{ "version": "1", "pip_version": "24.2", "installed": [ { "metadata": { "metadata_version": "2.1", "name": "Brotli", "version": "1.0.9", "platform": [ "Posix", "MacOS X", "Windows" ], "summary": "Python bindings for the Brotli compression library", "home_page": "https://github.com/google/brotli", "author": "The Brotli Authors", "license": "MIT", "classifier": [ "Development Status :: 4 - Beta", "Environment :: Console", "Intended Audience :: Developers", "License :: OSI Approved :: MIT License", "Operating System :: MacOS :: MacOS X", "Operating System :: Microsoft :: Windows", "Operating System :: POSIX :: Linux", "Programming Language :: C", "Programming Language :: C++", "Programming Language :: Python", "Programming Language :: Python :: 2", "Programming Language :: Python :: 2.7", "Programming Language :: Python :: 3", "Programming Language :: Python :: 3.3", "Programming Language :: Python :: 3.4", "Programming Language :: Python :: 3.5", "Programming Language :: Unix Shell", "Topic :: Software Development :: Libraries", "Topic :: Software Development :: Libraries :: Python Modules", "Topic :: System :: Archiving", "Topic :: System :: Archiving :: Compression", "Topic :: Text Processing :: Fonts", "Topic :: Utilities" ] }, "metadata_location": "/opt/conda/lib/python3.10/site-packages/Brotli-1.0.9.dist-info", "direct_url": { "url": "file:///croot/brotli-split_1714483155106/work", "dir_info": {} }, "installer": "conda", "requested": true }, { "metadata": { "metadata_version": "2.1", "name": "GitPython", "version": "3.1.43", "summary": "GitPython is a Python library used to interact with Git repositories", "description_content_type": "text/markdown", "home_page": "https://github.com/gitpython-developers/GitPython", "author": "Sebastian Thiel, Michael Trier", "author_email": "byronimo@gmail.com, mtrier@gmail.com", "license": "BSD-3-Clause", "classifier": [ "Development Status :: 5 - Production/Stable", "Environment :: Console", "Intended Audience :: Developers", "License :: OSI Approved :: BSD License", "Operating System :: OS Independent", "Operating System :: POSIX", "Operating System :: Microsoft :: Windows", "Operating System :: MacOS :: MacOS X", "Typing :: Typed", "Programming Language :: Python", "Programming Language :: Python :: 3", "Programming Language :: Python :: 3.7", "Programming Language :: Python :: 3.8", "Programming Language :: Python :: 3.9", "Programming Language :: Python :: 3.10", "Programming Language :: Python :: 3.11", "Programming Language :: Python :: 3.12" ], "requires_dist": [ "gitdb <5,>=4.0.1", "typing-extensions >=3.7.4.3 ; python_version < \"3.8\"", "sphinx ==4.3.2 ; extra == 'doc'", "sphinx-rtd-theme ; extra == 'doc'", "sphinxcontrib-applehelp <=1.0.4,>=1.0.2 ; extra == 'doc'", "sphinxcontrib-devhelp ==1.0.2 ; extra == 'doc'", "sphinxcontrib-htmlhelp <=2.0.1,>=2.0.0 ; extra == 'doc'", "sphinxcontrib-qthelp ==1.0.3 ; extra == 'doc'", "sphinxcontrib-serializinghtml ==1.1.5 ; extra == 'doc'", "sphinx-autodoc-typehints ; extra == 'doc'", "coverage[toml] ; extra == 'test'", "ddt !=1.4.3,>=1.1.1 ; extra == 'test'", "mypy ; extra == 'test'", "pre-commit ; extra == 'test'", "pytest >=7.3.1 ; extra == 'test'", "pytest-cov ; extra == 'test'", "pytest-instafail ; extra == 'test'", "pytest-mock ; extra == 'test'", "pytest-sugar ; extra == 'test'", "typing-extensions ; (python_version < \"3.11\") and extra == 'test'", "mock ; (python_version < \"3.8\") and extra == 'test'" ], "requires_python": ">=3.7", "provides_extra": [ "doc", "test" ], "description": "![Python package](https://github.com/gitpython-developers/GitPython/workflows/Python%20package/badge.svg)\n[![Documentation Status](https://readthedocs.org/projects/gitpython/badge/?version=stable)](https://readthedocs.org/projects/gitpython/?badge=stable)\n[![Packaging status](https://repology.org/badge/tiny-repos/python:gitpython.svg)](https://repology.org/metapackage/python:gitpython/versions)\n\n## [Gitoxide](https://github.com/Byron/gitoxide): A peek into the future…\n\nI started working on GitPython in 2009, back in the days when Python was 'my thing' and I had great plans with it.\nOf course, back in the days, I didn't really know what I was doing and this shows in many places. Somewhat similar to\nPython this happens to be 'good enough', but at the same time is deeply flawed and broken beyond repair.\n\nBy now, GitPython is widely used and I am sure there is a good reason for that, it's something to be proud of and happy about.\nThe community is maintaining the software and is keeping it relevant for which I am absolutely grateful. For the time to come I am happy to continue maintaining GitPython, remaining hopeful that one day it won't be needed anymore.\n\nMore than 15 years after my first meeting with 'git' I am still in excited about it, and am happy to finally have the tools and\nprobably the skills to scratch that itch of mine: implement `git` in a way that makes tool creation a piece of cake for most.\n\nIf you like the idea and want to learn more, please head over to [gitoxide](https://github.com/Byron/gitoxide), an\nimplementation of 'git' in [Rust](https://www.rust-lang.org).\n\n*(Please note that `gitoxide` is not currently available for use in Python, and that Rust is required.)*\n\n## GitPython\n\nGitPython is a python library used to interact with git repositories, high-level like git-porcelain,\nor low-level like git-plumbing.\n\nIt provides abstractions of git objects for easy access of repository data often backed by calling the `git`\ncommand-line program.\n\n### DEVELOPMENT STATUS\n\nThis project is in **maintenance mode**, which means that\n\n- …there will be no feature development, unless these are contributed\n- …there will be no bug fixes, unless they are relevant to the safety of users, or contributed\n- …issues will be responded to with waiting times of up to a month\n\nThe project is open to contributions of all kinds, as well as new maintainers.\n\n### REQUIREMENTS\n\nGitPython needs the `git` executable to be installed on the system and available in your\n`PATH` for most operations. If it is not in your `PATH`, you can help GitPython find it\nby setting the `GIT_PYTHON_GIT_EXECUTABLE=` environment variable.\n\n- Git (1.7.x or newer)\n- Python >= 3.7\n\nThe list of dependencies are listed in `./requirements.txt` and `./test-requirements.txt`.\nThe installer takes care of installing them for you.\n\n### INSTALL\n\nGitPython and its required package dependencies can be installed in any of the following ways, all of which should typically be done in a [virtual environment](https://docs.python.org/3/tutorial/venv.html).\n\n#### From PyPI\n\nTo obtain and install a copy [from PyPI](https://pypi.org/project/GitPython/), run:\n\n```sh\npip install GitPython\n```\n\n(A distribution package can also be downloaded for manual installation at [the PyPI page](https://pypi.org/project/GitPython/).)\n\n#### From downloaded source code\n\nIf you have downloaded the source code, run this from inside the unpacked `GitPython` directory:\n\n```sh\npip install .\n```\n\n#### By cloning the source code repository\n\nTo clone the [the GitHub repository](https://github.com/gitpython-developers/GitPython) from source to work on the code, you can do it like so:\n\n```sh\ngit clone https://github.com/gitpython-developers/GitPython\ncd GitPython\n./init-tests-after-clone.sh\n```\n\nOn Windows, `./init-tests-after-clone.sh` can be run in a Git Bash shell.\n\nIf you are cloning [your own fork](https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/working-with-forks/about-forks), then replace the above `git clone` command with one that gives the URL of your fork. Or use this [`gh`](https://cli.github.com/) command (assuming you have `gh` and your fork is called `GitPython`):\n\n```sh\ngh repo clone GitPython\n```\n\nHaving cloned the repo, create and activate your [virtual environment](https://docs.python.org/3/tutorial/venv.html).\n\nThen make an [editable install](https://pip.pypa.io/en/stable/topics/local-project-installs/#editable-installs):\n\n```sh\npip install -e \".