Add python packages for support HTTP, TELNET, FTP

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parent c7c520a3f1
commit 10429b6a30

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This package contains a modified version of ca-bundle.crt:
ca-bundle.crt -- Bundle of CA Root Certificates
Certificate data from Mozilla as of: Thu Nov 3 19:04:19 2011#
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:
http://mxr.mozilla.org/mozilla/source/security/nss/lib/ckfw/builtins/certdata.txt?raw=1#
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 $

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Metadata-Version: 2.1
Name: certifi
Version: 2021.10.8
Summary: Python package for providing Mozilla's CA Bundle.
Home-page: https://certifiio.readthedocs.io/en/latest/
Author: Kenneth Reitz
Author-email: me@kennethreitz.com
License: MPL-2.0
Project-URL: Documentation, https://certifiio.readthedocs.io/en/latest/
Project-URL: Source, https://github.com/certifi/python-certifi
Platform: UNKNOWN
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 :: 3.3
Classifier: Programming Language :: Python :: 3.4
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
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!
1024-bit Root Certificates
~~~~~~~~~~~~~~~~~~~~~~~~~~
Browsers and certificate authorities have concluded that 1024-bit keys are
unacceptably weak for certificates, particularly root certificates. For this
reason, Mozilla has removed any weak (i.e. 1024-bit key) certificate from its
bundle, replacing it with an equivalent strong (i.e. 2048-bit or greater key)
certificate from the same CA. Because Mozilla removed these certificates from
its bundle, ``certifi`` removed them as well.
In previous versions, ``certifi`` provided the ``certifi.old_where()`` function
to intentionally re-add the 1024-bit roots back into your bundle. This was not
recommended in production and therefore was removed at the end of 2018.
.. _`Certifi`: https://certifiio.readthedocs.io/en/latest/
.. _`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.

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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.

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Metadata-Version: 2.1
Name: charset-normalizer
Version: 2.0.7
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 @Ousret
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,i18n,txt,text,charset,charset-detector,normalization,unicode,chardet
Platform: UNKNOWN
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 :: 3.5
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: Topic :: Text Processing :: Linguistic
Classifier: Topic :: Utilities
Classifier: Programming Language :: Python :: Implementation :: PyPy
Classifier: Typing :: Typed
Requires-Python: >=3.5.0
Description-Content-Type: text/markdown
License-File: LICENSE
Provides-Extra: unicode_backport
Requires-Dist: unicodedata2 ; extra == 'unicode_backport'
<h1 align="center">Charset Detection, for Everyone 👋 <a href="https://twitter.com/intent/tweet?text=The%20Real%20First%20Universal%20Charset%20%26%20Language%20Detector&url=https://www.github.com/Ousret/charset_normalizer&hashtags=python,encoding,chardet,developers"><img src="https://img.shields.io/twitter/url/http/shields.io.svg?style=social"/></a></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://codecov.io/gh/Ousret/charset_normalizer">
<img src="https://codecov.io/gh/Ousret/charset_normalizer/branch/master/graph/badge.svg" />
</a>
<a href="https://pepy.tech/project/charset-normalizer/">
<img alt="Download Count Total" src="https://pepy.tech/badge/charset-normalizer" />
</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` | ❌<br> | ✅<br> | ✅ <br> |
| `Universal**` | ❌ | ✅ | ❌ |
| `Reliable` **without** distinguishable standards | ❌ | ✅ | ✅ |
| `Reliable` **with** distinguishable standards | ✅ | ✅ | ✅ |
| `Free & Open` | ✅ | ✅ | ✅ |
| `License` | LGPL-2.1 | MIT | MPL-1.1
| `Native Python` | ✅ | ✅ | ❌ |
| `Detect spoken language` | ❌ | ✅ | N/A |
| `Supported Encoding` | 30 | :tada: [93](https://charset-normalizer.readthedocs.io/en/latest/support.html) | 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"/>
*\*\* : They are clearly using specific code for a specific encoding even if covering most of used one*<br>
## ⭐ Your support
*Fork, test-it, star-it, submit your ideas! We do listen.*
## ⚡ 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) | 92 % | 220 ms | 5 file/sec |
| charset-normalizer | **98 %** | **40 ms** | 25 file/sec |
| Package | 99th percentile | 95th percentile | 50th percentile |
| ------------- | :-------------: | :------------------: | :------------------: |
| [chardet](https://github.com/chardet/chardet) | 1115 ms | 300 ms | 27 ms |
| charset-normalizer | 460 ms | 240 ms | 18 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.
[cchardet](https://github.com/PyYoshi/cChardet) is a non-native (cpp binding) faster alternative. If speed is the most important factor,
you should try it.
## ✨ Installation
Using PyPi for latest stable
```sh
pip install charset-normalizer -U
```
If you want a more up-to-date `unicodedata` than the one available in your Python setup.
```sh
pip install charset-normalizer[unicode_backport] -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
```
:tada: 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()))
```
*Normalize any text file*
```python
from charset_normalizer import normalize
try:
normalize('./my_subtitle.srt') # should write to disk my_subtitle-***.srt
except IOError as e:
print('Sadly, we are unable to perform charset normalization.', str(e))
```
*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 chaos, 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 chaos/mess and coherence according to **YOU ?**
*Chaos :* 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 chaotic is very subjective, 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.
## 👤 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 © 2019 [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/)

