"]
-__version__ = "2024.07.04"

path/to/venv/lib/python3.12/site-packages/certifi/__main__.py

@@ -1,12 +0,0 @@
-import argparse
-
-from certifi import contents, where
-
-parser = argparse.ArgumentParser()
-parser.add_argument("-c", "--contents", action="store_true")
-args = parser.parse_args()
-
-if args.contents:
-    print(contents())
-else:
-    print(where())

path/to/venv/lib/python3.12/site-packages/certifi/cacert.pem

@@ -1,4798 +0,0 @@
-
-# Issuer: CN=GlobalSign Root CA O=GlobalSign nv-sa OU=Root CA
-# Subject: CN=GlobalSign Root CA O=GlobalSign nv-sa OU=Root CA
-# Label: "GlobalSign Root CA"
-# Serial: 4835703278459707669005204
-# MD5 Fingerprint: 3e:45:52:15:09:51:92:e1:b7:5d:37:9f:b1:87:29:8a
-# SHA1 Fingerprint: b1:bc:96:8b:d4:f4:9d:62:2a:a8:9a:81:f2:15:01:52:a4:1d:82:9c
-# SHA256 Fingerprint: eb:d4:10:40:e4:bb:3e:c7:42:c9:e3:81:d3:1e:f2:a4:1a:48:b6:68:5c:96:e7:ce:f3:c1:df:6c:d4:33:1c:99
------BEGIN CERTIFICATE-----
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-HMUfpIBvFSDJ3gyICh3WZlXi/EjJKSZp4A==
------END CERTIFICATE-----
-
-# Issuer: CN=Entrust.net Certification Authority (2048) O=Entrust.net OU=www.entrust.net/CPS_2048 incorp. by ref. (limits liab.)/(c) 1999 Entrust.net Limited
-# Subject: CN=Entrust.net Certification Authority (2048) O=Entrust.net OU=www.entrust.net/CPS_2048 incorp. by ref. (limits liab.)/(c) 1999 Entrust.net Limited
-# Label: "Entrust.net Premium 2048 Secure Server CA"
-# Serial: 946069240
-# MD5 Fingerprint: ee:29:31:bc:32:7e:9a:e6:e8:b5:f7:51:b4:34:71:90
-# SHA1 Fingerprint: 50:30:06:09:1d:97:d4:f5:ae:39:f7:cb:e7:92:7d:7d:65:2d:34:31
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------BEGIN CERTIFICATE-----
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------END CERTIFICATE-----
-
-# Issuer: CN=Baltimore CyberTrust Root O=Baltimore OU=CyberTrust
-# Subject: CN=Baltimore CyberTrust Root O=Baltimore OU=CyberTrust
-# Label: "Baltimore CyberTrust Root"
-# Serial: 33554617
-# MD5 Fingerprint: ac:b6:94:a5:9c:17:e0:d7:91:52:9b:b1:97:06:a6:e4
-# SHA1 Fingerprint: d4:de:20:d0:5e:66:fc:53:fe:1a:50:88:2c:78:db:28:52:ca:e4:74
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------BEGIN CERTIFICATE-----
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------END CERTIFICATE-----
-
-# Issuer: CN=Entrust Root Certification Authority O=Entrust, Inc. OU=www.entrust.net/CPS is incorporated by reference/(c) 2006 Entrust, Inc.
-# Subject: CN=Entrust Root Certification Authority O=Entrust, Inc. OU=www.entrust.net/CPS is incorporated by reference/(c) 2006 Entrust, Inc.
-# Label: "Entrust Root Certification Authority"
-# Serial: 1164660820
-# MD5 Fingerprint: d6:a5:c3:ed:5d:dd:3e:00:c1:3d:87:92:1f:1d:3f:e4
-# SHA1 Fingerprint: b3:1e:b1:b7:40:e3:6c:84:02:da:dc:37:d4:4d:f5:d4:67:49:52:f9
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------BEGIN CERTIFICATE-----
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------END CERTIFICATE-----
-
-# Issuer: CN=AAA Certificate Services O=Comodo CA Limited
-# Subject: CN=AAA Certificate Services O=Comodo CA Limited
-# Label: "Comodo AAA Services root"
-# Serial: 1
-# MD5 Fingerprint: 49:79:04:b0:eb:87:19:ac:47:b0:bc:11:51:9b:74:d0
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------END CERTIFICATE-----
-
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-# Subject: CN=QuoVadis Root CA 2 O=QuoVadis Limited
-# Label: "QuoVadis Root CA 2"
-# Serial: 1289
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------BEGIN CERTIFICATE-----
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------END CERTIFICATE-----
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------BEGIN CERTIFICATE-----
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------END CERTIFICATE-----
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-# Issuer: CN=DigiCert Assured ID Root CA O=DigiCert Inc OU=www.digicert.com
-# Subject: CN=DigiCert Assured ID Root CA O=DigiCert Inc OU=www.digicert.com
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------BEGIN CERTIFICATE-----
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-# Issuer: CN=DigiCert Global Root CA O=DigiCert Inc OU=www.digicert.com
-# Subject: CN=DigiCert Global Root CA O=DigiCert Inc OU=www.digicert.com
-# Label: "DigiCert Global Root CA"
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------BEGIN CERTIFICATE-----
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-# Issuer: CN=DigiCert High Assurance EV Root CA O=DigiCert Inc OU=www.digicert.com
-# Subject: CN=DigiCert High Assurance EV Root CA O=DigiCert Inc OU=www.digicert.com
-# Label: "DigiCert High Assurance EV Root CA"
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------BEGIN CERTIFICATE-----
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-# Issuer: CN=SwissSign Gold CA - G2 O=SwissSign AG
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-# Label: "SwissSign Gold CA - G2"
-# Serial: 13492815561806991280
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------BEGIN CERTIFICATE-----
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-# Issuer: CN=SwissSign Silver CA - G2 O=SwissSign AG
-# Subject: CN=SwissSign Silver CA - G2 O=SwissSign AG
-# Label: "SwissSign Silver CA - G2"
-# Serial: 5700383053117599563
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------BEGIN CERTIFICATE-----
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------END CERTIFICATE-----
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-# Issuer: CN=SecureTrust CA O=SecureTrust Corporation
-# Subject: CN=SecureTrust CA O=SecureTrust Corporation
-# Label: "SecureTrust CA"
-# Serial: 17199774589125277788362757014266862032
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------BEGIN CERTIFICATE-----
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------END CERTIFICATE-----
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-# Issuer: CN=Secure Global CA O=SecureTrust Corporation
-# Subject: CN=Secure Global CA O=SecureTrust Corporation
-# Label: "Secure Global CA"
-# Serial: 9751836167731051554232119481456978597
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------BEGIN CERTIFICATE-----
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-# Issuer: CN=COMODO Certification Authority O=COMODO CA Limited
-# Subject: CN=COMODO Certification Authority O=COMODO CA Limited
-# Label: "COMODO Certification Authority"
-# Serial: 104350513648249232941998508985834464573
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------BEGIN CERTIFICATE-----
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------END CERTIFICATE-----
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-# Issuer: CN=COMODO ECC Certification Authority O=COMODO CA Limited
-# Subject: CN=COMODO ECC Certification Authority O=COMODO CA Limited
-# Label: "COMODO ECC Certification Authority"
-# Serial: 41578283867086692638256921589707938090
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-# Issuer: CN=Certigna O=Dhimyotis
-# Subject: CN=Certigna O=Dhimyotis
-# Label: "Certigna"
-# Serial: 18364802974209362175
-# MD5 Fingerprint: ab:57:a6:5b:7d:42:82:19:b5:d8:58:26:28:5e:fd:ff
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------BEGIN CERTIFICATE-----
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------END CERTIFICATE-----
-
-# Issuer: O=Chunghwa Telecom Co., Ltd. OU=ePKI Root Certification Authority
-# Subject: O=Chunghwa Telecom Co., Ltd. OU=ePKI Root Certification Authority
-# Label: "ePKI Root Certification Authority"
-# Serial: 28956088682735189655030529057352760477
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------BEGIN CERTIFICATE-----
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------END CERTIFICATE-----
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-# Issuer: O=certSIGN OU=certSIGN ROOT CA
-# Subject: O=certSIGN OU=certSIGN ROOT CA
-# Label: "certSIGN ROOT CA"
-# Serial: 35210227249154
-# MD5 Fingerprint: 18:98:c0:d6:e9:3a:fc:f9:b0:f5:0c:f7:4b:01:44:17
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------BEGIN CERTIFICATE-----
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------END CERTIFICATE-----
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-# Issuer: CN=NetLock Arany (Class Gold) F\u0151tan\xfas\xedtv\xe1ny O=NetLock Kft. OU=Tan\xfas\xedtv\xe1nykiad\xf3k (Certification Services)
-# Subject: CN=NetLock Arany (Class Gold) F\u0151tan\xfas\xedtv\xe1ny O=NetLock Kft. OU=Tan\xfas\xedtv\xe1nykiad\xf3k (Certification Services)
-# Label: "NetLock Arany (Class Gold) F\u0151tan\xfas\xedtv\xe1ny"
-# Serial: 80544274841616
-# MD5 Fingerprint: c5:a1:b7:ff:73:dd:d6:d7:34:32:18:df:fc:3c:ad:88
-# SHA1 Fingerprint: 06:08:3f:59:3f:15:a1:04:a0:69:a4:6b:a9:03:d0:06:b7:97:09:91
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------BEGIN CERTIFICATE-----
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-# Subject: CN=Actalis Authentication Root CA O=Actalis S.p.A./03358520967
-# Label: "Actalis Authentication Root CA"
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-# Issuer: CN=Buypass Class 2 Root CA O=Buypass AS-983163327
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-# Issuer: CN=Buypass Class 3 Root CA O=Buypass AS-983163327
-# Subject: CN=Buypass Class 3 Root CA O=Buypass AS-983163327
-# Label: "Buypass Class 3 Root CA"
-# Serial: 2
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------BEGIN CERTIFICATE-----
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------END CERTIFICATE-----
-
-# Issuer: CN=T-TeleSec GlobalRoot Class 3 O=T-Systems Enterprise Services GmbH OU=T-Systems Trust Center
-# Subject: CN=T-TeleSec GlobalRoot Class 3 O=T-Systems Enterprise Services GmbH OU=T-Systems Trust Center
-# Label: "T-TeleSec GlobalRoot Class 3"
-# Serial: 1
-# MD5 Fingerprint: ca:fb:40:a8:4e:39:92:8a:1d:fe:8e:2f:c4:27:ea:ef
-# SHA1 Fingerprint: 55:a6:72:3e:cb:f2:ec:cd:c3:23:74:70:19:9d:2a:be:11:e3:81:d1
-# SHA256 Fingerprint: fd:73:da:d3:1c:64:4f:f1:b4:3b:ef:0c:cd:da:96:71:0b:9c:d9:87:5e:ca:7e:31:70:7a:f3:e9:6d:52:2b:bd
------BEGIN CERTIFICATE-----
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------END CERTIFICATE-----
-
-# Issuer: CN=D-TRUST Root Class 3 CA 2 2009 O=D-Trust GmbH
-# Subject: CN=D-TRUST Root Class 3 CA 2 2009 O=D-Trust GmbH
-# Label: "D-TRUST Root Class 3 CA 2 2009"
-# Serial: 623603
-# MD5 Fingerprint: cd:e0:25:69:8d:47:ac:9c:89:35:90:f7:fd:51:3d:2f
-# SHA1 Fingerprint: 58:e8:ab:b0:36:15:33:fb:80:f7:9b:1b:6d:29:d3:ff:8d:5f:00:f0
-# SHA256 Fingerprint: 49:e7:a4:42:ac:f0:ea:62:87:05:00:54:b5:25:64:b6:50:e4:f4:9e:42:e3:48:d6:aa:38:e0:39:e9:57:b1:c1
------BEGIN CERTIFICATE-----
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------END CERTIFICATE-----
-
-# Issuer: CN=D-TRUST Root Class 3 CA 2 EV 2009 O=D-Trust GmbH
-# Subject: CN=D-TRUST Root Class 3 CA 2 EV 2009 O=D-Trust GmbH
-# Label: "D-TRUST Root Class 3 CA 2 EV 2009"
-# Serial: 623604
-# MD5 Fingerprint: aa:c6:43:2c:5e:2d:cd:c4:34:c0:50:4f:11:02:4f:b6
-# SHA1 Fingerprint: 96:c9:1b:0b:95:b4:10:98:42:fa:d0:d8:22:79:fe:60:fa:b9:16:83
-# SHA256 Fingerprint: ee:c5:49:6b:98:8c:e9:86:25:b9:34:09:2e:ec:29:08:be:d0:b0:f3:16:c2:d4:73:0c:84:ea:f1:f3:d3:48:81
------BEGIN CERTIFICATE-----
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------END CERTIFICATE-----
-
-# Issuer: CN=CA Disig Root R2 O=Disig a.s.
-# Subject: CN=CA Disig Root R2 O=Disig a.s.
-# Label: "CA Disig Root R2"
-# Serial: 10572350602393338211
-# MD5 Fingerprint: 26:01:fb:d8:27:a7:17:9a:45:54:38:1a:43:01:3b:03
-# SHA1 Fingerprint: b5:61:eb:ea:a4:de:e4:25:4b:69:1a:98:a5:57:47:c2:34:c7:d9:71
-# SHA256 Fingerprint: e2:3d:4a:03:6d:7b:70:e9:f5:95:b1:42:20:79:d2:b9:1e:df:bb:1f:b6:51:a0:63:3e:aa:8a:9d:c5:f8:07:03
------BEGIN CERTIFICATE-----
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------END CERTIFICATE-----
-
-# Issuer: CN=ACCVRAIZ1 O=ACCV OU=PKIACCV
-# Subject: CN=ACCVRAIZ1 O=ACCV OU=PKIACCV
-# Label: "ACCVRAIZ1"
-# Serial: 6828503384748696800
-# MD5 Fingerprint: d0:a0:5a:ee:05:b6:09:94:21:a1:7d:f1:b2:29:82:02
-# SHA1 Fingerprint: 93:05:7a:88:15:c6:4f:ce:88:2f:fa:91:16:52:28:78:bc:53:64:17
-# SHA256 Fingerprint: 9a:6e:c0:12:e1:a7:da:9d:be:34:19:4d:47:8a:d7:c0:db:18:22:fb:07:1d:f1:29:81:49:6e:d1:04:38:41:13
------BEGIN CERTIFICATE-----
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------END CERTIFICATE-----
-
-# Issuer: CN=TWCA Global Root CA O=TAIWAN-CA OU=Root CA
-# Subject: CN=TWCA Global Root CA O=TAIWAN-CA OU=Root CA
-# Label: "TWCA Global Root CA"
-# Serial: 3262
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------BEGIN CERTIFICATE-----
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------END CERTIFICATE-----
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-# Issuer: CN=TeliaSonera Root CA v1 O=TeliaSonera
-# Subject: CN=TeliaSonera Root CA v1 O=TeliaSonera
-# Label: "TeliaSonera Root CA v1"
-# Serial: 199041966741090107964904287217786801558
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------BEGIN CERTIFICATE-----
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------END CERTIFICATE-----
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-# Issuer: CN=T-TeleSec GlobalRoot Class 2 O=T-Systems Enterprise Services GmbH OU=T-Systems Trust Center
-# Subject: CN=T-TeleSec GlobalRoot Class 2 O=T-Systems Enterprise Services GmbH OU=T-Systems Trust Center
-# Label: "T-TeleSec GlobalRoot Class 2"
-# Serial: 1
-# MD5 Fingerprint: 2b:9b:9e:e4:7b:6c:1f:00:72:1a:cc:c1:77:79:df:6a
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------BEGIN CERTIFICATE-----
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------END CERTIFICATE-----
-
-# Issuer: CN=Atos TrustedRoot 2011 O=Atos
-# Subject: CN=Atos TrustedRoot 2011 O=Atos
-# Label: "Atos TrustedRoot 2011"
-# Serial: 6643877497813316402
-# MD5 Fingerprint: ae:b9:c4:32:4b:ac:7f:5d:66:cc:77:94:bb:2a:77:56
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------BEGIN CERTIFICATE-----
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------END CERTIFICATE-----
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-# Issuer: CN=QuoVadis Root CA 1 G3 O=QuoVadis Limited
-# Subject: CN=QuoVadis Root CA 1 G3 O=QuoVadis Limited
-# Label: "QuoVadis Root CA 1 G3"
-# Serial: 687049649626669250736271037606554624078720034195
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-# SHA1 Fingerprint: 1b:8e:ea:57:96:29:1a:c9:39:ea:b8:0a:81:1a:73:73:c0:93:79:67
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------BEGIN CERTIFICATE-----
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------END CERTIFICATE-----
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-# Issuer: CN=QuoVadis Root CA 2 G3 O=QuoVadis Limited
-# Subject: CN=QuoVadis Root CA 2 G3 O=QuoVadis Limited
-# Label: "QuoVadis Root CA 2 G3"
-# Serial: 390156079458959257446133169266079962026824725800
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------BEGIN CERTIFICATE-----
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-# Subject: CN=QuoVadis Root CA 3 G3 O=QuoVadis Limited
-# Label: "QuoVadis Root CA 3 G3"
-# Serial: 268090761170461462463995952157327242137089239581
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------BEGIN CERTIFICATE-----
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------END CERTIFICATE-----
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-# Issuer: CN=DigiCert Assured ID Root G2 O=DigiCert Inc OU=www.digicert.com
-# Subject: CN=DigiCert Assured ID Root G2 O=DigiCert Inc OU=www.digicert.com
-# Label: "DigiCert Assured ID Root G2"
-# Serial: 15385348160840213938643033620894905419
-# MD5 Fingerprint: 92:38:b9:f8:63:24:82:65:2c:57:33:e6:fe:81:8f:9d
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------BEGIN CERTIFICATE-----
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------END CERTIFICATE-----
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-# Issuer: CN=DigiCert Assured ID Root G3 O=DigiCert Inc OU=www.digicert.com
-# Subject: CN=DigiCert Assured ID Root G3 O=DigiCert Inc OU=www.digicert.com
-# Label: "DigiCert Assured ID Root G3"
-# Serial: 15459312981008553731928384953135426796
-# MD5 Fingerprint: 7c:7f:65:31:0c:81:df:8d:ba:3e:99:e2:5c:ad:6e:fb
-# SHA1 Fingerprint: f5:17:a2:4f:9a:48:c6:c9:f8:a2:00:26:9f:dc:0f:48:2c:ab:30:89
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------BEGIN CERTIFICATE-----
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------END CERTIFICATE-----
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-# Issuer: CN=DigiCert Global Root G2 O=DigiCert Inc OU=www.digicert.com
-# Subject: CN=DigiCert Global Root G2 O=DigiCert Inc OU=www.digicert.com
-# Label: "DigiCert Global Root G2"
-# Serial: 4293743540046975378534879503202253541
-# MD5 Fingerprint: e4:a6:8a:c8:54:ac:52:42:46:0a:fd:72:48:1b:2a:44
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------BEGIN CERTIFICATE-----
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------END CERTIFICATE-----
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-# Issuer: CN=DigiCert Global Root G3 O=DigiCert Inc OU=www.digicert.com
-# Subject: CN=DigiCert Global Root G3 O=DigiCert Inc OU=www.digicert.com
-# Label: "DigiCert Global Root G3"
-# Serial: 7089244469030293291760083333884364146
-# MD5 Fingerprint: f5:5d:a4:50:a5:fb:28:7e:1e:0f:0d:cc:96:57:56:ca
-# SHA1 Fingerprint: 7e:04:de:89:6a:3e:66:6d:00:e6:87:d3:3f:fa:d9:3b:e8:3d:34:9e
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------BEGIN CERTIFICATE-----
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------END CERTIFICATE-----
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-# Issuer: CN=DigiCert Trusted Root G4 O=DigiCert Inc OU=www.digicert.com
-# Subject: CN=DigiCert Trusted Root G4 O=DigiCert Inc OU=www.digicert.com
-# Label: "DigiCert Trusted Root G4"
-# Serial: 7451500558977370777930084869016614236
-# MD5 Fingerprint: 78:f2:fc:aa:60:1f:2f:b4:eb:c9:37:ba:53:2e:75:49
-# SHA1 Fingerprint: dd:fb:16:cd:49:31:c9:73:a2:03:7d:3f:c8:3a:4d:7d:77:5d:05:e4
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------BEGIN CERTIFICATE-----
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------END CERTIFICATE-----
-
-# Issuer: CN=COMODO RSA Certification Authority O=COMODO CA Limited
-# Subject: CN=COMODO RSA Certification Authority O=COMODO CA Limited
-# Label: "COMODO RSA Certification Authority"
-# Serial: 101909084537582093308941363524873193117
-# MD5 Fingerprint: 1b:31:b0:71:40:36:cc:14:36:91:ad:c4:3e:fd:ec:18
-# SHA1 Fingerprint: af:e5:d2:44:a8:d1:19:42:30:ff:47:9f:e2:f8:97:bb:cd:7a:8c:b4
-# SHA256 Fingerprint: 52:f0:e1:c4:e5:8e:c6:29:29:1b:60:31:7f:07:46:71:b8:5d:7e:a8:0d:5b:07:27:34:63:53:4b:32:b4:02:34
------BEGIN CERTIFICATE-----
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------END CERTIFICATE-----
-
-# Issuer: CN=USERTrust RSA Certification Authority O=The USERTRUST Network
-# Subject: CN=USERTrust RSA Certification Authority O=The USERTRUST Network
-# Label: "USERTrust RSA Certification Authority"
-# Serial: 2645093764781058787591871645665788717
-# MD5 Fingerprint: 1b:fe:69:d1:91:b7:19:33:a3:72:a8:0f:e1:55:e5:b5
-# SHA1 Fingerprint: 2b:8f:1b:57:33:0d:bb:a2:d0:7a:6c:51:f7:0e:e9:0d:da:b9:ad:8e
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------BEGIN CERTIFICATE-----
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------END CERTIFICATE-----
-
-# Issuer: CN=USERTrust ECC Certification Authority O=The USERTRUST Network
-# Subject: CN=USERTrust ECC Certification Authority O=The USERTRUST Network
-# Label: "USERTrust ECC Certification Authority"
-# Serial: 123013823720199481456569720443997572134
-# MD5 Fingerprint: fa:68:bc:d9:b5:7f:ad:fd:c9:1d:06:83:28:cc:24:c1
-# SHA1 Fingerprint: d1:cb:ca:5d:b2:d5:2a:7f:69:3b:67:4d:e5:f0:5a:1d:0c:95:7d:f0
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------BEGIN CERTIFICATE-----
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------END CERTIFICATE-----
-
-# Issuer: CN=GlobalSign O=GlobalSign OU=GlobalSign ECC Root CA - R5
-# Subject: CN=GlobalSign O=GlobalSign OU=GlobalSign ECC Root CA - R5
-# Label: "GlobalSign ECC Root CA - R5"
-# Serial: 32785792099990507226680698011560947931244
-# MD5 Fingerprint: 9f:ad:3b:1c:02:1e:8a:ba:17:74:38:81:0c:a2:bc:08
-# SHA1 Fingerprint: 1f:24:c6:30:cd:a4:18:ef:20:69:ff:ad:4f:dd:5f:46:3a:1b:69:aa
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------BEGIN CERTIFICATE-----
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------END CERTIFICATE-----
-
-# Issuer: CN=IdenTrust Commercial Root CA 1 O=IdenTrust
-# Subject: CN=IdenTrust Commercial Root CA 1 O=IdenTrust
-# Label: "IdenTrust Commercial Root CA 1"
-# Serial: 13298821034946342390520003877796839426
-# MD5 Fingerprint: b3:3e:77:73:75:ee:a0:d3:e3:7e:49:63:49:59:bb:c7
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------BEGIN CERTIFICATE-----
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-# Label: "Entrust Root Certification Authority - G2"
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------BEGIN CERTIFICATE-----
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-# Subject: CN=SZAFIR ROOT CA2 O=Krajowa Izba Rozliczeniowa S.A.
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------END CERTIFICATE-----
-
-# Issuer: CN=Amazon Root CA 1 O=Amazon
-# Subject: CN=Amazon Root CA 1 O=Amazon
-# Label: "Amazon Root CA 1"
-# Serial: 143266978916655856878034712317230054538369994
-# MD5 Fingerprint: 43:c6:bf:ae:ec:fe:ad:2f:18:c6:88:68:30:fc:c8:e6
-# SHA1 Fingerprint: 8d:a7:f9:65:ec:5e:fc:37:91:0f:1c:6e:59:fd:c1:cc:6a:6e:de:16
-# SHA256 Fingerprint: 8e:cd:e6:88:4f:3d:87:b1:12:5b:a3:1a:c3:fc:b1:3d:70:16:de:7f:57:cc:90:4f:e1:cb:97:c6:ae:98:19:6e
------BEGIN CERTIFICATE-----
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------END CERTIFICATE-----
-
-# Issuer: CN=Amazon Root CA 2 O=Amazon
-# Subject: CN=Amazon Root CA 2 O=Amazon
-# Label: "Amazon Root CA 2"
-# Serial: 143266982885963551818349160658925006970653239
-# MD5 Fingerprint: c8:e5:8d:ce:a8:42:e2:7a:c0:2a:5c:7c:9e:26:bf:66
-# SHA1 Fingerprint: 5a:8c:ef:45:d7:a6:98:59:76:7a:8c:8b:44:96:b5:78:cf:47:4b:1a
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------BEGIN CERTIFICATE-----
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------END CERTIFICATE-----
-
-# Issuer: CN=Amazon Root CA 3 O=Amazon
-# Subject: CN=Amazon Root CA 3 O=Amazon
-# Label: "Amazon Root CA 3"
-# Serial: 143266986699090766294700635381230934788665930
-# MD5 Fingerprint: a0:d4:ef:0b:f7:b5:d8:49:95:2a:ec:f5:c4:fc:81:87
-# SHA1 Fingerprint: 0d:44:dd:8c:3c:8c:1a:1a:58:75:64:81:e9:0f:2e:2a:ff:b3:d2:6e
-# SHA256 Fingerprint: 18:ce:6c:fe:7b:f1:4e:60:b2:e3:47:b8:df:e8:68:cb:31:d0:2e:bb:3a:da:27:15:69:f5:03:43:b4:6d:b3:a4
------BEGIN CERTIFICATE-----
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------END CERTIFICATE-----
-
-# Issuer: CN=Amazon Root CA 4 O=Amazon
-# Subject: CN=Amazon Root CA 4 O=Amazon
-# Label: "Amazon Root CA 4"
-# Serial: 143266989758080763974105200630763877849284878
-# MD5 Fingerprint: 89:bc:27:d5:eb:17:8d:06:6a:69:d5:fd:89:47:b4:cd
-# SHA1 Fingerprint: f6:10:84:07:d6:f8:bb:67:98:0c:c2:e2:44:c2:eb:ae:1c:ef:63:be
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------BEGIN CERTIFICATE-----
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------END CERTIFICATE-----
-
-# Issuer: CN=TUBITAK Kamu SM SSL Kok Sertifikasi - Surum 1 O=Turkiye Bilimsel ve Teknolojik Arastirma Kurumu - TUBITAK OU=Kamu Sertifikasyon Merkezi - Kamu SM
-# Subject: CN=TUBITAK Kamu SM SSL Kok Sertifikasi - Surum 1 O=Turkiye Bilimsel ve Teknolojik Arastirma Kurumu - TUBITAK OU=Kamu Sertifikasyon Merkezi - Kamu SM
-# Label: "TUBITAK Kamu SM SSL Kok Sertifikasi - Surum 1"
-# Serial: 1
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------BEGIN CERTIFICATE-----
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------END CERTIFICATE-----
-
-# Issuer: CN=GDCA TrustAUTH R5 ROOT O=GUANG DONG CERTIFICATE AUTHORITY CO.,LTD.
-# Subject: CN=GDCA TrustAUTH R5 ROOT O=GUANG DONG CERTIFICATE AUTHORITY CO.,LTD.
-# Label: "GDCA TrustAUTH R5 ROOT"
-# Serial: 9009899650740120186
-# MD5 Fingerprint: 63:cc:d9:3d:34:35:5c:6f:53:a3:e2:08:70:48:1f:b4
-# SHA1 Fingerprint: 0f:36:38:5b:81:1a:25:c3:9b:31:4e:83:ca:e9:34:66:70:cc:74:b4
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------BEGIN CERTIFICATE-----
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------END CERTIFICATE-----
-
-# Issuer: CN=SSL.com Root Certification Authority RSA O=SSL Corporation
-# Subject: CN=SSL.com Root Certification Authority RSA O=SSL Corporation
-# Label: "SSL.com Root Certification Authority RSA"
-# Serial: 8875640296558310041
-# MD5 Fingerprint: 86:69:12:c0:70:f1:ec:ac:ac:c2:d5:bc:a5:5b:a1:29
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------BEGIN CERTIFICATE-----
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------END CERTIFICATE-----
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-# Issuer: CN=SSL.com Root Certification Authority ECC O=SSL Corporation
-# Subject: CN=SSL.com Root Certification Authority ECC O=SSL Corporation
-# Label: "SSL.com Root Certification Authority ECC"
-# Serial: 8495723813297216424
-# MD5 Fingerprint: 2e:da:e4:39:7f:9c:8f:37:d1:70:9f:26:17:51:3a:8e
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------BEGIN CERTIFICATE-----
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------END CERTIFICATE-----
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-# Issuer: CN=SSL.com EV Root Certification Authority RSA R2 O=SSL Corporation
-# Subject: CN=SSL.com EV Root Certification Authority RSA R2 O=SSL Corporation
-# Label: "SSL.com EV Root Certification Authority RSA R2"
-# Serial: 6248227494352943350
-# MD5 Fingerprint: e1:1e:31:58:1a:ae:54:53:02:f6:17:6a:11:7b:4d:95
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------BEGIN CERTIFICATE-----
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------END CERTIFICATE-----
-
-# Issuer: CN=SSL.com EV Root Certification Authority ECC O=SSL Corporation
-# Subject: CN=SSL.com EV Root Certification Authority ECC O=SSL Corporation
-# Label: "SSL.com EV Root Certification Authority ECC"
-# Serial: 3182246526754555285
-# MD5 Fingerprint: 59:53:22:65:83:42:01:54:c0:ce:42:b9:5a:7c:f2:90
-# SHA1 Fingerprint: 4c:dd:51:a3:d1:f5:20:32:14:b0:c6:c5:32:23:03:91:c7:46:42:6d
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------BEGIN CERTIFICATE-----
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------END CERTIFICATE-----
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-# Issuer: CN=GlobalSign O=GlobalSign OU=GlobalSign Root CA - R6
-# Subject: CN=GlobalSign O=GlobalSign OU=GlobalSign Root CA - R6
-# Label: "GlobalSign Root CA - R6"
-# Serial: 1417766617973444989252670301619537
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------BEGIN CERTIFICATE-----
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-# Issuer: CN=OISTE WISeKey Global Root GC CA O=WISeKey OU=OISTE Foundation Endorsed
-# Subject: CN=OISTE WISeKey Global Root GC CA O=WISeKey OU=OISTE Foundation Endorsed
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------BEGIN CERTIFICATE-----
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-# Issuer: CN=UCA Global G2 Root O=UniTrust
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-# Label: "UCA Global G2 Root"
-# Serial: 124779693093741543919145257850076631279
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------BEGIN CERTIFICATE-----
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-# Issuer: CN=UCA Extended Validation Root O=UniTrust
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-# Label: "UCA Extended Validation Root"
-# Serial: 106100277556486529736699587978573607008
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------BEGIN CERTIFICATE-----
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-# Issuer: CN=Certigna Root CA O=Dhimyotis OU=0002 48146308100036
-# Subject: CN=Certigna Root CA O=Dhimyotis OU=0002 48146308100036
-# Label: "Certigna Root CA"
-# Serial: 269714418870597844693661054334862075617
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------BEGIN CERTIFICATE-----
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------END CERTIFICATE-----
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-# Issuer: CN=emSign Root CA - G1 O=eMudhra Technologies Limited OU=emSign PKI
-# Subject: CN=emSign Root CA - G1 O=eMudhra Technologies Limited OU=emSign PKI
-# Label: "emSign Root CA - G1"
-# Serial: 235931866688319308814040
-# MD5 Fingerprint: 9c:42:84:57:dd:cb:0b:a7:2e:95:ad:b6:f3:da:bc:ac
-# SHA1 Fingerprint: 8a:c7:ad:8f:73:ac:4e:c1:b5:75:4d:a5:40:f4:fc:cf:7c:b5:8e:8c
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------BEGIN CERTIFICATE-----
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------END CERTIFICATE-----
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-# Issuer: CN=emSign ECC Root CA - G3 O=eMudhra Technologies Limited OU=emSign PKI
-# Subject: CN=emSign ECC Root CA - G3 O=eMudhra Technologies Limited OU=emSign PKI
-# Label: "emSign ECC Root CA - G3"
-# Serial: 287880440101571086945156
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-# SHA1 Fingerprint: 30:43:fa:4f:f2:57:dc:a0:c3:80:ee:2e:58:ea:78:b2:3f:e6:bb:c1
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-# Subject: CN=emSign Root CA - C1 O=eMudhra Inc OU=emSign PKI
-# Label: "emSign Root CA - C1"
-# Serial: 825510296613316004955058
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------BEGIN CERTIFICATE-----
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-# Issuer: CN=emSign ECC Root CA - C3 O=eMudhra Inc OU=emSign PKI
-# Subject: CN=emSign ECC Root CA - C3 O=eMudhra Inc OU=emSign PKI
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-# Issuer: CN=Hongkong Post Root CA 3 O=Hongkong Post
-# Subject: CN=Hongkong Post Root CA 3 O=Hongkong Post
-# Label: "Hongkong Post Root CA 3"
-# Serial: 46170865288971385588281144162979347873371282084
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------BEGIN CERTIFICATE-----
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------END CERTIFICATE-----
-
-# Issuer: CN=Entrust Root Certification Authority - G4 O=Entrust, Inc. OU=See www.entrust.net/legal-terms/(c) 2015 Entrust, Inc. - for authorized use only
-# Subject: CN=Entrust Root Certification Authority - G4 O=Entrust, Inc. OU=See www.entrust.net/legal-terms/(c) 2015 Entrust, Inc. - for authorized use only
-# Label: "Entrust Root Certification Authority - G4"
-# Serial: 289383649854506086828220374796556676440
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------BEGIN CERTIFICATE-----
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-
-# Issuer: CN=Microsoft ECC Root Certificate Authority 2017 O=Microsoft Corporation
-# Subject: CN=Microsoft ECC Root Certificate Authority 2017 O=Microsoft Corporation
-# Label: "Microsoft ECC Root Certificate Authority 2017"
-# Serial: 136839042543790627607696632466672567020
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------BEGIN CERTIFICATE-----
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------END CERTIFICATE-----
-
-# Issuer: CN=Microsoft RSA Root Certificate Authority 2017 O=Microsoft Corporation
-# Subject: CN=Microsoft RSA Root Certificate Authority 2017 O=Microsoft Corporation
-# Label: "Microsoft RSA Root Certificate Authority 2017"
-# Serial: 40975477897264996090493496164228220339
-# MD5 Fingerprint: 10:ff:00:ff:cf:c9:f8:c7:7a:c0:ee:35:8e:c9:0f:47
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------BEGIN CERTIFICATE-----
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-# Label: "certSIGN Root CA G2"
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-# Issuer: CN=Trustwave Global Certification Authority O=Trustwave Holdings, Inc.
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-# Label: "Trustwave Global Certification Authority"
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------END CERTIFICATE-----
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-# Issuer: CN=Trustwave Global ECC P256 Certification Authority O=Trustwave Holdings, Inc.
-# Subject: CN=Trustwave Global ECC P256 Certification Authority O=Trustwave Holdings, Inc.
-# Label: "Trustwave Global ECC P256 Certification Authority"
-# Serial: 4151900041497450638097112925
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-# Issuer: CN=Trustwave Global ECC P384 Certification Authority O=Trustwave Holdings, Inc.
-# Subject: CN=Trustwave Global ECC P384 Certification Authority O=Trustwave Holdings, Inc.
-# Label: "Trustwave Global ECC P384 Certification Authority"
-# Serial: 2704997926503831671788816187
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------BEGIN CERTIFICATE-----
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------END CERTIFICATE-----
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-# Issuer: CN=NAVER Global Root Certification Authority O=NAVER BUSINESS PLATFORM Corp.
-# Subject: CN=NAVER Global Root Certification Authority O=NAVER BUSINESS PLATFORM Corp.
-# Label: "NAVER Global Root Certification Authority"
-# Serial: 9013692873798656336226253319739695165984492813
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------BEGIN CERTIFICATE-----
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-# Issuer: CN=AC RAIZ FNMT-RCM SERVIDORES SEGUROS O=FNMT-RCM OU=Ceres
-# Subject: CN=AC RAIZ FNMT-RCM SERVIDORES SEGUROS O=FNMT-RCM OU=Ceres
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-# Subject: CN=GlobalSign Root R46 O=GlobalSign nv-sa
-# Label: "GlobalSign Root R46"
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------BEGIN CERTIFICATE-----
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-# Issuer: CN=GlobalSign Root E46 O=GlobalSign nv-sa
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-# Label: "GlobalSign Root E46"
-# Serial: 1552617690338932563915843282459653771421763
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------BEGIN CERTIFICATE-----
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------END CERTIFICATE-----
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------BEGIN CERTIFICATE-----
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------END CERTIFICATE-----
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-# Issuer: CN=Certum EC-384 CA O=Asseco Data Systems S.A. OU=Certum Certification Authority
-# Subject: CN=Certum EC-384 CA O=Asseco Data Systems S.A. OU=Certum Certification Authority
-# Label: "Certum EC-384 CA"
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------BEGIN CERTIFICATE-----
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------END CERTIFICATE-----
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-# Issuer: CN=Certum Trusted Root CA O=Asseco Data Systems S.A. OU=Certum Certification Authority
-# Subject: CN=Certum Trusted Root CA O=Asseco Data Systems S.A. OU=Certum Certification Authority
-# Label: "Certum Trusted Root CA"
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------BEGIN CERTIFICATE-----
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-# Issuer: CN=TunTrust Root CA O=Agence Nationale de Certification Electronique
-# Subject: CN=TunTrust Root CA O=Agence Nationale de Certification Electronique
-# Label: "TunTrust Root CA"
-# Serial: 108534058042236574382096126452369648152337120275
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------BEGIN CERTIFICATE-----
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-# Issuer: CN=HARICA TLS RSA Root CA 2021 O=Hellenic Academic and Research Institutions CA
-# Subject: CN=HARICA TLS RSA Root CA 2021 O=Hellenic Academic and Research Institutions CA
-# Label: "HARICA TLS RSA Root CA 2021"
-# Serial: 76817823531813593706434026085292783742
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------BEGIN CERTIFICATE-----
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------END CERTIFICATE-----
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-# Issuer: CN=HARICA TLS ECC Root CA 2021 O=Hellenic Academic and Research Institutions CA
-# Subject: CN=HARICA TLS ECC Root CA 2021 O=Hellenic Academic and Research Institutions CA
-# Label: "HARICA TLS ECC Root CA 2021"
-# Serial: 137515985548005187474074462014555733966
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------BEGIN CERTIFICATE-----
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------END CERTIFICATE-----
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-# Issuer: CN=Autoridad de Certificacion Firmaprofesional CIF A62634068
-# Subject: CN=Autoridad de Certificacion Firmaprofesional CIF A62634068
-# Label: "Autoridad de Certificacion Firmaprofesional CIF A62634068"
-# Serial: 1977337328857672817
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------BEGIN CERTIFICATE-----
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------END CERTIFICATE-----
-
-# Issuer: CN=vTrus ECC Root CA O=iTrusChina Co.,Ltd.
-# Subject: CN=vTrus ECC Root CA O=iTrusChina Co.,Ltd.
-# Label: "vTrus ECC Root CA"
-# Serial: 630369271402956006249506845124680065938238527194
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-# Issuer: CN=vTrus Root CA O=iTrusChina Co.,Ltd.
-# Subject: CN=vTrus Root CA O=iTrusChina Co.,Ltd.
-# Label: "vTrus Root CA"
-# Serial: 387574501246983434957692974888460947164905180485
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------BEGIN CERTIFICATE-----
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-# Issuer: CN=ISRG Root X2 O=Internet Security Research Group
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-# Serial: 87493402998870891108772069816698636114
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-# Subject: CN=HiPKI Root CA - G1 O=Chunghwa Telecom Co., Ltd.
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------BEGIN CERTIFICATE-----
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-# Issuer: CN=GlobalSign O=GlobalSign OU=GlobalSign ECC Root CA - R4
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-# Label: "GlobalSign ECC Root CA - R4"
-# Serial: 159662223612894884239637590694
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------BEGIN CERTIFICATE-----
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-# Issuer: CN=GTS Root R1 O=Google Trust Services LLC
-# Subject: CN=GTS Root R1 O=Google Trust Services LLC
-# Label: "GTS Root R1"
-# Serial: 159662320309726417404178440727
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------BEGIN CERTIFICATE-----
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------END CERTIFICATE-----
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-# Issuer: CN=GTS Root R2 O=Google Trust Services LLC
-# Subject: CN=GTS Root R2 O=Google Trust Services LLC
-# Label: "GTS Root R2"
-# Serial: 159662449406622349769042896298
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------BEGIN CERTIFICATE-----
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-# Issuer: CN=GTS Root R3 O=Google Trust Services LLC
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-# Serial: 159662495401136852707857743206
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------END CERTIFICATE-----
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-# Issuer: CN=D-TRUST BR Root CA 1 2020 O=D-Trust GmbH
-# Subject: CN=D-TRUST BR Root CA 1 2020 O=D-Trust GmbH
-# Label: "D-TRUST BR Root CA 1 2020"
-# Serial: 165870826978392376648679885835942448534
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------BEGIN CERTIFICATE-----
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-# Issuer: CN=D-TRUST EV Root CA 1 2020 O=D-Trust GmbH
-# Subject: CN=D-TRUST EV Root CA 1 2020 O=D-Trust GmbH
-# Label: "D-TRUST EV Root CA 1 2020"
-# Serial: 126288379621884218666039612629459926992
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------BEGIN CERTIFICATE-----
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-# Issuer: CN=DigiCert TLS ECC P384 Root G5 O=DigiCert, Inc.
-# Subject: CN=DigiCert TLS ECC P384 Root G5 O=DigiCert, Inc.
-# Label: "DigiCert TLS ECC P384 Root G5"
-# Serial: 13129116028163249804115411775095713523
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------BEGIN CERTIFICATE-----
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------END CERTIFICATE-----
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-# Issuer: CN=DigiCert TLS RSA4096 Root G5 O=DigiCert, Inc.
-# Subject: CN=DigiCert TLS RSA4096 Root G5 O=DigiCert, Inc.
-# Label: "DigiCert TLS RSA4096 Root G5"
-# Serial: 11930366277458970227240571539258396554
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------BEGIN CERTIFICATE-----
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------END CERTIFICATE-----
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-# Issuer: CN=BJCA Global Root CA2 O=BEIJING CERTIFICATE AUTHORITY
-# Subject: CN=BJCA Global Root CA2 O=BEIJING CERTIFICATE AUTHORITY
-# Label: "BJCA Global Root CA2"
-# Serial: 58605626836079930195615843123109055211
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------BEGIN CERTIFICATE-----
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-# Issuer: CN=Sectigo Public Server Authentication Root E46 O=Sectigo Limited
-# Subject: CN=Sectigo Public Server Authentication Root E46 O=Sectigo Limited
-# Label: "Sectigo Public Server Authentication Root E46"
-# Serial: 88989738453351742415770396670917916916
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------BEGIN CERTIFICATE-----
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------END CERTIFICATE-----
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-# Subject: CN=Sectigo Public Server Authentication Root R46 O=Sectigo Limited
-# Label: "Sectigo Public Server Authentication Root R46"
-# Serial: 156256931880233212765902055439220583700
-# MD5 Fingerprint: 32:10:09:52:00:d5:7e:6c:43:df:15:c0:b1:16:93:e5
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------BEGIN CERTIFICATE-----
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------END CERTIFICATE-----
-
-# Issuer: CN=SSL.com TLS RSA Root CA 2022 O=SSL Corporation
-# Subject: CN=SSL.com TLS RSA Root CA 2022 O=SSL Corporation
-# Label: "SSL.com TLS RSA Root CA 2022"
-# Serial: 148535279242832292258835760425842727825
-# MD5 Fingerprint: d8:4e:c6:59:30:d8:fe:a0:d6:7a:5a:2c:2c:69:78:da
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------BEGIN CERTIFICATE-----
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------END CERTIFICATE-----
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-# Issuer: CN=SSL.com TLS ECC Root CA 2022 O=SSL Corporation
-# Subject: CN=SSL.com TLS ECC Root CA 2022 O=SSL Corporation
-# Label: "SSL.com TLS ECC Root CA 2022"
-# Serial: 26605119622390491762507526719404364228
-# MD5 Fingerprint: 99:d7:5c:f1:51:36:cc:e9:ce:d9:19:2e:77:71:56:c5
-# SHA1 Fingerprint: 9f:5f:d9:1a:54:6d:f5:0c:71:f0:ee:7a:bd:17:49:98:84:73:e2:39
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------BEGIN CERTIFICATE-----
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------END CERTIFICATE-----
-
-# Issuer: CN=Atos TrustedRoot Root CA ECC TLS 2021 O=Atos
-# Subject: CN=Atos TrustedRoot Root CA ECC TLS 2021 O=Atos
-# Label: "Atos TrustedRoot Root CA ECC TLS 2021"
-# Serial: 81873346711060652204712539181482831616
-# MD5 Fingerprint: 16:9f:ad:f1:70:ad:79:d6:ed:29:b4:d1:c5:79:70:a8
-# SHA1 Fingerprint: 9e:bc:75:10:42:b3:02:f3:81:f4:f7:30:62:d4:8f:c3:a7:51:b2:dd
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------BEGIN CERTIFICATE-----
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------END CERTIFICATE-----
-
-# Issuer: CN=Atos TrustedRoot Root CA RSA TLS 2021 O=Atos
-# Subject: CN=Atos TrustedRoot Root CA RSA TLS 2021 O=Atos
-# Label: "Atos TrustedRoot Root CA RSA TLS 2021"
-# Serial: 111436099570196163832749341232207667876
-# MD5 Fingerprint: d4:d3:46:b8:9a:c0:9c:76:5d:9e:3a:c3:b9:99:31:d2
-# SHA1 Fingerprint: 18:52:3b:0d:06:37:e4:d6:3a:df:23:e4:98:fb:5b:16:fb:86:74:48
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------BEGIN CERTIFICATE-----
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-
-# Issuer: CN=Telekom Security TLS ECC Root 2020 O=Deutsche Telekom Security GmbH
-# Subject: CN=Telekom Security TLS ECC Root 2020 O=Deutsche Telekom Security GmbH
-# Label: "Telekom Security TLS ECC Root 2020"
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-
-# Issuer: CN=Telekom Security TLS RSA Root 2023 O=Deutsche Telekom Security GmbH
-# Subject: CN=Telekom Security TLS RSA Root 2023 O=Deutsche Telekom Security GmbH
-# Label: "Telekom Security TLS RSA Root 2023"
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-# Subject: CN=FIRMAPROFESIONAL CA ROOT-A WEB O=Firmaprofesional SA
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path/to/venv/lib/python3.12/site-packages/certifi/core.py