[test]\"\n```\n\nIn the less common case that you do not want to install test dependencies, `pip install -e .` can be used instead.\n\n#### With editable *dependencies* (not preferred, and rarely needed)\n\nIn rare cases, you may want to work on GitPython and one or both of its [gitdb](https://github.com/gitpython-developers/gitdb) and [smmap](https://github.com/gitpython-developers/smmap) dependencies at the same time, with changes in your local working copy of gitdb or smmap immediatley reflected in the behavior of your local working copy of GitPython. This can be done by making editable installations of those dependencies in the same virtual environment where you install GitPython.\n\nIf you want to do that *and* you want the versions in GitPython's git submodules to be used, then pass `-e git/ext/gitdb` and/or `-e git/ext/gitdb/gitdb/ext/smmap` to `pip install`. This can be done in any order, and in separate `pip install` commands or the same one, so long as `-e` appears before *each* path. For example, you can install GitPython, gitdb, and smmap editably in the currently active virtual environment this way:\n\n```sh\npip install -e \".[test]\" -e git/ext/gitdb -e git/ext/gitdb/gitdb/ext/smmap\n```\n\nThe submodules must have been cloned for that to work, but that will already be the case if you have run `./init-tests-after-clone.sh`. You can use `pip list` to check which packages are installed editably and which are installed normally.\n\nTo reiterate, this approach should only rarely be used. For most development it is preferable to allow the gitdb and smmap dependencices to be retrieved automatically from PyPI in their latest stable packaged versions.\n\n### Limitations\n\n#### Leakage of System Resources\n\nGitPython is not suited for long-running processes (like daemons) as it tends to\nleak system resources. It was written in a time where destructors (as implemented\nin the `__del__` method) still ran deterministically.\n\nIn case you still want to use it in such a context, you will want to search the\ncodebase for `__del__` implementations and call these yourself when you see fit.\n\nAnother way assure proper cleanup of resources is to factor out GitPython into a\nseparate process which can be dropped periodically.\n\n#### Windows support\n\nSee [Issue #525](https://github.com/gitpython-developers/GitPython/issues/525).\n\n### RUNNING TESTS\n\n_Important_: Right after cloning this repository, please be sure to have executed\nthe `./init-tests-after-clone.sh` script in the repository root. Otherwise\nyou will encounter test failures.\n\n#### Install test dependencies\n\nEnsure testing libraries are installed. This is taken care of already if you installed with:\n\n```sh\npip install -e \".[test]\"\n```\n\nIf you had installed with a command like `pip install -e .` instead, you can still run\nthe above command to add the testing dependencies.\n\n#### Test commands\n\nTo test, run:\n\n```sh\npytest\n```\n\nTo lint, and apply some linting fixes as well as automatic code formatting, run:\n\n```sh\npre-commit run --all-files\n```\n\nThis includes the linting and autoformatting done by Ruff, as well as some other checks.\n\nTo typecheck, run:\n\n```sh\nmypy\n```\n\n#### CI (and tox)\n\nStyle and formatting checks, and running tests on all the different supported Python versions, will be performed:\n\n- Upon submitting a pull request.\n- On each push, *if* you have a fork with GitHub Actions enabled.\n- Locally, if you run [`tox`](https://tox.wiki/) (this skips any Python versions you don't have installed).\n\n#### Configuration files\n\nSpecific tools are all configured in the `./pyproject.toml` file:\n\n- `pytest` (test runner)\n- `coverage.py` (code coverage)\n- `ruff` (linter and formatter)\n- `mypy` (type checker)\n\nOrchestration tools:\n\n- Configuration for `pre-commit` is in the `./.pre-commit-config.yaml` file.\n- Configuration for `tox` is in `./tox.ini`.\n- Configuration for GitHub Actions (CI) is in files inside `./.github/workflows/`.\n\n### Contributions\n\nPlease have a look at the [contributions file][contributing].\n\n### INFRASTRUCTURE\n\n- [User Documentation](http://gitpython.readthedocs.org)\n- [Questions and Answers](http://stackexchange.com/filters/167317/gitpython)\n- Please post on Stack Overflow and use the `gitpython` tag\n- [Issue Tracker](https://github.com/gitpython-developers/GitPython/issues)\n - Post reproducible bugs and feature requests as a new issue.\n Please be sure to provide the following information if posting bugs:\n - GitPython version (e.g. `import git; git.__version__`)\n - Python version (e.g. `python --version`)\n - The encountered stack-trace, if applicable\n - Enough information to allow reproducing the issue\n\n### How to make a new release\n\n1. Update/verify the **version** in the `VERSION` file.\n2. Update/verify that the `doc/source/changes.rst` changelog file was updated. It should include a link to the forthcoming release page: `https://github.com/gitpython-developers/GitPython/releases/tag/`\n3. Commit everything.\n4. Run `git tag -s ` to tag the version in Git.\n5. _Optionally_ create and activate a [virtual environment](https://packaging.python.org/en/latest/guides/installing-using-pip-and-virtual-environments/#creating-a-virtual-environment). (Then the next step can install `build` and `twine`.)\n6. Run `make release`.\n7. Go to [GitHub Releases](https://github.com/gitpython-developers/GitPython/releases) and publish a new one with the recently pushed tag. Generate the changelog.\n\n### Projects using GitPython\n\n- [PyDriller](https://github.com/ishepard/pydriller)\n- [Kivy Designer](https://github.com/kivy/kivy-designer)\n- [Prowl](https://github.com/nettitude/Prowl)\n- [Python Taint](https://github.com/python-security/pyt)\n- [Buster](https://github.com/axitkhurana/buster)\n- [git-ftp](https://github.com/ezyang/git-ftp)\n- [Git-Pandas](https://github.com/wdm0006/git-pandas)\n- [PyGitUp](https://github.com/msiemens/PyGitUp)\n- [PyJFuzz](https://github.com/mseclab/PyJFuzz)\n- [Loki](https://github.com/Neo23x0/Loki)\n- [Omniwallet](https://github.com/OmniLayer/omniwallet)\n- [GitViper](https://github.com/BeayemX/GitViper)\n- [Git Gud](https://github.com/bthayer2365/git-gud)\n\n### LICENSE\n\n[3-Clause BSD License](https://opensource.org/license/bsd-3-clause/), also known as the New BSD License. See the [LICENSE file][license].\n\n[contributing]: https://github.com/gitpython-developers/GitPython/blob/main/CONTRIBUTING.md\n[license]: https://github.com/gitpython-developers/GitPython/blob/main/LICENSE\n" }, "metadata_location": "/opt/conda/lib/python3.10/site-packages/GitPython-3.1.43.dist-info", "installer": "pip", "requested": false }, { "metadata": { "metadata_version": "2.1", "name": "MarkupSafe", "version": "2.1.3", "summary": "Safely add untrusted strings to HTML/XML markup.", "description_content_type": "text/x-rst", "home_page": "https://palletsprojects.com/p/markupsafe/", "maintainer": "Pallets", "maintainer_email": "contact@palletsprojects.com", "license": "BSD-3-Clause", "classifier": [ "Development Status :: 5 - Production/Stable", "Environment :: Web Environment", "Intended Audience :: Developers", "License :: OSI Approved :: BSD License", "Operating System :: OS Independent", "Programming Language :: Python", "Topic :: Internet :: WWW/HTTP :: Dynamic Content", "Topic :: Text Processing :: Markup :: HTML" ], "requires_python": ">=3.7", "project_url": [ "Donate, https://palletsprojects.com/donate", "Documentation, https://markupsafe.palletsprojects.com/", "Changes, https://markupsafe.palletsprojects.com/changes/", "Source Code, https://github.com/pallets/markupsafe/", "Issue Tracker, https://github.com/pallets/markupsafe/issues/", "Chat, https://discord.gg/pallets" ], "description": "MarkupSafe\n==========\n\nMarkupSafe implements a text object that escapes characters so it is\nsafe to use in HTML and XML. Characters that have special meanings are\nreplaced so that they display as the actual characters. This mitigates\ninjection attacks, meaning untrusted user input can safely be displayed\non a page.