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[console_scripts]
normalizer = charset_normalizer.cli.normalizer:cli_detect

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BSD 3-Clause License
Copyright (c) 2013-2021, Kim Davies
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.

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Metadata-Version: 2.1
Name: idna
Version: 3.3
Summary: Internationalized Domain Names in Applications (IDNA)
Home-page: https://github.com/kjd/idna
Author: Kim Davies
Author-email: kim@cynosure.com.au
License: BSD-3-Clause
Platform: UNKNOWN
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 :: Implementation :: CPython
Classifier: Programming Language :: Python :: Implementation :: PyPy
Classifier: Topic :: Internet :: Name Service (DNS)
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Topic :: Utilities
Requires-Python: >=3.5
License-File: LICENSE.md
Internationalized Domain Names in Applications (IDNA)
=====================================================
Support for the Internationalised 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
------------
To install this library, you can use pip:
.. code-block:: bash
$ pip install idna
Alternatively, you can install the package using the bundled setup script:
.. code-block:: bash
$ python setup.py install
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('idna'))
b'xn--d1acufc.xn--80akhbyknj4f'
>>> print(b'xn--d1acufc.xn--80akhbyknj4f'.decode('idna'))
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'
Implementors 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 using for IDNA and UTS 46 conversions. Implementors
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 use
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 intepreter 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 wish 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.