@@ -1,114 +0,0 @@
-"""
-certifi.py
-~~~~~~~~~~
-
-This module returns the installation location of cacert.pem or its contents.
-"""
-import sys
-import atexit
-
-def exit_cacert_ctx() -> None:
-    _CACERT_CTX.__exit__(None, None, None)  # type: ignore[union-attr]
-
-
-if sys.version_info >= (3, 11):
-
-    from importlib.resources import as_file, files
-
-    _CACERT_CTX = None
-    _CACERT_PATH = None
-
-    def where() -> str:
-        # This is slightly terrible, but we want to delay extracting the file
-        # in cases where we're inside of a zipimport situation until someone
-        # actually calls where(), but we don't want to re-extract the file
-        # on every call of where(), so we'll do it once then store it in a
-        # global variable.
-        global _CACERT_CTX
-        global _CACERT_PATH
-        if _CACERT_PATH is None:
-            # This is slightly janky, the importlib.resources API wants you to
-            # manage the cleanup of this file, so it doesn't actually return a
-            # path, it returns a context manager that will give you the path
-            # when you enter it and will do any cleanup when you leave it. In
-            # the common case of not needing a temporary file, it will just
-            # return the file system location and the __exit__() is a no-op.
-            #
-            # We also have to hold onto the actual context manager, because
-            # it will do the cleanup whenever it gets garbage collected, so
-            # we will also store that at the global level as well.
-            _CACERT_CTX = as_file(files("certifi").joinpath("cacert.pem"))
-            _CACERT_PATH = str(_CACERT_CTX.__enter__())
-            atexit.register(exit_cacert_ctx)
-
-        return _CACERT_PATH
-
-    def contents() -> str:
-        return files("certifi").joinpath("cacert.pem").read_text(encoding="ascii")
-
-elif sys.version_info >= (3, 7):
-
-    from importlib.resources import path as get_path, read_text
-
-    _CACERT_CTX = None
-    _CACERT_PATH = None
-
-    def where() -> str:
-        # This is slightly terrible, but we want to delay extracting the
-        # file in cases where we're inside of a zipimport situation until
-        # someone actually calls where(), but we don't want to re-extract
-        # the file on every call of where(), so we'll do it once then store
-        # it in a global variable.
-        global _CACERT_CTX
-        global _CACERT_PATH
-        if _CACERT_PATH is None:
-            # This is slightly janky, the importlib.resources API wants you
-            # to manage the cleanup of this file, so it doesn't actually
-            # return a path, it returns a context manager that will give
-            # you the path when you enter it and will do any cleanup when
-            # you leave it. In the common case of not needing a temporary
-            # file, it will just return the file system location and the
-            # __exit__() is a no-op.
-            #
-            # We also have to hold onto the actual context manager, because
-            # it will do the cleanup whenever it gets garbage collected, so
-            # we will also store that at the global level as well.
-            _CACERT_CTX = get_path("certifi", "cacert.pem")
-            _CACERT_PATH = str(_CACERT_CTX.__enter__())
-            atexit.register(exit_cacert_ctx)
-
-        return _CACERT_PATH
-
-    def contents() -> str:
-        return read_text("certifi", "cacert.pem", encoding="ascii")
-
-else:
-    import os
-    import types
-    from typing import Union
-
-    Package = Union[types.ModuleType, str]
-    Resource = Union[str, "os.PathLike"]
-
-    # This fallback will work for Python versions prior to 3.7 that lack the
-    # importlib.resources module but relies on the existing `where` function
-    # so won't address issues with environments like PyOxidizer that don't set
-    # __file__ on modules.
-    def read_text(
-        package: Package,
-        resource: Resource,
-        encoding: str = 'utf-8',
-        errors: str = 'strict'
-    ) -> str:
-        with open(where(), encoding=encoding) as data:
-            return data.read()
-
-    # If we don't have importlib.resources, then we will just do the old logic
-    # of assuming we're on the filesystem and munge the path directly.
-    def where() -> str:
-        f = os.path.dirname(__file__)
-
-        return os.path.join(f, "cacert.pem")
-
-    def contents() -> str:
-        return read_text("certifi", "cacert.pem", encoding="ascii")

path/to/venv/lib/python3.12/site-packages/charset_normalizer-3.3.2.dist-info/INSTALLER

@@ -1 +0,0 @@
-pip

path/to/venv/lib/python3.12/site-packages/charset_normalizer-3.3.2.dist-info/LICENSE

@@ -1,21 +0,0 @@
-MIT License
-
-Copyright (c) 2019 TAHRI Ahmed R.
-
-Permission is hereby granted, free of charge, to any person obtaining a copy
-of this software and associated documentation files (the "Software"), to deal
-in the Software without restriction, including without limitation the rights
-to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
-copies of the Software, and to permit persons to whom the Software is
-furnished to do so, subject to the following conditions:
-
-The above copyright notice and this permission notice shall be included in all
-copies or substantial portions of the Software.
-
-THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
-IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
-FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
-AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
-LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
-OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
-SOFTWARE.

path/to/venv/lib/python3.12/site-packages/charset_normalizer-3.3.2.dist-info/METADATA