\n\n\nInstalling\n----------\n\nInstall and update using `pip`_:\n\n.. code-block:: text\n\n pip install -U MarkupSafe\n\n.. _pip: https://pip.pypa.io/en/stable/getting-started/\n\n\nExamples\n--------\n\n.. code-block:: pycon\n\n >>> from markupsafe import Markup, escape\n\n >>> # escape replaces special characters and wraps in Markup\n >>> escape(\"\")\n Markup('<script>alert(document.cookie);</script>')\n\n >>> # wrap in Markup to mark text \"safe\" and prevent escaping\n >>> Markup(\"Hello\")\n Markup('hello')\n\n >>> escape(Markup(\"Hello\"))\n Markup('hello')\n\n >>> # Markup is a str subclass\n >>> # methods and operators escape their arguments\n >>> template = Markup(\"Hello {name}\")\n >>> template.format(name='\"World\"')\n Markup('Hello "World"')\n\n\nDonate\n------\n\nThe Pallets organization develops and supports MarkupSafe and other\npopular packages. In order to grow the community of contributors and\nusers, and allow the maintainers to devote more time to the projects,\n`please donate today`_.\n\n.. _please donate today: https://palletsprojects.com/donate\n\n\nLinks\n-----\n\n- Documentation: https://markupsafe.palletsprojects.com/\n- Changes: https://markupsafe.palletsprojects.com/changes/\n- PyPI Releases: https://pypi.org/project/MarkupSafe/\n- Source Code: https://github.com/pallets/markupsafe/\n- Issue Tracker: https://github.com/pallets/markupsafe/issues/\n- Chat: https://discord.gg/pallets\n" }, "metadata_location": "/opt/conda/lib/python3.10/site-packages/MarkupSafe-2.1.3.dist-info", "direct_url": { "url": "file:///croot/markupsafe_1704205993651/work", "dir_info": {} }, "installer": "conda", "requested": true }, { "metadata": { "metadata_version": "2.1", "name": "PySocks", "version": "1.7.1", "platform": [ "UNKNOWN" ], "summary": "A Python SOCKS client module. See https://github.com/Anorov/PySocks for more information.", "description_content_type": "text/markdown", "keywords": [ "socks", "proxy" ], "home_page": "https://github.com/Anorov/PySocks", "author": "Anorov", "author_email": "anorov.vorona@gmail.com", "license": "BSD", "classifier": [ "Programming Language :: Python :: 2", "Programming Language :: Python :: 2.7", "Programming Language :: Python :: 3", "Programming Language :: Python :: 3.4", "Programming Language :: Python :: 3.5", "Programming Language :: Python :: 3.6" ], "requires_python": ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*", "description": "PySocks\n=======\n\nPySocks lets you send traffic through SOCKS and HTTP proxy servers. It is a modern fork of [SocksiPy](http://socksipy.sourceforge.net/) with bug fixes and extra features.\n\nActs as a drop-in replacement to the socket module. Seamlessly configure SOCKS proxies for any socket object by calling `socket_object.set_proxy()`.\n\n----------------\n\nFeatures\n========\n\n* SOCKS proxy client for Python 2.7 and 3.4+\n* TCP supported\n* UDP mostly supported (issues may occur in some edge cases)\n* HTTP proxy client included but not supported or recommended (you should use urllib2's or requests' own HTTP proxy interface)\n* urllib2 handler included. `pip install` / `setup.py install` will automatically install the `sockshandler` module.\n\nInstallation\n============\n\n pip install PySocks\n\nOr download the tarball / `git clone` and...\n\n python setup.py install\n\nThese will install both the `socks` and `sockshandler` modules.\n\nAlternatively, include just `socks.py` in your project.\n\n--------------------------------------------\n\n*Warning:* PySocks/SocksiPy only supports HTTP proxies that use CONNECT tunneling. Certain HTTP proxies may not work with this library. If you wish to use HTTP (not SOCKS) proxies, it is recommended that you rely on your HTTP client's native proxy support (`proxies` dict for `requests`, or `urllib2.ProxyHandler` for `urllib2`) instead.\n\n--------------------------------------------\n\nUsage\n=====\n\n## socks.socksocket ##\n\n import socks\n\n s = socks.socksocket() # Same API as socket.socket in the standard lib\n\n s.set_proxy(socks.SOCKS5, \"localhost\") # SOCKS4 and SOCKS5 use port 1080 by default\n # Or\n s.set_proxy(socks.SOCKS4, \"localhost\", 4444)\n # Or\n s.set_proxy(socks.HTTP, \"5.5.5.5\", 8888)\n\n # Can be treated identical to a regular socket object\n s.connect((\"www.somesite.com\", 80))\n s.sendall(\"GET / HTTP/1.1 ...\")\n print s.recv(4096)\n\n## Monkeypatching ##\n\nTo monkeypatch the entire standard library with a single default proxy:\n\n import urllib2\n import socket\n import socks\n\n socks.set_default_proxy(socks.SOCKS5, \"localhost\")\n socket.socket = socks.socksocket\n\n urllib2.urlopen(\"http://www.somesite.com/\") # All requests will pass through the SOCKS proxy\n\nNote that monkeypatching may not work for all standard modules or for all third party modules, and generally isn't recommended. Monkeypatching is usually an anti-pattern in Python.\n\n## urllib2 Handler ##\n\nExample use case with the `sockshandler` urllib2 handler. Note that you must import both `socks` and `sockshandler`, as the handler is its own module separate from PySocks. The module is included in the PyPI package.\n\n import urllib2\n import socks\n from sockshandler import SocksiPyHandler\n\n opener = urllib2.build_opener(SocksiPyHandler(socks.SOCKS5, \"127.0.0.1\", 9050))\n print opener.open(\"http://www.somesite.com/\") # All requests made by the opener will pass through the SOCKS proxy\n\n--------------------------------------------\n\nOriginal SocksiPy README attached below, amended to reflect API changes.\n\n--------------------------------------------\n\nSocksiPy\n\nA Python SOCKS module.\n\n(C) 2006 Dan-Haim. All rights reserved.\n\nSee LICENSE file for details.\n\n\n*WHAT IS A SOCKS PROXY?*\n\nA SOCKS proxy is a proxy server at the TCP level. In other words, it acts as\na tunnel, relaying all traffic going through it without modifying it.\nSOCKS proxies can be used to relay traffic using any network protocol that\nuses TCP.\n\n*WHAT IS SOCKSIPY?*\n\nThis Python module allows you to create TCP connections through a SOCKS\nproxy without any special effort.\nIt also supports relaying UDP packets with a SOCKS5 proxy.\n\n*PROXY COMPATIBILITY*\n\nSocksiPy is compatible with three different types of proxies:\n\n1. SOCKS Version 4 (SOCKS4), including the SOCKS4a extension.\n2. SOCKS Version 5 (SOCKS5).\n3. HTTP Proxies which support tunneling using the CONNECT method.\n\n*SYSTEM REQUIREMENTS*\n\nBeing written in Python, SocksiPy can run on any platform that has a Python\ninterpreter and TCP/IP support.\nThis module has been tested with Python 2.3 and should work with greater versions\njust as well.\n\n\nINSTALLATION\n-------------\n\nSimply copy the file \"socks.py\" to your Python's `lib/site-packages` directory,\nand you're ready to go. [Editor's note: it is better to use `python setup.py install` for PySocks]\n\n\nUSAGE\n------\n\nFirst load the socks module with the command:\n\n >>> import socks\n >>>\n\nThe socks module provides a class called `socksocket`, which is the base to all of the module's functionality.\n\nThe `socksocket` object has the same initialization parameters as the normal socket\nobject to ensure maximal compatibility, however it should be noted that `socksocket` will only function with family being `AF_INET` and\ntype being either `SOCK_STREAM` or `SOCK_DGRAM`.\nGenerally, it is best to initialize the `socksocket` object with no parameters\n\n >>> s = socks.socksocket()\n >>>\n\nThe `socksocket` object has an interface which is very similiar to socket's (in fact\nthe `socksocket` class is derived from socket) with a few extra methods.\nTo select the proxy server you would like to use, use the `set_proxy` method, whose\nsyntax is:\n\n set_proxy(proxy_type, addr[, port[, rdns[, username[, password]]]])\n\nExplanation of the parameters:\n\n`proxy_type` - The type of the proxy server. This can be one of three possible\nchoices: `PROXY_TYPE_SOCKS4`, `PROXY_TYPE_SOCKS5` and `PROXY_TYPE_HTTP` for SOCKS4,\nSOCKS5 and HTTP servers respectively. `SOCKS4`, `SOCKS5`, and `HTTP` are all aliases, respectively.\n\n`addr` - The IP address or DNS name of the proxy server.\n\n`port` - The port of the proxy server. Defaults to 1080 for socks and 8080 for http.