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@ -0,0 +1,245 @@
Metadata-Version: 2.1
Name: pyftpdlib
Version: 1.5.6
Summary: Very fast asynchronous FTP server library
Home-page: https://github.com/giampaolo/pyftpdlib/
Author: Giampaolo Rodola'
Author-email: g.rodola@gmail.com
License: MIT
Description: .. image:: http://pepy.tech/badge/pyftpdlib
:target: http://pepy.tech/project/pyftpdlib
:alt: Downloads
.. image:: https://img.shields.io/travis/giampaolo/pyftpdlib/master.svg?maxAge=3600&label=Linux%20/%20OSX
:target: https://travis-ci.org/giampaolo/pyftpdlib
:alt: Linux tests (Travis)
.. image:: https://img.shields.io/appveyor/ci/giampaolo/pyftpdlib/master.svg?maxAge=3600&label=Windows
:target: https://ci.appveyor.com/project/giampaolo/pyftpdlib
:alt: Windows tests (Appveyor)
.. image:: https://coveralls.io/repos/github/giampaolo/pyftpdlib/badge.svg?branch=master
:target: https://coveralls.io/github/giampaolo/pyftpdlib?branch=master
:alt: Test coverage (coverall.io)
.. image:: https://readthedocs.org/projects/pyftpdlib/badge/?version=latest
:target: http://pyftpdlib.readthedocs.io/en/latest/?badge=latest
:alt: Documentation Status
.. image:: https://img.shields.io/pypi/v/pyftpdlib.svg?label=pypi
:target: https://pypi.python.org/pypi/pyftpdlib/
:alt: Latest version
.. image:: https://img.shields.io/github/stars/giampaolo/pyftpdlib.svg
:target: https://github.com/giampaolo/pyftpdlib/
:alt: Github stars
.. image:: https://img.shields.io/pypi/l/pyftpdlib.svg
:target: https://pypi.python.org/pypi/pyftpdlib/
:alt: License
Quick links
===========
- `Home <https://github.com/giampaolo/pyftpdlib>`__
- `Documentation <http://pyftpdlib.readthedocs.io>`__
- `Download <https://pypi.python.org/pypi/pyftpdlib/>`__
- `Blog <http://grodola.blogspot.com/search/label/pyftpdlib>`__
- `Mailing list <http://groups.google.com/group/pyftpdlib/topics>`__
- `What's new <https://github.com/giampaolo/pyftpdlib/blob/master/HISTORY.rst>`__
About
=====
Python FTP server library provides a high-level portable interface to easily
write very efficient, scalable and asynchronous FTP servers with Python. It is
the most complete `RFC-959 <http://www.faqs.org/rfcs/rfc959.html>`__ FTP server
implementation available for `Python <http://www.python.org/>`__ programming
language and it's used in projects like
`Google Chromium <http://www.code.google.com/chromium/>`__ and
`Bazaar <http://bazaar-vcs.org/>`__ and included in
`Debian <http://packages.debian.org/sid/python-pyftpdlib>`__,
`Fedora <https://admin.fedoraproject.org/pkgdb/packages/name/pyftpdlib>`__ and
`FreeBSD <http://www.freshports.org/ftp/py-pyftpdlib/>`__ package repositories.
Features
========
- Extremely **lightweight**, **fast** and **scalable** (see
`why <https://github.com/giampaolo/pyftpdlib/issues/203>`__ and
`benchmarks <http://pyftpdlib.readthedocs.io/en/latest/benchmarks.html>`__).
- Uses **sendfile(2)** (see `pysendfile <https://github.com/giampaolo/pysendfile>`__)
system call for uploads.
- Uses epoll() / kqueue() / select() to handle concurrency asynchronously.
- ...But can optionally skip to a
`multiple thread / process <http://pyftpdlib.readthedocs.io/en/latest/tutorial.html#changing-the-concurrency-model>`__
model (as in: you'll be free to block or use slow filesystems).
- Portable: entirely written in pure Python; works with Python from **2.6** to
**3.5** by using a single code base.
- Supports **FTPS** (`RFC-4217 <http://tools.ietf.org/html/rfc4217>`__),
**IPv6** (`RFC-2428 <ftp://ftp.rfc-editor.org/in-notes/rfc2428.txt>`__),
**Unicode** file names (`RFC-2640 <http://tools.ietf.org/html/rfc2640>`__),
**MLSD/MLST** commands (`RFC-3659 <ftp://ftp.rfc-editor.org/in-notes/rfc3659.txt>`__).
- Support for virtual users and virtual filesystem.
- Extremely flexible system of "authorizers" able to manage both "virtual" and
"real" users on on both