@@ -1,683 +0,0 @@
-Metadata-Version: 2.1
-Name: charset-normalizer
-Version: 3.3.2
-Summary: The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet.
-Home-page: https://github.com/Ousret/charset_normalizer
-Author: Ahmed TAHRI
-Author-email: ahmed.tahri@cloudnursery.dev
-License: MIT
-Project-URL: Bug Reports, https://github.com/Ousret/charset_normalizer/issues
-Project-URL: Documentation, https://charset-normalizer.readthedocs.io/en/latest
-Keywords: encoding,charset,charset-detector,detector,normalization,unicode,chardet,detect
-Classifier: Development Status :: 5 - Production/Stable
-Classifier: License :: OSI Approved :: MIT License
-Classifier: Intended Audience :: Developers
-Classifier: Topic :: Software Development :: Libraries :: Python Modules
-Classifier: Operating System :: OS Independent
-Classifier: Programming Language :: Python
-Classifier: Programming Language :: Python :: 3
-Classifier: Programming Language :: Python :: 3.7
-Classifier: Programming Language :: Python :: 3.8
-Classifier: Programming Language :: Python :: 3.9
-Classifier: Programming Language :: Python :: 3.10
-Classifier: Programming Language :: Python :: 3.11
-Classifier: Programming Language :: Python :: 3.12
-Classifier: Programming Language :: Python :: Implementation :: PyPy
-Classifier: Topic :: Text Processing :: Linguistic
-Classifier: Topic :: Utilities
-Classifier: Typing :: Typed
-Requires-Python: >=3.7.0
-Description-Content-Type: text/markdown
-License-File: LICENSE
-Provides-Extra: unicode_backport
-
-<h1 align="center">Charset Detection, for Everyone 👋</h1>
-
-<p align="center">
-  <sup>The Real First Universal Charset Detector</sup><br>
-  <a href="https://pypi.org/project/charset-normalizer">
-    <img src="https://img.shields.io/pypi/pyversions/charset_normalizer.svg?orange=blue" />
-  </a>
-  <a href="https://pepy.tech/project/charset-normalizer/">
-    <img alt="Download Count Total" src="https://static.pepy.tech/badge/charset-normalizer/month" />
-  </a>
-  <a href="https://bestpractices.coreinfrastructure.org/projects/7297">
-    <img src="https://bestpractices.coreinfrastructure.org/projects/7297/badge">
-  </a>
-</p>
-<p align="center">
-  <sup><i>Featured Packages</i></sup><br>
-  <a href="https://github.com/jawah/niquests">
-   <img alt="Static Badge" src="https://img.shields.io/badge/Niquests-HTTP_1.1%2C%202%2C_and_3_Client-cyan">
-  </a>
-  <a href="https://github.com/jawah/wassima">
-   <img alt="Static Badge" src="https://img.shields.io/badge/Wassima-Certifi_Killer-cyan">
-  </a>
-</p>
-<p align="center">
-  <sup><i>In other language (unofficial port - by the community)</i></sup><br>
-  <a href="https://github.com/nickspring/charset-normalizer-rs">
-   <img alt="Static Badge" src="https://img.shields.io/badge/Rust-red">
-  </a>
-</p>
-
-> A library that helps you read text from an unknown charset encoding.<br /> Motivated by `chardet`,
-> I'm trying to resolve the issue by taking a new approach.
-> All IANA character set names for which the Python core library provides codecs are supported.
-
-<p align="center">
-  >>>>> <a href="https://charsetnormalizerweb.ousret.now.sh" target="_blank">👉 Try Me Online Now, Then Adopt Me 👈 </a> <<<<<
-</p>
-
-This project offers you an alternative to **Universal Charset Encoding Detector**, also known as **Chardet**.
-
-| Feature                                          | [Chardet](https://github.com/chardet/chardet) |                                         Charset Normalizer                                         | [cChardet](https://github.com/PyYoshi/cChardet) |
-|--------------------------------------------------|:---------------------------------------------:|:--------------------------------------------------------------------------------------------------:|:-----------------------------------------------:|
-| `Fast`                                           |                       ❌                       |                                                 ✅                                                  |                        ✅                        |
-| `Universal**`                                    |                       ❌                       |                                                 ✅                                                  |                        ❌                        |
-| `Reliable` **without** distinguishable standards |                       ❌                       |                                                 ✅                                                  |                        ✅                        |
-| `Reliable` **with** distinguishable standards    |                       ✅                       |                                                 ✅                                                  |                        ✅                        |
-| `License`                                        |           LGPL-2.1<br>_restrictive_           |                                                MIT                                                 |            MPL-1.1<br>_restrictive_             |
-| `Native Python`                                  |                       ✅                       |                                                 ✅                                                  |                        ❌                        |
-| `Detect spoken language`                         |                       ❌                       |                                                 ✅                                                  |                       N/A                       |
-| `UnicodeDecodeError Safety`                      |                       ❌                       |                                                 ✅                                                  |                        ❌                        |
-| `Whl Size (min)`                                 |                   193.6 kB                    |                                               42 kB                                                |                     ~200 kB                     |
-| `Supported Encoding`                             |                      33                       | 🎉 [99](https://charset-normalizer.readthedocs.io/en/latest/user/support.html#supported-encodings) |                       40                        |
-
-<p align="center">
-<img src="https://i.imgflip.com/373iay.gif" alt="Reading Normalized Text" width="226"/><img src="https://media.tenor.com/images/c0180f70732a18b4965448d33adba3d0/tenor.gif" alt="Cat Reading Text" width="200"/>
-</p>
-
-*\*\* : They are clearly using specific code for a specific encoding even if covering most of used one*<br> 
-Did you got there because of the logs? See [https://charset-normalizer.readthedocs.io/en/latest/user/miscellaneous.html](https://charset-normalizer.readthedocs.io/en/latest/user/miscellaneous.html)
-
-## ⚡ Performance
-
-This package offer better performance than its counterpart Chardet. Here are some numbers.
-
-| Package                                       | Accuracy | Mean per file (ms) | File per sec (est) |
-|-----------------------------------------------|:--------:|:------------------:|:------------------:|
-| [chardet](https://github.com/chardet/chardet) |   86 %   |       200 ms       |     5 file/sec     |
-| charset-normalizer                            | **98 %** |     **10 ms**      |    100 file/sec    |
-
-| Package                                       | 99th percentile | 95th percentile | 50th percentile |
-|-----------------------------------------------|:---------------:|:---------------:|:---------------:|
-| [chardet](https://github.com/chardet/chardet) |     1200 ms     |     287 ms      |      23 ms      |
-| charset-normalizer                            |     100 ms      |      50 ms      |      5 ms       |
-
-Chardet's performance on larger file (1MB+) are very poor. Expect huge difference on large payload.
-
-> Stats are generated using 400+ files using default parameters. More details on used files, see GHA workflows.
-> And yes, these results might change at any time. The dataset can be updated to include more files.
-> The actual delays heavily depends on your CPU capabilities. The factors should remain the same.
-> Keep in mind that the stats are generous and that Chardet accuracy vs our is measured using Chardet initial capability
-> (eg. Supported Encoding) Challenge-them if you want.
-
-## ✨ Installation
-
-Using pip:
-
-```sh
-pip install charset-normalizer -U
-```
-
-## 🚀 Basic Usage
-
-### CLI
-This package comes with a CLI.
-
-```
-usage: normalizer [-h] [-v] [-a] [-n] [-m] [-r] [-f] [-t THRESHOLD]
-                  file [file ...]
-
-The Real First Universal Charset Detector. Discover originating encoding used
-on text file. Normalize text to unicode.
-
-positional arguments:
-  files                 File(s) to be analysed
-
-optional arguments:
-  -h, --help            show this help message and exit
-  -v, --verbose         Display complementary information about file if any.
-                        Stdout will contain logs about the detection process.
-  -a, --with-alternative
-                        Output complementary possibilities if any. Top-level
-                        JSON WILL be a list.
-  -n, --normalize       Permit to normalize input file. If not set, program
-                        does not write anything.
-  -m, --minimal         Only output the charset detected to STDOUT. Disabling
-                        JSON output.
-  -r, --replace         Replace file when trying to normalize it instead of
-                        creating a new one.
-  -f, --force           Replace file without asking if you are sure, use this
-                        flag with caution.
-  -t THRESHOLD, --threshold THRESHOLD
-                        Define a custom maximum amount of chaos allowed in
-                        decoded content. 0. <= chaos <= 1.
-  --version             Show version information and exit.
-```
-
-```bash
-normalizer ./data/sample.1.fr.srt
-```
-
-or
-
-```bash
-python -m charset_normalizer ./data/sample.1.fr.srt
-```
-
-🎉 Since version 1.4.0 the CLI produce easily usable stdout result in JSON format.
-
-```json
-{
-    "path": "/home/default/projects/charset_normalizer/data/sample.1.fr.srt",
-    "encoding": "cp1252",
-    "encoding_aliases": [
-        "1252",
-        "windows_1252"
-    ],
-    "alternative_encodings": [
-        "cp1254",
-        "cp1256",
-        "cp1258",
-        "iso8859_14",
-        "iso8859_15",
-        "iso8859_16",
-        "iso8859_3",
-        "iso8859_9",
-        "latin_1",
-        "mbcs"
-    ],
-    "language": "French",
-    "alphabets": [
-        "Basic Latin",
-        "Latin-1 Supplement"
-    ],
-    "has_sig_or_bom": false,
-    "chaos": 0.149,
-    "coherence": 97.152,
-    "unicode_path": null,
-    "is_preferred": true
-}
-```
-
-### Python
-*Just print out normalized text*
-```python
-from charset_normalizer import from_path
-
-results = from_path('./my_subtitle.srt')
-
-print(str(results.best()))
-```
-
-*Upgrade your code without effort*
-```python
-from charset_normalizer import detect
-```
-
-The above code will behave the same as **chardet**. We ensure that we offer the best (reasonable) BC result possible.
-
-See the docs for advanced usage : [readthedocs.io](https://charset-normalizer.readthedocs.io/en/latest/)
-
-## 😇 Why
-
-When I started using Chardet, I noticed that it was not suited to my expectations, and I wanted to propose a
-reliable alternative using a completely different method. Also! I never back down on a good challenge!
-
-I **don't care** about the **originating charset** encoding, because **two different tables** can
-produce **two identical rendered string.**
-What I want is to get readable text, the best I can. 
-
-In a way, **I'm brute forcing text decoding.** How cool is that ? 😎
-
-Don't confuse package **ftfy** with charset-normalizer or chardet. ftfy goal is to repair unicode string whereas charset-normalizer to convert raw file in unknown encoding to unicode.
-
-## 🍰 How
-
-  - Discard all charset encoding table that could not fit the binary content.
-  - Measure noise, or the mess once opened (by chunks) with a corresponding charset encoding.
-  - Extract matches with the lowest mess detected.
-  - Additionally, we measure coherence / probe for a language.
-
-**Wait a minute**, what is noise/mess and coherence according to **YOU ?**
-
-*Noise :* I opened hundred of text files, **written by humans**, with the wrong encoding table. **I observed**, then
-**I established** some ground rules about **what is obvious** when **it seems like** a mess.
- I know that my interpretation of what is noise is probably incomplete, feel free to contribute in order to
- improve or rewrite it.
-
-*Coherence :* For each language there is on earth, we have computed ranked letter appearance occurrences (the best we can). So I thought
-that intel is worth something here. So I use those records against decoded text to check if I can detect intelligent design.
-
-## ⚡ Known limitations
-
-  - Language detection is unreliable when text contains two or more languages sharing identical letters. (eg. HTML (english tags) + Turkish content (Sharing Latin characters))
-  - Every charset detector heavily depends on sufficient content. In common cases, do not bother run detection on very tiny content.
-
-## ⚠️ About Python EOLs
-
-**If you are running:**
-
-- Python >=2.7,<3.5: Unsupported
-- Python 3.5: charset-normalizer < 2.1
-- Python 3.6: charset-normalizer < 3.1
-- Python 3.7: charset-normalizer < 4.0
-
-Upgrade your Python interpreter as soon as possible.
-
-## 👤 Contributing
-
-Contributions, issues and feature requests are very much welcome.<br />
-Feel free to check [issues page](https://github.com/ousret/charset_normalizer/issues) if you want to contribute.
-
-## 📝 License
-
-Copyright © [Ahmed TAHRI @Ousret](https://github.com/Ousret).<br />
-This project is [MIT](https://github.com/Ousret/charset_normalizer/blob/master/LICENSE) licensed.
-
-Characters frequencies used in this project © 2012 [Denny Vrandečić](http://simia.net/letters/)
-
-## 💼 For Enterprise
-
-Professional support for charset-normalizer is available as part of the [Tidelift
-Subscription][1]. Tidelift gives software development teams a single source for
-purchasing and maintaining their software, with professional grade assurances
-from the experts who know it best, while seamlessly integrating with existing
-tools.
-
-[1]: https://tidelift.com/subscription/pkg/pypi-charset-normalizer?utm_source=pypi-charset-normalizer&utm_medium=readme
-
-# Changelog
-All notable changes to charset-normalizer will be documented in this file. This project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
-The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/).
-
-## [3.3.2](https://github.com/Ousret/charset_normalizer/compare/3.3.1...3.3.2) (2023-10-31)
-
-### Fixed
-- Unintentional memory usage regression when using large payload that match several encoding (#376)
-- Regression on some detection case showcased in the documentation (#371)
-
-### Added
-- Noise (md) probe that identify malformed arabic representation due to the presence of letters in isolated form (credit to my wife)
-
-## [3.3.1](https://github.com/Ousret/charset_normalizer/compare/3.3.0...3.3.1) (2023-10-22)
-
-### Changed
-- Optional mypyc compilation upgraded to version 1.6.1 for Python >= 3.8
-- Improved the general detection reliability based on reports from the community
-
-## [3.3.0](https://github.com/Ousret/charset_normalizer/compare/3.2.0...3.3.0) (2023-09-30)
-
-### Added
-- Allow to execute the CLI (e.g. normalizer) through `python -m charset_normalizer.cli` or `python -m charset_normalizer`
-- Support for 9 forgotten encoding that are supported by Python but unlisted in `encoding.aliases` as they have no alias (#323)
-
-### Removed
-- (internal) Redundant utils.is_ascii function and unused function is_private_use_only
-- (internal) charset_normalizer.assets is moved inside charset_normalizer.constant
-
-### Changed
-- (internal) Unicode code blocks in constants are updated using the latest v15.0.0 definition to improve detection
-- Optional mypyc compilation upgraded to version 1.5.1 for Python >= 3.8
-
-### Fixed
-- Unable to properly sort CharsetMatch when both chaos/noise and coherence were close due to an unreachable condition in \_\_lt\_\_ (#350)
-
-## [3.2.0](https://github.com/Ousret/charset_normalizer/compare/3.1.0...3.2.0) (2023-06-07)
-
-### Changed
-- Typehint for function `from_path` no longer enforce `PathLike` as its first argument
-- Minor improvement over the global detection reliability
-
-### Added
-- Introduce function `is_binary` that relies on main capabilities, and optimized to detect binaries
-- Propagate `enable_fallback` argument throughout `from_bytes`, `from_path`, and `from_fp` that allow a deeper control over the detection (default True)
-- Explicit support for Python 3.12
-
-### Fixed
-- Edge case detection failure where a file would contain 'very-long' camel cased word (Issue #289)
-
-## [3.1.0](https://github.com/Ousret/charset_normalizer/compare/3.0.1...3.1.0) (2023-03-06)
-
-### Added
-- Argument `should_rename_legacy` for legacy function `detect` and disregard any new arguments without errors (PR #262)
-
-### Removed
-- Support for Python 3.6 (PR #260)
-
-### Changed
-- Optional speedup provided by mypy/c 1.0.1
-
-## [3.0.1](https://github.com/Ousret/charset_normalizer/compare/3.0.0...3.0.1) (2022-11-18)
-
-### Fixed
-- Multi-bytes cutter/chunk generator did not always cut correctly (PR #233)
-
-### Changed
-- Speedup provided by mypy/c 0.990 on Python >= 3.7
-
-## [3.0.0](https://github.com/Ousret/charset_normalizer/compare/2.1.1...3.0.0) (2022-10-20)
-
-### Added
-- Extend the capability of explain=True when cp_isolation contains at most two entries (min one), will log in details of the Mess-detector results
-- Support for alternative language frequency set in charset_normalizer.assets.FREQUENCIES
-- Add parameter `language_threshold` in `from_bytes`, `from_path` and `from_fp` to adjust the minimum expected coherence ratio
-- `normalizer --version` now specify if current version provide extra speedup (meaning mypyc compilation whl)
-
-### Changed
-- Build with static metadata using 'build' frontend
-- Make the language detection stricter
-- Optional: Module `md.py` can be compiled using Mypyc to provide an extra speedup up to 4x faster than v2.1
-
-### Fixed
-- CLI with opt --normalize fail when using full path for files
-- TooManyAccentuatedPlugin induce false positive on the mess detection when too few alpha character have been fed to it
-- Sphinx warnings when generating the documentation
-
-### Removed
-- Coherence detector no longer return 'Simple English' instead return 'English'
-- Coherence detector no longer return 'Classical Chinese' instead return 'Chinese'
-- Breaking: Method `first()` and `best()` from CharsetMatch
-- UTF-7 will no longer appear as "detected" without a recognized SIG/mark (is unreliable/conflict with ASCII)
-- Breaking: Class aliases CharsetDetector, CharsetDoctor, CharsetNormalizerMatch and CharsetNormalizerMatches
-- Breaking: Top-level function `normalize`
-- Breaking: Properties `chaos_secondary_pass`, `coherence_non_latin` and `w_counter` from CharsetMatch
-- Support for the backport `unicodedata2`
-
-## [3.0.0rc1](https://github.com/Ousret/charset_normalizer/compare/3.0.0b2...3.0.0rc1) (2022-10-18)
-
-### Added
-- Extend the capability of explain=True when cp_isolation contains at most two entries (min one), will log in details of the Mess-detector results
-- Support for alternative language frequency set in charset_normalizer.assets.FREQUENCIES
-- Add parameter `language_threshold` in `from_bytes`, `from_path` and `from_fp` to adjust the minimum expected coherence ratio
-
-### Changed
-- Build with static metadata using 'build' frontend
-- Make the language detection stricter
-
-### Fixed
-- CLI with opt --normalize fail when using full path for files
-- TooManyAccentuatedPlugin induce false positive on the mess detection when too few alpha character have been fed to it
-
-### Removed
-- Coherence detector no longer return 'Simple English' instead return 'English'
-- Coherence detector no longer return 'Classical Chinese' instead return 'Chinese'
-
-## [3.0.0b2](https://github.com/Ousret/charset_normalizer/compare/3.0.0b1...3.0.0b2) (2022-08-21)
-
-### Added
-- `normalizer --version` now specify if current version provide extra speedup (meaning mypyc compilation whl)
-
-### Removed
-- Breaking: Method `first()` and `best()` from CharsetMatch
-- UTF-7 will no longer appear as "detected" without a recognized SIG/mark (is unreliable/conflict with ASCII)
-
-### Fixed
-- Sphinx warnings when generating the documentation
-
-## [3.0.0b1](https://github.com/Ousret/charset_normalizer/compare/2.1.0...3.0.0b1) (2022-08-15)
-
-### Changed
-- Optional: Module `md.py` can be compiled using Mypyc to provide an extra speedup up to 4x faster than v2.1
-
-### Removed
-- Breaking: Class aliases CharsetDetector, CharsetDoctor, CharsetNormalizerMatch and CharsetNormalizerMatches
-- Breaking: Top-level function `normalize`
-- Breaking: Properties `chaos_secondary_pass`, `coherence_non_latin` and `w_counter` from CharsetMatch
-- Support for the backport `unicodedata2`
-
-## [2.1.1](https://github.com/Ousret/charset_normalizer/compare/2.1.0...2.1.1) (2022-08-19)
-
-### Deprecated
-- Function `normalize` scheduled for removal in 3.0
-
-### Changed
-- Removed useless call to decode in fn is_unprintable (#206)
-
-### Fixed
-- Third-party library (i18n xgettext) crashing not recognizing utf_8 (PEP 263) with underscore from [@aleksandernovikov](https://github.com/aleksandernovikov) (#204)
-
-## [2.1.0](https://github.com/Ousret/charset_normalizer/compare/2.0.12...2.1.0) (2022-06-19)
-
-### Added
-- Output the Unicode table version when running the CLI with `--version` (PR #194)
-
-### Changed
-- Re-use decoded buffer for single byte character sets from [@nijel](https://github.com/nijel) (PR #175)
-- Fixing some performance bottlenecks from [@deedy5](https://github.com/deedy5) (PR #183)
-
-### Fixed
-- Workaround potential bug in cpython with Zero Width No-Break Space located in Arabic Presentation Forms-B, Unicode 1.1 not acknowledged as space (PR #175)
-- CLI default threshold aligned with the API threshold from [@oleksandr-kuzmenko](https://github.com/oleksandr-kuzmenko) (PR #181)
-
-### Removed
-- Support for Python 3.5 (PR #192)
-
-### Deprecated
-- Use of backport unicodedata from `unicodedata2` as Python is quickly catching up, scheduled for removal in 3.0 (PR #194)
-
-## [2.0.12](https://github.com/Ousret/charset_normalizer/compare/2.0.11...2.0.12) (2022-02-12)
-
-### Fixed
-- ASCII miss-detection on rare cases (PR #170) 
-
-## [2.0.11](https://github.com/Ousret/charset_normalizer/compare/2.0.10...2.0.11) (2022-01-30)
-
-### Added
-- Explicit support for Python 3.11 (PR #164)
-
-### Changed
-- The logging behavior have been completely reviewed, now using only TRACE and DEBUG levels (PR #163 #165)
-
-## [2.0.10](https://github.com/Ousret/charset_normalizer/compare/2.0.9...2.0.10) (2022-01-04)
-
-### Fixed
-- Fallback match entries might lead to UnicodeDecodeError for large bytes sequence (PR #154)
-
-### Changed
-- Skipping the language-detection (CD) on ASCII (PR #155)
-
-## [2.0.9](https://github.com/Ousret/charset_normalizer/compare/2.0.8...2.0.9) (2021-12-03)
-
-### Changed
-- Moderating the logging impact (since 2.0.8) for specific environments (PR #147)
-
-### Fixed
-- Wrong logging level applied when setting kwarg `explain` to True (PR #146)
-
-## [2.0.8](https://github.com/Ousret/charset_normalizer/compare/2.0.7...2.0.8) (2021-11-24)
-### Changed
-- Improvement over Vietnamese detection (PR #126)
-- MD improvement on trailing data and long foreign (non-pure latin) data (PR #124)
-- Efficiency improvements in cd/alphabet_languages from [@adbar](https://github.com/adbar) (PR #122)
-- call sum() without an intermediary list following PEP 289 recommendations from [@adbar](https://github.com/adbar) (PR #129)
-- Code style as refactored by Sourcery-AI (PR #131) 
-- Minor adjustment on the MD around european words (PR #133)
-- Remove and replace SRTs from assets / tests (PR #139)
-- Initialize the library logger with a `NullHandler` by default from [@nmaynes](https://github.com/nmaynes) (PR #135)
-- Setting kwarg `explain` to True will add provisionally (bounded to function lifespan) a specific stream handler (PR #135)
-
-### Fixed
-- Fix large (misleading) sequence giving UnicodeDecodeError (PR #137)
-- Avoid using too insignificant chunk (PR #137)
-
-### Added
-- Add and expose function `set_logging_handler` to configure a specific StreamHandler from [@nmaynes](https://github.com/nmaynes) (PR #135)
-- Add `CHANGELOG.md` entries, format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/) (PR #141)
-
-## [2.0.7](https://github.com/Ousret/charset_normalizer/compare/2.0.6...2.0.7) (2021-10-11)
-### Added
-- Add support for Kazakh (Cyrillic) language detection (PR #109)
-
-### Changed
-- Further, improve inferring the language from a given single-byte code page (PR #112)
-- Vainly trying to leverage PEP263 when PEP3120 is not supported (PR #116)
-- Refactoring for potential performance improvements in loops from [@adbar](https://github.com/adbar) (PR #113)
-- Various detection improvement (MD+CD) (PR #117)
-
-### Removed
-- Remove redundant logging entry about detected language(s) (PR #115)
-
-### Fixed
-- Fix a minor inconsistency between Python 3.5 and other versions regarding language detection (PR #117 #102)
-
-## [2.0.6](https://github.com/Ousret/charset_normalizer/compare/2.0.5...2.0.6) (2021-09-18)
-### Fixed
-- Unforeseen regression with the loss of the backward-compatibility with some older minor of Python 3.5.x (PR #100)
-- Fix CLI crash when using --minimal output in certain cases (PR #103)
-
-### Changed
-- Minor improvement to the detection efficiency (less than 1%) (PR #106 #101)
-
-## [2.0.5](https://github.com/Ousret/charset_normalizer/compare/2.0.4...2.0.5) (2021-09-14)
-### Changed
-- The project now comply with: flake8, mypy, isort and black to ensure a better overall quality (PR #81)
-- The BC-support with v1.x was improved, the old staticmethods are restored (PR #82)
-- The Unicode detection is slightly improved (PR #93)
-- Add syntax sugar \_\_bool\_\_ for results CharsetMatches list-container (PR #91)
-
-### Removed
-- The project no longer raise warning on tiny content given for detection, will be simply logged as warning instead (PR #92)
-
-### Fixed
-- In some rare case, the chunks extractor could cut in the middle of a multi-byte character and could mislead the mess detection (PR #95)
-- Some rare 'space' characters could trip up the UnprintablePlugin/Mess detection (PR #96)
-- The MANIFEST.in was not exhaustive (PR #78)
-
-## [2.0.4](https://github.com/Ousret/charset_normalizer/compare/2.0.3...2.0.4) (2021-07-30)
-### Fixed
-- The CLI no longer raise an unexpected exception when no encoding has been found (PR #70)
-- Fix accessing the 'alphabets' property when the payload contains surrogate characters (PR #68)
-- The logger could mislead (explain=True) on detected languages and the impact of one MBCS match (PR #72)
-- Submatch factoring could be wrong in rare edge cases (PR #72)
-- Multiple files given to the CLI were ignored when publishing results to STDOUT. (After the first path) (PR #72)
-- Fix line endings from CRLF to LF for certain project files (PR #67)
-
-### Changed
-- Adjust the MD to lower the sensitivity, thus improving the global detection reliability (PR #69 #76)
-- Allow fallback on specified encoding if any (PR #71)
-
-## [2.0.3](https://github.com/Ousret/charset_normalizer/compare/2.0.2...2.0.3) (2021-07-16)
-### Changed
-- Part of the detection mechanism has been improved to be less sensitive, resulting in more accurate detection results. Especially ASCII. (PR #63)
-- According to the community wishes, the detection will fall back on ASCII or UTF-8 in a last-resort case. (PR #64)
-
-## [2.0.2](https://github.com/Ousret/charset_normalizer/compare/2.0.1...2.0.2) (2021-07-15)
-### Fixed
-- Empty/Too small JSON payload miss-detection fixed. Report from [@tseaver](https://github.com/tseaver) (PR #59) 
-
-### Changed
-- Don't inject unicodedata2 into sys.modules from [@akx](https://github.com/akx) (PR #57)
-
-## [2.0.1](https://github.com/Ousret/charset_normalizer/compare/2.0.0...2.0.1) (2021-07-13)
-### Fixed
-- Make it work where there isn't a filesystem available, dropping assets frequencies.json. Report from [@sethmlarson](https://github.com/sethmlarson). (PR #55)
-- Using explain=False permanently disable the verbose output in the current runtime (PR #47)
-- One log entry (language target preemptive) was not show in logs when using explain=True (PR #47)
-- Fix undesired exception (ValueError) on getitem of instance CharsetMatches (PR #52)
-
-### Changed
-- Public function normalize default args values were not aligned with from_bytes (PR #53)
-
-### Added
-- You may now use charset aliases in cp_isolation and cp_exclusion arguments (PR #47)
-
-## [2.0.0](https://github.com/Ousret/charset_normalizer/compare/1.4.1...2.0.0) (2021-07-02)
-### Changed
-- 4x to 5 times faster than the previous 1.4.0 release. At least 2x faster than Chardet.
-- Accent has been made on UTF-8 detection, should perform rather instantaneous.
-- The backward compatibility with Chardet has been greatly improved. The legacy detect function returns an identical charset name whenever possible.
-- The detection mechanism has been slightly improved, now Turkish content is detected correctly (most of the time)
-- The program has been rewritten to ease the readability and maintainability. (+Using static typing)+
-- utf_7 detection has been reinstated.
-
-### Removed
-- This package no longer require anything when used with Python 3.5 (Dropped cached_property)
-- Removed support for these languages: Catalan, Esperanto, Kazakh, Baque, Volapük, Azeri, Galician, Nynorsk, Macedonian, and Serbocroatian.
-- The exception hook on UnicodeDecodeError has been removed.
-
-### Deprecated
-- Methods coherence_non_latin, w_counter, chaos_secondary_pass of the class CharsetMatch are now deprecated and scheduled for removal in v3.0
-
-### Fixed
-- The CLI output used the relative path of the file(s). Should be absolute.
-
-## [1.4.1](https://github.com/Ousret/charset_normalizer/compare/1.4.0...1.4.1) (2021-05-28)
-### Fixed
-- Logger configuration/usage no longer conflict with others (PR #44)
-
-## [1.4.0](https://github.com/Ousret/charset_normalizer/compare/1.3.9...1.4.0) (2021-05-21)
-### Removed
-- Using standard logging instead of using the package loguru.
-- Dropping nose test framework in favor of the maintained pytest.
-- Choose to not use dragonmapper package to help with gibberish Chinese/CJK text.
-- Require cached_property only for Python 3.5 due to constraint. Dropping for every other interpreter version.
-- Stop support for UTF-7 that does not contain a SIG.
-- Dropping PrettyTable, replaced with pure JSON output in CLI.
-
-### Fixed
-- BOM marker in a CharsetNormalizerMatch instance could be False in rare cases even if obviously present. Due to the sub-match factoring process.
-- Not searching properly for the BOM when trying utf32/16 parent codec.
-
-### Changed
-- Improving the package final size by compressing frequencies.json.
-- Huge improvement over the larges payload.
-
-### Added
-- CLI now produces JSON consumable output.
-- Return ASCII if given sequences fit. Given reasonable confidence.
-
-## [1.3.9](https://github.com/Ousret/charset_normalizer/compare/1.3.8...1.3.9) (2021-05-13)
-
-### Fixed
-- In some very rare cases, you may end up getting encode/decode errors due to a bad bytes payload (PR #40)
-
-## [1.3.8](https://github.com/Ousret/charset_normalizer/compare/1.3.7...1.3.8) (2021-05-12)
-
-### Fixed
-- Empty given payload for detection may cause an exception if trying to access the `alphabets` property. (PR #39)
-
-## [1.3.7](https://github.com/Ousret/charset_normalizer/compare/1.3.6...1.3.7) (2021-05-12)
-
-### Fixed
-- The legacy detect function should return UTF-8-SIG if sig is present in the payload. (PR #38)
-
-## [1.3.6](https://github.com/Ousret/charset_normalizer/compare/1.3.5...1.3.6) (2021-02-09)
-
-### Changed
-- Amend the previous release to allow prettytable 2.0 (PR #35)
-
-## [1.3.5](https://github.com/Ousret/charset_normalizer/compare/1.3.4...1.3.5) (2021-02-08)
-
-### Fixed
-- Fix error while using the package with a python pre-release interpreter (PR #33)
-
-### Changed
-- Dependencies refactoring, constraints revised.
-
-### Added
-- Add python 3.9 and 3.10 to the supported interpreters
-
-MIT License
-
-Copyright (c) 2019 TAHRI Ahmed R.
-
-Permission is hereby granted, free of charge, to any person obtaining a copy
-of this software and associated documentation files (the "Software"), to deal
-in the Software without restriction, including without limitation the rights
-to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
-copies of the Software, and to permit persons to whom the Software is
-furnished to do so, subject to the following conditions:
-
-The above copyright notice and this permission notice shall be included in all
-copies or substantial portions of the Software.
-
-THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
-IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
-FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
-AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
-LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
-OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
-SOFTWARE.

path/to/venv/lib/python3.12/site-packages/charset_normalizer-3.3.2.dist-info/RECORD

@@ -1,35 +0,0 @@
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-charset_normalizer-3.3.2.dist-info/INSTALLER,sha256=zuuue4knoyJ-UwPPXg8fezS7VCrXJQrAP7zeNuwvFQg,4
-charset_normalizer-3.3.2.dist-info/LICENSE,sha256=6zGgxaT7Cbik4yBV0lweX5w1iidS_vPNcgIT0cz-4kE,1070
-charset_normalizer-3.3.2.dist-info/METADATA,sha256=cfLhl5A6SI-F0oclm8w8ux9wshL1nipdeCdVnYb4AaA,33550
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-charset_normalizer-3.3.2.dist-info/WHEEL,sha256=FCrbbeH_Uuw2ZMaB8nW-JE7XeUWVfF-XtWcVJYU0Zm8,110
-charset_normalizer-3.3.2.dist-info/entry_points.txt,sha256=ADSTKrkXZ3hhdOVFi6DcUEHQRS0xfxDIE_pEz4wLIXA,65
-charset_normalizer-3.3.2.dist-info/top_level.txt,sha256=7ASyzePr8_xuZWJsnqJjIBtyV8vhEo0wBCv1MPRRi3Q,19
-charset_normalizer/__init__.py,sha256=UzI3xC8PhmcLRMzSgPb6minTmRq0kWznnCBJ8ZCc2XI,1577
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path/to/venv/lib/python3.12/site-packages/charset_normalizer-3.3.2.dist-info/WHEEL

@@ -1,5 +0,0 @@
-Wheel-Version: 1.0
-Generator: bdist_wheel (0.41.2)
-Root-Is-Purelib: false
-Tag: cp312-cp312-macosx_11_0_arm64
-

path/to/venv/lib/python3.12/site-packages/charset_normalizer-3.3.2.dist-info/entry_points.txt

@@ -1,2 +0,0 @@
-[console_scripts]
-normalizer = charset_normalizer.cli:cli_detect

path/to/venv/lib/python3.12/site-packages/charset_normalizer-3.3.2.dist-info/top_level.txt

@@ -1 +0,0 @@
-charset_normalizer

path/to/venv/lib/python3.12/site-packages/charset_normalizer/__init__.py

@@ -1,46 +0,0 @@
-# -*- coding: utf-8 -*-
-"""
-Charset-Normalizer
-~~~~~~~~~~~~~~
-The Real First Universal Charset Detector.
-A library that helps you read text from an unknown charset encoding.
-Motivated by chardet, This package is trying to resolve the issue by taking a new approach.
-All IANA character set names for which the Python core library provides codecs are supported.
-
-Basic usage:
-   >>> from charset_normalizer import from_bytes
-   >>> results = from_bytes('Bсеки човек има право на образование. Oбразованието!'.encode('utf_8'))
-   >>> best_guess = results.best()
-   >>> str(best_guess)
-   'Bсеки човек има право на образование. Oбразованието!'
-
-Others methods and usages are available - see the full documentation
-at <https://github.com/Ousret/charset_normalizer>.
-:copyright: (c) 2021 by Ahmed TAHRI
-:license: MIT, see LICENSE for more details.
-"""
-import logging
-
-from .api import from_bytes, from_fp, from_path, is_binary
-from .legacy import detect
-from .models import CharsetMatch, CharsetMatches
-from .utils import set_logging_handler
-from .version import VERSION, __version__
-
-__all__ = (
-    "from_fp",
-    "from_path",
-    "from_bytes",
-    "is_binary",
-    "detect",
-    "CharsetMatch",
-    "CharsetMatches",
-    "__version__",
-    "VERSION",
-    "set_logging_handler",
-)
-
-# Attach a NullHandler to the top level logger by default
-# https://docs.python.org/3.3/howto/logging.html#configuring-logging-for-a-library
-
-logging.getLogger("charset_normalizer").addHandler(logging.NullHandler())

path/to/venv/lib/python3.12/site-packages/charset_normalizer/__main__.py

@@ -1,4 +0,0 @@
-from .cli import cli_detect
-
-if __name__ == "__main__":
-    cli_detect()