\n\n`rdns` - This is a boolean flag than modifies the behavior regarding DNS resolving.\nIf it is set to True, DNS resolving will be preformed remotely, on the server.\nIf it is set to False, DNS resolving will be preformed locally. Please note that\nsetting this to True with SOCKS4 servers actually use an extension to the protocol,\ncalled SOCKS4a, which may not be supported on all servers (SOCKS5 and http servers\nalways support DNS). The default is True.\n\n`username` - For SOCKS5 servers, this allows simple username / password authentication\nwith the server. For SOCKS4 servers, this parameter will be sent as the userid.\nThis parameter is ignored if an HTTP server is being used. If it is not provided,\nauthentication will not be used (servers may accept unauthenticated requests).\n\n`password` - This parameter is valid only for SOCKS5 servers and specifies the\nrespective password for the username provided.\n\nExample of usage:\n\n >>> s.set_proxy(socks.SOCKS5, \"socks.example.com\") # uses default port 1080\n >>> s.set_proxy(socks.SOCKS4, \"socks.test.com\", 1081)\n\nAfter the set_proxy method has been called, simply call the connect method with the\ntraditional parameters to establish a connection through the proxy:\n\n >>> s.connect((\"www.sourceforge.net\", 80))\n >>>\n\nConnection will take a bit longer to allow negotiation with the proxy server.\nPlease note that calling connect without calling `set_proxy` earlier will connect\nwithout a proxy (just like a regular socket).\n\nErrors: Any errors in the connection process will trigger exceptions. The exception\nmay either be generated by the underlying socket layer or may be custom module\nexceptions, whose details follow:\n\nclass `ProxyError` - This is a base exception class. It is not raised directly but\nrather all other exception classes raised by this module are derived from it.\nThis allows an easy way to catch all proxy-related errors. It descends from `IOError`.\n\nAll `ProxyError` exceptions have an attribute `socket_err`, which will contain either a\ncaught `socket.error` exception, or `None` if there wasn't any.\n\nclass `GeneralProxyError` - When thrown, it indicates a problem which does not fall\ninto another category.\n\n* `Sent invalid data` - This error means that unexpected data has been received from\nthe server. The most common reason is that the server specified as the proxy is\nnot really a SOCKS4/SOCKS5/HTTP proxy, or maybe the proxy type specified is wrong.\n\n* `Connection closed unexpectedly` - The proxy server unexpectedly closed the connection.\nThis may indicate that the proxy server is experiencing network or software problems.\n\n* `Bad proxy type` - This will be raised if the type of the proxy supplied to the\nset_proxy function was not one of `SOCKS4`/`SOCKS5`/`HTTP`.\n\n* `Bad input` - This will be raised if the `connect()` method is called with bad input\nparameters.\n\nclass `SOCKS5AuthError` - This indicates that the connection through a SOCKS5 server\nfailed due to an authentication problem.\n\n* `Authentication is required` - This will happen if you use a SOCKS5 server which\nrequires authentication without providing a username / password at all.\n\n* `All offered authentication methods were rejected` - This will happen if the proxy\nrequires a special authentication method which is not supported by this module.\n\n* `Unknown username or invalid password` - Self descriptive.\n\nclass `SOCKS5Error` - This will be raised for SOCKS5 errors which are not related to\nauthentication.\nThe parameter is a tuple containing a code, as given by the server,\nand a description of the\nerror. The possible errors, according to the RFC, are:\n\n* `0x01` - General SOCKS server failure - If for any reason the proxy server is unable to\nfulfill your request (internal server error).\n* `0x02` - connection not allowed by ruleset - If the address you're trying to connect to\nis blacklisted on the server or requires authentication.\n* `0x03` - Network unreachable - The target could not be contacted. A router on the network\nhad replied with a destination net unreachable error.\n* `0x04` - Host unreachable - The target could not be contacted. A router on the network\nhad replied with a destination host unreachable error.\n* `0x05` - Connection refused - The target server has actively refused the connection\n(the requested port is closed).\n* `0x06` - TTL expired - The TTL value of the SYN packet from the proxy to the target server\nhas expired. This usually means that there are network problems causing the packet\nto be caught in a router-to-router \"ping-pong\".\n* `0x07` - Command not supported - For instance if the server does not support UDP.\n* `0x08` - Address type not supported - The client has provided an invalid address type.\nWhen using this module, this error should not occur.\n\nclass `SOCKS4Error` - This will be raised for SOCKS4 errors. The parameter is a tuple\ncontaining a code and a description of the error, as given by the server. The\npossible error, according to the specification are:\n\n* `0x5B` - Request rejected or failed - Will be raised in the event of an failure for any\nreason other then the two mentioned next.\n* `0x5C` - request rejected because SOCKS server cannot connect to identd on the client -\nThe Socks server had tried an ident lookup on your computer and has failed. In this\ncase you should run an identd server and/or configure your firewall to allow incoming\nconnections to local port 113 from the remote server.\n* `0x5D` - request rejected because the client program and identd report different user-ids -\nThe Socks server had performed an ident lookup on your computer and has received a\ndifferent userid than the one you have provided. Change your userid (through the\nusername parameter of the set_proxy method) to match and try again.\n\nclass `HTTPError` - This will be raised for HTTP errors. The message will contain\nthe HTTP status code and provided error message.\n\nAfter establishing the connection, the object behaves like a standard socket.\n\nMethods like `makefile()` and `settimeout()` should behave just like regular sockets.\nCall the `close()` method to close the connection.\n\nIn addition to the `socksocket` class, an additional function worth mentioning is the\n`set_default_proxy` function. The parameters are the same as the `set_proxy` method.\nThis function will set default proxy settings for newly created `socksocket` objects,\nin which the proxy settings haven't been changed via the `set_proxy` method.\nThis is quite useful if you wish to force 3rd party modules to use a SOCKS proxy,\nby overriding the socket object.\nFor example:\n\n >>> socks.set_default_proxy(socks.SOCKS5, \"socks.example.com\")\n >>> socket.socket = socks.socksocket\n >>> urllib.urlopen(\"http://www.sourceforge.net/\")\n\n\nPROBLEMS\n---------\n\nPlease open a GitHub issue at https://github.com/Anorov/PySocks\n\n\n" }, "metadata_location": "/opt/conda/lib/python3.10/site-packages/PySocks-1.7.1.dist-info", "direct_url": { "url": "file:///home/builder/ci_310/pysocks_1640793678128/work", "dir_info": {} }, "installer": "conda", "requested": true }, { "metadata": { "metadata_version": "2.1", "name": "PyYAML", "version": "6.0.2", "platform": [ "Any" ], "summary": "YAML parser and emitter for Python", "home_page": "https://pyyaml.org/", "download_url": "https://pypi.org/project/PyYAML/", "author": "Kirill Simonov", "author_email": "xi@resolvent.net", "license": "MIT", "classifier": [ "Development Status :: 5 - Production/Stable", "Intended Audience :: Developers", "License :: OSI Approved :: MIT License", "Operating System :: OS Independent", "Programming Language :: Cython", "Programming Language :: Python", "Programming Language :: Python :: 3", "Programming Language :: Python :: 3.8", "Programming Language :: Python :: 3.9", "Programming Language :: Python :: 3.10", "Programming Language :: Python :: 3.11", "Programming Language :: Python :: 3.12", "Programming Language :: Python :: 3.13", "Programming Language :: Python :: Implementation :: CPython", "Programming Language :: Python :: Implementation :: PyPy", "Topic :: Software Development :: Libraries :: Python Modules", "Topic :: Text Processing :: Markup" ], "requires_python": ">=3.8", "project_url": [ "Bug Tracker, https://github.com/yaml/pyyaml/issues", "CI, https://github.com/yaml/pyyaml/actions", "Documentation, https://pyyaml.org/wiki/PyYAMLDocumentation", "Mailing lists, http://lists.sourceforge.net/lists/listinfo/yaml-core", "Source Code, https://github.com/yaml/pyyaml" ], "description": "YAML is a data serialization format designed for human readability\nand interaction with scripting languages. PyYAML is a YAML parser\nand emitter for Python.