`UNIX <http://pyftpdlib.readthedocs.io/en/latest/tutorial.html#unix-ftp-server>`__
and
`Windows <http://pyftpdlib.readthedocs.io/en/latest/tutorial.html#windows-ftp-server>`__.
- `Test coverage <https://github.com/giampaolo/pyftpdlib/blob/master/pyftpdlib/test/>`__
close to 100%.
Performances
============
Despite being written in an intepreted language, pyftpdlib has transfer rates
superior to most common UNIX FTP servers. It also scales better since whereas
vsftpd and proftpd use multiple processes to achieve concurrency, pyftpdlib
will only use one process and handle concurrency asynchronously (see
`the C10K problem <http://www.kegel.com/c10k.html>`__). Here are some
`benchmarks <https://github.com/giampaolo/pyftpdlib/blob/master/scripts/ftpbench>`__
made against my Linux 3.0.0 box, Intel core-duo 3.1 Ghz:
pyftpdlib vs. proftpd 1.3.4
---------------------------
+-----------------------------------------+----------------+----------------+-------------+
| **benchmark type** | **pyftpdlib** | **proftpd** | **speedup** |
+-----------------------------------------+----------------+----------------+-------------+
| STOR (client -> server) | 585.90 MB/sec | 600.49 MB/sec | -0.02x |
+-----------------------------------------+----------------+----------------+-------------+
| RETR (server -> client) | 1652.72 MB/sec | 1524.05 MB/sec | **+0.08** |
+-----------------------------------------+----------------+----------------+-------------+
| 300 concurrent clients (connect, login) | 0.19 secs | 9.98 secs | **+51x** |
+-----------------------------------------+----------------+----------------+-------------+
| STOR (1 file with 300 idle clients) | 585.59 MB/sec | 518.55 MB/sec | **+0.1x** |
+-----------------------------------------+----------------+----------------+-------------+
| RETR (1 file with 300 idle clients) | 1497.58 MB/sec | 1478.19 MB/sec | 0x |
+-----------------------------------------+----------------+----------------+-------------+
| 300 concurrent clients (RETR 10M file) | 3.41 secs | 3.60 secs | **+0.05x** |
+-----------------------------------------+----------------+----------------+-------------+
| 300 concurrent clients (STOR 10M file) | 8.60 secs | 11.56 secs | **+0.3x** |
+-----------------------------------------+----------------+----------------+-------------+
| 300 concurrent clients (QUIT) | 0.03 secs | 0.39 secs | **+12x** |
+-----------------------------------------+----------------+----------------+-------------+
pyftpdlib vs. vsftpd 2.3.5
--------------------------
+-----------------------------------------+----------------+----------------+-------------+
| **benchmark type** | **pyftpdlib** | **vsftpd** | **speedup** |
+-----------------------------------------+----------------+----------------+-------------+
| STOR (client -> server) | 585.90 MB/sec | 611.73 MB/sec | -0.04x |
+-----------------------------------------+----------------+----------------+-------------+
| RETR (server -> client) | 1652.72 MB/sec | 1512.92 MB/sec | **+0.09** |
+-----------------------------------------+----------------+----------------+-------------+
| 300 concurrent clients (connect, login) | 0.19 secs | 20.39 secs | **+106x** |
+-----------------------------------------+----------------+----------------+-------------+
| STOR (1 file with 300 idle clients) | 585.59 MB/sec | 610.23 MB/sec | -0.04x |
+-----------------------------------------+----------------+----------------+-------------+
| RETR (1 file with 300 idle clients) | 1497.58 MB/sec | 1493.01 MB/sec | 0x |
+-----------------------------------------+----------------+----------------+-------------+
| 300 concurrent clients (RETR 10M file) | 3.41 secs | 3.67 secs | **+0.07x** |
+-----------------------------------------+----------------+----------------+-------------+
| 300 concurrent clients (STOR 10M file) | 8.60 secs | 9.82 secs | **+0.07x** |