path/to/venv/lib/python3.12/site-packages/charset_normalizer/api.py

@@ -1,626 +0,0 @@
-import logging
-from os import PathLike
-from typing import BinaryIO, List, Optional, Set, Union
-
-from .cd import (
-    coherence_ratio,
-    encoding_languages,
-    mb_encoding_languages,
-    merge_coherence_ratios,
-)
-from .constant import IANA_SUPPORTED, TOO_BIG_SEQUENCE, TOO_SMALL_SEQUENCE, TRACE
-from .md import mess_ratio
-from .models import CharsetMatch, CharsetMatches
-from .utils import (
-    any_specified_encoding,
-    cut_sequence_chunks,
-    iana_name,
-    identify_sig_or_bom,
-    is_cp_similar,
-    is_multi_byte_encoding,
-    should_strip_sig_or_bom,
-)
-
-# Will most likely be controversial
-# logging.addLevelName(TRACE, "TRACE")
-logger = logging.getLogger("charset_normalizer")
-explain_handler = logging.StreamHandler()
-explain_handler.setFormatter(
-    logging.Formatter("%(asctime)s | %(levelname)s | %(message)s")
-)
-
-
-def from_bytes(
-    sequences: Union[bytes, bytearray],
-    steps: int = 5,
-    chunk_size: int = 512,
-    threshold: float = 0.2,
-    cp_isolation: Optional[List[str]] = None,
-    cp_exclusion: Optional[List[str]] = None,
-    preemptive_behaviour: bool = True,
-    explain: bool = False,
-    language_threshold: float = 0.1,
-    enable_fallback: bool = True,
-) -> CharsetMatches:
-    """
-    Given a raw bytes sequence, return the best possibles charset usable to render str objects.
-    If there is no results, it is a strong indicator that the source is binary/not text.
-    By default, the process will extract 5 blocks of 512o each to assess the mess and coherence of a given sequence.
-    And will give up a particular code page after 20% of measured mess. Those criteria are customizable at will.
-
-    The preemptive behavior DOES NOT replace the traditional detection workflow, it prioritize a particular code page
-    but never take it for granted. Can improve the performance.
-
-    You may want to focus your attention to some code page or/and not others, use cp_isolation and cp_exclusion for that
-    purpose.
-
-    This function will strip the SIG in the payload/sequence every time except on UTF-16, UTF-32.
-    By default the library does not setup any handler other than the NullHandler, if you choose to set the 'explain'
-    toggle to True it will alter the logger configuration to add a StreamHandler that is suitable for debugging.
-    Custom logging format and handler can be set manually.
-    """
-
-    if not isinstance(sequences, (bytearray, bytes)):
-        raise TypeError(
-            "Expected object of type bytes or bytearray, got: {0}".format(
-                type(sequences)
-            )
-        )
-
-    if explain:
-        previous_logger_level: int = logger.level
-        logger.addHandler(explain_handler)
-        logger.setLevel(TRACE)
-
-    length: int = len(sequences)
-
-    if length == 0:
-        logger.debug("Encoding detection on empty bytes, assuming utf_8 intention.")
-        if explain:
-            logger.removeHandler(explain_handler)
-            logger.setLevel(previous_logger_level or logging.WARNING)
-        return CharsetMatches([CharsetMatch(sequences, "utf_8", 0.0, False, [], "")])
-
-    if cp_isolation is not None:
-        logger.log(
-            TRACE,
-            "cp_isolation is set. use this flag for debugging purpose. "
-            "limited list of encoding allowed : %s.",
-            ", ".join(cp_isolation),
-        )
-        cp_isolation = [iana_name(cp, False) for cp in cp_isolation]
-    else:
-        cp_isolation = []
-
-    if cp_exclusion is not None:
-        logger.log(
-            TRACE,
-            "cp_exclusion is set. use this flag for debugging purpose. "
-            "limited list of encoding excluded : %s.",
-            ", ".join(cp_exclusion),
-        )
-        cp_exclusion = [iana_name(cp, False) for cp in cp_exclusion]
-    else:
-        cp_exclusion = []
-
-    if length <= (chunk_size * steps):
-        logger.log(
-            TRACE,
-            "override steps (%i) and chunk_size (%i) as content does not fit (%i byte(s) given) parameters.",
-            steps,
-            chunk_size,
-            length,
-        )
-        steps = 1
-        chunk_size = length
-
-    if steps > 1 and length / steps < chunk_size:
-        chunk_size = int(length / steps)
-
-    is_too_small_sequence: bool = len(sequences) < TOO_SMALL_SEQUENCE
-    is_too_large_sequence: bool = len(sequences) >= TOO_BIG_SEQUENCE
-
-    if is_too_small_sequence:
-        logger.log(
-            TRACE,
-            "Trying to detect encoding from a tiny portion of ({}) byte(s).".format(
-                length
-            ),
-        )
-    elif is_too_large_sequence:
-        logger.log(
-            TRACE,
-            "Using lazy str decoding because the payload is quite large, ({}) byte(s).".format(
-                length
-            ),
-        )
-
-    prioritized_encodings: List[str] = []
-
-    specified_encoding: Optional[str] = (
-        any_specified_encoding(sequences) if preemptive_behaviour else None
-    )
-
-    if specified_encoding is not None:
-        prioritized_encodings.append(specified_encoding)
-        logger.log(
-            TRACE,
-            "Detected declarative mark in sequence. Priority +1 given for %s.",
-            specified_encoding,
-        )
-
-    tested: Set[str] = set()
-    tested_but_hard_failure: List[str] = []
-    tested_but_soft_failure: List[str] = []
-
-    fallback_ascii: Optional[CharsetMatch] = None
-    fallback_u8: Optional[CharsetMatch] = None
-    fallback_specified: Optional[CharsetMatch] = None
-
-    results: CharsetMatches = CharsetMatches()
-
-    sig_encoding, sig_payload = identify_sig_or_bom(sequences)
-
-    if sig_encoding is not None:
-        prioritized_encodings.append(sig_encoding)
-        logger.log(
-            TRACE,
-            "Detected a SIG or BOM mark on first %i byte(s). Priority +1 given for %s.",
-            len(sig_payload),
-            sig_encoding,
-        )
-
-    prioritized_encodings.append("ascii")
-
-    if "utf_8" not in prioritized_encodings:
-        prioritized_encodings.append("utf_8")
-
-    for encoding_iana in prioritized_encodings + IANA_SUPPORTED:
-        if cp_isolation and encoding_iana not in cp_isolation:
-            continue
-
-        if cp_exclusion and encoding_iana in cp_exclusion:
-            continue
-
-        if encoding_iana in tested:
-            continue
-
-        tested.add(encoding_iana)
-
-        decoded_payload: Optional[str] = None
-        bom_or_sig_available: bool = sig_encoding == encoding_iana
-        strip_sig_or_bom: bool = bom_or_sig_available and should_strip_sig_or_bom(
-            encoding_iana
-        )
-
-        if encoding_iana in {"utf_16", "utf_32"} and not bom_or_sig_available:
-            logger.log(
-                TRACE,
-                "Encoding %s won't be tested as-is because it require a BOM. Will try some sub-encoder LE/BE.",
-                encoding_iana,
-            )
-            continue
-        if encoding_iana in {"utf_7"} and not bom_or_sig_available:
-            logger.log(
-                TRACE,
-                "Encoding %s won't be tested as-is because detection is unreliable without BOM/SIG.",
-                encoding_iana,
-            )
-            continue
-
-        try:
-            is_multi_byte_decoder: bool = is_multi_byte_encoding(encoding_iana)
-        except (ModuleNotFoundError, ImportError):
-            logger.log(
-                TRACE,
-                "Encoding %s does not provide an IncrementalDecoder",
-                encoding_iana,
-            )
-            continue
-
-        try:
-            if is_too_large_sequence and is_multi_byte_decoder is False:
-                str(
-                    sequences[: int(50e4)]
-                    if strip_sig_or_bom is False
-                    else sequences[len(sig_payload) : int(50e4)],
-                    encoding=encoding_iana,
-                )
-            else:
-                decoded_payload = str(
-                    sequences
-                    if strip_sig_or_bom is False
-                    else sequences[len(sig_payload) :],
-                    encoding=encoding_iana,
-                )
-        except (UnicodeDecodeError, LookupError) as e:
-            if not isinstance(e, LookupError):
-                logger.log(
-                    TRACE,
-                    "Code page %s does not fit given bytes sequence at ALL. %s",
-                    encoding_iana,
-                    str(e),
-                )
-            tested_but_hard_failure.append(encoding_iana)
-            continue
-
-        similar_soft_failure_test: bool = False
-
-        for encoding_soft_failed in tested_but_soft_failure:
-            if is_cp_similar(encoding_iana, encoding_soft_failed):
-                similar_soft_failure_test = True
-                break
-
-        if similar_soft_failure_test:
-            logger.log(
-                TRACE,
-                "%s is deemed too similar to code page %s and was consider unsuited already. Continuing!",
-                encoding_iana,
-                encoding_soft_failed,
-            )
-            continue
-
-        r_ = range(
-            0 if not bom_or_sig_available else len(sig_payload),
-            length,
-            int(length / steps),
-        )
-
-        multi_byte_bonus: bool = (
-            is_multi_byte_decoder
-            and decoded_payload is not None
-            and len(decoded_payload) < length
-        )
-
-        if multi_byte_bonus:
-            logger.log(
-                TRACE,
-                "Code page %s is a multi byte encoding table and it appear that at least one character "
-                "was encoded using n-bytes.",
-                encoding_iana,
-            )
-
-        max_chunk_gave_up: int = int(len(r_) / 4)
-
-        max_chunk_gave_up = max(max_chunk_gave_up, 2)
-        early_stop_count: int = 0
-        lazy_str_hard_failure = False
-
-        md_chunks: List[str] = []
-        md_ratios = []
-
-        try:
-            for chunk in cut_sequence_chunks(
-                sequences,
-                encoding_iana,
-                r_,
-                chunk_size,
-                bom_or_sig_available,
-                strip_sig_or_bom,
-                sig_payload,
-                is_multi_byte_decoder,
-                decoded_payload,
-            ):
-                md_chunks.append(chunk)
-
-                md_ratios.append(
-                    mess_ratio(
-                        chunk,
-                        threshold,
-                        explain is True and 1 <= len(cp_isolation) <= 2,
-                    )
-                )
-
-                if md_ratios[-1] >= threshold:
-                    early_stop_count += 1
-
-                if (early_stop_count >= max_chunk_gave_up) or (
-                    bom_or_sig_available and strip_sig_or_bom is False
-                ):
-                    break
-        except (
-            UnicodeDecodeError
-        ) as e:  # Lazy str loading may have missed something there
-            logger.log(
-                TRACE,
-                "LazyStr Loading: After MD chunk decode, code page %s does not fit given bytes sequence at ALL. %s",
-                encoding_iana,
-                str(e),
-            )
-            early_stop_count = max_chunk_gave_up
-            lazy_str_hard_failure = True
-
-        # We might want to check the sequence again with the whole content
-        # Only if initial MD tests passes
-        if (
-            not lazy_str_hard_failure
-            and is_too_large_sequence
-            and not is_multi_byte_decoder
-        ):
-            try:
-                sequences[int(50e3) :].decode(encoding_iana, errors="strict")
-            except UnicodeDecodeError as e:
-                logger.log(
-                    TRACE,
-                    "LazyStr Loading: After final lookup, code page %s does not fit given bytes sequence at ALL. %s",
-                    encoding_iana,
-                    str(e),
-                )
-                tested_but_hard_failure.append(encoding_iana)
-                continue
-
-        mean_mess_ratio: float = sum(md_ratios) / len(md_ratios) if md_ratios else 0.0
-        if mean_mess_ratio >= threshold or early_stop_count >= max_chunk_gave_up:
-            tested_but_soft_failure.append(encoding_iana)
-            logger.log(
-                TRACE,
-                "%s was excluded because of initial chaos probing. Gave up %i time(s). "
-                "Computed mean chaos is %f %%.",
-                encoding_iana,
-                early_stop_count,
-                round(mean_mess_ratio * 100, ndigits=3),
-            )
-            # Preparing those fallbacks in case we got nothing.
-            if (
-                enable_fallback
-                and encoding_iana in ["ascii", "utf_8", specified_encoding]
-                and not lazy_str_hard_failure
-            ):
-                fallback_entry = CharsetMatch(
-                    sequences, encoding_iana, threshold, False, [], decoded_payload
-                )
-                if encoding_iana == specified_encoding:
-                    fallback_specified = fallback_entry
-                elif encoding_iana == "ascii":
-                    fallback_ascii = fallback_entry
-                else:
-                    fallback_u8 = fallback_entry
-            continue
-
-        logger.log(
-            TRACE,
-            "%s passed initial chaos probing. Mean measured chaos is %f %%",
-            encoding_iana,
-            round(mean_mess_ratio * 100, ndigits=3),
-        )
-
-        if not is_multi_byte_decoder:
-            target_languages: List[str] = encoding_languages(encoding_iana)
-        else:
-            target_languages = mb_encoding_languages(encoding_iana)
-
-        if target_languages:
-            logger.log(
-                TRACE,
-                "{} should target any language(s) of {}".format(
-                    encoding_iana, str(target_languages)
-                ),
-            )
-
-        cd_ratios = []
-
-        # We shall skip the CD when its about ASCII
-        # Most of the time its not relevant to run "language-detection" on it.
-        if encoding_iana != "ascii":
-            for chunk in md_chunks:
-                chunk_languages = coherence_ratio(
-                    chunk,
-                    language_threshold,
-                    ",".join(target_languages) if target_languages else None,
-                )
-
-                cd_ratios.append(chunk_languages)
-
-        cd_ratios_merged = merge_coherence_ratios(cd_ratios)
-
-        if cd_ratios_merged:
-            logger.log(
-                TRACE,
-                "We detected language {} using {}".format(
-                    cd_ratios_merged, encoding_iana
-                ),
-            )
-
-        results.append(
-            CharsetMatch(
-                sequences,
-                encoding_iana,
-                mean_mess_ratio,
-                bom_or_sig_available,
-                cd_ratios_merged,
-                decoded_payload,
-            )
-        )
-
-        if (
-            encoding_iana in [specified_encoding, "ascii", "utf_8"]
-            and mean_mess_ratio < 0.1
-        ):
-            logger.debug(
-                "Encoding detection: %s is most likely the one.", encoding_iana
-            )
-            if explain:
-                logger.removeHandler(explain_handler)
-                logger.setLevel(previous_logger_level)
-            return CharsetMatches([results[encoding_iana]])
-
-        if encoding_iana == sig_encoding:
-            logger.debug(
-                "Encoding detection: %s is most likely the one as we detected a BOM or SIG within "
-                "the beginning of the sequence.",
-                encoding_iana,
-            )
-            if explain:
-                logger.removeHandler(explain_handler)
-                logger.setLevel(previous_logger_level)
-            return CharsetMatches([results[encoding_iana]])
-
-    if len(results) == 0:
-        if fallback_u8 or fallback_ascii or fallback_specified:
-            logger.log(
-                TRACE,
-                "Nothing got out of the detection process. Using ASCII/UTF-8/Specified fallback.",
-            )
-
-        if fallback_specified:
-            logger.debug(
-                "Encoding detection: %s will be used as a fallback match",
-                fallback_specified.encoding,
-            )
-            results.append(fallback_specified)
-        elif (
-            (fallback_u8 and fallback_ascii is None)
-            or (
-                fallback_u8
-                and fallback_ascii
-                and fallback_u8.fingerprint != fallback_ascii.fingerprint
-            )
-            or (fallback_u8 is not None)
-        ):
-            logger.debug("Encoding detection: utf_8 will be used as a fallback match")
-            results.append(fallback_u8)
-        elif fallback_ascii:
-            logger.debug("Encoding detection: ascii will be used as a fallback match")
-            results.append(fallback_ascii)
-
-    if results:
-        logger.debug(
-            "Encoding detection: Found %s as plausible (best-candidate) for content. With %i alternatives.",
-            results.best().encoding,  # type: ignore
-            len(results) - 1,
-        )
-    else:
-        logger.debug("Encoding detection: Unable to determine any suitable charset.")
-
-    if explain:
-        logger.removeHandler(explain_handler)
-        logger.setLevel(previous_logger_level)
-
-    return results
-
-
-def from_fp(
-    fp: BinaryIO,
-    steps: int = 5,
-    chunk_size: int = 512,
-    threshold: float = 0.20,
-    cp_isolation: Optional[List[str]] = None,
-    cp_exclusion: Optional[List[str]] = None,
-    preemptive_behaviour: bool = True,
-    explain: bool = False,
-    language_threshold: float = 0.1,
-    enable_fallback: bool = True,
-) -> CharsetMatches:
-    """
-    Same thing than the function from_bytes but using a file pointer that is already ready.
-    Will not close the file pointer.
-    """
-    return from_bytes(
-        fp.read(),
-        steps,
-        chunk_size,
-        threshold,
-        cp_isolation,
-        cp_exclusion,
-        preemptive_behaviour,
-        explain,
-        language_threshold,
-        enable_fallback,
-    )
-
-
-def from_path(
-    path: Union[str, bytes, PathLike],  # type: ignore[type-arg]
-    steps: int = 5,
-    chunk_size: int = 512,
-    threshold: float = 0.20,
-    cp_isolation: Optional[List[str]] = None,
-    cp_exclusion: Optional[List[str]] = None,
-    preemptive_behaviour: bool = True,
-    explain: bool = False,
-    language_threshold: float = 0.1,
-    enable_fallback: bool = True,
-) -> CharsetMatches:
-    """
-    Same thing than the function from_bytes but with one extra step. Opening and reading given file path in binary mode.
-    Can raise IOError.
-    """
-    with open(path, "rb") as fp:
-        return from_fp(
-            fp,
-            steps,
-            chunk_size,
-            threshold,
-            cp_isolation,
-            cp_exclusion,
-            preemptive_behaviour,
-            explain,
-            language_threshold,
-            enable_fallback,
-        )
-
-
-def is_binary(
-    fp_or_path_or_payload: Union[PathLike, str, BinaryIO, bytes],  # type: ignore[type-arg]
-    steps: int = 5,
-    chunk_size: int = 512,
-    threshold: float = 0.20,
-    cp_isolation: Optional[List[str]] = None,
-    cp_exclusion: Optional[List[str]] = None,
-    preemptive_behaviour: bool = True,
-    explain: bool = False,
-    language_threshold: float = 0.1,
-    enable_fallback: bool = False,
-) -> bool:
-    """
-    Detect if the given input (file, bytes, or path) points to a binary file. aka. not a string.
-    Based on the same main heuristic algorithms and default kwargs at the sole exception that fallbacks match
-    are disabled to be stricter around ASCII-compatible but unlikely to be a string.
-    """
-    if isinstance(fp_or_path_or_payload, (str, PathLike)):
-        guesses = from_path(
-            fp_or_path_or_payload,
-            steps=steps,
-            chunk_size=chunk_size,
-            threshold=threshold,
-            cp_isolation=cp_isolation,
-            cp_exclusion=cp_exclusion,
-            preemptive_behaviour=preemptive_behaviour,
-            explain=explain,
-            language_threshold=language_threshold,
-            enable_fallback=enable_fallback,
-        )
-    elif isinstance(
-        fp_or_path_or_payload,
-        (
-            bytes,
-            bytearray,
-        ),
-    ):
-        guesses = from_bytes(
-            fp_or_path_or_payload,
-            steps=steps,
-            chunk_size=chunk_size,
-            threshold=threshold,
-            cp_isolation=cp_isolation,
-            cp_exclusion=cp_exclusion,
-            preemptive_behaviour=preemptive_behaviour,
-            explain=explain,
-            language_threshold=language_threshold,
-            enable_fallback=enable_fallback,
-        )
-    else:
-        guesses = from_fp(
-            fp_or_path_or_payload,
-            steps=steps,
-            chunk_size=chunk_size,
-            threshold=threshold,
-            cp_isolation=cp_isolation,
-            cp_exclusion=cp_exclusion,
-            preemptive_behaviour=preemptive_behaviour,
-            explain=explain,
-            language_threshold=language_threshold,
-            enable_fallback=enable_fallback,
-        )
-
-    return not guesses

path/to/venv/lib/python3.12/site-packages/charset_normalizer/cd.py

@@ -1,395 +0,0 @@
-import importlib
-from codecs import IncrementalDecoder
-from collections import Counter
-from functools import lru_cache
-from typing import Counter as TypeCounter, Dict, List, Optional, Tuple
-
-from .constant import (
-    FREQUENCIES,
-    KO_NAMES,
-    LANGUAGE_SUPPORTED_COUNT,
-    TOO_SMALL_SEQUENCE,
-    ZH_NAMES,
-)
-from .md import is_suspiciously_successive_range
-from .models import CoherenceMatches
-from .utils import (
-    is_accentuated,
-    is_latin,
-    is_multi_byte_encoding,
-    is_unicode_range_secondary,
-    unicode_range,
-)
-
-
-def encoding_unicode_range(iana_name: str) -> List[str]:
-    """
-    Return associated unicode ranges in a single byte code page.
-    """
-    if is_multi_byte_encoding(iana_name):
-        raise IOError("Function not supported on multi-byte code page")
-
-    decoder = importlib.import_module(
-        "encodings.{}".format(iana_name)
-    ).IncrementalDecoder
-
-    p: IncrementalDecoder = decoder(errors="ignore")
-    seen_ranges: Dict[str, int] = {}
-    character_count: int = 0
-
-    for i in range(0x40, 0xFF):
-        chunk: str = p.decode(bytes([i]))
-
-        if chunk:
-            character_range: Optional[str] = unicode_range(chunk)
-
-            if character_range is None:
-                continue
-
-            if is_unicode_range_secondary(character_range) is False:
-                if character_range not in seen_ranges:
-                    seen_ranges[character_range] = 0
-                seen_ranges[character_range] += 1
-                character_count += 1
-
-    return sorted(
-        [
-            character_range
-            for character_range in seen_ranges
-            if seen_ranges[character_range] / character_count >= 0.15
-        ]
-    )
-
-
-def unicode_range_languages(primary_range: str) -> List[str]:
-    """
-    Return inferred languages used with a unicode range.
-    """
-    languages: List[str] = []
-
-    for language, characters in FREQUENCIES.items():
-        for character in characters:
-            if unicode_range(character) == primary_range:
-                languages.append(language)
-                break
-
-    return languages
-
-
-@lru_cache()
-def encoding_languages(iana_name: str) -> List[str]:
-    """
-    Single-byte encoding language association. Some code page are heavily linked to particular language(s).
-    This function does the correspondence.
-    """
-    unicode_ranges: List[str] = encoding_unicode_range(iana_name)
-    primary_range: Optional[str] = None
-
-    for specified_range in unicode_ranges:
-        if "Latin" not in specified_range:
-            primary_range = specified_range
-            break
-
-    if primary_range is None:
-        return ["Latin Based"]
-
-    return unicode_range_languages(primary_range)
-
-
-@lru_cache()
-def mb_encoding_languages(iana_name: str) -> List[str]:
-    """
-    Multi-byte encoding language association. Some code page are heavily linked to particular language(s).
-    This function does the correspondence.
-    """
-    if (
-        iana_name.startswith("shift_")
-        or iana_name.startswith("iso2022_jp")
-        or iana_name.startswith("euc_j")
-        or iana_name == "cp932"
-    ):
-        return ["Japanese"]
-    if iana_name.startswith("gb") or iana_name in ZH_NAMES:
-        return ["Chinese"]
-    if iana_name.startswith("iso2022_kr") or iana_name in KO_NAMES:
-        return ["Korean"]
-
-    return []
-
-
-@lru_cache(maxsize=LANGUAGE_SUPPORTED_COUNT)
-def get_target_features(language: str) -> Tuple[bool, bool]:
-    """
-    Determine main aspects from a supported language if it contains accents and if is pure Latin.
-    """
-    target_have_accents: bool = False
-    target_pure_latin: bool = True
-
-    for character in FREQUENCIES[language]:
-        if not target_have_accents and is_accentuated(character):
-            target_have_accents = True
-        if target_pure_latin and is_latin(character) is False:
-            target_pure_latin = False
-
-    return target_have_accents, target_pure_latin
-
-
-def alphabet_languages(
-    characters: List[str], ignore_non_latin: bool = False
-) -> List[str]:
-    """
-    Return associated languages associated to given characters.
-    """
-    languages: List[Tuple[str, float]] = []
-
-    source_have_accents = any(is_accentuated(character) for character in characters)
-
-    for language, language_characters in FREQUENCIES.items():
-        target_have_accents, target_pure_latin = get_target_features(language)
-
-        if ignore_non_latin and target_pure_latin is False:
-            continue
-
-        if target_have_accents is False and source_have_accents:
-            continue
-
-        character_count: int = len(language_characters)
-
-        character_match_count: int = len(
-            [c for c in language_characters if c in characters]
-        )
-
-        ratio: float = character_match_count / character_count
-
-        if ratio >= 0.2:
-            languages.append((language, ratio))
-
-    languages = sorted(languages, key=lambda x: x[1], reverse=True)
-
-    return [compatible_language[0] for compatible_language in languages]
-
-
-def characters_popularity_compare(
-    language: str, ordered_characters: List[str]
-) -> float:
-    """
-    Determine if a ordered characters list (by occurrence from most appearance to rarest) match a particular language.
-    The result is a ratio between 0. (absolutely no correspondence) and 1. (near perfect fit).
-    Beware that is function is not strict on the match in order to ease the detection. (Meaning close match is 1.)
-    """
-    if language not in FREQUENCIES:
-        raise ValueError("{} not available".format(language))
-
-    character_approved_count: int = 0
-    FREQUENCIES_language_set = set(FREQUENCIES[language])
-
-    ordered_characters_count: int = len(ordered_characters)
-    target_language_characters_count: int = len(FREQUENCIES[language])
-
-    large_alphabet: bool = target_language_characters_count > 26
-
-    for character, character_rank in zip(
-        ordered_characters, range(0, ordered_characters_count)
-    ):
-        if character not in FREQUENCIES_language_set:
-            continue
-
-        character_rank_in_language: int = FREQUENCIES[language].index(character)
-        expected_projection_ratio: float = (
-            target_language_characters_count / ordered_characters_count
-        )
-        character_rank_projection: int = int(character_rank * expected_projection_ratio)
-
-        if (
-            large_alphabet is False
-            and abs(character_rank_projection - character_rank_in_language) > 4
-        ):
-            continue
-
-        if (
-            large_alphabet is True
-            and abs(character_rank_projection - character_rank_in_language)
-            < target_language_characters_count / 3
-        ):
-            character_approved_count += 1
-            continue
-
-        characters_before_source: List[str] = FREQUENCIES[language][
-            0:character_rank_in_language
-        ]
-        characters_after_source: List[str] = FREQUENCIES[language][
-            character_rank_in_language:
-        ]
-        characters_before: List[str] = ordered_characters[0:character_rank]
-        characters_after: List[str] = ordered_characters[character_rank:]
-
-        before_match_count: int = len(
-            set(characters_before) & set(characters_before_source)
-        )
-
-        after_match_count: int = len(
-            set(characters_after) & set(characters_after_source)
-        )
-
-        if len(characters_before_source) == 0 and before_match_count <= 4:
-            character_approved_count += 1
-            continue
-
-        if len(characters_after_source) == 0 and after_match_count <= 4:
-            character_approved_count += 1
-            continue
-
-        if (
-            before_match_count / len(characters_before_source) >= 0.4
-            or after_match_count / len(characters_after_source) >= 0.4
-        ):
-            character_approved_count += 1
-            continue
-
-    return character_approved_count / len(ordered_characters)
-
-
-def alpha_unicode_split(decoded_sequence: str) -> List[str]:
-    """
-    Given a decoded text sequence, return a list of str. Unicode range / alphabet separation.
-    Ex. a text containing English/Latin with a bit a Hebrew will return two items in the resulting list;
-    One containing the latin letters and the other hebrew.
-    """
-    layers: Dict[str, str] = {}
-
-    for character in decoded_sequence:
-        if character.isalpha() is False:
-            continue
-
-        character_range: Optional[str] = unicode_range(character)
-
-        if character_range is None:
-            continue
-
-        layer_target_range: Optional[str] = None
-
-        for discovered_range in layers:
-            if (
-                is_suspiciously_successive_range(discovered_range, character_range)
-                is False
-            ):
-                layer_target_range = discovered_range
-                break
-
-        if layer_target_range is None:
-            layer_target_range = character_range
-
-        if layer_target_range not in layers:
-            layers[layer_target_range] = character.lower()
-            continue
-
-        layers[layer_target_range] += character.lower()
-
-    return list(layers.values())
-
-
-def merge_coherence_ratios(results: List[CoherenceMatches]) -> CoherenceMatches:
-    """
-    This function merge results previously given by the function coherence_ratio.
-    The return type is the same as coherence_ratio.
-    """
-    per_language_ratios: Dict[str, List[float]] = {}
-    for result in results:
-        for sub_result in result:
-            language, ratio = sub_result
-            if language not in per_language_ratios:
-                per_language_ratios[language] = [ratio]
-                continue
-            per_language_ratios[language].append(ratio)
-
-    merge = [
-        (
-            language,
-            round(
-                sum(per_language_ratios[language]) / len(per_language_ratios[language]),
-                4,
-            ),
-        )
-        for language in per_language_ratios
-    ]
-
-    return sorted(merge, key=lambda x: x[1], reverse=True)
-
-
-def filter_alt_coherence_matches(results: CoherenceMatches) -> CoherenceMatches:
-    """
-    We shall NOT return "English—" in CoherenceMatches because it is an alternative
-    of "English". This function only keeps the best match and remove the em-dash in it.
-    """
-    index_results: Dict[str, List[float]] = dict()
-
-    for result in results:
-        language, ratio = result
-        no_em_name: str = language.replace("—", "")
-
-        if no_em_name not in index_results:
-            index_results[no_em_name] = []
-
-        index_results[no_em_name].append(ratio)
-
-    if any(len(index_results[e]) > 1 for e in index_results):
-        filtered_results: CoherenceMatches = []
-
-        for language in index_results:
-            filtered_results.append((language, max(index_results[language])))
-
-        return filtered_results
-
-    return results
-
-
-@lru_cache(maxsize=2048)
-def coherence_ratio(
-    decoded_sequence: str, threshold: float = 0.1, lg_inclusion: Optional[str] = None
-) -> CoherenceMatches:
-    """
-    Detect ANY language that can be identified in given sequence. The sequence will be analysed by layers.
-    A layer = Character extraction by alphabets/ranges.
-    """
-
-    results: List[Tuple[str, float]] = []
-    ignore_non_latin: bool = False
-
-    sufficient_match_count: int = 0
-
-    lg_inclusion_list = lg_inclusion.split(",") if lg_inclusion is not None else []
-    if "Latin Based" in lg_inclusion_list:
-        ignore_non_latin = True
-        lg_inclusion_list.remove("Latin Based")
-
-    for layer in alpha_unicode_split(decoded_sequence):
-        sequence_frequencies: TypeCounter[str] = Counter(layer)
-        most_common = sequence_frequencies.most_common()
-
-        character_count: int = sum(o for c, o in most_common)
-
-        if character_count <= TOO_SMALL_SEQUENCE:
-            continue
-
-        popular_character_ordered: List[str] = [c for c, o in most_common]
-
-        for language in lg_inclusion_list or alphabet_languages(
-            popular_character_ordered, ignore_non_latin
-        ):
-            ratio: float = characters_popularity_compare(
-                language, popular_character_ordered
-            )
-
-            if ratio < threshold:
-                continue
-            elif ratio >= 0.8:
-                sufficient_match_count += 1
-
-            results.append((language, round(ratio, 4)))
-
-            if sufficient_match_count >= 3:
-                break
-
-    return sorted(
-        filter_alt_coherence_matches(results), key=lambda x: x[1], reverse=True
-    )

path/to/venv/lib/python3.12/site-packages/charset_normalizer/cli/__init__.py

@@ -1,6 +0,0 @@
-from .__main__ import cli_detect, query_yes_no
-
-__all__ = (
-    "cli_detect",
-    "query_yes_no",
-)

path/to/venv/lib/python3.12/site-packages/charset_normalizer/cli/__main__.py

@@ -1,296 +0,0 @@
-import argparse
-import sys
-from json import dumps
-from os.path import abspath, basename, dirname, join, realpath
-from platform import python_version
-from typing import List, Optional
-from unicodedata import unidata_version
-
-import charset_normalizer.md as md_module
-from charset_normalizer import from_fp
-from charset_normalizer.models import CliDetectionResult
-from charset_normalizer.version import __version__
-
-
-def query_yes_no(question: str, default: str = "yes") -> bool:
-    """Ask a yes/no question via input() and return their answer.
-
-    "question" is a string that is presented to the user.
-    "default" is the presumed answer if the user just hits <Enter>.
-        It must be "yes" (the default), "no" or None (meaning
-        an answer is required of the user).
-
-    The "answer" return value is True for "yes" or False for "no".
-
-    Credit goes to (c) https://stackoverflow.com/questions/3041986/apt-command-line-interface-like-yes-no-input
-    """
-    valid = {"yes": True, "y": True, "ye": True, "no": False, "n": False}
-    if default is None:
-        prompt = " [y/n] "
-    elif default == "yes":
-        prompt = " [Y/n] "
-    elif default == "no":
-        prompt = " [y/N] "
-    else:
-        raise ValueError("invalid default answer: '%s'" % default)
-
-    while True:
-        sys.stdout.write(question + prompt)
-        choice = input().lower()
-        if default is not None and choice == "":
-            return valid[default]
-        elif choice in valid:
-            return valid[choice]
-        else:
-            sys.stdout.write("Please respond with 'yes' or 'no' " "(or 'y' or 'n').\n")
-
-
-def cli_detect(argv: Optional[List[str]] = None) -> int:
-    """
-    CLI assistant using ARGV and ArgumentParser
-    :param argv:
-    :return: 0 if everything is fine, anything else equal trouble
-    """
-    parser = argparse.ArgumentParser(
-        description="The Real First Universal Charset Detector. "
-        "Discover originating encoding used on text file. "
-        "Normalize text to unicode."
-    )
-
-    parser.add_argument(
-        "files", type=argparse.FileType("rb"), nargs="+", help="File(s) to be analysed"
-    )
-    parser.add_argument(
-        "-v",
-        "--verbose",
-        action="store_true",
-        default=False,
-        dest="verbose",
-        help="Display complementary information about file if any. "
-        "Stdout will contain logs about the detection process.",
-    )
-    parser.add_argument(
-        "-a",
-        "--with-alternative",
-        action="store_true",
-        default=False,
-        dest="alternatives",
-        help="Output complementary possibilities if any. Top-level JSON WILL be a list.",
-    )
-    parser.add_argument(
-        "-n",
-        "--normalize",
-        action="store_true",
-        default=False,
-        dest="normalize",
-        help="Permit to normalize input file. If not set, program does not write anything.",
-    )
-    parser.add_argument(
-        "-m",
-        "--minimal",
-        action="store_true",
-        default=False,
-        dest="minimal",
-        help="Only output the charset detected to STDOUT. Disabling JSON output.",
-    )
-    parser.add_argument(
-        "-r",
-        "--replace",
-        action="store_true",
-        default=False,
-        dest="replace",
-        help="Replace file when trying to normalize it instead of creating a new one.",
-    )
-    parser.add_argument(
-        "-f",
-        "--force",
-        action="store_true",
-        default=False,
-        dest="force",
-        help="Replace file without asking if you are sure, use this flag with caution.",
-    )
-    parser.add_argument(
-        "-t",
-        "--threshold",
-        action="store",
-        default=0.2,
-        type=float,
-        dest="threshold",
-        help="Define a custom maximum amount of chaos allowed in decoded content. 0. <= chaos <= 1.",
-    )
-    parser.add_argument(
-        "--version",
-        action="version",
-        version="Charset-Normalizer {} - Python {} - Unicode {} - SpeedUp {}".format(
-            __version__,
-            python_version(),
-            unidata_version,
-            "OFF" if md_module.__file__.lower().endswith(".py") else "ON",
-        ),
-        help="Show version information and exit.",
-    )
-
-    args = parser.parse_args(argv)
-
-    if args.replace is True and args.normalize is False:
-        print("Use --replace in addition of --normalize only.", file=sys.stderr)
-        return 1
-
-    if args.force is True and args.replace is False:
-        print("Use --force in addition of --replace only.", file=sys.stderr)
-        return 1
-
-    if args.threshold < 0.0 or args.threshold > 1.0:
-        print("--threshold VALUE should be between 0. AND 1.", file=sys.stderr)
-        return 1
-
-    x_ = []
-
-    for my_file in args.files:
-        matches = from_fp(my_file, threshold=args.threshold, explain=args.verbose)
-
-        best_guess = matches.best()
-
-        if best_guess is None:
-            print(
-                'Unable to identify originating encoding for "{}". {}'.format(
-                    my_file.name,
-                    "Maybe try increasing maximum amount of chaos."
-                    if args.threshold < 1.0
-                    else "",
-                ),
-                file=sys.stderr,
-            )
-            x_.append(
-                CliDetectionResult(
-                    abspath(my_file.name),
-                    None,
-                    [],
-                    [],
-                    "Unknown",
-                    [],
-                    False,
-                    1.0,
-                    0.0,
-                    None,
-                    True,
-                )
-            )
-        else:
-            x_.append(
-                CliDetectionResult(
-                    abspath(my_file.name),
-                    best_guess.encoding,
-                    best_guess.encoding_aliases,
-                    [
-                        cp
-                        for cp in best_guess.could_be_from_charset
-                        if cp != best_guess.encoding
-                    ],
-                    best_guess.language,
-                    best_guess.alphabets,
-                    best_guess.bom,
-                    best_guess.percent_chaos,
-                    best_guess.percent_coherence,
-                    None,
-                    True,
-                )
-            )
-
-            if len(matches) > 1 and args.alternatives:
-                for el in matches:
-                    if el != best_guess:
-                        x_.append(
-                            CliDetectionResult(
-                                abspath(my_file.name),
-                                el.encoding,
-                                el.encoding_aliases,
-                                [
-                                    cp
-                                    for cp in el.could_be_from_charset
-                                    if cp != el.encoding
-                                ],
-                                el.language,
-                                el.alphabets,
-                                el.bom,
-                                el.percent_chaos,
-                                el.percent_coherence,
-                                None,
-                                False,
-                            )
-                        )
-
-            if args.normalize is True:
-                if best_guess.encoding.startswith("utf") is True:
-                    print(
-                        '"{}" file does not need to be normalized, as it already came from unicode.'.format(
-                            my_file.name
-                        ),
-                        file=sys.stderr,
-                    )
-                    if my_file.closed is False:
-                        my_file.close()
-                    continue
-
-                dir_path = dirname(realpath(my_file.name))
-                file_name = basename(realpath(my_file.name))
-
-                o_: List[str] = file_name.split(".")
-
-                if args.replace is False:
-                    o_.insert(-1, best_guess.encoding)
-                    if my_file.closed is False:
-                        my_file.close()
-                elif (
-                    args.force is False
-                    and query_yes_no(
-                        'Are you sure to normalize "{}" by replacing it ?'.format(
-                            my_file.name
-                        ),
-                        "no",
-                    )
-                    is False
-                ):
-                    if my_file.closed is False:
-                        my_file.close()
-                    continue
-
-                try:
-                    x_[0].unicode_path = join(dir_path, ".".join(o_))
-
-                    with open(x_[0].unicode_path, "w", encoding="utf-8") as fp:
-                        fp.write(str(best_guess))
-                except IOError as e:
-                    print(str(e), file=sys.stderr)
-                    if my_file.closed is False:
-                        my_file.close()
-                    return 2
-
-        if my_file.closed is False:
-            my_file.close()
-
-    if args.minimal is False:
-        print(
-            dumps(
-                [el.__dict__ for el in x_] if len(x_) > 1 else x_[0].__dict__,
-                ensure_ascii=True,
-                indent=4,
-            )
-        )
-    else:
-        for my_file in args.files:
-            print(
-                ", ".join(
-                    [
-                        el.encoding or "undefined"
-                        for el in x_
-                        if el.path == abspath(my_file.name)
-                    ]
-                )
-            )
-
-    return 0
-
-
-if __name__ == "__main__":
-    cli_detect()