\n\nPyYAML features a complete YAML 1.1 parser, Unicode support, pickle\nsupport, capable extension API, and sensible error messages. PyYAML\nsupports standard YAML tags and provides Python-specific tags that\nallow to represent an arbitrary Python object.\n\nPyYAML is applicable for a broad range of tasks from complex\nconfiguration files to object serialization and persistence.\n" }, "metadata_location": "/opt/conda/lib/python3.10/site-packages/PyYAML-6.0.2.dist-info", "direct_url": { "url": "file:///croot/pyyaml_1728657952215/work", "dir_info": {} }, "installer": "conda", "requested": true }, { "metadata": { "metadata_version": "2.1", "name": "accelerate", "version": "1.1.1", "platform": [ "UNKNOWN" ], "summary": "Accelerate", "description_content_type": "text/markdown", "keywords": [ "deep", "learning" ], "home_page": "https://github.com/huggingface/accelerate", "author": "The HuggingFace team", "author_email": "zach.mueller@huggingface.co", "license": "Apache", "classifier": [ "Development Status :: 5 - Production/Stable", "Intended Audience :: Developers", "Intended Audience :: Education", "Intended Audience :: Science/Research", "License :: OSI Approved :: Apache Software License", "Operating System :: OS Independent", "Programming Language :: Python :: 3", "Programming Language :: Python :: 3.8", "Topic :: Scientific/Engineering :: Artificial Intelligence" ], "requires_dist": [ "huggingface-hub>=0.21.0", "numpy<3.0.0,>=1.17", "packaging>=20.0", "psutil", "pyyaml", "safetensors>=0.4.3", "torch>=1.10.0", "deepspeed; extra == \"deepspeed\"", "bitsandbytes; extra == \"dev\"", "black~=23.1; extra == \"dev\"", "datasets; extra == \"dev\"", "diffusers; extra == \"dev\"", "evaluate; extra == \"dev\"", "hf-doc-builder>=0.3.0; extra == \"dev\"", "parameterized; extra == \"dev\"", "pytest-subtests; extra == \"dev\"", "pytest-xdist; extra == \"dev\"", "pytest<=8.0.0,>=7.2.0; extra == \"dev\"", "rich; extra == \"dev\"", "ruff~=0.6.4; extra == \"dev\"", "scikit-learn; extra == \"dev\"", "scipy; extra == \"dev\"", "timm; extra == \"dev\"", "torchdata>=0.8.0; extra == \"dev\"", "torchpippy>=0.2.0; extra == \"dev\"", "tqdm; extra == \"dev\"", "transformers; extra == \"dev\"", "black~=23.1; extra == \"quality\"", "hf-doc-builder>=0.3.0; extra == \"quality\"", "ruff~=0.6.4; extra == \"quality\"", "rich; extra == \"rich\"", "sagemaker; extra == \"sagemaker\"", "bitsandbytes; extra == \"test-dev\"", "datasets; extra == \"test-dev\"", "diffusers; extra == \"test-dev\"", "evaluate; extra == \"test-dev\"", "scikit-learn; extra == \"test-dev\"", "scipy; extra == \"test-dev\"", "timm; extra == \"test-dev\"", "torchdata>=0.8.0; extra == \"test-dev\"", "torchpippy>=0.2.0; extra == \"test-dev\"", "tqdm; extra == \"test-dev\"", "transformers; extra == \"test-dev\"", "parameterized; extra == \"test-prod\"", "pytest-subtests; extra == \"test-prod\"", "pytest-xdist; extra == \"test-prod\"", "pytest<=8.0.0,>=7.2.0; extra == \"test-prod\"", "comet-ml; extra == \"test-trackers\"", "dvclive; extra == \"test-trackers\"", "tensorboard; extra == \"test-trackers\"", "wandb; extra == \"test-trackers\"", "bitsandbytes; extra == \"testing\"", "datasets; extra == \"testing\"", "diffusers; extra == \"testing\"", "evaluate; extra == \"testing\"", "parameterized; extra == \"testing\"", "pytest-subtests; extra == \"testing\"", "pytest-xdist; extra == \"testing\"", "pytest<=8.0.0,>=7.2.0; extra == \"testing\"", "scikit-learn; extra == \"testing\"", "scipy; extra == \"testing\"", "timm; extra == \"testing\"", "torchdata>=0.8.0; extra == \"testing\"", "torchpippy>=0.2.0; extra == \"testing\"", "tqdm; extra == \"testing\"", "transformers; extra == \"testing\"" ], "requires_python": ">=3.9.0", "provides_extra": [ "deepspeed", "dev", "docs", "quality", "rich", "sagemaker", "test_dev", "test_prod", "test_trackers", "testing" ], "description": "\n\n

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\n \n \"License\"\n \"Documentation\"\n \"GitHub\n \"Contributor\n

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Run your *raw* PyTorch training script on any kind of device\n

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\n\n## Easy to integrate\n\n🤗 Accelerate was created for PyTorch users who like to write the training loop of PyTorch models but are reluctant to write and maintain the boilerplate code needed to use multi-GPUs/TPU/fp16.\n\n🤗 Accelerate abstracts exactly and only the boilerplate code related to multi-GPUs/TPU/fp16 and leaves the rest of your code unchanged.\n\nHere is an example:\n\n```diff\n import torch\n import torch.nn.functional as F\n from datasets import load_dataset\n+ from accelerate import Accelerator\n\n+ accelerator = Accelerator()\n- device = 'cpu'\n+ device = accelerator.device\n\n model = torch.nn.Transformer().to(device)\n optimizer = torch.optim.Adam(model.parameters())\n\n dataset = load_dataset('my_dataset')\n data = torch.utils.data.DataLoader(dataset, shuffle=True)\n\n+ model, optimizer, data = accelerator.prepare(model, optimizer, data)\n\n model.train()\n for epoch in range(10):\n for source, targets in data:\n source = source.to(device)\n targets = targets.to(device)\n\n optimizer.zero_grad()\n\n output = model(source)\n loss = F.cross_entropy(output, targets)\n\n- loss.backward()\n+ accelerator.backward(loss)\n\n optimizer.step()\n```\n\nAs you can see in this example, by adding 5-lines to any standard PyTorch training script you can now run on any kind of single or distributed node setting (single CPU, single GPU, multi-GPUs and TPUs) as well as with or without mixed precision (fp8, fp16, bf16).\n\nIn particular, the same code can then be run without modification on your local machine for debugging or your training environment.\n\n🤗 Accelerate even handles the device placement for you (which requires a few more changes to your code, but is safer in general), so you can even simplify your training loop further:\n\n```diff\n import torch\n import torch.nn.functional as F\n from datasets import load_dataset\n+ from accelerate import Accelerator\n\n- device = 'cpu'\n+ accelerator = Accelerator()\n\n- model = torch.nn.Transformer().to(device)\n+ model = torch.nn.Transformer()\n optimizer = torch.optim.Adam(model.parameters())\n\n dataset = load_dataset('my_dataset')\n data = torch.utils.data.DataLoader(dataset, shuffle=True)\n\n+ model, optimizer, data = accelerator.prepare(model, optimizer, data)\n\n model.train()\n for epoch in range(10):\n for source, targets in data:\n- source = source.to(device)\n- targets = targets.to(device)\n\n optimizer.zero_grad()\n\n output = model(source)\n loss = F.cross_entropy(output, targets)\n\n- loss.backward()\n+ accelerator.backward(loss)\n\n optimizer.step()\n```\n\nWant to learn more? Check out the [documentation](https://huggingface.co/docs/accelerate) or have a look at our [examples](https://github.com/huggingface/accelerate/tree/main/examples).\n\n## Launching script\n\n🤗 Accelerate also provides an optional CLI tool that allows you to quickly configure and test your training environment before launching the scripts. No need to remember how to use `torch.distributed.run` or to write a specific launcher for TPU training!\nOn your machine(s) just run:\n\n```bash\naccelerate config\n```\n\nand answer the questions asked. This will generate a config file that will be used automatically to properly set the default options when doing\n\n```bash\naccelerate launch my_script.py --args_to_my_script\n``` \n\nFor instance, here is how you would run the GLUE example on the MRPC task (from the root of the repo):\n\n```bash\naccelerate launch examples/nlp_example.py\n```\n\nThis CLI tool is **optional**, and you can still use `python my_script.py` or `python -m torchrun my_script.py` at your convenience.