+-----------------------------------------+----------------+----------------+-------------+
| 300 concurrent clients (QUIT) | 0.03 secs | 0.01 secs | +0.14x |
+-----------------------------------------+----------------+----------------+-------------+
For more benchmarks see `here <http://pyftpdlib.readthedocs.io/en/latest/benchmarks.html>`__.
Quick start
===========
.. code-block:: python
>>> from pyftpdlib.authorizers import DummyAuthorizer
>>> from pyftpdlib.handlers import FTPHandler
>>> from pyftpdlib.servers import FTPServer
>>>
>>> authorizer = DummyAuthorizer()
>>> authorizer.add_user("user", "12345", "/home/giampaolo", perm="elradfmwMT")
>>> authorizer.add_anonymous("/home/nobody")
>>>
>>> handler = FTPHandler
>>> handler.authorizer = authorizer
>>>
>>> server = FTPServer(("127.0.0.1", 21), handler)
>>> server.serve_forever()
[I 13-02-19 10:55:42] >>> starting FTP server on 127.0.0.1:21 <<<
[I 13-02-19 10:55:42] poller: <class 'pyftpdlib.ioloop.Epoll'>
[I 13-02-19 10:55:42] masquerade (NAT) address: None
[I 13-02-19 10:55:42] passive ports: None
[I 13-02-19 10:55:42] use sendfile(2): True
[I 13-02-19 10:55:45] 127.0.0.1:34178-[] FTP session opened (connect)
[I 13-02-19 10:55:48] 127.0.0.1:34178-[user] USER 'user' logged in.
[I 13-02-19 10:56:27] 127.0.0.1:34179-[user] RETR /home/giampaolo/.vimrc completed=1 bytes=1700 seconds=0.001
[I 13-02-19 10:56:39] 127.0.0.1:34179-[user] FTP session closed (disconnect).
`other code samples <http://pyftpdlib.readthedocs.io/en/latest/tutorial.html>`__
Donate
======
A lot of time and effort went into making pyftpdlib as it is right now.
If you feel pyftpdlib is useful to you or your business and want to support its
future development please consider donating me
(`Giampaolo Rodola' <http://grodola.blogspot.com/p/about.html>`_) some money.
I only ask for a small donation, but of course I appreciate any amount.
.. image:: https://www.paypal.com/en_US/i/btn/btn_donateCC_LG.gif
:target: https://www.paypal.com/cgi-bin/webscr?cmd=_s-xclick&hosted_button_id=ZSSF7G42VA2XE
:alt: Donate via PayPal
Don't want to donate money? Then maybe you could
`write me a recommendation on Linkedin <http://www.linkedin.com/in/grodola>`_.
In case you're using pyftpdlib into a software of yours
`mail me <http://grodola.blogspot.com/p/about.html>`_ and I'll add your
software to the
`adoptions list <http://pyftpdlib.readthedocs.io/en/latest/adoptions.html>`__.
Trademarks
==========
Some famous trademarks which adopted pyftpdlib (`complete list <http://pyftpdlib.readthedocs.io/en/latest/adoptions.html>`__).
.. image:: docs/images/chrome.jpg
:target: http://www.google.com/chrome
.. image:: docs/images/debian.png
:target: http://www.debian.org
.. image:: docs/images/fedora.png
:target: http://fedoraproject.org/
.. image:: docs/images/freebsd.gif
:target: http://www.freebsd.org
.. image:: docs/images/openerp.jpg
:target: http://openerp.com
.. image:: docs/images/bazaar.jpg
:target: http://bazaar-vcs.org
.. image:: docs/images/bitsontherun.png
:target: http://www.bitsontherun.com
.. image:: docs/images/openvms.png
:target: http://www.openvms.org/
.. image:: docs/images/smartfile.png
:target: https://www.smartfile.com/
Keywords: ftp,ftps,server,ftpd,daemon,python,ssl,sendfile,asynchronous,nonblocking,eventdriven,rfc959,rfc1123,rfc2228,rfc2428,rfc2640,rfc3659
Platform: Platform Independent
Classifier: Development Status :: 5 - Production/Stable
Classifier: Environment :: Console
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: System Administrators
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Topic :: Internet :: File Transfer Protocol (FTP)
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Topic :: System :: Filesystems
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.6
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Provides-Extra: ssl