path/to/venv/lib/python3.12/site-packages/charset_normalizer/constant.py

@@ -1,1995 +0,0 @@
-# -*- coding: utf-8 -*-
-from codecs import BOM_UTF8, BOM_UTF16_BE, BOM_UTF16_LE, BOM_UTF32_BE, BOM_UTF32_LE
-from encodings.aliases import aliases
-from re import IGNORECASE, compile as re_compile
-from typing import Dict, List, Set, Union
-
-# Contain for each eligible encoding a list of/item bytes SIG/BOM
-ENCODING_MARKS: Dict[str, Union[bytes, List[bytes]]] = {
-    "utf_8": BOM_UTF8,
-    "utf_7": [
-        b"\x2b\x2f\x76\x38",
-        b"\x2b\x2f\x76\x39",
-        b"\x2b\x2f\x76\x2b",
-        b"\x2b\x2f\x76\x2f",
-        b"\x2b\x2f\x76\x38\x2d",
-    ],
-    "gb18030": b"\x84\x31\x95\x33",
-    "utf_32": [BOM_UTF32_BE, BOM_UTF32_LE],
-    "utf_16": [BOM_UTF16_BE, BOM_UTF16_LE],
-}
-
-TOO_SMALL_SEQUENCE: int = 32
-TOO_BIG_SEQUENCE: int = int(10e6)
-
-UTF8_MAXIMAL_ALLOCATION: int = 1_112_064
-
-# Up-to-date Unicode ucd/15.0.0
-UNICODE_RANGES_COMBINED: Dict[str, range] = {
-    "Control character": range(32),
-    "Basic Latin": range(32, 128),
-    "Latin-1 Supplement": range(128, 256),
-    "Latin Extended-A": range(256, 384),
-    "Latin Extended-B": range(384, 592),
-    "IPA Extensions": range(592, 688),
-    "Spacing Modifier Letters": range(688, 768),
-    "Combining Diacritical Marks": range(768, 880),
-    "Greek and Coptic": range(880, 1024),
-    "Cyrillic": range(1024, 1280),
-    "Cyrillic Supplement": range(1280, 1328),
-    "Armenian": range(1328, 1424),
-    "Hebrew": range(1424, 1536),
-    "Arabic": range(1536, 1792),
-    "Syriac": range(1792, 1872),
-    "Arabic Supplement": range(1872, 1920),
-    "Thaana": range(1920, 1984),
-    "NKo": range(1984, 2048),
-    "Samaritan": range(2048, 2112),
-    "Mandaic": range(2112, 2144),
-    "Syriac Supplement": range(2144, 2160),
-    "Arabic Extended-B": range(2160, 2208),
-    "Arabic Extended-A": range(2208, 2304),
-    "Devanagari": range(2304, 2432),
-    "Bengali": range(2432, 2560),
-    "Gurmukhi": range(2560, 2688),
-    "Gujarati": range(2688, 2816),
-    "Oriya": range(2816, 2944),
-    "Tamil": range(2944, 3072),
-    "Telugu": range(3072, 3200),
-    "Kannada": range(3200, 3328),
-    "Malayalam": range(3328, 3456),
-    "Sinhala": range(3456, 3584),
-    "Thai": range(3584, 3712),
-    "Lao": range(3712, 3840),
-    "Tibetan": range(3840, 4096),
-    "Myanmar": range(4096, 4256),
-    "Georgian": range(4256, 4352),
-    "Hangul Jamo": range(4352, 4608),
-    "Ethiopic": range(4608, 4992),
-    "Ethiopic Supplement": range(4992, 5024),
-    "Cherokee": range(5024, 5120),
-    "Unified Canadian Aboriginal Syllabics": range(5120, 5760),
-    "Ogham": range(5760, 5792),
-    "Runic": range(5792, 5888),
-    "Tagalog": range(5888, 5920),
-    "Hanunoo": range(5920, 5952),
-    "Buhid": range(5952, 5984),
-    "Tagbanwa": range(5984, 6016),
-    "Khmer": range(6016, 6144),
-    "Mongolian": range(6144, 6320),
-    "Unified Canadian Aboriginal Syllabics Extended": range(6320, 6400),
-    "Limbu": range(6400, 6480),
-    "Tai Le": range(6480, 6528),
-    "New Tai Lue": range(6528, 6624),
-    "Khmer Symbols": range(6624, 6656),
-    "Buginese": range(6656, 6688),
-    "Tai Tham": range(6688, 6832),
-    "Combining Diacritical Marks Extended": range(6832, 6912),
-    "Balinese": range(6912, 7040),
-    "Sundanese": range(7040, 7104),
-    "Batak": range(7104, 7168),
-    "Lepcha": range(7168, 7248),
-    "Ol Chiki": range(7248, 7296),
-    "Cyrillic Extended-C": range(7296, 7312),
-    "Georgian Extended": range(7312, 7360),
-    "Sundanese Supplement": range(7360, 7376),
-    "Vedic Extensions": range(7376, 7424),
-    "Phonetic Extensions": range(7424, 7552),
-    "Phonetic Extensions Supplement": range(7552, 7616),
-    "Combining Diacritical Marks Supplement": range(7616, 7680),
-    "Latin Extended Additional": range(7680, 7936),
-    "Greek Extended": range(7936, 8192),
-    "General Punctuation": range(8192, 8304),
-    "Superscripts and Subscripts": range(8304, 8352),
-    "Currency Symbols": range(8352, 8400),
-    "Combining Diacritical Marks for Symbols": range(8400, 8448),
-    "Letterlike Symbols": range(8448, 8528),
-    "Number Forms": range(8528, 8592),
-    "Arrows": range(8592, 8704),
-    "Mathematical Operators": range(8704, 8960),
-    "Miscellaneous Technical": range(8960, 9216),
-    "Control Pictures": range(9216, 9280),
-    "Optical Character Recognition": range(9280, 9312),
-    "Enclosed Alphanumerics": range(9312, 9472),
-    "Box Drawing": range(9472, 9600),
-    "Block Elements": range(9600, 9632),
-    "Geometric Shapes": range(9632, 9728),
-    "Miscellaneous Symbols": range(9728, 9984),
-    "Dingbats": range(9984, 10176),
-    "Miscellaneous Mathematical Symbols-A": range(10176, 10224),
-    "Supplemental Arrows-A": range(10224, 10240),
-    "Braille Patterns": range(10240, 10496),
-    "Supplemental Arrows-B": range(10496, 10624),
-    "Miscellaneous Mathematical Symbols-B": range(10624, 10752),
-    "Supplemental Mathematical Operators": range(10752, 11008),
-    "Miscellaneous Symbols and Arrows": range(11008, 11264),
-    "Glagolitic": range(11264, 11360),
-    "Latin Extended-C": range(11360, 11392),
-    "Coptic": range(11392, 11520),
-    "Georgian Supplement": range(11520, 11568),
-    "Tifinagh": range(11568, 11648),
-    "Ethiopic Extended": range(11648, 11744),
-    "Cyrillic Extended-A": range(11744, 11776),
-    "Supplemental Punctuation": range(11776, 11904),
-    "CJK Radicals Supplement": range(11904, 12032),
-    "Kangxi Radicals": range(12032, 12256),
-    "Ideographic Description Characters": range(12272, 12288),
-    "CJK Symbols and Punctuation": range(12288, 12352),
-    "Hiragana": range(12352, 12448),
-    "Katakana": range(12448, 12544),
-    "Bopomofo": range(12544, 12592),
-    "Hangul Compatibility Jamo": range(12592, 12688),
-    "Kanbun": range(12688, 12704),
-    "Bopomofo Extended": range(12704, 12736),
-    "CJK Strokes": range(12736, 12784),
-    "Katakana Phonetic Extensions": range(12784, 12800),
-    "Enclosed CJK Letters and Months": range(12800, 13056),
-    "CJK Compatibility": range(13056, 13312),
-    "CJK Unified Ideographs Extension A": range(13312, 19904),
-    "Yijing Hexagram Symbols": range(19904, 19968),
-    "CJK Unified Ideographs": range(19968, 40960),
-    "Yi Syllables": range(40960, 42128),
-    "Yi Radicals": range(42128, 42192),
-    "Lisu": range(42192, 42240),
-    "Vai": range(42240, 42560),
-    "Cyrillic Extended-B": range(42560, 42656),
-    "Bamum": range(42656, 42752),
-    "Modifier Tone Letters": range(42752, 42784),
-    "Latin Extended-D": range(42784, 43008),
-    "Syloti Nagri": range(43008, 43056),
-    "Common Indic Number Forms": range(43056, 43072),
-    "Phags-pa": range(43072, 43136),
-    "Saurashtra": range(43136, 43232),
-    "Devanagari Extended": range(43232, 43264),
-    "Kayah Li": range(43264, 43312),
-    "Rejang": range(43312, 43360),
-    "Hangul Jamo Extended-A": range(43360, 43392),
-    "Javanese": range(43392, 43488),
-    "Myanmar Extended-B": range(43488, 43520),
-    "Cham": range(43520, 43616),
-    "Myanmar Extended-A": range(43616, 43648),
-    "Tai Viet": range(43648, 43744),
-    "Meetei Mayek Extensions": range(43744, 43776),
-    "Ethiopic Extended-A": range(43776, 43824),
-    "Latin Extended-E": range(43824, 43888),
-    "Cherokee Supplement": range(43888, 43968),
-    "Meetei Mayek": range(43968, 44032),
-    "Hangul Syllables": range(44032, 55216),
-    "Hangul Jamo Extended-B": range(55216, 55296),
-    "High Surrogates": range(55296, 56192),
-    "High Private Use Surrogates": range(56192, 56320),
-    "Low Surrogates": range(56320, 57344),
-    "Private Use Area": range(57344, 63744),
-    "CJK Compatibility Ideographs": range(63744, 64256),
-    "Alphabetic Presentation Forms": range(64256, 64336),
-    "Arabic Presentation Forms-A": range(64336, 65024),
-    "Variation Selectors": range(65024, 65040),
-    "Vertical Forms": range(65040, 65056),
-    "Combining Half Marks": range(65056, 65072),
-    "CJK Compatibility Forms": range(65072, 65104),
-    "Small Form Variants": range(65104, 65136),
-    "Arabic Presentation Forms-B": range(65136, 65280),
-    "Halfwidth and Fullwidth Forms": range(65280, 65520),
-    "Specials": range(65520, 65536),
-    "Linear B Syllabary": range(65536, 65664),
-    "Linear B Ideograms": range(65664, 65792),
-    "Aegean Numbers": range(65792, 65856),
-    "Ancient Greek Numbers": range(65856, 65936),
-    "Ancient Symbols": range(65936, 66000),
-    "Phaistos Disc": range(66000, 66048),
-    "Lycian": range(66176, 66208),
-    "Carian": range(66208, 66272),
-    "Coptic Epact Numbers": range(66272, 66304),
-    "Old Italic": range(66304, 66352),
-    "Gothic": range(66352, 66384),
-    "Old Permic": range(66384, 66432),
-    "Ugaritic": range(66432, 66464),
-    "Old Persian": range(66464, 66528),
-    "Deseret": range(66560, 66640),
-    "Shavian": range(66640, 66688),
-    "Osmanya": range(66688, 66736),
-    "Osage": range(66736, 66816),
-    "Elbasan": range(66816, 66864),
-    "Caucasian Albanian": range(66864, 66928),
-    "Vithkuqi": range(66928, 67008),
-    "Linear A": range(67072, 67456),
-    "Latin Extended-F": range(67456, 67520),
-    "Cypriot Syllabary": range(67584, 67648),
-    "Imperial Aramaic": range(67648, 67680),
-    "Palmyrene": range(67680, 67712),
-    "Nabataean": range(67712, 67760),
-    "Hatran": range(67808, 67840),
-    "Phoenician": range(67840, 67872),
-    "Lydian": range(67872, 67904),
-    "Meroitic Hieroglyphs": range(67968, 68000),
-    "Meroitic Cursive": range(68000, 68096),
-    "Kharoshthi": range(68096, 68192),
-    "Old South Arabian": range(68192, 68224),
-    "Old North Arabian": range(68224, 68256),
-    "Manichaean": range(68288, 68352),
-    "Avestan": range(68352, 68416),
-    "Inscriptional Parthian": range(68416, 68448),
-    "Inscriptional Pahlavi": range(68448, 68480),
-    "Psalter Pahlavi": range(68480, 68528),
-    "Old Turkic": range(68608, 68688),
-    "Old Hungarian": range(68736, 68864),
-    "Hanifi Rohingya": range(68864, 68928),
-    "Rumi Numeral Symbols": range(69216, 69248),
-    "Yezidi": range(69248, 69312),
-    "Arabic Extended-C": range(69312, 69376),
-    "Old Sogdian": range(69376, 69424),
-    "Sogdian": range(69424, 69488),
-    "Old Uyghur": range(69488, 69552),
-    "Chorasmian": range(69552, 69600),
-    "Elymaic": range(69600, 69632),
-    "Brahmi": range(69632, 69760),
-    "Kaithi": range(69760, 69840),
-    "Sora Sompeng": range(69840, 69888),
-    "Chakma": range(69888, 69968),
-    "Mahajani": range(69968, 70016),
-    "Sharada": range(70016, 70112),
-    "Sinhala Archaic Numbers": range(70112, 70144),
-    "Khojki": range(70144, 70224),
-    "Multani": range(70272, 70320),
-    "Khudawadi": range(70320, 70400),
-    "Grantha": range(70400, 70528),
-    "Newa": range(70656, 70784),
-    "Tirhuta": range(70784, 70880),
-    "Siddham": range(71040, 71168),
-    "Modi": range(71168, 71264),
-    "Mongolian Supplement": range(71264, 71296),
-    "Takri": range(71296, 71376),
-    "Ahom": range(71424, 71504),
-    "Dogra": range(71680, 71760),
-    "Warang Citi": range(71840, 71936),
-    "Dives Akuru": range(71936, 72032),
-    "Nandinagari": range(72096, 72192),
-    "Zanabazar Square": range(72192, 72272),
-    "Soyombo": range(72272, 72368),
-    "Unified Canadian Aboriginal Syllabics Extended-A": range(72368, 72384),
-    "Pau Cin Hau": range(72384, 72448),
-    "Devanagari Extended-A": range(72448, 72544),
-    "Bhaiksuki": range(72704, 72816),
-    "Marchen": range(72816, 72896),
-    "Masaram Gondi": range(72960, 73056),
-    "Gunjala Gondi": range(73056, 73136),
-    "Makasar": range(73440, 73472),
-    "Kawi": range(73472, 73568),
-    "Lisu Supplement": range(73648, 73664),
-    "Tamil Supplement": range(73664, 73728),
-    "Cuneiform": range(73728, 74752),
-    "Cuneiform Numbers and Punctuation": range(74752, 74880),
-    "Early Dynastic Cuneiform": range(74880, 75088),
-    "Cypro-Minoan": range(77712, 77824),
-    "Egyptian Hieroglyphs": range(77824, 78896),
-    "Egyptian Hieroglyph Format Controls": range(78896, 78944),
-    "Anatolian Hieroglyphs": range(82944, 83584),
-    "Bamum Supplement": range(92160, 92736),
-    "Mro": range(92736, 92784),
-    "Tangsa": range(92784, 92880),
-    "Bassa Vah": range(92880, 92928),
-    "Pahawh Hmong": range(92928, 93072),
-    "Medefaidrin": range(93760, 93856),
-    "Miao": range(93952, 94112),
-    "Ideographic Symbols and Punctuation": range(94176, 94208),
-    "Tangut": range(94208, 100352),
-    "Tangut Components": range(100352, 101120),
-    "Khitan Small Script": range(101120, 101632),
-    "Tangut Supplement": range(101632, 101760),
-    "Kana Extended-B": range(110576, 110592),
-    "Kana Supplement": range(110592, 110848),
-    "Kana Extended-A": range(110848, 110896),
-    "Small Kana Extension": range(110896, 110960),
-    "Nushu": range(110960, 111360),
-    "Duployan": range(113664, 113824),
-    "Shorthand Format Controls": range(113824, 113840),
-    "Znamenny Musical Notation": range(118528, 118736),
-    "Byzantine Musical Symbols": range(118784, 119040),
-    "Musical Symbols": range(119040, 119296),
-    "Ancient Greek Musical Notation": range(119296, 119376),
-    "Kaktovik Numerals": range(119488, 119520),
-    "Mayan Numerals": range(119520, 119552),
-    "Tai Xuan Jing Symbols": range(119552, 119648),
-    "Counting Rod Numerals": range(119648, 119680),
-    "Mathematical Alphanumeric Symbols": range(119808, 120832),
-    "Sutton SignWriting": range(120832, 121520),
-    "Latin Extended-G": range(122624, 122880),
-    "Glagolitic Supplement": range(122880, 122928),
-    "Cyrillic Extended-D": range(122928, 123024),
-    "Nyiakeng Puachue Hmong": range(123136, 123216),
-    "Toto": range(123536, 123584),
-    "Wancho": range(123584, 123648),
-    "Nag Mundari": range(124112, 124160),
-    "Ethiopic Extended-B": range(124896, 124928),
-    "Mende Kikakui": range(124928, 125152),
-    "Adlam": range(125184, 125280),
-    "Indic Siyaq Numbers": range(126064, 126144),
-    "Ottoman Siyaq Numbers": range(126208, 126288),
-    "Arabic Mathematical Alphabetic Symbols": range(126464, 126720),
-    "Mahjong Tiles": range(126976, 127024),
-    "Domino Tiles": range(127024, 127136),
-    "Playing Cards": range(127136, 127232),
-    "Enclosed Alphanumeric Supplement": range(127232, 127488),
-    "Enclosed Ideographic Supplement": range(127488, 127744),
-    "Miscellaneous Symbols and Pictographs": range(127744, 128512),
-    "Emoticons range(Emoji)": range(128512, 128592),
-    "Ornamental Dingbats": range(128592, 128640),
-    "Transport and Map Symbols": range(128640, 128768),
-    "Alchemical Symbols": range(128768, 128896),
-    "Geometric Shapes Extended": range(128896, 129024),
-    "Supplemental Arrows-C": range(129024, 129280),
-    "Supplemental Symbols and Pictographs": range(129280, 129536),
-    "Chess Symbols": range(129536, 129648),
-    "Symbols and Pictographs Extended-A": range(129648, 129792),
-    "Symbols for Legacy Computing": range(129792, 130048),
-    "CJK Unified Ideographs Extension B": range(131072, 173792),
-    "CJK Unified Ideographs Extension C": range(173824, 177984),
-    "CJK Unified Ideographs Extension D": range(177984, 178208),
-    "CJK Unified Ideographs Extension E": range(178208, 183984),
-    "CJK Unified Ideographs Extension F": range(183984, 191472),
-    "CJK Compatibility Ideographs Supplement": range(194560, 195104),
-    "CJK Unified Ideographs Extension G": range(196608, 201552),
-    "CJK Unified Ideographs Extension H": range(201552, 205744),
-    "Tags": range(917504, 917632),
-    "Variation Selectors Supplement": range(917760, 918000),
-    "Supplementary Private Use Area-A": range(983040, 1048576),
-    "Supplementary Private Use Area-B": range(1048576, 1114112),
-}
-
-
-UNICODE_SECONDARY_RANGE_KEYWORD: List[str] = [
-    "Supplement",
-    "Extended",
-    "Extensions",
-    "Modifier",
-    "Marks",
-    "Punctuation",
-    "Symbols",
-    "Forms",
-    "Operators",
-    "Miscellaneous",
-    "Drawing",
-    "Block",
-    "Shapes",
-    "Supplemental",
-    "Tags",
-]
-
-RE_POSSIBLE_ENCODING_INDICATION = re_compile(
-    r"(?:(?:encoding)|(?:charset)|(?:coding))(?:[\:= ]{1,10})(?:[\"\']?)([a-zA-Z0-9\-_]+)(?:[\"\']?)",
-    IGNORECASE,
-)
-
-IANA_NO_ALIASES = [
-    "cp720",
-    "cp737",
-    "cp856",
-    "cp874",
-    "cp875",
-    "cp1006",
-    "koi8_r",
-    "koi8_t",
-    "koi8_u",
-]
-
-IANA_SUPPORTED: List[str] = sorted(
-    filter(
-        lambda x: x.endswith("_codec") is False
-        and x not in {"rot_13", "tactis", "mbcs"},
-        list(set(aliases.values())) + IANA_NO_ALIASES,
-    )
-)
-
-IANA_SUPPORTED_COUNT: int = len(IANA_SUPPORTED)
-
-# pre-computed code page that are similar using the function cp_similarity.
-IANA_SUPPORTED_SIMILAR: Dict[str, List[str]] = {
-    "cp037": ["cp1026", "cp1140", "cp273", "cp500"],
-    "cp1026": ["cp037", "cp1140", "cp273", "cp500"],
-    "cp1125": ["cp866"],
-    "cp1140": ["cp037", "cp1026", "cp273", "cp500"],
-    "cp1250": ["iso8859_2"],
-    "cp1251": ["kz1048", "ptcp154"],
-    "cp1252": ["iso8859_15", "iso8859_9", "latin_1"],
-    "cp1253": ["iso8859_7"],
-    "cp1254": ["iso8859_15", "iso8859_9", "latin_1"],
-    "cp1257": ["iso8859_13"],
-    "cp273": ["cp037", "cp1026", "cp1140", "cp500"],
-    "cp437": ["cp850", "cp858", "cp860", "cp861", "cp862", "cp863", "cp865"],
-    "cp500": ["cp037", "cp1026", "cp1140", "cp273"],
-    "cp850": ["cp437", "cp857", "cp858", "cp865"],
-    "cp857": ["cp850", "cp858", "cp865"],
-    "cp858": ["cp437", "cp850", "cp857", "cp865"],
-    "cp860": ["cp437", "cp861", "cp862", "cp863", "cp865"],
-    "cp861": ["cp437", "cp860", "cp862", "cp863", "cp865"],
-    "cp862": ["cp437", "cp860", "cp861", "cp863", "cp865"],
-    "cp863": ["cp437", "cp860", "cp861", "cp862", "cp865"],
-    "cp865": ["cp437", "cp850", "cp857", "cp858", "cp860", "cp861", "cp862", "cp863"],
-    "cp866": ["cp1125"],
-    "iso8859_10": ["iso8859_14", "iso8859_15", "iso8859_4", "iso8859_9", "latin_1"],
-    "iso8859_11": ["tis_620"],
-    "iso8859_13": ["cp1257"],
-    "iso8859_14": [
-        "iso8859_10",
-        "iso8859_15",
-        "iso8859_16",
-        "iso8859_3",
-        "iso8859_9",
-        "latin_1",
-    ],
-    "iso8859_15": [
-        "cp1252",
-        "cp1254",
-        "iso8859_10",
-        "iso8859_14",
-        "iso8859_16",
-        "iso8859_3",
-        "iso8859_9",
-        "latin_1",
-    ],
-    "iso8859_16": [
-        "iso8859_14",
-        "iso8859_15",
-        "iso8859_2",
-        "iso8859_3",
-        "iso8859_9",
-        "latin_1",
-    ],
-    "iso8859_2": ["cp1250", "iso8859_16", "iso8859_4"],
-    "iso8859_3": ["iso8859_14", "iso8859_15", "iso8859_16", "iso8859_9", "latin_1"],
-    "iso8859_4": ["iso8859_10", "iso8859_2", "iso8859_9", "latin_1"],
-    "iso8859_7": ["cp1253"],
-    "iso8859_9": [
-        "cp1252",
-        "cp1254",
-        "cp1258",
-        "iso8859_10",
-        "iso8859_14",
-        "iso8859_15",
-        "iso8859_16",
-        "iso8859_3",
-        "iso8859_4",
-        "latin_1",
-    ],
-    "kz1048": ["cp1251", "ptcp154"],
-    "latin_1": [
-        "cp1252",
-        "cp1254",
-        "cp1258",
-        "iso8859_10",
-        "iso8859_14",
-        "iso8859_15",
-        "iso8859_16",
-        "iso8859_3",
-        "iso8859_4",
-        "iso8859_9",
-    ],
-    "mac_iceland": ["mac_roman", "mac_turkish"],
-    "mac_roman": ["mac_iceland", "mac_turkish"],
-    "mac_turkish": ["mac_iceland", "mac_roman"],
-    "ptcp154": ["cp1251", "kz1048"],
-    "tis_620": ["iso8859_11"],
-}
-
-
-CHARDET_CORRESPONDENCE: Dict[str, str] = {
-    "iso2022_kr": "ISO-2022-KR",
-    "iso2022_jp": "ISO-2022-JP",
-    "euc_kr": "EUC-KR",
-    "tis_620": "TIS-620",
-    "utf_32": "UTF-32",
-    "euc_jp": "EUC-JP",
-    "koi8_r": "KOI8-R",
-    "iso8859_1": "ISO-8859-1",
-    "iso8859_2": "ISO-8859-2",
-    "iso8859_5": "ISO-8859-5",
-    "iso8859_6": "ISO-8859-6",
-    "iso8859_7": "ISO-8859-7",
-    "iso8859_8": "ISO-8859-8",
-    "utf_16": "UTF-16",
-    "cp855": "IBM855",
-    "mac_cyrillic": "MacCyrillic",
-    "gb2312": "GB2312",
-    "gb18030": "GB18030",
-    "cp932": "CP932",
-    "cp866": "IBM866",
-    "utf_8": "utf-8",
-    "utf_8_sig": "UTF-8-SIG",
-    "shift_jis": "SHIFT_JIS",
-    "big5": "Big5",
-    "cp1250": "windows-1250",
-    "cp1251": "windows-1251",
-    "cp1252": "Windows-1252",
-    "cp1253": "windows-1253",
-    "cp1255": "windows-1255",
-    "cp1256": "windows-1256",
-    "cp1254": "Windows-1254",
-    "cp949": "CP949",
-}
-
-
-COMMON_SAFE_ASCII_CHARACTERS: Set[str] = {
-    "<",
-    ">",
-    "=",
-    ":",
-    "/",
-    "&",
-    ";",
-    "{",
-    "}",
-    "[",
-    "]",
-    ",",
-    "|",
-    '"',
-    "-",
-}
-
-
-KO_NAMES: Set[str] = {"johab", "cp949", "euc_kr"}
-ZH_NAMES: Set[str] = {"big5", "cp950", "big5hkscs", "hz"}
-
-# Logging LEVEL below DEBUG
-TRACE: int = 5
-
-
-# Language label that contain the em dash "—"
-# character are to be considered alternative seq to origin
-FREQUENCIES: Dict[str, List[str]] = {
-    "English": [
-        "e",
-        "a",
-        "t",
-        "i",
-        "o",
-        "n",
-        "s",
-        "r",
-        "h",
-        "l",
-        "d",
-        "c",
-        "u",
-        "m",
-        "f",
-        "p",
-        "g",
-        "w",
-        "y",
-        "b",
-        "v",
-        "k",
-        "x",
-        "j",
-        "z",
-        "q",
-    ],
-    "English—": [
-        "e",
-        "a",
-        "t",
-        "i",
-        "o",
-        "n",
-        "s",
-        "r",
-        "h",
-        "l",
-        "d",
-        "c",
-        "m",
-        "u",
-        "f",
-        "p",
-        "g",
-        "w",
-        "b",
-        "y",
-        "v",
-        "k",
-        "j",
-        "x",
-        "z",
-        "q",
-    ],
-    "German": [
-        "e",
-        "n",
-        "i",
-        "r",
-        "s",
-        "t",
-        "a",
-        "d",
-        "h",
-        "u",
-        "l",
-        "g",
-        "o",
-        "c",
-        "m",
-        "b",
-        "f",
-        "k",
-        "w",
-        "z",
-        "p",
-        "v",
-        "ü",
-        "ä",
-        "ö",
-        "j",
-    ],
-    "French": [
-        "e",
-        "a",
-        "s",
-        "n",
-        "i",
-        "t",
-        "r",
-        "l",
-        "u",
-        "o",
-        "d",
-        "c",
-        "p",
-        "m",
-        "é",
-        "v",
-        "g",
-        "f",
-        "b",
-        "h",
-        "q",
-        "à",
-        "x",
-        "è",
-        "y",
-        "j",
-    ],
-    "Dutch": [
-        "e",
-        "n",
-        "a",
-        "i",
-        "r",
-        "t",
-        "o",
-        "d",
-        "s",
-        "l",
-        "g",
-        "h",
-        "v",
-        "m",
-        "u",
-        "k",
-        "c",
-        "p",
-        "b",
-        "w",
-        "j",
-        "z",
-        "f",
-        "y",
-        "x",
-        "ë",
-    ],
-    "Italian": [
-        "e",
-        "i",
-        "a",
-        "o",
-        "n",
-        "l",
-        "t",
-        "r",
-        "s",
-        "c",
-        "d",
-        "u",
-        "p",
-        "m",
-        "g",
-        "v",
-        "f",
-        "b",
-        "z",
-        "h",
-        "q",
-        "è",
-        "à",
-        "k",
-        "y",
-        "ò",
-    ],
-    "Polish": [
-        "a",
-        "i",
-        "o",
-        "e",
-        "n",
-        "r",
-        "z",
-        "w",
-        "s",
-        "c",
-        "t",
-        "k",
-        "y",
-        "d",
-        "p",
-        "m",
-        "u",
-        "l",
-        "j",
-        "ł",
-        "g",
-        "b",
-        "h",
-        "ą",
-        "ę",
-        "ó",
-    ],
-    "Spanish": [
-        "e",
-        "a",
-        "o",
-        "n",
-        "s",
-        "r",
-        "i",
-        "l",
-        "d",
-        "t",
-        "c",
-        "u",
-        "m",
-        "p",
-        "b",
-        "g",
-        "v",
-        "f",
-        "y",
-        "ó",
-        "h",
-        "q",
-        "í",
-        "j",
-        "z",
-        "á",
-    ],
-    "Russian": [
-        "о",
-        "а",
-        "е",
-        "и",
-        "н",
-        "с",
-        "т",
-        "р",
-        "в",
-        "л",
-        "к",
-        "м",
-        "д",
-        "п",
-        "у",
-        "г",
-        "я",
-        "ы",
-        "з",
-        "б",
-        "й",
-        "ь",
-        "ч",
-        "х",
-        "ж",
-        "ц",
-    ],
-    # Jap-Kanji
-    "Japanese": [
-        "人",
-        "一",
-        "大",
-        "亅",
-        "丁",
-        "丨",
-        "竹",
-        "笑",
-        "口",
-        "日",
-        "今",
-        "二",
-        "彳",
-        "行",
-        "十",
-        "土",
-        "丶",
-        "寸",
-        "寺",
-        "時",
-        "乙",
-        "丿",
-        "乂",
-        "气",
-        "気",
-        "冂",
-        "巾",
-        "亠",
-        "市",
-        "目",
-        "儿",
-        "見",
-        "八",
-        "小",
-        "凵",
-        "県",
-        "月",
-        "彐",
-        "門",
-        "間",
-        "木",
-        "東",
-        "山",
-        "出",
-        "本",
-        "中",
-        "刀",
-        "分",
-        "耳",
-        "又",
-        "取",
-        "最",
-        "言",
-        "田",
-        "心",
-        "思",
-        "刂",
-        "前",
-        "京",
-        "尹",
-        "事",
-        "生",
-        "厶",
-        "云",
-        "会",
-        "未",
-        "来",
-        "白",
-        "冫",
-        "楽",
-        "灬",
-        "馬",
-        "尸",
-        "尺",
-        "駅",
-        "明",
-        "耂",
-        "者",
-        "了",
-        "阝",
-        "都",
-        "高",
-        "卜",
-        "占",
-        "厂",
-        "广",
-        "店",
-        "子",
-        "申",
-        "奄",
-        "亻",
-        "俺",
-        "上",
-        "方",
-        "冖",
-        "学",
-        "衣",
-        "艮",
-        "食",
-        "自",
-    ],
-    # Jap-Katakana
-    "Japanese—": [
-        "ー",
-        "ン",
-        "ス",
-        "・",
-        "ル",
-        "ト",
-        "リ",
-        "イ",
-        "ア",
-        "ラ",
-        "ッ",
-        "ク",
-        "ド",
-        "シ",
-        "レ",
-        "ジ",
-        "タ",
-        "フ",
-        "ロ",
-        "カ",
-        "テ",
-        "マ",
-        "ィ",
-        "グ",
-        "バ",
-        "ム",
-        "プ",
-        "オ",
-        "コ",
-        "デ",
-        "ニ",
-        "ウ",
-        "メ",
-        "サ",
-        "ビ",
-        "ナ",
-        "ブ",
-        "ャ",
-        "エ",
-        "ュ",
-        "チ",
-        "キ",
-        "ズ",
-        "ダ",
-        "パ",
-        "ミ",
-        "ェ",
-        "ョ",
-        "ハ",
-        "セ",
-        "ベ",
-        "ガ",
-        "モ",
-        "ツ",
-        "ネ",
-        "ボ",
-        "ソ",
-        "ノ",
-        "ァ",
-        "ヴ",
-        "ワ",
-        "ポ",
-        "ペ",
-        "ピ",
-        "ケ",
-        "ゴ",
-        "ギ",
-        "ザ",
-        "ホ",
-        "ゲ",
-        "ォ",
-        "ヤ",
-        "ヒ",
-        "ユ",
-        "ヨ",
-        "ヘ",
-        "ゼ",
-        "ヌ",
-        "ゥ",
-        "ゾ",
-        "ヶ",
-        "ヂ",
-        "ヲ",
-        "ヅ",
-        "ヵ",
-        "ヱ",
-        "ヰ",
-        "ヮ",
-        "ヽ",
-        "゠",
-        "ヾ",
-        "ヷ",
-        "ヿ",
-        "ヸ",
-        "ヹ",
-        "ヺ",
-    ],
-    # Jap-Hiragana
-    "Japanese——": [
-        "の",
-        "に",
-        "る",
-        "た",
-        "と",
-        "は",
-        "し",
-        "い",
-        "を",
-        "で",
-        "て",
-        "が",
-        "な",
-        "れ",
-        "か",
-        "ら",
-        "さ",
-        "っ",
-        "り",
-        "す",
-        "あ",
-        "も",
-        "こ",
-        "ま",
-        "う",
-        "く",
-        "よ",
-        "き",
-        "ん",
-        "め",
-        "お",
-        "け",
-        "そ",
-        "つ",
-        "だ",
-        "や",
-        "え",
-        "ど",
-        "わ",
-        "ち",
-        "み",
-        "せ",
-        "じ",
-        "ば",
-        "へ",
-        "び",
-        "ず",
-        "ろ",
-        "ほ",
-        "げ",
-        "む",
-        "べ",
-        "ひ",
-        "ょ",
-        "ゆ",
-        "ぶ",
-        "ご",
-        "ゃ",
-        "ね",
-        "ふ",
-        "ぐ",
-        "ぎ",
-        "ぼ",
-        "ゅ",
-        "づ",
-        "ざ",
-        "ぞ",
-        "ぬ",
-        "ぜ",
-        "ぱ",
-        "ぽ",
-        "ぷ",
-        "ぴ",
-        "ぃ",
-        "ぁ",
-        "ぇ",
-        "ぺ",
-        "ゞ",
-        "ぢ",
-        "ぉ",
-        "ぅ",
-        "ゐ",
-        "ゝ",
-        "ゑ",
-        "゛",
-        "゜",
-        "ゎ",
-        "ゔ",
-        "゚",
-        "ゟ",
-        "゙",
-        "ゕ",
-        "ゖ",
-    ],
-    "Portuguese": [
-        "a",
-        "e",
-        "o",
-        "s",
-        "i",
-        "r",
-        "d",
-        "n",
-        "t",
-        "m",
-        "u",
-        "c",
-        "l",
-        "p",
-        "g",
-        "v",
-        "b",
-        "f",
-        "h",
-        "ã",
-        "q",
-        "é",
-        "ç",
-        "á",
-        "z",
-        "í",
-    ],
-    "Swedish": [
-        "e",
-        "a",
-        "n",
-        "r",
-        "t",
-        "s",
-        "i",
-        "l",
-        "d",
-        "o",
-        "m",
-        "k",
-        "g",
-        "v",
-        "h",
-        "f",
-        "u",
-        "p",
-        "ä",
-        "c",
-        "b",
-        "ö",
-        "å",
-        "y",
-        "j",
-        "x",
-    ],
-    "Chinese": [
-        "的",
-        "一",
-        "是",
-        "不",
-        "了",
-        "在",
-        "人",
-        "有",
-        "我",
-        "他",
-        "这",
-        "个",
-        "们",
-        "中",
-        "来",
-        "上",
-        "大",
-        "为",
-        "和",
-        "国",
-        "地",
-        "到",
-        "以",
-        "说",
-        "时",
-        "要",
-        "就",
-        "出",
-        "会",
-        "可",
-        "也",
-        "你",
-        "对",
-        "生",
-        "能",
-        "而",
-        "子",
-        "那",
-        "得",
-        "于",
-        "着",
-        "下",
-        "自",
-        "之",
-        "年",
-        "过",
-        "发",
-        "后",
-        "作",
-        "里",
-        "用",
-        "道",
-        "行",
-        "所",
-        "然",
-        "家",
-        "种",
-        "事",
-        "成",
-        "方",
-        "多",
-        "经",
-        "么",
-        "去",
-        "法",
-        "学",
-        "如",
-        "都",
-        "同",
-        "现",
-        "当",
-        "没",
-        "动",
-        "面",
-        "起",
-        "看",
-        "定",
-        "天",
-        "分",
-        "还",
-        "进",
-        "好",
-        "小",
-        "部",
-        "其",
-        "些",
-        "主",
-        "样",
-        "理",
-        "心",
-        "她",
-        "本",
-        "前",
-        "开",
-        "但",
-        "因",
-        "只",
-        "从",
-        "想",
-        "实",
-    ],
-    "Ukrainian": [
-        "о",
-        "а",
-        "н",
-        "і",
-        "и",
-        "р",
-        "в",
-        "т",
-        "е",
-        "с",
-        "к",
-        "л",
-        "у",
-        "д",
-        "м",
-        "п",
-        "з",
-        "я",
-        "ь",
-        "б",
-        "г",
-        "й",
-        "ч",
-        "х",
-        "ц",
-        "ї",
-    ],
-    "Norwegian": [
-        "e",
-        "r",
-        "n",
-        "t",
-        "a",
-        "s",
-        "i",
-        "o",
-        "l",
-        "d",
-        "g",
-        "k",
-        "m",
-        "v",
-        "f",
-        "p",
-        "u",
-        "b",
-        "h",
-        "å",
-        "y",
-        "j",
-        "ø",
-        "c",
-        "æ",
-        "w",
-    ],
-    "Finnish": [
-        "a",
-        "i",
-        "n",
-        "t",
-        "e",
-        "s",
-        "l",
-        "o",
-        "u",
-        "k",
-        "ä",
-        "m",
-        "r",
-        "v",
-        "j",
-        "h",
-        "p",
-        "y",
-        "d",
-        "ö",
-        "g",
-        "c",
-        "b",
-        "f",
-        "w",
-        "z",
-    ],
-    "Vietnamese": [
-        "n",
-        "h",
-        "t",
-        "i",
-        "c",
-        "g",
-        "a",
-        "o",
-        "u",
-        "m",
-        "l",
-        "r",
-        "à",
-        "đ",
-        "s",
-        "e",
-        "v",
-        "p",
-        "b",
-        "y",
-        "ư",
-        "d",
-        "á",
-        "k",
-        "ộ",
-        "ế",
-    ],
-    "Czech": [
-        "o",
-        "e",
-        "a",
-        "n",
-        "t",
-        "s",
-        "i",
-        "l",
-        "v",
-        "r",
-        "k",
-        "d",
-        "u",
-        "m",
-        "p",
-        "í",
-        "c",
-        "h",
-        "z",
-        "á",
-        "y",
-        "j",
-        "b",
-        "ě",
-        "é",
-        "ř",
-    ],
-    "Hungarian": [
-        "e",
-        "a",
-        "t",
-        "l",
-        "s",
-        "n",
-        "k",
-        "r",
-        "i",
-        "o",
-        "z",
-        "á",
-        "é",
-        "g",
-        "m",
-        "b",
-        "y",
-        "v",
-        "d",
-        "h",
-        "u",
-        "p",
-        "j",
-        "ö",
-        "f",
-        "c",
-    ],
-    "Korean": [
-        "이",
-        "다",
-        "에",
-        "의",
-        "는",
-        "로",
-        "하",
-        "을",
-        "가",
-        "고",
-        "지",
-        "서",
-        "한",
-        "은",
-        "기",
-        "으",
-        "년",
-        "대",
-        "사",
-        "시",
-        "를",
-        "리",
-        "도",
-        "인",
-        "스",
-        "일",
-    ],
-    "Indonesian": [
-        "a",
-        "n",
-        "e",
-        "i",
-        "r",
-        "t",
-        "u",
-        "s",
-        "d",
-        "k",
-        "m",
-        "l",
-        "g",
-        "p",
-        "b",
-        "o",
-        "h",
-        "y",
-        "j",
-        "c",
-        "w",
-        "f",
-        "v",
-        "z",
-        "x",
-        "q",
-    ],
-    "Turkish": [
-        "a",
-        "e",
-        "i",
-        "n",
-        "r",
-        "l",
-        "ı",
-        "k",
-        "d",
-        "t",
-        "s",
-        "m",
-        "y",
-        "u",
-        "o",
-        "b",
-        "ü",
-        "ş",
-        "v",
-        "g",
-        "z",
-        "h",
-        "c",
-        "p",
-        "ç",
-        "ğ",
-    ],
-    "Romanian": [
-        "e",
-        "i",
-        "a",
-        "r",
-        "n",
-        "t",
-        "u",
-        "l",
-        "o",
-        "c",
-        "s",
-        "d",
-        "p",
-        "m",
-        "ă",
-        "f",
-        "v",
-        "î",
-        "g",
-        "b",
-        "ș",
-        "ț",
-        "z",
-        "h",
-        "â",
-        "j",
-    ],
-    "Farsi": [
-        "ا",
-        "ی",
-        "ر",
-        "د",
-        "ن",
-        "ه",
-        "و",
-        "م",
-        "ت",
-        "ب",
-        "س",
-        "ل",
-        "ک",
-        "ش",
-        "ز",
-        "ف",
-        "گ",
-        "ع",
-        "خ",
-        "ق",
-        "ج",
-        "آ",
-        "پ",
-        "ح",
-        "ط",
-        "ص",
-    ],
-    "Arabic": [
-        "ا",
-        "ل",
-        "ي",
-        "م",
-        "و",
-        "ن",
-        "ر",
-        "ت",
-        "ب",
-        "ة",
-        "ع",
-        "د",
-        "س",
-        "ف",
-        "ه",
-        "ك",
-        "ق",
-        "أ",
-        "ح",
-        "ج",
-        "ش",
-        "ط",
-        "ص",
-        "ى",
-        "خ",
-        "إ",
-    ],
-    "Danish": [
-        "e",
-        "r",
-        "n",
-        "t",
-        "a",
-        "i",
-        "s",
-        "d",
-        "l",
-        "o",
-        "g",
-        "m",
-        "k",
-        "f",
-        "v",
-        "u",
-        "b",
-        "h",
-        "p",
-        "å",
-        "y",
-        "ø",
-        "æ",
-        "c",
-        "j",
-        "w",
-    ],
-    "Serbian": [
-        "а",
-        "и",
-        "о",
-        "е",
-        "н",
-        "р",
-        "с",
-        "у",
-        "т",
-        "к",
-        "ј",
-        "в",
-        "д",
-        "м",
-        "п",
-        "л",
-        "г",
-        "з",
-        "б",
-        "a",
-        "i",
-        "e",
-        "o",
-        "n",
-        "ц",
-        "ш",
-    ],
-    "Lithuanian": [
-        "i",
-        "a",
-        "s",
-        "o",
-        "r",
-        "e",
-        "t",
-        "n",
-        "u",
-        "k",
-        "m",
-        "l",
-        "p",
-        "v",
-        "d",
-        "j",
-        "g",
-        "ė",
-        "b",
-        "y",
-        "ų",
-        "š",
-        "ž",
-        "c",
-        "ą",
-        "į",
-    ],
-    "Slovene": [
-        "e",
-        "a",
-        "i",
-        "o",
-        "n",
-        "r",
-        "s",
-        "l",
-        "t",
-        "j",
-        "v",
-        "k",
-        "d",
-        "p",
-        "m",
-        "u",
-        "z",
-        "b",
-        "g",
-        "h",
-        "č",
-        "c",
-        "š",
-        "ž",
-        "f",
-        "y",
-    ],
-    "Slovak": [
-        "o",
-        "a",
-        "e",
-        "n",
-        "i",
-        "r",
-        "v",
-        "t",
-        "s",
-        "l",
-        "k",
-        "d",
-        "m",
-        "p",
-        "u",
-        "c",
-        "h",
-        "j",
-        "b",
-        "z",
-        "á",
-        "y",
-        "ý",
-        "í",
-        "č",
-        "é",
-    ],
-    "Hebrew": [
-        "י",
-        "ו",
-        "ה",
-        "ל",
-        "ר",
-        "ב",
-        "ת",
-        "מ",
-        "א",
-        "ש",
-        "נ",
-        "ע",
-        "ם",
-        "ד",
-        "ק",
-        "ח",
-        "פ",
-        "ס",
-        "כ",
-        "ג",
-        "ט",
-        "צ",
-        "ן",
-        "ז",
-        "ך",
-    ],
-    "Bulgarian": [
-        "а",
-        "и",
-        "о",
-        "е",
-        "н",
-        "т",
-        "р",
-        "с",
-        "в",
-        "л",
-        "к",
-        "д",
-        "п",
-        "м",
-        "з",
-        "г",
-        "я",
-        "ъ",
-        "у",
-        "б",
-        "ч",
-        "ц",
-        "й",
-        "ж",
-        "щ",
-        "х",
-    ],
-    "Croatian": [
-        "a",
-        "i",
-        "o",
-        "e",
-        "n",
-        "r",
-        "j",
-        "s",
-        "t",
-        "u",
-        "k",
-        "l",
-        "v",
-        "d",
-        "m",
-        "p",
-        "g",
-        "z",
-        "b",
-        "c",
-        "č",
-        "h",
-        "š",
-        "ž",
-        "ć",
-        "f",
-    ],
-    "Hindi": [
-        "क",
-        "र",
-        "स",
-        "न",
-        "त",
-        "म",
-        "ह",
-        "प",
-        "य",
-        "ल",
-        "व",
-        "ज",
-        "द",
-        "ग",
-        "ब",
-        "श",
-        "ट",
-        "अ",
-        "ए",
-        "थ",
-        "भ",
-        "ड",
-        "च",
-        "ध",
-        "ष",
-        "इ",
-    ],
-    "Estonian": [
-        "a",
-        "i",
-        "e",
-        "s",
-        "t",
-        "l",
-        "u",
-        "n",
-        "o",
-        "k",
-        "r",
-        "d",
-        "m",
-        "v",
-        "g",
-        "p",
-        "j",
-        "h",
-        "ä",
-        "b",
-        "õ",
-        "ü",
-        "f",
-        "c",
-        "ö",
-        "y",
-    ],
-    "Thai": [
-        "า",
-        "น",
-        "ร",
-        "อ",
-        "ก",
-        "เ",
-        "ง",
-        "ม",
-        "ย",
-        "ล",
-        "ว",
-        "ด",
-        "ท",
-        "ส",
-        "ต",
-        "ะ",
-        "ป",
-        "บ",
-        "ค",
-        "ห",
-        "แ",
-        "จ",
-        "พ",
-        "ช",
-        "ข",
-        "ใ",
-    ],
-    "Greek": [
-        "α",
-        "τ",
-        "ο",
-        "ι",
-        "ε",
-        "ν",
-        "ρ",
-        "σ",
-        "κ",
-        "η",
-        "π",
-        "ς",
-        "υ",
-        "μ",
-        "λ",
-        "ί",
-        "ό",
-        "ά",
-        "γ",
-        "έ",
-        "δ",
-        "ή",
-        "ω",
-        "χ",
-        "θ",
-        "ύ",
-    ],
-    "Tamil": [
-        "க",
-        "த",
-        "ப",
-        "ட",
-        "ர",
-        "ம",
-        "ல",
-        "ன",
-        "வ",
-        "ற",
-        "ய",
-        "ள",
-        "ச",
-        "ந",
-        "இ",
-        "ண",
-        "அ",
-        "ஆ",
-        "ழ",
-        "ங",
-        "எ",
-        "உ",
-        "ஒ",
-        "ஸ",
-    ],
-    "Kazakh": [
-        "а",
-        "ы",
-        "е",
-        "н",
-        "т",
-        "р",
-        "л",
-        "і",
-        "д",
-        "с",
-        "м",
-        "қ",
-        "к",
-        "о",
-        "б",
-        "и",
-        "у",
-        "ғ",
-        "ж",
-        "ң",
-        "з",
-        "ш",
-        "й",
-        "п",
-        "г",
-        "ө",
-    ],
-}
-
-LANGUAGE_SUPPORTED_COUNT: int = len(FREQUENCIES)