\n\nYou can also directly pass in the arguments you would to `torchrun` as arguments to `accelerate launch` if you wish to not run` accelerate config`.\n\nFor example, here is how to launch on two GPUs:\n\n```bash\naccelerate launch --multi_gpu --num_processes 2 examples/nlp_example.py\n```\n\nTo learn more, check the CLI documentation available [here](https://huggingface.co/docs/accelerate/package_reference/cli).\n\nOr view the configuration zoo [here](https://github.com/huggingface/accelerate/blob/main/examples/config_yaml_templates/)\n\n## Launching multi-CPU run using MPI\n\n🤗 Here is another way to launch multi-CPU run using MPI. You can learn how to install Open MPI on [this page](https://www.open-mpi.org/faq/?category=building#easy-build). You can use Intel MPI or MVAPICH as well.\nOnce you have MPI setup on your cluster, just run:\n```bash\naccelerate config\n```\nAnswer the questions that are asked, selecting to run using multi-CPU, and answer \"yes\" when asked if you want accelerate to launch mpirun.\nThen, use `accelerate launch` with your script like:\n```bash\naccelerate launch examples/nlp_example.py\n```\nAlternatively, you can use mpirun directly, without using the CLI like:\n```bash\nmpirun -np 2 python examples/nlp_example.py\n```\n\n## Launching training using DeepSpeed\n\n🤗 Accelerate supports training on single/multiple GPUs using DeepSpeed. To use it, you don't need to change anything in your training code; you can set everything using just `accelerate config`. However, if you desire to tweak your DeepSpeed related args from your Python script, we provide you the `DeepSpeedPlugin`.\n\n```python\nfrom accelerate import Accelerator, DeepSpeedPlugin\n\n# deepspeed needs to know your gradient accumulation steps beforehand, so don't forget to pass it\n# Remember you still need to do gradient accumulation by yourself, just like you would have done without deepspeed\ndeepspeed_plugin = DeepSpeedPlugin(zero_stage=2, gradient_accumulation_steps=2)\naccelerator = Accelerator(mixed_precision='fp16', deepspeed_plugin=deepspeed_plugin)\n\n# How to save your 🤗 Transformer?\naccelerator.wait_for_everyone()\nunwrapped_model = accelerator.unwrap_model(model)\nunwrapped_model.save_pretrained(save_dir, save_function=accelerator.save, state_dict=accelerator.get_state_dict(model))\n```\n\nNote: DeepSpeed support is experimental for now. In case you get into some problem, please open an issue.\n\n## Launching your training from a notebook\n\n🤗 Accelerate also provides a `notebook_launcher` function you can use in a notebook to launch a distributed training. This is especially useful for Colab or Kaggle notebooks with a TPU backend. Just define your training loop in a `training_function` then in your last cell, add:\n\n```python\nfrom accelerate import notebook_launcher\n\nnotebook_launcher(training_function)\n```\n\nAn example can be found in [this notebook](https://github.com/huggingface/notebooks/blob/main/examples/accelerate_examples/simple_nlp_example.ipynb). [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/accelerate_examples/simple_nlp_example.ipynb)\n\n## Why should I use 🤗 Accelerate?\n\nYou should use 🤗 Accelerate when you want to easily run your training scripts in a distributed environment without having to renounce full control over your training loop. This is not a high-level framework above PyTorch, just a thin wrapper so you don't have to learn a new library. In fact, the whole API of 🤗 Accelerate is in one class, the `Accelerator` object.\n\n## Why shouldn't I use 🤗 Accelerate?\n\nYou shouldn't use 🤗 Accelerate if you don't want to write a training loop yourself. There are plenty of high-level libraries above PyTorch that will offer you that, 🤗 Accelerate is not one of them.\n\n## Frameworks using 🤗 Accelerate\n\nIf you like the simplicity of 🤗 Accelerate but would prefer a higher-level abstraction around its capabilities, some frameworks and libraries that are built on top of 🤗 Accelerate are listed below:\n\n* [Amphion](https://github.com/open-mmlab/Amphion) is a toolkit for Audio, Music, and Speech Generation. Its purpose is to support reproducible research and help junior researchers and engineers get started in the field of audio, music, and speech generation research and development.\n* [Animus](https://github.com/Scitator/animus) is a minimalistic framework to run machine learning experiments. Animus highlights common \"breakpoints\" in ML experiments and provides a unified interface for them within [IExperiment](https://github.com/Scitator/animus/blob/main/animus/core.py#L76).\n* [Catalyst](https://github.com/catalyst-team/catalyst#getting-started) is a PyTorch framework for Deep Learning Research and Development. It focuses on reproducibility, rapid experimentation, and codebase reuse so you can create something new rather than write yet another train loop. Catalyst provides a [Runner](https://catalyst-team.github.io/catalyst/api/core.html#runner) to connect all parts of the experiment: hardware backend, data transformations, model training, and inference logic.\n* [fastai](https://github.com/fastai/fastai#installing) is a PyTorch framework for Deep Learning that simplifies training fast and accurate neural nets using modern best practices. fastai provides a [Learner](https://docs.fast.ai/learner.html#Learner) to handle the training, fine-tuning, and inference of deep learning algorithms.\n* [Finetuner](https://github.com/jina-ai/finetuner) is a service that enables models to create higher-quality embeddings for semantic search, visual similarity search, cross-modal text<->image search, recommendation systems, clustering, duplication detection, anomaly detection, or other uses.\n* [InvokeAI](https://github.com/invoke-ai/InvokeAI) is a creative engine for Stable Diffusion models, offering industry-leading WebUI, terminal usage support, and serves as the foundation for many commercial products.\n* [Kornia](https://kornia.readthedocs.io/en/latest/get-started/introduction.html) is a differentiable library that allows classical computer vision to be integrated into deep learning models. Kornia provides a [Trainer](https://kornia.readthedocs.io/en/latest/x.html#kornia.x.Trainer) with the specific purpose to train and fine-tune the supported deep learning algorithms within the library.\n* [Open Assistant](https://projects.laion.ai/Open-Assistant/) is a chat-based assistant that understands tasks, can interact with their party systems, and retrieve information dynamically to do so. \n* [pytorch-accelerated](https://github.com/Chris-hughes10/pytorch-accelerated) is a lightweight training library, with a streamlined feature set centered around a general-purpose [Trainer](https://pytorch-accelerated.readthedocs.io/en/latest/trainer.html), that places a huge emphasis on simplicity and transparency; enabling users to understand exactly what is going on under the hood, but without having to write and maintain the boilerplate themselves!\n* [Stable Diffusion web UI](https://github.com/AUTOMATIC1111/stable-diffusion-webui) is an open-source browser-based easy-to-use interface based on the Gradio library for Stable Diffusion.\n* [torchkeras](https://github.com/lyhue1991/torchkeras) is a simple tool for training pytorch model just in a keras style, a dynamic and beautiful plot is provided in notebook to monitor your loss or metric.\n* [transformers](https://github.com/huggingface/transformers) as a tool for helping train state-of-the-art machine learning models in PyTorch, Tensorflow, and JAX. (Accelerate is the backend for the PyTorch side).\n\n\n## Installation\n\nThis repository is tested on Python 3.8+ and PyTorch 1.10.0+\n\nYou should install 🤗 Accelerate in a [virtual environment](https://docs.python.org/3/library/venv.html). If you're unfamiliar with Python virtual environments, check out the [user guide](https://packaging.python.org/guides/installing-using-pip-and-virtual-environments/).