@ -0,0 +1,67 @@
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pyftpdlib/test/test_misc.py
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@ -0,0 +1,48 @@
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@ -0,0 +1,120 @@
Metadata-Version: 2.1
Name: requests
Version: 2.26.0
Summary: Python HTTP for Humans.
Home-page: https://requests.readthedocs.io
Author: Kenneth Reitz
Author-email: me@kennethreitz.org
License: Apache 2.0
Project-URL: Documentation, https://requests.readthedocs.io
Project-URL: Source, https://github.com/psf/requests
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: Natural Language :: English
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
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 :: Implementation :: CPython
Classifier: Programming Language :: Python :: Implementation :: PyPy
Requires-Python: >=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*
Description-Content-Type: text/markdown
Requires-Dist: urllib3 (<1.27,>=1.21.1)
Requires-Dist: certifi (>=2017.4.17)
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Requires-Dist: idna (<3,>=2.5) ; python_version < "3"
Requires-Dist: charset-normalizer (~=2.0.0) ; python_version >= "3"
Requires-Dist: idna (<4,>=2.5) ; python_version >= "3"
Provides-Extra: security
Provides-Extra: socks
Requires-Dist: PySocks (!=1.5.7,>=1.5.6) ; extra == 'socks'
Requires-Dist: win-inet-pton ; (sys_platform == "win32" and python_version == "2.7") and extra == 'socks'
Provides-Extra: use_chardet_on_py3
Requires-Dist: chardet (<5,>=3.0.2) ; extra == 'use_chardet_on_py3'
# Requests
**Requests** is a simple, yet elegant, HTTP library.
```python
>>> import requests
>>> r = requests.get('https://api.github.com/user', auth=('user', 'pass'))
>>> r.status_code
200
>>> r.headers['content-type']
'application/json; charset=utf8'
>>> r.encoding
'utf-8'
>>> r.text
'{"type":"User"...'
>>> r.json()
{'disk_usage': 368627, 'private_gists': 484, ...}
```
Requests allows you to send HTTP/1.1 requests extremely easily. Theres no need to manually add query strings to your URLs, or to form-encode your `PUT` & `POST` data — but nowadays, just use the `json` method!
Requests is one of the most downloaded Python package today, pulling in around `14M downloads / week`— according to GitHub, Requests is currently [depended upon](https://github.com/psf/requests/network/dependents?package_id=UGFja2FnZS01NzA4OTExNg%3D%3D) by `500,000+` repositories. You may certainly put your trust in this code.
[![Downloads](https://pepy.tech/badge/requests/month)](https://pepy.tech/project/requests/month)
[![Supported Versions](https://img.shields.io/pypi/pyversions/requests.svg)](https://pypi.org/project/requests)
[![Contributors](https://img.shields.io/github/contributors/psf/requests.svg)](https://github.com/psf/requests/graphs/contributors)
## Installing Requests and Supported Versions
Requests is available on PyPI:
```console
$ python -m pip install requests
```
Requests officially supports Python 2.7 & 3.6+.
## Supported Features & BestPractices
Requests is ready for the demands of building robust and reliable HTTPspeaking applications, for the needs of today.
- Keep-Alive & Connection Pooling
- International Domains and URLs
- Sessions with Cookie Persistence
- Browser-style TLS/SSL Verification
- Basic & Digest Authentication
- Familiar `dict`like Cookies
- Automatic Content Decompression and Decoding
- Multi-part File Uploads
- SOCKS Proxy Support
- Connection Timeouts
- Streaming Downloads
- Automatic honoring of `.netrc`
- Chunked HTTP Requests
## API Reference and User Guide available on [Read the Docs](https://requests.readthedocs.io)
[![Read the Docs](https://raw.githubusercontent.com/psf/requests/master/ext/ss.png)](https://requests.readthedocs.io)
## Cloning the repository
When cloning the Requests repository, you may need to add the `-c
fetch.fsck.badTimezone=ignore` flag to avoid an error about a bad commit (see
[this issue](https://github.com/psf/requests/issues/2690) for more background):
```shell
git clone -c fetch.fsck.badTimezone=ignore https://github.com/psf/requests.git
```
You can also apply this setting to your global Git config:
```shell
git config --global fetch.fsck.badTimezone ignore
```
---
[![Kenneth Reitz](https://raw.githubusercontent.com/psf/requests/master/ext/kr.png)](https://kennethreitz.org) [![Python Software Foundation](https://raw.githubusercontent.com/psf/requests/master/ext/psf.png)](https://www.python.org/psf)

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Wheel-Version: 1.0
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MIT License
Copyright (c) 2008-2020 Andrey Petrov and contributors (see CONTRIBUTORS.txt)
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.

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Generator: bdist_wheel (0.37.0)
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Tag: py2-none-any
Tag: py3-none-any

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