path/to/venv/lib/python3.12/site-packages/charset_normalizer/legacy.py

@@ -1,54 +0,0 @@
-from typing import Any, Dict, Optional, Union
-from warnings import warn
-
-from .api import from_bytes
-from .constant import CHARDET_CORRESPONDENCE
-
-
-def detect(
-    byte_str: bytes, should_rename_legacy: bool = False, **kwargs: Any
-) -> Dict[str, Optional[Union[str, float]]]:
-    """
-    chardet legacy method
-    Detect the encoding of the given byte string. It should be mostly backward-compatible.
-    Encoding name will match Chardet own writing whenever possible. (Not on encoding name unsupported by it)
-    This function is deprecated and should be used to migrate your project easily, consult the documentation for
-    further information. Not planned for removal.
-
-    :param byte_str:     The byte sequence to examine.
-    :param should_rename_legacy:  Should we rename legacy encodings
-                                  to their more modern equivalents?
-    """
-    if len(kwargs):
-        warn(
-            f"charset-normalizer disregard arguments '{','.join(list(kwargs.keys()))}' in legacy function detect()"
-        )
-
-    if not isinstance(byte_str, (bytearray, bytes)):
-        raise TypeError(  # pragma: nocover
-            "Expected object of type bytes or bytearray, got: "
-            "{0}".format(type(byte_str))
-        )
-
-    if isinstance(byte_str, bytearray):
-        byte_str = bytes(byte_str)
-
-    r = from_bytes(byte_str).best()
-
-    encoding = r.encoding if r is not None else None
-    language = r.language if r is not None and r.language != "Unknown" else ""
-    confidence = 1.0 - r.chaos if r is not None else None
-
-    # Note: CharsetNormalizer does not return 'UTF-8-SIG' as the sig get stripped in the detection/normalization process
-    # but chardet does return 'utf-8-sig' and it is a valid codec name.
-    if r is not None and encoding == "utf_8" and r.bom:
-        encoding += "_sig"
-
-    if should_rename_legacy is False and encoding in CHARDET_CORRESPONDENCE:
-        encoding = CHARDET_CORRESPONDENCE[encoding]
-
-    return {
-        "encoding": encoding,
-        "language": language,
-        "confidence": confidence,
-    }

path/to/venv/lib/python3.12/site-packages/charset_normalizer/md.py

@@ -1,615 +0,0 @@
-from functools import lru_cache
-from logging import getLogger
-from typing import List, Optional
-
-from .constant import (
-    COMMON_SAFE_ASCII_CHARACTERS,
-    TRACE,
-    UNICODE_SECONDARY_RANGE_KEYWORD,
-)
-from .utils import (
-    is_accentuated,
-    is_arabic,
-    is_arabic_isolated_form,
-    is_case_variable,
-    is_cjk,
-    is_emoticon,
-    is_hangul,
-    is_hiragana,
-    is_katakana,
-    is_latin,
-    is_punctuation,
-    is_separator,
-    is_symbol,
-    is_thai,
-    is_unprintable,
-    remove_accent,
-    unicode_range,
-)
-
-
-class MessDetectorPlugin:
-    """
-    Base abstract class used for mess detection plugins.
-    All detectors MUST extend and implement given methods.
-    """
-
-    def eligible(self, character: str) -> bool:
-        """
-        Determine if given character should be fed in.
-        """
-        raise NotImplementedError  # pragma: nocover
-
-    def feed(self, character: str) -> None:
-        """
-        The main routine to be executed upon character.
-        Insert the logic in witch the text would be considered chaotic.
-        """
-        raise NotImplementedError  # pragma: nocover
-
-    def reset(self) -> None:  # pragma: no cover
-        """
-        Permit to reset the plugin to the initial state.
-        """
-        raise NotImplementedError
-
-    @property
-    def ratio(self) -> float:
-        """
-        Compute the chaos ratio based on what your feed() has seen.
-        Must NOT be lower than 0.; No restriction gt 0.
-        """
-        raise NotImplementedError  # pragma: nocover
-
-
-class TooManySymbolOrPunctuationPlugin(MessDetectorPlugin):
-    def __init__(self) -> None:
-        self._punctuation_count: int = 0
-        self._symbol_count: int = 0
-        self._character_count: int = 0
-
-        self._last_printable_char: Optional[str] = None
-        self._frenzy_symbol_in_word: bool = False
-
-    def eligible(self, character: str) -> bool:
-        return character.isprintable()
-
-    def feed(self, character: str) -> None:
-        self._character_count += 1
-
-        if (
-            character != self._last_printable_char
-            and character not in COMMON_SAFE_ASCII_CHARACTERS
-        ):
-            if is_punctuation(character):
-                self._punctuation_count += 1
-            elif (
-                character.isdigit() is False
-                and is_symbol(character)
-                and is_emoticon(character) is False
-            ):
-                self._symbol_count += 2
-
-        self._last_printable_char = character
-
-    def reset(self) -> None:  # pragma: no cover
-        self._punctuation_count = 0
-        self._character_count = 0
-        self._symbol_count = 0
-
-    @property
-    def ratio(self) -> float:
-        if self._character_count == 0:
-            return 0.0
-
-        ratio_of_punctuation: float = (
-            self._punctuation_count + self._symbol_count
-        ) / self._character_count
-
-        return ratio_of_punctuation if ratio_of_punctuation >= 0.3 else 0.0
-
-
-class TooManyAccentuatedPlugin(MessDetectorPlugin):
-    def __init__(self) -> None:
-        self._character_count: int = 0
-        self._accentuated_count: int = 0
-
-    def eligible(self, character: str) -> bool:
-        return character.isalpha()
-
-    def feed(self, character: str) -> None:
-        self._character_count += 1
-
-        if is_accentuated(character):
-            self._accentuated_count += 1
-
-    def reset(self) -> None:  # pragma: no cover
-        self._character_count = 0
-        self._accentuated_count = 0
-
-    @property
-    def ratio(self) -> float:
-        if self._character_count < 8:
-            return 0.0
-
-        ratio_of_accentuation: float = self._accentuated_count / self._character_count
-        return ratio_of_accentuation if ratio_of_accentuation >= 0.35 else 0.0
-
-
-class UnprintablePlugin(MessDetectorPlugin):
-    def __init__(self) -> None:
-        self._unprintable_count: int = 0
-        self._character_count: int = 0
-
-    def eligible(self, character: str) -> bool:
-        return True
-
-    def feed(self, character: str) -> None:
-        if is_unprintable(character):
-            self._unprintable_count += 1
-        self._character_count += 1
-
-    def reset(self) -> None:  # pragma: no cover
-        self._unprintable_count = 0
-
-    @property
-    def ratio(self) -> float:
-        if self._character_count == 0:
-            return 0.0
-
-        return (self._unprintable_count * 8) / self._character_count
-
-
-class SuspiciousDuplicateAccentPlugin(MessDetectorPlugin):
-    def __init__(self) -> None:
-        self._successive_count: int = 0
-        self._character_count: int = 0
-
-        self._last_latin_character: Optional[str] = None
-
-    def eligible(self, character: str) -> bool:
-        return character.isalpha() and is_latin(character)
-
-    def feed(self, character: str) -> None:
-        self._character_count += 1
-        if (
-            self._last_latin_character is not None
-            and is_accentuated(character)
-            and is_accentuated(self._last_latin_character)
-        ):
-            if character.isupper() and self._last_latin_character.isupper():
-                self._successive_count += 1
-            # Worse if its the same char duplicated with different accent.
-            if remove_accent(character) == remove_accent(self._last_latin_character):
-                self._successive_count += 1
-        self._last_latin_character = character
-
-    def reset(self) -> None:  # pragma: no cover
-        self._successive_count = 0
-        self._character_count = 0
-        self._last_latin_character = None
-
-    @property
-    def ratio(self) -> float:
-        if self._character_count == 0:
-            return 0.0
-
-        return (self._successive_count * 2) / self._character_count
-
-
-class SuspiciousRange(MessDetectorPlugin):
-    def __init__(self) -> None:
-        self._suspicious_successive_range_count: int = 0
-        self._character_count: int = 0
-        self._last_printable_seen: Optional[str] = None
-
-    def eligible(self, character: str) -> bool:
-        return character.isprintable()
-
-    def feed(self, character: str) -> None:
-        self._character_count += 1
-
-        if (
-            character.isspace()
-            or is_punctuation(character)
-            or character in COMMON_SAFE_ASCII_CHARACTERS
-        ):
-            self._last_printable_seen = None
-            return
-
-        if self._last_printable_seen is None:
-            self._last_printable_seen = character
-            return
-
-        unicode_range_a: Optional[str] = unicode_range(self._last_printable_seen)
-        unicode_range_b: Optional[str] = unicode_range(character)
-
-        if is_suspiciously_successive_range(unicode_range_a, unicode_range_b):
-            self._suspicious_successive_range_count += 1
-
-        self._last_printable_seen = character
-
-    def reset(self) -> None:  # pragma: no cover
-        self._character_count = 0
-        self._suspicious_successive_range_count = 0
-        self._last_printable_seen = None
-
-    @property
-    def ratio(self) -> float:
-        if self._character_count <= 24:
-            return 0.0
-
-        ratio_of_suspicious_range_usage: float = (
-            self._suspicious_successive_range_count * 2
-        ) / self._character_count
-
-        return ratio_of_suspicious_range_usage
-
-
-class SuperWeirdWordPlugin(MessDetectorPlugin):
-    def __init__(self) -> None:
-        self._word_count: int = 0
-        self._bad_word_count: int = 0
-        self._foreign_long_count: int = 0
-
-        self._is_current_word_bad: bool = False
-        self._foreign_long_watch: bool = False
-
-        self._character_count: int = 0
-        self._bad_character_count: int = 0
-
-        self._buffer: str = ""
-        self._buffer_accent_count: int = 0
-
-    def eligible(self, character: str) -> bool:
-        return True
-
-    def feed(self, character: str) -> None:
-        if character.isalpha():
-            self._buffer += character
-            if is_accentuated(character):
-                self._buffer_accent_count += 1
-            if (
-                self._foreign_long_watch is False
-                and (is_latin(character) is False or is_accentuated(character))
-                and is_cjk(character) is False
-                and is_hangul(character) is False
-                and is_katakana(character) is False
-                and is_hiragana(character) is False
-                and is_thai(character) is False
-            ):
-                self._foreign_long_watch = True
-            return
-        if not self._buffer:
-            return
-        if (
-            character.isspace() or is_punctuation(character) or is_separator(character)
-        ) and self._buffer:
-            self._word_count += 1
-            buffer_length: int = len(self._buffer)
-
-            self._character_count += buffer_length
-
-            if buffer_length >= 4:
-                if self._buffer_accent_count / buffer_length > 0.34:
-                    self._is_current_word_bad = True
-                # Word/Buffer ending with an upper case accentuated letter are so rare,
-                # that we will consider them all as suspicious. Same weight as foreign_long suspicious.
-                if (
-                    is_accentuated(self._buffer[-1])
-                    and self._buffer[-1].isupper()
-                    and all(_.isupper() for _ in self._buffer) is False
-                ):
-                    self._foreign_long_count += 1
-                    self._is_current_word_bad = True
-            if buffer_length >= 24 and self._foreign_long_watch:
-                camel_case_dst = [
-                    i
-                    for c, i in zip(self._buffer, range(0, buffer_length))
-                    if c.isupper()
-                ]
-                probable_camel_cased: bool = False
-
-                if camel_case_dst and (len(camel_case_dst) / buffer_length <= 0.3):
-                    probable_camel_cased = True
-
-                if not probable_camel_cased:
-                    self._foreign_long_count += 1
-                    self._is_current_word_bad = True
-
-            if self._is_current_word_bad:
-                self._bad_word_count += 1
-                self._bad_character_count += len(self._buffer)
-                self._is_current_word_bad = False
-
-            self._foreign_long_watch = False
-            self._buffer = ""
-            self._buffer_accent_count = 0
-        elif (
-            character not in {"<", ">", "-", "=", "~", "|", "_"}
-            and character.isdigit() is False
-            and is_symbol(character)
-        ):
-            self._is_current_word_bad = True
-            self._buffer += character
-
-    def reset(self) -> None:  # pragma: no cover
-        self._buffer = ""
-        self._is_current_word_bad = False
-        self._foreign_long_watch = False
-        self._bad_word_count = 0
-        self._word_count = 0
-        self._character_count = 0
-        self._bad_character_count = 0
-        self._foreign_long_count = 0
-
-    @property
-    def ratio(self) -> float:
-        if self._word_count <= 10 and self._foreign_long_count == 0:
-            return 0.0
-
-        return self._bad_character_count / self._character_count
-
-
-class CjkInvalidStopPlugin(MessDetectorPlugin):
-    """
-    GB(Chinese) based encoding often render the stop incorrectly when the content does not fit and
-    can be easily detected. Searching for the overuse of '丅' and '丄'.
-    """
-
-    def __init__(self) -> None:
-        self._wrong_stop_count: int = 0
-        self._cjk_character_count: int = 0
-
-    def eligible(self, character: str) -> bool:
-        return True
-
-    def feed(self, character: str) -> None:
-        if character in {"丅", "丄"}:
-            self._wrong_stop_count += 1
-            return
-        if is_cjk(character):
-            self._cjk_character_count += 1
-
-    def reset(self) -> None:  # pragma: no cover
-        self._wrong_stop_count = 0
-        self._cjk_character_count = 0
-
-    @property
-    def ratio(self) -> float:
-        if self._cjk_character_count < 16:
-            return 0.0
-        return self._wrong_stop_count / self._cjk_character_count
-
-
-class ArchaicUpperLowerPlugin(MessDetectorPlugin):
-    def __init__(self) -> None:
-        self._buf: bool = False
-
-        self._character_count_since_last_sep: int = 0
-
-        self._successive_upper_lower_count: int = 0
-        self._successive_upper_lower_count_final: int = 0
-
-        self._character_count: int = 0
-
-        self._last_alpha_seen: Optional[str] = None
-        self._current_ascii_only: bool = True
-
-    def eligible(self, character: str) -> bool:
-        return True
-
-    def feed(self, character: str) -> None:
-        is_concerned = character.isalpha() and is_case_variable(character)
-        chunk_sep = is_concerned is False
-
-        if chunk_sep and self._character_count_since_last_sep > 0:
-            if (
-                self._character_count_since_last_sep <= 64
-                and character.isdigit() is False
-                and self._current_ascii_only is False
-            ):
-                self._successive_upper_lower_count_final += (
-                    self._successive_upper_lower_count
-                )
-
-            self._successive_upper_lower_count = 0
-            self._character_count_since_last_sep = 0
-            self._last_alpha_seen = None
-            self._buf = False
-            self._character_count += 1
-            self._current_ascii_only = True
-
-            return
-
-        if self._current_ascii_only is True and character.isascii() is False:
-            self._current_ascii_only = False
-
-        if self._last_alpha_seen is not None:
-            if (character.isupper() and self._last_alpha_seen.islower()) or (
-                character.islower() and self._last_alpha_seen.isupper()
-            ):
-                if self._buf is True:
-                    self._successive_upper_lower_count += 2
-                    self._buf = False
-                else:
-                    self._buf = True
-            else:
-                self._buf = False
-
-        self._character_count += 1
-        self._character_count_since_last_sep += 1
-        self._last_alpha_seen = character
-
-    def reset(self) -> None:  # pragma: no cover
-        self._character_count = 0
-        self._character_count_since_last_sep = 0
-        self._successive_upper_lower_count = 0
-        self._successive_upper_lower_count_final = 0
-        self._last_alpha_seen = None
-        self._buf = False
-        self._current_ascii_only = True
-
-    @property
-    def ratio(self) -> float:
-        if self._character_count == 0:
-            return 0.0
-
-        return self._successive_upper_lower_count_final / self._character_count
-
-
-class ArabicIsolatedFormPlugin(MessDetectorPlugin):
-    def __init__(self) -> None:
-        self._character_count: int = 0
-        self._isolated_form_count: int = 0
-
-    def reset(self) -> None:  # pragma: no cover
-        self._character_count = 0
-        self._isolated_form_count = 0
-
-    def eligible(self, character: str) -> bool:
-        return is_arabic(character)
-
-    def feed(self, character: str) -> None:
-        self._character_count += 1
-
-        if is_arabic_isolated_form(character):
-            self._isolated_form_count += 1
-
-    @property
-    def ratio(self) -> float:
-        if self._character_count < 8:
-            return 0.0
-
-        isolated_form_usage: float = self._isolated_form_count / self._character_count
-
-        return isolated_form_usage
-
-
-@lru_cache(maxsize=1024)
-def is_suspiciously_successive_range(
-    unicode_range_a: Optional[str], unicode_range_b: Optional[str]
-) -> bool:
-    """
-    Determine if two Unicode range seen next to each other can be considered as suspicious.
-    """
-    if unicode_range_a is None or unicode_range_b is None:
-        return True
-
-    if unicode_range_a == unicode_range_b:
-        return False
-
-    if "Latin" in unicode_range_a and "Latin" in unicode_range_b:
-        return False
-
-    if "Emoticons" in unicode_range_a or "Emoticons" in unicode_range_b:
-        return False
-
-    # Latin characters can be accompanied with a combining diacritical mark
-    # eg. Vietnamese.
-    if ("Latin" in unicode_range_a or "Latin" in unicode_range_b) and (
-        "Combining" in unicode_range_a or "Combining" in unicode_range_b
-    ):
-        return False
-
-    keywords_range_a, keywords_range_b = unicode_range_a.split(
-        " "
-    ), unicode_range_b.split(" ")
-
-    for el in keywords_range_a:
-        if el in UNICODE_SECONDARY_RANGE_KEYWORD:
-            continue
-        if el in keywords_range_b:
-            return False
-
-    # Japanese Exception
-    range_a_jp_chars, range_b_jp_chars = (
-        unicode_range_a
-        in (
-            "Hiragana",
-            "Katakana",
-        ),
-        unicode_range_b in ("Hiragana", "Katakana"),
-    )
-    if (range_a_jp_chars or range_b_jp_chars) and (
-        "CJK" in unicode_range_a or "CJK" in unicode_range_b
-    ):
-        return False
-    if range_a_jp_chars and range_b_jp_chars:
-        return False
-
-    if "Hangul" in unicode_range_a or "Hangul" in unicode_range_b:
-        if "CJK" in unicode_range_a or "CJK" in unicode_range_b:
-            return False
-        if unicode_range_a == "Basic Latin" or unicode_range_b == "Basic Latin":
-            return False
-
-    # Chinese/Japanese use dedicated range for punctuation and/or separators.
-    if ("CJK" in unicode_range_a or "CJK" in unicode_range_b) or (
-        unicode_range_a in ["Katakana", "Hiragana"]
-        and unicode_range_b in ["Katakana", "Hiragana"]
-    ):
-        if "Punctuation" in unicode_range_a or "Punctuation" in unicode_range_b:
-            return False
-        if "Forms" in unicode_range_a or "Forms" in unicode_range_b:
-            return False
-        if unicode_range_a == "Basic Latin" or unicode_range_b == "Basic Latin":
-            return False
-
-    return True
-
-
-@lru_cache(maxsize=2048)
-def mess_ratio(
-    decoded_sequence: str, maximum_threshold: float = 0.2, debug: bool = False
-) -> float:
-    """
-    Compute a mess ratio given a decoded bytes sequence. The maximum threshold does stop the computation earlier.
-    """
-
-    detectors: List[MessDetectorPlugin] = [
-        md_class() for md_class in MessDetectorPlugin.__subclasses__()
-    ]
-
-    length: int = len(decoded_sequence) + 1
-
-    mean_mess_ratio: float = 0.0
-
-    if length < 512:
-        intermediary_mean_mess_ratio_calc: int = 32
-    elif length <= 1024:
-        intermediary_mean_mess_ratio_calc = 64
-    else:
-        intermediary_mean_mess_ratio_calc = 128
-
-    for character, index in zip(decoded_sequence + "\n", range(length)):
-        for detector in detectors:
-            if detector.eligible(character):
-                detector.feed(character)
-
-        if (
-            index > 0 and index % intermediary_mean_mess_ratio_calc == 0
-        ) or index == length - 1:
-            mean_mess_ratio = sum(dt.ratio for dt in detectors)
-
-            if mean_mess_ratio >= maximum_threshold:
-                break
-
-    if debug:
-        logger = getLogger("charset_normalizer")
-
-        logger.log(
-            TRACE,
-            "Mess-detector extended-analysis start. "
-            f"intermediary_mean_mess_ratio_calc={intermediary_mean_mess_ratio_calc} mean_mess_ratio={mean_mess_ratio} "
-            f"maximum_threshold={maximum_threshold}",
-        )
-
-        if len(decoded_sequence) > 16:
-            logger.log(TRACE, f"Starting with: {decoded_sequence[:16]}")
-            logger.log(TRACE, f"Ending with: {decoded_sequence[-16::]}")
-
-        for dt in detectors:  # pragma: nocover
-            logger.log(TRACE, f"{dt.__class__}: {dt.ratio}")
-
-    return round(mean_mess_ratio, 3)