\n\nFirst, create a virtual environment with the version of Python you're going to use and activate it.\n\nThen, you will need to install PyTorch: refer to the [official installation page](https://pytorch.org/get-started/locally/#start-locally) regarding the specific install command for your platform. Then 🤗 Accelerate can be installed using pip as follows:\n\n```bash\npip install accelerate\n```\n\n## Supported integrations\n\n- CPU only\n- multi-CPU on one node (machine)\n- multi-CPU on several nodes (machines)\n- single GPU\n- multi-GPU on one node (machine)\n- multi-GPU on several nodes (machines)\n- TPU\n- FP16/BFloat16 mixed precision\n- FP8 mixed precision with [Transformer Engine](https://github.com/NVIDIA/TransformerEngine) or [MS-AMP](https://github.com/Azure/MS-AMP/)\n- DeepSpeed support (Experimental)\n- PyTorch Fully Sharded Data Parallel (FSDP) support (Experimental)\n- Megatron-LM support (Experimental)\n\n## Citing 🤗 Accelerate\n\nIf you use 🤗 Accelerate in your publication, please cite it by using the following BibTeX entry.\n\n```bibtex\n@Misc{accelerate,\n title = {Accelerate: Training and inference at scale made simple, efficient and adaptable.},\n author = {Sylvain Gugger and Lysandre Debut and Thomas Wolf and Philipp Schmid and Zachary Mueller and Sourab Mangrulkar and Marc Sun and Benjamin Bossan},\n howpublished = {\\url{https://github.com/huggingface/accelerate}},\n year = {2022}\n}\n```\n\n\n" }, "metadata_location": "/opt/conda/lib/python3.10/site-packages/accelerate-1.1.1.dist-info", "installer": "pip", "requested": true }, { "metadata": { "metadata_version": "2.3", "name": "aiofiles", "version": "24.1.0", "summary": "File support for asyncio.", "description_content_type": "text/markdown", "author_email": "Tin Tvrtkovic ", "license": "Apache-2.0", "classifier": [ "Development Status :: 5 - Production/Stable", "Framework :: AsyncIO", "License :: OSI Approved :: Apache Software License", "Operating System :: OS Independent", "Programming Language :: Python :: 3.8", "Programming Language :: Python :: 3.9", "Programming Language :: Python :: 3.10", "Programming Language :: Python :: 3.11", "Programming Language :: Python :: 3.12", "Programming Language :: Python :: 3.13", "Programming Language :: Python :: Implementation :: CPython", "Programming Language :: Python :: Implementation :: PyPy" ], "requires_python": ">=3.8", "project_url": [ "Changelog, https://github.com/Tinche/aiofiles#history", "Bug Tracker, https://github.com/Tinche/aiofiles/issues", "repository, https://github.com/Tinche/aiofiles" ], "description": "# aiofiles: file support for asyncio\n\n[![PyPI](https://img.shields.io/pypi/v/aiofiles.svg)](https://pypi.python.org/pypi/aiofiles)\n[![Build](https://github.com/Tinche/aiofiles/workflows/CI/badge.svg)](https://github.com/Tinche/aiofiles/actions)\n[![Coverage](https://img.shields.io/endpoint?url=https://gist.githubusercontent.com/Tinche/882f02e3df32136c847ba90d2688f06e/raw/covbadge.json)](https://github.com/Tinche/aiofiles/actions/workflows/main.yml)\n[![Supported Python versions](https://img.shields.io/pypi/pyversions/aiofiles.svg)](https://github.com/Tinche/aiofiles)\n[![Black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)\n\n**aiofiles** is an Apache2 licensed library, written in Python, for handling local\ndisk files in asyncio applications.\n\nOrdinary local file IO is blocking, and cannot easily and portably be made\nasynchronous. This means doing file IO may interfere with asyncio applications,\nwhich shouldn't block the executing thread. aiofiles helps with this by\nintroducing asynchronous versions of files that support delegating operations to\na separate thread pool.\n\n```python\nasync with aiofiles.open('filename', mode='r') as f:\n contents = await f.read()\nprint(contents)\n'My file contents'\n```\n\nAsynchronous iteration is also supported.\n\n```python\nasync with aiofiles.open('filename') as f:\n async for line in f:\n ...\n```\n\nAsynchronous interface to tempfile module.\n\n```python\nasync with aiofiles.tempfile.TemporaryFile('wb') as f:\n await f.write(b'Hello, World!')\n```\n\n## Features\n\n- a file API very similar to Python's standard, blocking API\n- support for buffered and unbuffered binary files, and buffered text files\n- support for `async`/`await` ([PEP 492](https://peps.python.org/pep-0492/)) constructs\n- async interface to tempfile module\n\n## Installation\n\nTo install aiofiles, simply:\n\n```bash\n$ pip install aiofiles\n```\n\n## Usage\n\nFiles are opened using the `aiofiles.open()` coroutine, which in addition to\nmirroring the builtin `open` accepts optional `loop` and `executor`\narguments. If `loop` is absent, the default loop will be used, as per the\nset asyncio policy. If `executor` is not specified, the default event loop\nexecutor will be used.\n\nIn case of success, an asynchronous file object is returned with an\nAPI identical to an ordinary file, except the following methods are coroutines\nand delegate to an executor:\n\n- `close`\n- `flush`\n- `isatty`\n- `read`\n- `readall`\n- `read1`\n- `readinto`\n- `readline`\n- `readlines`\n- `seek`\n- `seekable`\n- `tell`\n- `truncate`\n- `writable`\n- `write`\n- `writelines`\n\nIn case of failure, one of the usual exceptions will be raised.\n\n`aiofiles.stdin`, `aiofiles.stdout`, `aiofiles.stderr`,\n`aiofiles.stdin_bytes`, `aiofiles.stdout_bytes`, and\n`aiofiles.stderr_bytes` provide async access to `sys.stdin`,\n`sys.stdout`, `sys.stderr`, and their corresponding `.buffer` properties.\n\nThe `aiofiles.os` module contains executor-enabled coroutine versions of\nseveral useful `os` functions that deal with files:\n\n- `stat`\n- `statvfs`\n- `sendfile`\n- `rename`\n- `renames`\n- `replace`\n- `remove`\n- `unlink`\n- `mkdir`\n- `makedirs`\n- `rmdir`\n- `removedirs`\n- `link`\n- `symlink`\n- `readlink`\n- `listdir`\n- `scandir`\n- `access`\n- `getcwd`\n- `path.abspath`\n- `path.exists`\n- `path.isfile`\n- `path.isdir`\n- `path.islink`\n- `path.ismount`\n- `path.getsize`\n- `path.getatime`\n- `path.getctime`\n- `path.samefile`\n- `path.sameopenfile`\n\n### Tempfile\n\n**aiofiles.tempfile** implements the following interfaces:\n\n- TemporaryFile\n- NamedTemporaryFile\n- SpooledTemporaryFile\n- TemporaryDirectory\n\nResults return wrapped with a context manager allowing use with async with and async for.\n\n```python\nasync with aiofiles.tempfile.NamedTemporaryFile('wb+') as f:\n await f.write(b'Line1\\n Line2')\n await f.seek(0)\n async for line in f:\n print(line)\n\nasync with aiofiles.tempfile.TemporaryDirectory() as d:\n filename = os.path.join(d, \"file.ext\")\n```\n\n### Writing tests for aiofiles\n\nReal file IO can be mocked by patching `aiofiles.threadpool.sync_open`\nas desired. The return type also needs to be registered with the\n`aiofiles.threadpool.wrap` dispatcher:\n\n```python\naiofiles.threadpool.wrap.register(mock.MagicMock)(\n lambda *args, **kwargs: aiofiles.threadpool.AsyncBufferedIOBase(*args, **kwargs)\n)\n\nasync def test_stuff():\n write_data = 'data'\n read_file_chunks = [\n b'file chunks 1',\n b'file chunks 2',\n b'file chunks 3',\n b'',\n ]\n file_chunks_iter = iter(read_file_chunks)\n\n mock_file_stream = mock.MagicMock(\n read=lambda *args, **kwargs: next(file_chunks_iter)\n )\n\n with mock.patch('aiofiles.threadpool.sync_open', return_value=mock_file_stream) as mock_open:\n async with aiofiles.open('filename', 'w') as f:\n await f.write(write_data)\n assert f.read() == b'file chunks 1'\n\n mock_file_stream.write.assert_called_once_with(write_data)\n```\n\n### History\n\n#### 24.1.0 (2024-06-24)\n\n- Import `os.link` conditionally to fix importing on android.\n [#175](https://github.com/Tinche/aiofiles/issues/175)\n- Remove spurious items from `aiofiles.os.__all__` when running on Windows.\n- Switch to more modern async idioms: Remove types.coroutine and make AiofilesContextManager an awaitable instead a coroutine.\n- Add `aiofiles.os.path.abspath` and `aiofiles.os.getcwd`.\n [#174](https://github.com/Tinche/aiofiles/issues/181)\n- _aiofiles_ is now tested on Python 3.13 too.