path/to/venv/lib/python3.12/site-packages/charset_normalizer/models.py

@@ -1,340 +0,0 @@
-from encodings.aliases import aliases
-from hashlib import sha256
-from json import dumps
-from typing import Any, Dict, Iterator, List, Optional, Tuple, Union
-
-from .constant import TOO_BIG_SEQUENCE
-from .utils import iana_name, is_multi_byte_encoding, unicode_range
-
-
-class CharsetMatch:
-    def __init__(
-        self,
-        payload: bytes,
-        guessed_encoding: str,
-        mean_mess_ratio: float,
-        has_sig_or_bom: bool,
-        languages: "CoherenceMatches",
-        decoded_payload: Optional[str] = None,
-    ):
-        self._payload: bytes = payload
-
-        self._encoding: str = guessed_encoding
-        self._mean_mess_ratio: float = mean_mess_ratio
-        self._languages: CoherenceMatches = languages
-        self._has_sig_or_bom: bool = has_sig_or_bom
-        self._unicode_ranges: Optional[List[str]] = None
-
-        self._leaves: List[CharsetMatch] = []
-        self._mean_coherence_ratio: float = 0.0
-
-        self._output_payload: Optional[bytes] = None
-        self._output_encoding: Optional[str] = None
-
-        self._string: Optional[str] = decoded_payload
-
-    def __eq__(self, other: object) -> bool:
-        if not isinstance(other, CharsetMatch):
-            raise TypeError(
-                "__eq__ cannot be invoked on {} and {}.".format(
-                    str(other.__class__), str(self.__class__)
-                )
-            )
-        return self.encoding == other.encoding and self.fingerprint == other.fingerprint
-
-    def __lt__(self, other: object) -> bool:
-        """
-        Implemented to make sorted available upon CharsetMatches items.
-        """
-        if not isinstance(other, CharsetMatch):
-            raise ValueError
-
-        chaos_difference: float = abs(self.chaos - other.chaos)
-        coherence_difference: float = abs(self.coherence - other.coherence)
-
-        # Below 1% difference --> Use Coherence
-        if chaos_difference < 0.01 and coherence_difference > 0.02:
-            return self.coherence > other.coherence
-        elif chaos_difference < 0.01 and coherence_difference <= 0.02:
-            # When having a difficult decision, use the result that decoded as many multi-byte as possible.
-            # preserve RAM usage!
-            if len(self._payload) >= TOO_BIG_SEQUENCE:
-                return self.chaos < other.chaos
-            return self.multi_byte_usage > other.multi_byte_usage
-
-        return self.chaos < other.chaos
-
-    @property
-    def multi_byte_usage(self) -> float:
-        return 1.0 - (len(str(self)) / len(self.raw))
-
-    def __str__(self) -> str:
-        # Lazy Str Loading
-        if self._string is None:
-            self._string = str(self._payload, self._encoding, "strict")
-        return self._string
-
-    def __repr__(self) -> str:
-        return "<CharsetMatch '{}' bytes({})>".format(self.encoding, self.fingerprint)
-
-    def add_submatch(self, other: "CharsetMatch") -> None:
-        if not isinstance(other, CharsetMatch) or other == self:
-            raise ValueError(
-                "Unable to add instance <{}> as a submatch of a CharsetMatch".format(
-                    other.__class__
-                )
-            )
-
-        other._string = None  # Unload RAM usage; dirty trick.
-        self._leaves.append(other)
-
-    @property
-    def encoding(self) -> str:
-        return self._encoding
-
-    @property
-    def encoding_aliases(self) -> List[str]:
-        """
-        Encoding name are known by many name, using this could help when searching for IBM855 when it's listed as CP855.
-        """
-        also_known_as: List[str] = []
-        for u, p in aliases.items():
-            if self.encoding == u:
-                also_known_as.append(p)
-            elif self.encoding == p:
-                also_known_as.append(u)
-        return also_known_as
-
-    @property
-    def bom(self) -> bool:
-        return self._has_sig_or_bom
-
-    @property
-    def byte_order_mark(self) -> bool:
-        return self._has_sig_or_bom
-
-    @property
-    def languages(self) -> List[str]:
-        """
-        Return the complete list of possible languages found in decoded sequence.
-        Usually not really useful. Returned list may be empty even if 'language' property return something != 'Unknown'.
-        """
-        return [e[0] for e in self._languages]
-
-    @property
-    def language(self) -> str:
-        """
-        Most probable language found in decoded sequence. If none were detected or inferred, the property will return
-        "Unknown".
-        """
-        if not self._languages:
-            # Trying to infer the language based on the given encoding
-            # Its either English or we should not pronounce ourselves in certain cases.
-            if "ascii" in self.could_be_from_charset:
-                return "English"
-
-            # doing it there to avoid circular import
-            from charset_normalizer.cd import encoding_languages, mb_encoding_languages
-
-            languages = (
-                mb_encoding_languages(self.encoding)
-                if is_multi_byte_encoding(self.encoding)
-                else encoding_languages(self.encoding)
-            )
-
-            if len(languages) == 0 or "Latin Based" in languages:
-                return "Unknown"
-
-            return languages[0]
-
-        return self._languages[0][0]
-
-    @property
-    def chaos(self) -> float:
-        return self._mean_mess_ratio
-
-    @property
-    def coherence(self) -> float:
-        if not self._languages:
-            return 0.0
-        return self._languages[0][1]
-
-    @property
-    def percent_chaos(self) -> float:
-        return round(self.chaos * 100, ndigits=3)
-
-    @property
-    def percent_coherence(self) -> float:
-        return round(self.coherence * 100, ndigits=3)
-
-    @property
-    def raw(self) -> bytes:
-        """
-        Original untouched bytes.
-        """
-        return self._payload
-
-    @property
-    def submatch(self) -> List["CharsetMatch"]:
-        return self._leaves
-
-    @property
-    def has_submatch(self) -> bool:
-        return len(self._leaves) > 0
-
-    @property
-    def alphabets(self) -> List[str]:
-        if self._unicode_ranges is not None:
-            return self._unicode_ranges
-        # list detected ranges
-        detected_ranges: List[Optional[str]] = [
-            unicode_range(char) for char in str(self)
-        ]
-        # filter and sort
-        self._unicode_ranges = sorted(list({r for r in detected_ranges if r}))
-        return self._unicode_ranges
-
-    @property
-    def could_be_from_charset(self) -> List[str]:
-        """
-        The complete list of encoding that output the exact SAME str result and therefore could be the originating
-        encoding.
-        This list does include the encoding available in property 'encoding'.
-        """
-        return [self._encoding] + [m.encoding for m in self._leaves]
-
-    def output(self, encoding: str = "utf_8") -> bytes:
-        """
-        Method to get re-encoded bytes payload using given target encoding. Default to UTF-8.
-        Any errors will be simply ignored by the encoder NOT replaced.
-        """
-        if self._output_encoding is None or self._output_encoding != encoding:
-            self._output_encoding = encoding
-            self._output_payload = str(self).encode(encoding, "replace")
-
-        return self._output_payload  # type: ignore
-
-    @property
-    def fingerprint(self) -> str:
-        """
-        Retrieve the unique SHA256 computed using the transformed (re-encoded) payload. Not the original one.
-        """
-        return sha256(self.output()).hexdigest()
-
-
-class CharsetMatches:
-    """
-    Container with every CharsetMatch items ordered by default from most probable to the less one.
-    Act like a list(iterable) but does not implements all related methods.
-    """
-
-    def __init__(self, results: Optional[List[CharsetMatch]] = None):
-        self._results: List[CharsetMatch] = sorted(results) if results else []
-
-    def __iter__(self) -> Iterator[CharsetMatch]:
-        yield from self._results
-
-    def __getitem__(self, item: Union[int, str]) -> CharsetMatch:
-        """
-        Retrieve a single item either by its position or encoding name (alias may be used here).
-        Raise KeyError upon invalid index or encoding not present in results.
-        """
-        if isinstance(item, int):
-            return self._results[item]
-        if isinstance(item, str):
-            item = iana_name(item, False)
-            for result in self._results:
-                if item in result.could_be_from_charset:
-                    return result
-        raise KeyError
-
-    def __len__(self) -> int:
-        return len(self._results)
-
-    def __bool__(self) -> bool:
-        return len(self._results) > 0
-
-    def append(self, item: CharsetMatch) -> None:
-        """
-        Insert a single match. Will be inserted accordingly to preserve sort.
-        Can be inserted as a submatch.
-        """
-        if not isinstance(item, CharsetMatch):
-            raise ValueError(
-                "Cannot append instance '{}' to CharsetMatches".format(
-                    str(item.__class__)
-                )
-            )
-        # We should disable the submatch factoring when the input file is too heavy (conserve RAM usage)
-        if len(item.raw) <= TOO_BIG_SEQUENCE:
-            for match in self._results:
-                if match.fingerprint == item.fingerprint and match.chaos == item.chaos:
-                    match.add_submatch(item)
-                    return
-        self._results.append(item)
-        self._results = sorted(self._results)
-
-    def best(self) -> Optional["CharsetMatch"]:
-        """
-        Simply return the first match. Strict equivalent to matches[0].
-        """
-        if not self._results:
-            return None
-        return self._results[0]
-
-    def first(self) -> Optional["CharsetMatch"]:
-        """
-        Redundant method, call the method best(). Kept for BC reasons.
-        """
-        return self.best()
-
-
-CoherenceMatch = Tuple[str, float]
-CoherenceMatches = List[CoherenceMatch]
-
-
-class CliDetectionResult:
-    def __init__(
-        self,
-        path: str,
-        encoding: Optional[str],
-        encoding_aliases: List[str],
-        alternative_encodings: List[str],
-        language: str,
-        alphabets: List[str],
-        has_sig_or_bom: bool,
-        chaos: float,
-        coherence: float,
-        unicode_path: Optional[str],
-        is_preferred: bool,
-    ):
-        self.path: str = path
-        self.unicode_path: Optional[str] = unicode_path
-        self.encoding: Optional[str] = encoding
-        self.encoding_aliases: List[str] = encoding_aliases
-        self.alternative_encodings: List[str] = alternative_encodings
-        self.language: str = language
-        self.alphabets: List[str] = alphabets
-        self.has_sig_or_bom: bool = has_sig_or_bom
-        self.chaos: float = chaos
-        self.coherence: float = coherence
-        self.is_preferred: bool = is_preferred
-
-    @property
-    def __dict__(self) -> Dict[str, Any]:  # type: ignore
-        return {
-            "path": self.path,
-            "encoding": self.encoding,
-            "encoding_aliases": self.encoding_aliases,
-            "alternative_encodings": self.alternative_encodings,
-            "language": self.language,
-            "alphabets": self.alphabets,
-            "has_sig_or_bom": self.has_sig_or_bom,
-            "chaos": self.chaos,
-            "coherence": self.coherence,
-            "unicode_path": self.unicode_path,
-            "is_preferred": self.is_preferred,
-        }
-
-    def to_json(self) -> str:
-        return dumps(self.__dict__, ensure_ascii=True, indent=4)

path/to/venv/lib/python3.12/site-packages/charset_normalizer/utils.py

@@ -1,421 +0,0 @@
-import importlib
-import logging
-import unicodedata
-from codecs import IncrementalDecoder
-from encodings.aliases import aliases
-from functools import lru_cache
-from re import findall
-from typing import Generator, List, Optional, Set, Tuple, Union
-
-from _multibytecodec import MultibyteIncrementalDecoder
-
-from .constant import (
-    ENCODING_MARKS,
-    IANA_SUPPORTED_SIMILAR,
-    RE_POSSIBLE_ENCODING_INDICATION,
-    UNICODE_RANGES_COMBINED,
-    UNICODE_SECONDARY_RANGE_KEYWORD,
-    UTF8_MAXIMAL_ALLOCATION,
-)
-
-
-@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION)
-def is_accentuated(character: str) -> bool:
-    try:
-        description: str = unicodedata.name(character)
-    except ValueError:
-        return False
-    return (
-        "WITH GRAVE" in description
-        or "WITH ACUTE" in description
-        or "WITH CEDILLA" in description
-        or "WITH DIAERESIS" in description
-        or "WITH CIRCUMFLEX" in description
-        or "WITH TILDE" in description
-        or "WITH MACRON" in description
-        or "WITH RING ABOVE" in description
-    )
-
-
-@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION)
-def remove_accent(character: str) -> str:
-    decomposed: str = unicodedata.decomposition(character)
-    if not decomposed:
-        return character
-
-    codes: List[str] = decomposed.split(" ")
-
-    return chr(int(codes[0], 16))
-
-
-@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION)
-def unicode_range(character: str) -> Optional[str]:
-    """
-    Retrieve the Unicode range official name from a single character.
-    """
-    character_ord: int = ord(character)
-
-    for range_name, ord_range in UNICODE_RANGES_COMBINED.items():
-        if character_ord in ord_range:
-            return range_name
-
-    return None
-
-
-@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION)
-def is_latin(character: str) -> bool:
-    try:
-        description: str = unicodedata.name(character)
-    except ValueError:
-        return False
-    return "LATIN" in description
-
-
-@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION)
-def is_punctuation(character: str) -> bool:
-    character_category: str = unicodedata.category(character)
-
-    if "P" in character_category:
-        return True
-
-    character_range: Optional[str] = unicode_range(character)
-
-    if character_range is None:
-        return False
-
-    return "Punctuation" in character_range
-
-
-@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION)
-def is_symbol(character: str) -> bool:
-    character_category: str = unicodedata.category(character)
-
-    if "S" in character_category or "N" in character_category:
-        return True
-
-    character_range: Optional[str] = unicode_range(character)
-
-    if character_range is None:
-        return False
-
-    return "Forms" in character_range and character_category != "Lo"
-
-
-@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION)
-def is_emoticon(character: str) -> bool:
-    character_range: Optional[str] = unicode_range(character)
-
-    if character_range is None:
-        return False
-
-    return "Emoticons" in character_range or "Pictographs" in character_range
-
-
-@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION)
-def is_separator(character: str) -> bool:
-    if character.isspace() or character in {"｜", "+", "<", ">"}:
-        return True
-
-    character_category: str = unicodedata.category(character)
-
-    return "Z" in character_category or character_category in {"Po", "Pd", "Pc"}
-
-
-@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION)
-def is_case_variable(character: str) -> bool:
-    return character.islower() != character.isupper()
-
-
-@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION)
-def is_cjk(character: str) -> bool:
-    try:
-        character_name = unicodedata.name(character)
-    except ValueError:
-        return False
-
-    return "CJK" in character_name
-
-
-@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION)
-def is_hiragana(character: str) -> bool:
-    try:
-        character_name = unicodedata.name(character)
-    except ValueError:
-        return False
-
-    return "HIRAGANA" in character_name
-
-
-@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION)
-def is_katakana(character: str) -> bool:
-    try:
-        character_name = unicodedata.name(character)
-    except ValueError:
-        return False
-
-    return "KATAKANA" in character_name
-
-
-@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION)
-def is_hangul(character: str) -> bool:
-    try:
-        character_name = unicodedata.name(character)
-    except ValueError:
-        return False
-
-    return "HANGUL" in character_name
-
-
-@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION)
-def is_thai(character: str) -> bool:
-    try:
-        character_name = unicodedata.name(character)
-    except ValueError:
-        return False
-
-    return "THAI" in character_name
-
-
-@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION)
-def is_arabic(character: str) -> bool:
-    try:
-        character_name = unicodedata.name(character)
-    except ValueError:
-        return False
-
-    return "ARABIC" in character_name
-
-
-@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION)
-def is_arabic_isolated_form(character: str) -> bool:
-    try:
-        character_name = unicodedata.name(character)
-    except ValueError:
-        return False
-
-    return "ARABIC" in character_name and "ISOLATED FORM" in character_name
-
-
-@lru_cache(maxsize=len(UNICODE_RANGES_COMBINED))
-def is_unicode_range_secondary(range_name: str) -> bool:
-    return any(keyword in range_name for keyword in UNICODE_SECONDARY_RANGE_KEYWORD)
-
-
-@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION)
-def is_unprintable(character: str) -> bool:
-    return (
-        character.isspace() is False  # includes \n \t \r \v
-        and character.isprintable() is False
-        and character != "\x1A"  # Why? Its the ASCII substitute character.
-        and character != "\ufeff"  # bug discovered in Python,
-        # Zero Width No-Break Space located in 	Arabic Presentation Forms-B, Unicode 1.1 not acknowledged as space.
-    )
-
-
-def any_specified_encoding(sequence: bytes, search_zone: int = 8192) -> Optional[str]:
-    """
-    Extract using ASCII-only decoder any specified encoding in the first n-bytes.
-    """
-    if not isinstance(sequence, bytes):
-        raise TypeError
-
-    seq_len: int = len(sequence)
-
-    results: List[str] = findall(
-        RE_POSSIBLE_ENCODING_INDICATION,
-        sequence[: min(seq_len, search_zone)].decode("ascii", errors="ignore"),
-    )
-
-    if len(results) == 0:
-        return None
-
-    for specified_encoding in results:
-        specified_encoding = specified_encoding.lower().replace("-", "_")
-
-        encoding_alias: str
-        encoding_iana: str
-
-        for encoding_alias, encoding_iana in aliases.items():
-            if encoding_alias == specified_encoding:
-                return encoding_iana
-            if encoding_iana == specified_encoding:
-                return encoding_iana
-
-    return None
-
-
-@lru_cache(maxsize=128)
-def is_multi_byte_encoding(name: str) -> bool:
-    """
-    Verify is a specific encoding is a multi byte one based on it IANA name
-    """
-    return name in {
-        "utf_8",
-        "utf_8_sig",
-        "utf_16",
-        "utf_16_be",
-        "utf_16_le",
-        "utf_32",
-        "utf_32_le",
-        "utf_32_be",
-        "utf_7",
-    } or issubclass(
-        importlib.import_module("encodings.{}".format(name)).IncrementalDecoder,
-        MultibyteIncrementalDecoder,
-    )
-
-
-def identify_sig_or_bom(sequence: bytes) -> Tuple[Optional[str], bytes]:
-    """
-    Identify and extract SIG/BOM in given sequence.
-    """
-
-    for iana_encoding in ENCODING_MARKS:
-        marks: Union[bytes, List[bytes]] = ENCODING_MARKS[iana_encoding]
-
-        if isinstance(marks, bytes):
-            marks = [marks]
-
-        for mark in marks:
-            if sequence.startswith(mark):
-                return iana_encoding, mark
-
-    return None, b""
-
-
-def should_strip_sig_or_bom(iana_encoding: str) -> bool:
-    return iana_encoding not in {"utf_16", "utf_32"}
-
-
-def iana_name(cp_name: str, strict: bool = True) -> str:
-    cp_name = cp_name.lower().replace("-", "_")
-
-    encoding_alias: str
-    encoding_iana: str
-
-    for encoding_alias, encoding_iana in aliases.items():
-        if cp_name in [encoding_alias, encoding_iana]:
-            return encoding_iana
-
-    if strict:
-        raise ValueError("Unable to retrieve IANA for '{}'".format(cp_name))
-
-    return cp_name
-
-
-def range_scan(decoded_sequence: str) -> List[str]:
-    ranges: Set[str] = set()
-
-    for character in decoded_sequence:
-        character_range: Optional[str] = unicode_range(character)
-
-        if character_range is None:
-            continue
-
-        ranges.add(character_range)
-
-    return list(ranges)
-
-
-def cp_similarity(iana_name_a: str, iana_name_b: str) -> float:
-    if is_multi_byte_encoding(iana_name_a) or is_multi_byte_encoding(iana_name_b):
-        return 0.0
-
-    decoder_a = importlib.import_module(
-        "encodings.{}".format(iana_name_a)
-    ).IncrementalDecoder
-    decoder_b = importlib.import_module(
-        "encodings.{}".format(iana_name_b)
-    ).IncrementalDecoder
-
-    id_a: IncrementalDecoder = decoder_a(errors="ignore")
-    id_b: IncrementalDecoder = decoder_b(errors="ignore")
-
-    character_match_count: int = 0
-
-    for i in range(255):
-        to_be_decoded: bytes = bytes([i])
-        if id_a.decode(to_be_decoded) == id_b.decode(to_be_decoded):
-            character_match_count += 1
-
-    return character_match_count / 254
-
-
-def is_cp_similar(iana_name_a: str, iana_name_b: str) -> bool:
-    """
-    Determine if two code page are at least 80% similar. IANA_SUPPORTED_SIMILAR dict was generated using
-    the function cp_similarity.
-    """
-    return (
-        iana_name_a in IANA_SUPPORTED_SIMILAR
-        and iana_name_b in IANA_SUPPORTED_SIMILAR[iana_name_a]
-    )
-
-
-def set_logging_handler(
-    name: str = "charset_normalizer",
-    level: int = logging.INFO,
-    format_string: str = "%(asctime)s | %(levelname)s | %(message)s",
-) -> None:
-    logger = logging.getLogger(name)
-    logger.setLevel(level)
-
-    handler = logging.StreamHandler()
-    handler.setFormatter(logging.Formatter(format_string))
-    logger.addHandler(handler)
-
-
-def cut_sequence_chunks(
-    sequences: bytes,
-    encoding_iana: str,
-    offsets: range,
-    chunk_size: int,
-    bom_or_sig_available: bool,
-    strip_sig_or_bom: bool,
-    sig_payload: bytes,
-    is_multi_byte_decoder: bool,
-    decoded_payload: Optional[str] = None,
-) -> Generator[str, None, None]:
-    if decoded_payload and is_multi_byte_decoder is False:
-        for i in offsets:
-            chunk = decoded_payload[i : i + chunk_size]
-            if not chunk:
-                break
-            yield chunk
-    else:
-        for i in offsets:
-            chunk_end = i + chunk_size
-            if chunk_end > len(sequences) + 8:
-                continue
-
-            cut_sequence = sequences[i : i + chunk_size]
-
-            if bom_or_sig_available and strip_sig_or_bom is False:
-                cut_sequence = sig_payload + cut_sequence
-
-            chunk = cut_sequence.decode(
-                encoding_iana,
-                errors="ignore" if is_multi_byte_decoder else "strict",
-            )
-
-            # multi-byte bad cutting detector and adjustment
-            # not the cleanest way to perform that fix but clever enough for now.
-            if is_multi_byte_decoder and i > 0:
-                chunk_partial_size_chk: int = min(chunk_size, 16)
-
-                if (
-                    decoded_payload
-                    and chunk[:chunk_partial_size_chk] not in decoded_payload
-                ):
-                    for j in range(i, i - 4, -1):
-                        cut_sequence = sequences[j:chunk_end]
-
-                        if bom_or_sig_available and strip_sig_or_bom is False:
-                            cut_sequence = sig_payload + cut_sequence
-
-                        chunk = cut_sequence.decode(encoding_iana, errors="ignore")
-
-                        if chunk[:chunk_partial_size_chk] in decoded_payload:
-                            break
-
-            yield chunk

path/to/venv/lib/python3.12/site-packages/charset_normalizer/version.py

@@ -1,6 +0,0 @@
-"""
-Expose version
-"""
-
-__version__ = "3.3.2"
-VERSION = __version__.split(".")

path/to/venv/lib/python3.12/site-packages/idna-3.7.dist-info/INSTALLER

@@ -1 +0,0 @@
-pip

path/to/venv/lib/python3.12/site-packages/idna-3.7.dist-info/LICENSE.md

@@ -1,31 +0,0 @@
-BSD 3-Clause License
-
-Copyright (c) 2013-2024, Kim Davies and contributors.
-All rights reserved.
-
-Redistribution and use in source and binary forms, with or without
-modification, are permitted provided that the following conditions are
-met:
-
-1. Redistributions of source code must retain the above copyright
-   notice, this list of conditions and the following disclaimer.
-
-2. Redistributions in binary form must reproduce the above copyright
-   notice, this list of conditions and the following disclaimer in the
-   documentation and/or other materials provided with the distribution.
-
-3. Neither the name of the copyright holder nor the names of its
-   contributors may be used to endorse or promote products derived from
-   this software without specific prior written permission.
-
-THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
-"AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
-LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
-A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
-HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
-SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED
-TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
-PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
-LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
-NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
-SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

path/to/venv/lib/python3.12/site-packages/idna-3.7.dist-info/METADATA

@@ -1,243 +0,0 @@
-Metadata-Version: 2.1
-Name: idna
-Version: 3.7
-Summary: Internationalized Domain Names in Applications (IDNA)
-Author-email: Kim Davies <kim+pypi@gumleaf.org>
-Requires-Python: >=3.5
-Description-Content-Type: text/x-rst
-Classifier: Development Status :: 5 - Production/Stable
-Classifier: Intended Audience :: Developers
-Classifier: Intended Audience :: System Administrators
-Classifier: License :: OSI Approved :: BSD License
-Classifier: Operating System :: OS Independent
-Classifier: Programming Language :: Python
-Classifier: Programming Language :: Python :: 3
-Classifier: Programming Language :: Python :: 3 :: Only
-Classifier: Programming Language :: Python :: 3.5
-Classifier: Programming Language :: Python :: 3.6
-Classifier: Programming Language :: Python :: 3.7
-Classifier: Programming Language :: Python :: 3.8
-Classifier: Programming Language :: Python :: 3.9
-Classifier: Programming Language :: Python :: 3.10
-Classifier: Programming Language :: Python :: 3.11
-Classifier: Programming Language :: Python :: 3.12
-Classifier: Programming Language :: Python :: Implementation :: CPython
-Classifier: Programming Language :: Python :: Implementation :: PyPy
-Classifier: Topic :: Internet :: Name Service (DNS)
-Classifier: Topic :: Software Development :: Libraries :: Python Modules
-Classifier: Topic :: Utilities
-Project-URL: Changelog, https://github.com/kjd/idna/blob/master/HISTORY.rst
-Project-URL: Issue tracker, https://github.com/kjd/idna/issues
-Project-URL: Source, https://github.com/kjd/idna
-
-Internationalized Domain Names in Applications (IDNA)
-=====================================================
-
-Support for the Internationalized Domain Names in
-Applications (IDNA) protocol as specified in `RFC 5891
-<https://tools.ietf.org/html/rfc5891>`_. This is the latest version of
-the protocol and is sometimes referred to as “IDNA 2008”.
-
-This library also provides support for Unicode Technical
-Standard 46, `Unicode IDNA Compatibility Processing
-<https://unicode.org/reports/tr46/>`_.
-
-This acts as a suitable replacement for the “encodings.idna”
-module that comes with the Python standard library, but which
-only supports the older superseded IDNA specification (`RFC 3490
-<https://tools.ietf.org/html/rfc3490>`_).
-
-Basic functions are simply executed:
-
-.. code-block:: pycon
-
-    >>> import idna
-    >>> idna.encode('ドメイン.テスト')
-    b'xn--eckwd4c7c.xn--zckzah'
-    >>> print(idna.decode('xn--eckwd4c7c.xn--zckzah'))
-    ドメイン.テスト
-
-
-Installation
-------------
-
-This package is available for installation from PyPI:
-
-.. code-block:: bash
-
-    $ python3 -m pip install idna
-
-
-Usage
------
-
-For typical usage, the ``encode`` and ``decode`` functions will take a
-domain name argument and perform a conversion to A-labels or U-labels
-respectively.
-
-.. code-block:: pycon
-
-    >>> import idna
-    >>> idna.encode('ドメイン.テスト')
-    b'xn--eckwd4c7c.xn--zckzah'
-    >>> print(idna.decode('xn--eckwd4c7c.xn--zckzah'))
-    ドメイン.テスト
-
-You may use the codec encoding and decoding methods using the
-``idna.codec`` module:
-
-.. code-block:: pycon
-
-    >>> import idna.codec
-    >>> print('домен.испытание'.encode('idna2008'))
-    b'xn--d1acufc.xn--80akhbyknj4f'
-    >>> print(b'xn--d1acufc.xn--80akhbyknj4f'.decode('idna2008'))
-    домен.испытание
-
-Conversions can be applied at a per-label basis using the ``ulabel`` or
-``alabel`` functions if necessary:
-
-.. code-block:: pycon
-
-    >>> idna.alabel('测试')
-    b'xn--0zwm56d'
-
-Compatibility Mapping (UTS #46)
-+++++++++++++++++++++++++++++++
-
-As described in `RFC 5895 <https://tools.ietf.org/html/rfc5895>`_, the
-IDNA specification does not normalize input from different potential
-ways a user may input a domain name. This functionality, known as
-a “mapping”, is considered by the specification to be a local
-user-interface issue distinct from IDNA conversion functionality.
-
-This library provides one such mapping that was developed by the
-Unicode Consortium. Known as `Unicode IDNA Compatibility Processing
-<https://unicode.org/reports/tr46/>`_, it provides for both a regular
-mapping for typical applications, as well as a transitional mapping to
-help migrate from older IDNA 2003 applications.
-
-For example, “Königsgäßchen” is not a permissible label as *LATIN
-CAPITAL LETTER K* is not allowed (nor are capital letters in general).
-UTS 46 will convert this into lower case prior to applying the IDNA
-conversion.
-
-.. code-block:: pycon
-
-    >>> import idna
-    >>> idna.encode('Königsgäßchen')
-    ...
-    idna.core.InvalidCodepoint: Codepoint U+004B at position 1 of 'Königsgäßchen' not allowed
-    >>> idna.encode('Königsgäßchen', uts46=True)
-    b'xn--knigsgchen-b4a3dun'
-    >>> print(idna.decode('xn--knigsgchen-b4a3dun'))
-    königsgäßchen
-
-Transitional processing provides conversions to help transition from
-the older 2003 standard to the current standard. For example, in the
-original IDNA specification, the *LATIN SMALL LETTER SHARP S* (ß) was
-converted into two *LATIN SMALL LETTER S* (ss), whereas in the current
-IDNA specification this conversion is not performed.
-
-.. code-block:: pycon
-
-    >>> idna.encode('Königsgäßchen', uts46=True, transitional=True)
-    'xn--knigsgsschen-lcb0w'
-
-Implementers should use transitional processing with caution, only in
-rare cases where conversion from legacy labels to current labels must be
-performed (i.e. IDNA implementations that pre-date 2008). For typical
-applications that just need to convert labels, transitional processing
-is unlikely to be beneficial and could produce unexpected incompatible
-results.
-
-``encodings.idna`` Compatibility
-++++++++++++++++++++++++++++++++
-
-Function calls from the Python built-in ``encodings.idna`` module are
-mapped to their IDNA 2008 equivalents using the ``idna.compat`` module.
-Simply substitute the ``import`` clause in your code to refer to the new
-module name.
-
-Exceptions
-----------
-
-All errors raised during the conversion following the specification
-should raise an exception derived from the ``idna.IDNAError`` base
-class.
-
-More specific exceptions that may be generated as ``idna.IDNABidiError``
-when the error reflects an illegal combination of left-to-right and
-right-to-left characters in a label; ``idna.InvalidCodepoint`` when
-a specific codepoint is an illegal character in an IDN label (i.e.
-INVALID); and ``idna.InvalidCodepointContext`` when the codepoint is
-illegal based on its positional context (i.e. it is CONTEXTO or CONTEXTJ
-but the contextual requirements are not satisfied.)
-
-Building and Diagnostics
-------------------------
-
-The IDNA and UTS 46 functionality relies upon pre-calculated lookup
-tables for performance. These tables are derived from computing against
-eligibility criteria in the respective standards. These tables are
-computed using the command-line script ``tools/idna-data``.
-
-This tool will fetch relevant codepoint data from the Unicode repository
-and perform the required calculations to identify eligibility. There are
-three main modes:
-
-* ``idna-data make-libdata``. Generates ``idnadata.py`` and
-  ``uts46data.py``, the pre-calculated lookup tables used for IDNA and
-  UTS 46 conversions. Implementers who wish to track this library against
-  a different Unicode version may use this tool to manually generate a
-  different version of the ``idnadata.py`` and ``uts46data.py`` files.
-
-* ``idna-data make-table``. Generate a table of the IDNA disposition
-  (e.g. PVALID, CONTEXTJ, CONTEXTO) in the format found in Appendix
-  B.1 of RFC 5892 and the pre-computed tables published by `IANA
-  <https://www.iana.org/>`_.
-
-* ``idna-data U+0061``. Prints debugging output on the various
-  properties associated with an individual Unicode codepoint (in this
-  case, U+0061), that are used to assess the IDNA and UTS 46 status of a
-  codepoint. This is helpful in debugging or analysis.
-
-The tool accepts a number of arguments, described using ``idna-data
--h``. Most notably, the ``--version`` argument allows the specification
-of the version of Unicode to be used in computing the table data. For
-example, ``idna-data --version 9.0.0 make-libdata`` will generate
-library data against Unicode 9.0.0.
-
-
-Additional Notes
-----------------
-
-* **Packages**. The latest tagged release version is published in the
-  `Python Package Index <https://pypi.org/project/idna/>`_.
-
-* **Version support**. This library supports Python 3.5 and higher.
-  As this library serves as a low-level toolkit for a variety of
-  applications, many of which strive for broad compatibility with older
-  Python versions, there is no rush to remove older interpreter support.
-  Removing support for older versions should be well justified in that the
-  maintenance burden has become too high.
-
-* **Python 2**. Python 2 is supported by version 2.x of this library.
-  While active development of the version 2.x series has ended, notable
-  issues being corrected may be backported to 2.x. Use "idna<3" in your
-  requirements file if you need this library for a Python 2 application.
-
-* **Testing**. The library has a test suite based on each rule of the
-  IDNA specification, as well as tests that are provided as part of the
-  Unicode Technical Standard 46, `Unicode IDNA Compatibility Processing
-  <https://unicode.org/reports/tr46/>`_.
-
-* **Emoji**. It is an occasional request to support emoji domains in
-  this library. Encoding of symbols like emoji is expressly prohibited by
-  the technical standard IDNA 2008 and emoji domains are broadly phased
-  out across the domain industry due to associated security risks. For
-  now, applications that need to support these non-compliant labels
-  may wish to consider trying the encode/decode operation in this library
-  first, and then falling back to using `encodings.idna`. See `the Github
-  project <https://github.com/kjd/idna/issues/18>`_ for more discussion.
-

path/to/venv/lib/python3.12/site-packages/idna-3.7.dist-info/RECORD

@@ -1,22 +0,0 @@
-idna-3.7.dist-info/INSTALLER,sha256=zuuue4knoyJ-UwPPXg8fezS7VCrXJQrAP7zeNuwvFQg,4
-idna-3.7.dist-info/LICENSE.md,sha256=pZ8LDvNjWHQQmkRhykT_enDVBpboFHZ7-vch1Mmw2w8,1541
-idna-3.7.dist-info/METADATA,sha256=OixCk-dKLZkPy-MfviOmiPvwJ1O2K_8rqCrFjC_uxy4,9888
-idna-3.7.dist-info/RECORD,,
-idna-3.7.dist-info/WHEEL,sha256=EZbGkh7Ie4PoZfRQ8I0ZuP9VklN_TvcZ6DSE5Uar4z4,81
-idna/__init__.py,sha256=KJQN1eQBr8iIK5SKrJ47lXvxG0BJ7Lm38W4zT0v_8lk,849
-idna/__pycache__/__init__.cpython-312.pyc,,
-idna/__pycache__/codec.cpython-312.pyc,,
-idna/__pycache__/compat.cpython-312.pyc,,
-idna/__pycache__/core.cpython-312.pyc,,
-idna/__pycache__/idnadata.cpython-312.pyc,,
-idna/__pycache__/intranges.cpython-312.pyc,,
-idna/__pycache__/package_data.cpython-312.pyc,,
-idna/__pycache__/uts46data.cpython-312.pyc,,
-idna/codec.py,sha256=PS6m-XmdST7Wj7J7ulRMakPDt5EBJyYrT3CPtjh-7t4,3426
-idna/compat.py,sha256=0_sOEUMT4CVw9doD3vyRhX80X19PwqFoUBs7gWsFME4,321
-idna/core.py,sha256=lyhpoe2vulEaB_65xhXmoKgO-xUqFDvcwxu5hpNNO4E,12663
-idna/idnadata.py,sha256=dqRwytzkjIHMBa2R1lYvHDwACenZPt8eGVu1Y8UBE-E,78320
-idna/intranges.py,sha256=YBr4fRYuWH7kTKS2tXlFjM24ZF1Pdvcir-aywniInqg,1881
-idna/package_data.py,sha256=Tkt0KnIeyIlnHddOaz9WSkkislNgokJAuE-p5GorMqo,21
-idna/py.typed,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
-idna/uts46data.py,sha256=1KuksWqLuccPXm2uyRVkhfiFLNIhM_H2m4azCcnOqEU,206503

path/to/venv/lib/python3.12/site-packages/idna-3.7.dist-info/WHEEL

@@ -1,4 +0,0 @@
-Wheel-Version: 1.0
-Generator: flit 3.9.0
-Root-Is-Purelib: true
-Tag: py3-none-any

path/to/venv/lib/python3.12/site-packages/idna/__init__.py

@@ -1,44 +0,0 @@
-from .package_data import __version__
-from .core import (
-    IDNABidiError,
-    IDNAError,
-    InvalidCodepoint,
-    InvalidCodepointContext,
-    alabel,
-    check_bidi,
-    check_hyphen_ok,
-    check_initial_combiner,
-    check_label,
-    check_nfc,
-    decode,
-    encode,
-    ulabel,
-    uts46_remap,
-    valid_contextj,
-    valid_contexto,
-    valid_label_length,
-    valid_string_length,
-)
-from .intranges import intranges_contain
-
-__all__ = [
-    "IDNABidiError",
-    "IDNAError",
-    "InvalidCodepoint",
-    "InvalidCodepointContext",
-    "alabel",
-    "check_bidi",
-    "check_hyphen_ok",
-    "check_initial_combiner",
-    "check_label",
-    "check_nfc",
-    "decode",
-    "encode",
-    "intranges_contain",
-    "ulabel",
-    "uts46_remap",
-    "valid_contextj",
-    "valid_contexto",
-    "valid_label_length",
-    "valid_string_length",
-]

path/to/venv/lib/python3.12/site-packages/idna/codec.py

@@ -1,118 +0,0 @@
-from .core import encode, decode, alabel, ulabel, IDNAError
-import codecs
-import re
-from typing import Any, Tuple, Optional
-
-_unicode_dots_re = re.compile('[\u002e\u3002\uff0e\uff61]')
-
-class Codec(codecs.Codec):
-
-    def encode(self, data: str, errors: str = 'strict') -> Tuple[bytes, int]:
-        if errors != 'strict':
-            raise IDNAError('Unsupported error handling \"{}\"'.format(errors))
-
-        if not data:
-            return b"", 0
-
-        return encode(data), len(data)
-
-    def decode(self, data: bytes, errors: str = 'strict') -> Tuple[str, int]:
-        if errors != 'strict':
-            raise IDNAError('Unsupported error handling \"{}\"'.format(errors))
-
-        if not data:
-            return '', 0
-
-        return decode(data), len(data)
-
-class IncrementalEncoder(codecs.BufferedIncrementalEncoder):
-    def _buffer_encode(self, data: str, errors: str, final: bool) -> Tuple[bytes, int]:
-        if errors != 'strict':
-            raise IDNAError('Unsupported error handling \"{}\"'.format(errors))
-
-        if not data:
-            return b'', 0
-
-        labels = _unicode_dots_re.split(data)
-        trailing_dot = b''
-        if labels:
-            if not labels[-1]:
-                trailing_dot = b'.'
-                del labels[-1]
-            elif not final:
-                # Keep potentially unfinished label until the next call
-                del labels[-1]
-                if labels:
-                    trailing_dot = b'.'
-
-        result = []
-        size = 0
-        for label in labels:
-            result.append(alabel(label))
-            if size:
-                size += 1
-            size += len(label)
-
-        # Join with U+002E
-        result_bytes = b'.'.join(result) + trailing_dot
-        size += len(trailing_dot)
-        return result_bytes, size
-
-class IncrementalDecoder(codecs.BufferedIncrementalDecoder):
-    def _buffer_decode(self, data: Any, errors: str, final: bool) -> Tuple[str, int]:
-        if errors != 'strict':
-            raise IDNAError('Unsupported error handling \"{}\"'.format(errors))
-
-        if not data:
-            return ('', 0)
-
-        if not isinstance(data, str):
-            data = str(data, 'ascii')
-
-        labels = _unicode_dots_re.split(data)
-        trailing_dot = ''
-        if labels:
-            if not labels[-1]:
-                trailing_dot = '.'
-                del labels[-1]
-            elif not final:
-                # Keep potentially unfinished label until the next call
-                del labels[-1]
-                if labels:
-                    trailing_dot = '.'
-
-        result = []
-        size = 0
-        for label in labels:
-            result.append(ulabel(label))
-            if size:
-                size += 1
-            size += len(label)
-
-        result_str = '.'.join(result) + trailing_dot
-        size += len(trailing_dot)
-        return (result_str, size)
-
-
-class StreamWriter(Codec, codecs.StreamWriter):
-    pass
-
-
-class StreamReader(Codec, codecs.StreamReader):
-    pass
-
-
-def search_function(name: str) -> Optional[codecs.CodecInfo]:
-    if name != 'idna2008':
-        return None
-    return codecs.CodecInfo(
-        name=name,
-        encode=Codec().encode,
-        decode=Codec().decode,
-        incrementalencoder=IncrementalEncoder,
-        incrementaldecoder=IncrementalDecoder,
-        streamwriter=StreamWriter,
-        streamreader=StreamReader,
-    )
-
-codecs.register(search_function)

path/to/venv/lib/python3.12/site-packages/idna/compat.py

@@ -1,13 +0,0 @@
-from .core import *
-from .codec import *
-from typing import Any, Union
-
-def ToASCII(label: str) -> bytes:
-    return encode(label)
-
-def ToUnicode(label: Union[bytes, bytearray]) -> str:
-    return decode(label)
-
-def nameprep(s: Any) -> None:
-    raise NotImplementedError('IDNA 2008 does not utilise nameprep protocol')
-

path/to/venv/lib/python3.12/site-packages/idna/core.py

@@ -1,395 +0,0 @@
-from . import idnadata
-import bisect
-import unicodedata
-import re
-from typing import Union, Optional
-from .intranges import intranges_contain
-
-_virama_combining_class = 9
-_alabel_prefix = b'xn--'
-_unicode_dots_re = re.compile('[\u002e\u3002\uff0e\uff61]')
-
-class IDNAError(UnicodeError):
-    """ Base exception for all IDNA-encoding related problems """
-    pass
-
-
-class IDNABidiError(IDNAError):
-    """ Exception when bidirectional requirements are not satisfied """
-    pass
-
-
-class InvalidCodepoint(IDNAError):
-    """ Exception when a disallowed or unallocated codepoint is used """
-    pass
-
-
-class InvalidCodepointContext(IDNAError):
-    """ Exception when the codepoint is not valid in the context it is used """
-    pass
-
-
-def _combining_class(cp: int) -> int:
-    v = unicodedata.combining(chr(cp))
-    if v == 0:
-        if not unicodedata.name(chr(cp)):
-            raise ValueError('Unknown character in unicodedata')
-    return v
-
-def _is_script(cp: str, script: str) -> bool:
-    return intranges_contain(ord(cp), idnadata.scripts[script])
-
-def _punycode(s: str) -> bytes:
-    return s.encode('punycode')
-
-def _unot(s: int) -> str:
-    return 'U+{:04X}'.format(s)
-
-
-def valid_label_length(label: Union[bytes, str]) -> bool:
-    if len(label) > 63:
-        return False
-    return True
-
-
-def valid_string_length(label: Union[bytes, str], trailing_dot: bool) -> bool:
-    if len(label) > (254 if trailing_dot else 253):
-        return False
-    return True
-
-
-def check_bidi(label: str, check_ltr: bool = False) -> bool:
-    # Bidi rules should only be applied if string contains RTL characters
-    bidi_label = False
-    for (idx, cp) in enumerate(label, 1):
-        direction = unicodedata.bidirectional(cp)
-        if direction == '':
-            # String likely comes from a newer version of Unicode
-            raise IDNABidiError('Unknown directionality in label {} at position {}'.format(repr(label), idx))
-        if direction in ['R', 'AL', 'AN']:
-            bidi_label = True
-    if not bidi_label and not check_ltr:
-        return True
-
-    # Bidi rule 1
-    direction = unicodedata.bidirectional(label[0])
-    if direction in ['R', 'AL']:
-        rtl = True
-    elif direction == 'L':
-        rtl = False
-    else:
-        raise IDNABidiError('First codepoint in label {} must be directionality L, R or AL'.format(repr(label)))
-
-    valid_ending = False
-    number_type = None  # type: Optional[str]
-    for (idx, cp) in enumerate(label, 1):
-        direction = unicodedata.bidirectional(cp)
-
-        if rtl:
-            # Bidi rule 2
-            if not direction in ['R', 'AL', 'AN', 'EN', 'ES', 'CS', 'ET', 'ON', 'BN', 'NSM']:
-                raise IDNABidiError('Invalid direction for codepoint at position {} in a right-to-left label'.format(idx))
-            # Bidi rule 3
-            if direction in ['R', 'AL', 'EN', 'AN']:
-                valid_ending = True
-            elif direction != 'NSM':
-                valid_ending = False
-            # Bidi rule 4
-            if direction in ['AN', 'EN']:
-                if not number_type:
-                    number_type = direction
-                else:
-                    if number_type != direction:
-                        raise IDNABidiError('Can not mix numeral types in a right-to-left label')
-        else:
-            # Bidi rule 5
-            if not direction in ['L', 'EN', 'ES', 'CS', 'ET', 'ON', 'BN', 'NSM']:
-                raise IDNABidiError('Invalid direction for codepoint at position {} in a left-to-right label'.format(idx))
-            # Bidi rule 6
-            if direction in ['L', 'EN']:
-                valid_ending = True
-            elif direction != 'NSM':
-                valid_ending = False
-
-    if not valid_ending:
-        raise IDNABidiError('Label ends with illegal codepoint directionality')
-
-    return True
-
-
-def check_initial_combiner(label: str) -> bool:
-    if unicodedata.category(label[0])[0] == 'M':
-        raise IDNAError('Label begins with an illegal combining character')
-    return True
-
-
-def check_hyphen_ok(label: str) -> bool:
-    if label[2:4] == '--':
-        raise IDNAError('Label has disallowed hyphens in 3rd and 4th position')
-    if label[0] == '-' or label[-1] == '-':
-        raise IDNAError('Label must not start or end with a hyphen')
-    return True
-
-
-def check_nfc(label: str) -> None:
-    if unicodedata.normalize('NFC', label) != label:
-        raise IDNAError('Label must be in Normalization Form C')
-
-
-def valid_contextj(label: str, pos: int) -> bool:
-    cp_value = ord(label[pos])
-
-    if cp_value == 0x200c:
-
-        if pos > 0:
-            if _combining_class(ord(label[pos - 1])) == _virama_combining_class:
-                return True
-
-        ok = False
-        for i in range(pos-1, -1, -1):
-            joining_type = idnadata.joining_types.get(ord(label[i]))
-            if joining_type == ord('T'):
-                continue
-            elif joining_type in [ord('L'), ord('D')]:
-                ok = True
-                break
-            else:
-                break
-
-        if not ok:
-            return False
-
-        ok = False
-        for i in range(pos+1, len(label)):
-            joining_type = idnadata.joining_types.get(ord(label[i]))
-            if joining_type == ord('T'):
-                continue
-            elif joining_type in [ord('R'), ord('D')]:
-                ok = True
-                break
-            else:
-                break
-        return ok
-
-    if cp_value == 0x200d:
-
-        if pos > 0:
-            if _combining_class(ord(label[pos - 1])) == _virama_combining_class:
-                return True
-        return False
-
-    else:
-
-        return False
-
-
-def valid_contexto(label: str, pos: int, exception: bool = False) -> bool:
-    cp_value = ord(label[pos])
-
-    if cp_value == 0x00b7:
-        if 0 < pos < len(label)-1:
-            if ord(label[pos - 1]) == 0x006c and ord(label[pos + 1]) == 0x006c:
-                return True
-        return False
-
-    elif cp_value == 0x0375:
-        if pos < len(label)-1 and len(label) > 1:
-            return _is_script(label[pos + 1], 'Greek')
-        return False
-
-    elif cp_value == 0x05f3 or cp_value == 0x05f4:
-        if pos > 0:
-            return _is_script(label[pos - 1], 'Hebrew')
-        return False
-
-    elif cp_value == 0x30fb:
-        for cp in label:
-            if cp == '\u30fb':
-                continue
-            if _is_script(cp, 'Hiragana') or _is_script(cp, 'Katakana') or _is_script(cp, 'Han'):
-                return True
-        return False
-
-    elif 0x660 <= cp_value <= 0x669:
-        for cp in label:
-            if 0x6f0 <= ord(cp) <= 0x06f9:
-                return False
-        return True
-
-    elif 0x6f0 <= cp_value <= 0x6f9:
-        for cp in label:
-            if 0x660 <= ord(cp) <= 0x0669:
-                return False
-        return True
-
-    return False
-
-
-def check_label(label: Union[str, bytes, bytearray]) -> None:
-    if isinstance(label, (bytes, bytearray)):
-        label = label.decode('utf-8')
-    if len(label) == 0:
-        raise IDNAError('Empty Label')
-
-    check_nfc(label)
-    check_hyphen_ok(label)
-    check_initial_combiner(label)
-
-    for (pos, cp) in enumerate(label):
-        cp_value = ord(cp)
-        if intranges_contain(cp_value, idnadata.codepoint_classes['PVALID']):
-            continue
-        elif intranges_contain(cp_value, idnadata.codepoint_classes['CONTEXTJ']):
-            if not valid_contextj(label, pos):
-                raise InvalidCodepointContext('Joiner {} not allowed at position {} in {}'.format(
-                    _unot(cp_value), pos+1, repr(label)))
-        elif intranges_contain(cp_value, idnadata.codepoint_classes['CONTEXTO']):
-            if not valid_contexto(label, pos):
-                raise InvalidCodepointContext('Codepoint {} not allowed at position {} in {}'.format(_unot(cp_value), pos+1, repr(label)))
-        else:
-            raise InvalidCodepoint('Codepoint {} at position {} of {} not allowed'.format(_unot(cp_value), pos+1, repr(label)))
-
-    check_bidi(label)
-
-
-def alabel(label: str) -> bytes:
-    try:
-        label_bytes = label.encode('ascii')
-        ulabel(label_bytes)
-        if not valid_label_length(label_bytes):
-            raise IDNAError('Label too long')
-        return label_bytes
-    except UnicodeEncodeError:
-        pass
-
-    check_label(label)
-    label_bytes = _alabel_prefix + _punycode(label)
-
-    if not valid_label_length(label_bytes):
-        raise IDNAError('Label too long')
-
-    return label_bytes
-
-
-def ulabel(label: Union[str, bytes, bytearray]) -> str:
-    if not isinstance(label, (bytes, bytearray)):
-        try:
-            label_bytes = label.encode('ascii')
-        except UnicodeEncodeError:
-            check_label(label)
-            return label
-    else:
-        label_bytes = label
-
-    label_bytes = label_bytes.lower()
-    if label_bytes.startswith(_alabel_prefix):
-        label_bytes = label_bytes[len(_alabel_prefix):]
-        if not label_bytes:
-            raise IDNAError('Malformed A-label, no Punycode eligible content found')
-        if label_bytes.decode('ascii')[-1] == '-':
-            raise IDNAError('A-label must not end with a hyphen')
-    else:
-        check_label(label_bytes)
-        return label_bytes.decode('ascii')
-
-    try:
-        label = label_bytes.decode('punycode')
-    except UnicodeError:
-        raise IDNAError('Invalid A-label')
-    check_label(label)
-    return label
-
-
-def uts46_remap(domain: str, std3_rules: bool = True, transitional: bool = False) -> str:
-    """Re-map the characters in the string according to UTS46 processing."""
-    from .uts46data import uts46data
-    output = ''
-
-    for pos, char in enumerate(domain):
-        code_point = ord(char)
-        try:
-            uts46row = uts46data[code_point if code_point < 256 else
-                bisect.bisect_left(uts46data, (code_point, 'Z')) - 1]
-            status = uts46row[1]
-            replacement = None  # type: Optional[str]
-            if len(uts46row) == 3:
-                replacement = uts46row[2]
-            if (status == 'V' or
-                    (status == 'D' and not transitional) or
-                    (status == '3' and not std3_rules and replacement is None)):
-                output += char
-            elif replacement is not None and (status == 'M' or
-                    (status == '3' and not std3_rules) or
-                    (status == 'D' and transitional)):
-                output += replacement
-            elif status != 'I':
-                raise IndexError()
-        except IndexError:
-            raise InvalidCodepoint(
-                'Codepoint {} not allowed at position {} in {}'.format(
-                _unot(code_point), pos + 1, repr(domain)))
-
-    return unicodedata.normalize('NFC', output)
-
-
-def encode(s: Union[str, bytes, bytearray], strict: bool = False, uts46: bool = False, std3_rules: bool = False, transitional: bool = False) -> bytes:
-    if not isinstance(s, str):
-        try:
-            s = str(s, 'ascii')
-        except UnicodeDecodeError:
-            raise IDNAError('should pass a unicode string to the function rather than a byte string.')
-    if uts46:
-        s = uts46_remap(s, std3_rules, transitional)
-    trailing_dot = False
-    result = []
-    if strict:
-        labels = s.split('.')
-    else:
-        labels = _unicode_dots_re.split(s)
-    if not labels or labels == ['']:
-        raise IDNAError('Empty domain')
-    if labels[-1] == '':
-        del labels[-1]
-        trailing_dot = True
-    for label in labels:
-        s = alabel(label)
-        if s:
-            result.append(s)
-        else:
-            raise IDNAError('Empty label')
-    if trailing_dot:
-        result.append(b'')
-    s = b'.'.join(result)
-    if not valid_string_length(s, trailing_dot):
-        raise IDNAError('Domain too long')
-    return s
-
-
-def decode(s: Union[str, bytes, bytearray], strict: bool = False, uts46: bool = False, std3_rules: bool = False) -> str:
-    try:
-        if not isinstance(s, str):
-            s = str(s, 'ascii')
-    except UnicodeDecodeError:
-        raise IDNAError('Invalid ASCII in A-label')
-    if uts46:
-        s = uts46_remap(s, std3_rules, False)
-    trailing_dot = False
-    result = []
-    if not strict:
-        labels = _unicode_dots_re.split(s)
-    else:
-        labels = s.split('.')
-    if not labels or labels == ['']:
-        raise IDNAError('Empty domain')
-    if not labels[-1]:
-        del labels[-1]
-        trailing_dot = True
-    for label in labels:
-        s = ulabel(label)
-        if s:
-            result.append(s)
-        else:
-            raise IDNAError('Empty label')
-    if trailing_dot:
-        result.append('')
-    return '.'.join(result)

path/to/venv/lib/python3.12/site-packages/idna/idnadata.py

@@ -1,4245 +0,0 @@
-# This file is automatically generated by tools/idna-data
-
-__version__ = '15.1.0'
-scripts = {
-    'Greek': (
-        0x37000000374,
-        0x37500000378,
-        0x37a0000037e,
-        0x37f00000380,
-        0x38400000385,
-        0x38600000387,
-        0x3880000038b,
-        0x38c0000038d,
-        0x38e000003a2,
-        0x3a3000003e2,
-        0x3f000000400,
-        0x1d2600001d2b,
-        0x1d5d00001d62,
-        0x1d6600001d6b,
-        0x1dbf00001dc0,
-        0x1f0000001f16,
-        0x1f1800001f1e,
-        0x1f2000001f46,
-        0x1f4800001f4e,
-        0x1f5000001f58,
-        0x1f5900001f5a,
-        0x1f5b00001f5c,
-        0x1f5d00001f5e,
-        0x1f5f00001f7e,
-        0x1f8000001fb5,
-        0x1fb600001fc5,
-        0x1fc600001fd4,
-        0x1fd600001fdc,
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path/to/venv/lib/python3.12/site-packages/idna/intranges.py

@@ -1,54 +0,0 @@
-"""
-Given a list of integers, made up of (hopefully) a small number of long runs
-of consecutive integers, compute a representation of the form
-((start1, end1), (start2, end2) ...). Then answer the question "was x present
-in the original list?" in time O(log(# runs)).
-"""
-
-import bisect
-from typing import List, Tuple
-
-def intranges_from_list(list_: List[int]) -> Tuple[int, ...]:
-    """Represent a list of integers as a sequence of ranges:
-    ((start_0, end_0), (start_1, end_1), ...), such that the original
-    integers are exactly those x such that start_i <= x < end_i for some i.
-
-    Ranges are encoded as single integers (start << 32 | end), not as tuples.
-    """
-
-    sorted_list = sorted(list_)
-    ranges = []
-    last_write = -1
-    for i in range(len(sorted_list)):
-        if i+1 < len(sorted_list):
-            if sorted_list[i] == sorted_list[i+1]-1:
-                continue
-        current_range = sorted_list[last_write+1:i+1]
-        ranges.append(_encode_range(current_range[0], current_range[-1] + 1))
-        last_write = i
-
-    return tuple(ranges)
-
-def _encode_range(start: int, end: int) -> int:
-    return (start << 32) | end
-
-def _decode_range(r: int) -> Tuple[int, int]:
-    return (r >> 32), (r & ((1 << 32) - 1))
-
-
-def intranges_contain(int_: int, ranges: Tuple[int, ...]) -> bool:
-    """Determine if `int_` falls into one of the ranges in `ranges`."""
-    tuple_ = _encode_range(int_, 0)
-    pos = bisect.bisect_left(ranges, tuple_)
-    # we could be immediately ahead of a tuple (start, end)
-    # with start < int_ <= end
-    if pos > 0:
-        left, right = _decode_range(ranges[pos-1])
-        if left <= int_ < right:
-            return True
-    # or we could be immediately behind a tuple (int_, end)
-    if pos < len(ranges):
-        left, _ = _decode_range(ranges[pos])
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path/to/venv/lib/python3.12/site-packages/idna/package_data.py

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path/to/venv/lib/python3.12/site-packages/idna/uts46data.py

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path/to/venv/lib/python3.12/site-packages/pip-24.0.dist-info/AUTHORS.txt

@@ -1,760 +0,0 @@
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-Project-URL: Documentation, https://pip.pypa.io
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----------------
-
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-.. _Installation: https://pip.pypa.io/en/stable/installation/
-.. _Usage: https://pip.pypa.io/en/stable/
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path/to/venv/lib/python3.12/site-packages/pip-24.0.dist-info/WHEEL

@@ -1,5 +0,0 @@
-Wheel-Version: 1.0
-Generator: bdist_wheel (0.43.0)
-Root-Is-Purelib: true
-Tag: py3-none-any
-

path/to/venv/lib/python3.12/site-packages/pip-24.0.dist-info/entry_points.txt

@@ -1,4 +0,0 @@
-[console_scripts]
-pip = pip._internal.cli.main:main
-pip3 = pip._internal.cli.main:main
-pip3.12 = pip._internal.cli.main:main

path/to/venv/lib/python3.12/site-packages/pip-24.0.dist-info/top_level.txt

@@ -1 +0,0 @@
-pip

path/to/venv/lib/python3.12/site-packages/pip/__init__.py

@@ -1,13 +0,0 @@
-from typing import List, Optional
-
-__version__ = "24.0"
-
-
-def main(args: Optional[List[str]] = None) -> int:
-    """This is an internal API only meant for use by pip's own console scripts.
-
-    For additional details, see https://github.com/pypa/pip/issues/7498.
-    """
-    from pip._internal.utils.entrypoints import _wrapper
-
-    return _wrapper(args)

path/to/venv/lib/python3.12/site-packages/pip/__main__.py

@@ -1,24 +0,0 @@
-import os
-import sys
-
-# Remove '' and current working directory from the first entry
-# of sys.path, if present to avoid using current directory
-# in pip commands check, freeze, install, list and show,
-# when invoked as python -m pip <command>
-if sys.path[0] in ("", os.getcwd()):
-    sys.path.pop(0)
-
-# If we are running from a wheel, add the wheel to sys.path
-# This allows the usage python pip-*.whl/pip install pip-*.whl
-if __package__ == "":
-    # __file__ is pip-*.whl/pip/__main__.py
-    # first dirname call strips of '/__main__.py', second strips off '/pip'
-    # Resulting path is the name of the wheel itself
-    # Add that to sys.path so we can import pip
-    path = os.path.dirname(os.path.dirname(__file__))
-    sys.path.insert(0, path)
-
-if __name__ == "__main__":
-    from pip._internal.cli.main import main as _main
-
-    sys.exit(_main())

path/to/venv/lib/python3.12/site-packages/pip/__pip-runner__.py

@@ -1,50 +0,0 @@
-"""Execute exactly this copy of pip, within a different environment.
-
-This file is named as it is, to ensure that this module can't be imported via
-an import statement.
-"""
-
-# /!\ This version compatibility check section must be Python 2 compatible. /!\
-
-import sys
-
-# Copied from setup.py
-PYTHON_REQUIRES = (3, 7)
-
-
-def version_str(version):  # type: ignore
-    return ".".join(str(v) for v in version)
-
-
-if sys.version_info[:2] < PYTHON_REQUIRES:
-    raise SystemExit(
-        "This version of pip does not support python {} (requires >={}).".format(
-            version_str(sys.version_info[:2]), version_str(PYTHON_REQUIRES)
-        )
-    )
-
-# From here on, we can use Python 3 features, but the syntax must remain
-# Python 2 compatible.
-
-import runpy  # noqa: E402
-from importlib.machinery import PathFinder  # noqa: E402
-from os.path import dirname  # noqa: E402
-
-PIP_SOURCES_ROOT = dirname(dirname(__file__))
-
-
-class PipImportRedirectingFinder:
-    @classmethod
-    def find_spec(self, fullname, path=None, target=None):  # type: ignore
-        if fullname != "pip":
-            return None
-
-        spec = PathFinder.find_spec(fullname, [PIP_SOURCES_ROOT], target)
-        assert spec, (PIP_SOURCES_ROOT, fullname)
-        return spec
-
-
-sys.meta_path.insert(0, PipImportRedirectingFinder())
-
-assert __name__ == "__main__", "Cannot run __pip-runner__.py as a non-main module"
-runpy.run_module("pip", run_name="__main__", alter_sys=True)

path/to/venv/lib/python3.12/site-packages/pip/_internal/__init__.py

@@ -1,18 +0,0 @@
-from typing import List, Optional
-
-from pip._internal.utils import _log
-
-# init_logging() must be called before any call to logging.getLogger()
-# which happens at import of most modules.
-_log.init_logging()
-
-
-def main(args: (Optional[List[str]]) = None) -> int:
-    """This is preserved for old console scripts that may still be referencing
-    it.
-
-    For additional details, see https://github.com/pypa/pip/issues/7498.
-    """
-    from pip._internal.utils.entrypoints import _wrapper
-
-    return _wrapper(args)