\n [#184](https://github.com/Tinche/aiofiles/pull/184)\n- Dropped Python 3.7 support. If you require it, use version 23.2.1.\n\n#### 23.2.1 (2023-08-09)\n\n- Import `os.statvfs` conditionally to fix importing on non-UNIX systems.\n [#171](https://github.com/Tinche/aiofiles/issues/171) [#172](https://github.com/Tinche/aiofiles/pull/172)\n- aiofiles is now also tested on Windows.\n\n#### 23.2.0 (2023-08-09)\n\n- aiofiles is now tested on Python 3.12 too.\n [#166](https://github.com/Tinche/aiofiles/issues/166) [#168](https://github.com/Tinche/aiofiles/pull/168)\n- On Python 3.12, `aiofiles.tempfile.NamedTemporaryFile` now accepts a `delete_on_close` argument, just like the stdlib version.\n- On Python 3.12, `aiofiles.tempfile.NamedTemporaryFile` no longer exposes a `delete` attribute, just like the stdlib version.\n- Added `aiofiles.os.statvfs` and `aiofiles.os.path.ismount`.\n [#162](https://github.com/Tinche/aiofiles/pull/162)\n- Use [PDM](https://pdm.fming.dev/latest/) instead of Poetry.\n [#169](https://github.com/Tinche/aiofiles/pull/169)\n\n#### 23.1.0 (2023-02-09)\n\n- Added `aiofiles.os.access`.\n [#146](https://github.com/Tinche/aiofiles/pull/146)\n- Removed `aiofiles.tempfile.temptypes.AsyncSpooledTemporaryFile.softspace`.\n [#151](https://github.com/Tinche/aiofiles/pull/151)\n- Added `aiofiles.stdin`, `aiofiles.stdin_bytes`, and other stdio streams.\n [#154](https://github.com/Tinche/aiofiles/pull/154)\n- Transition to `asyncio.get_running_loop` (vs `asyncio.get_event_loop`) internally.\n\n#### 22.1.0 (2022-09-04)\n\n- Added `aiofiles.os.path.islink`.\n [#126](https://github.com/Tinche/aiofiles/pull/126)\n- Added `aiofiles.os.readlink`.\n [#125](https://github.com/Tinche/aiofiles/pull/125)\n- Added `aiofiles.os.symlink`.\n [#124](https://github.com/Tinche/aiofiles/pull/124)\n- Added `aiofiles.os.unlink`.\n [#123](https://github.com/Tinche/aiofiles/pull/123)\n- Added `aiofiles.os.link`.\n [#121](https://github.com/Tinche/aiofiles/pull/121)\n- Added `aiofiles.os.renames`.\n [#120](https://github.com/Tinche/aiofiles/pull/120)\n- Added `aiofiles.os.{listdir, scandir}`.\n [#143](https://github.com/Tinche/aiofiles/pull/143)\n- Switched to CalVer.\n- Dropped Python 3.6 support. If you require it, use version 0.8.0.\n- aiofiles is now tested on Python 3.11.\n\n#### 0.8.0 (2021-11-27)\n\n- aiofiles is now tested on Python 3.10.\n- Added `aiofiles.os.replace`.\n [#107](https://github.com/Tinche/aiofiles/pull/107)\n- Added `aiofiles.os.{makedirs, removedirs}`.\n- Added `aiofiles.os.path.{exists, isfile, isdir, getsize, getatime, getctime, samefile, sameopenfile}`.\n [#63](https://github.com/Tinche/aiofiles/pull/63)\n- Added `suffix`, `prefix`, `dir` args to `aiofiles.tempfile.TemporaryDirectory`.\n [#116](https://github.com/Tinche/aiofiles/pull/116)\n\n#### 0.7.0 (2021-05-17)\n\n- Added the `aiofiles.tempfile` module for async temporary files.\n [#56](https://github.com/Tinche/aiofiles/pull/56)\n- Switched to Poetry and GitHub actions.\n- Dropped 3.5 support.\n\n#### 0.6.0 (2020-10-27)\n\n- `aiofiles` is now tested on ppc64le.\n- Added `name` and `mode` properties to async file objects.\n [#82](https://github.com/Tinche/aiofiles/pull/82)\n- Fixed a DeprecationWarning internally.\n [#75](https://github.com/Tinche/aiofiles/pull/75)\n- Python 3.9 support and tests.\n\n#### 0.5.0 (2020-04-12)\n\n- Python 3.8 support. Code base modernization (using `async/await` instead of `asyncio.coroutine`/`yield from`).\n- Added `aiofiles.os.remove`, `aiofiles.os.rename`, `aiofiles.os.mkdir`, `aiofiles.os.rmdir`.\n [#62](https://github.com/Tinche/aiofiles/pull/62)\n\n#### 0.4.0 (2018-08-11)\n\n- Python 3.7 support.\n- Removed Python 3.3/3.4 support. If you use these versions, stick to aiofiles 0.3.x.\n\n#### 0.3.2 (2017-09-23)\n\n- The LICENSE is now included in the sdist.\n [#31](https://github.com/Tinche/aiofiles/pull/31)\n\n#### 0.3.1 (2017-03-10)\n\n- Introduced a changelog.\n- `aiofiles.os.sendfile` will now work if the standard `os` module contains a `sendfile` function.\n\n### Contributing\n\nContributions are very welcome. Tests can be run with `tox`, please ensure\nthe coverage at least stays the same before you submit a pull request.\n" }, "metadata_location": "/opt/conda/lib/python3.10/site-packages/aiofiles-24.1.0.dist-info", "installer": "pip", "requested": true }, { "metadata": { "metadata_version": "2.1", "name": "aiohappyeyeballs", "version": "2.4.3", "summary": "Happy Eyeballs for asyncio", "description_content_type": "text/markdown", "home_page": "https://github.com/aio-libs/aiohappyeyeballs", "author": "J. Nick Koston", "author_email": "nick@koston.org", "license": "PSF-2.0", "classifier": [ "Development Status :: 5 - Production/Stable", "Intended Audience :: Developers", "License :: OSI Approved :: Python Software Foundation License", "License :: Other/Proprietary License", "Natural Language :: English", "Operating System :: OS Independent", "Programming Language :: Python :: 3", "Programming Language :: Python :: 3.8", "Programming Language :: Python :: 3.9", "Programming Language :: Python :: 3.10", "Programming Language :: Python :: 3.11", "Programming Language :: Python :: 3.12", "Programming Language :: Python :: 3.13", "Topic :: Software Development :: Libraries" ], "requires_python": ">=3.8", "project_url": [ "Bug Tracker, https://github.com/aio-libs/aiohappyeyeballs/issues", "Changelog, https://github.com/aio-libs/aiohappyeyeballs/blob/main/CHANGELOG.md", "Documentation, https://aiohappyeyeballs.readthedocs.io", "Repository, https://github.com/aio-libs/aiohappyeyeballs" ], "description": "# aiohappyeyeballs\n\n

\n \n \"CI\n \n \n \"Documentation\n \n \n \"Test\n \n

\n

\n \n \"Poetry\"\n \n \n \"Ruff\"\n \n \n \"pre-commit\"\n \n

\n

\n \n \"PyPI\n \n \"Supported\n \"License\"\n

\n\n---\n\n**Documentation**: https://aiohappyeyeballs.readthedocs.io \n\n**Source Code**: https://github.com/aio-libs/aiohappyeyeballs \n\n---\n\n[Happy Eyeballs](https://en.wikipedia.org/wiki/Happy_Eyeballs)\n([RFC 8305](https://www.rfc-editor.org/rfc/rfc8305.html))\n\n## Use case\n\nThis library exists to allow connecting with\n[Happy Eyeballs](https://en.wikipedia.org/wiki/Happy_Eyeballs)\n([RFC 8305](https://www.rfc-editor.org/rfc/rfc8305.html))\nwhen you\nalready have a list of addrinfo and not a DNS name.\n\nThe stdlib version of `loop.create_connection()`\nwill only work when you pass in an unresolved name which\nis not a good fit when using DNS caching or resolving\nnames via another method such as `zeroconf`.\n\n## Installation\n\nInstall this via pip (or your favourite package manager):\n\n`pip install aiohappyeyeballs`\n\n## License\n\n[aiohappyeyeballs is licensed under the same terms as cpython itself.](https://github.com/python/cpython/blob/main/LICENSE)\n\n## Example usage\n\n```python\n\naddr_infos = await loop.getaddrinfo(\"example.org\", 80)\n\nsocket = await start_connection(addr_infos)\nsocket = await start_connection(addr_infos, local_addr_infos=local_addr_infos, happy_eyeballs_delay=0.2)\n\ntransport, protocol = await loop.create_connection(\n MyProtocol, sock=socket, ...)\n\n# Remove the first address for each family from addr_info\npop_addr_infos_interleave(addr_info, 1)\n\n# Remove all matching address from addr_info\nremove_addr_infos(addr_info, \"dead::beef::\")\n\n# Convert a local_addr to local_addr_infos\nlocal_addr_infos = addr_to_addr_infos((\"127.0.0.1\",0))\n```\n\n## Credits\n\nThis package contains code from cpython and is licensed under the same terms as cpython itself.\n\nThis package was created with\n[Copier](https://copier.readthedocs.io/) and the\n[browniebroke/pypackage-template](https://github.com/browniebroke/pypackage-template)\nproject template.\n\n" }, "metadata_location": "/opt/conda/lib/python3.10/site-packages/aiohappyeyeballs-2.4.3.dist-info", "installer": "pip", "requested": false }, { "metadata": { "metadata_version": "2.1", "name": "aiohttp", "version": "3.11.8", "summary": "Async http client/server framework (asyncio)", "description_content_type": "text/x-rst", "home_page": "https://github.com/aio-libs/aiohttp", "maintainer": "aiohttp team ", "maintainer_email": "team@aiohttp.org", "license": "Apache-2.0", "classifier": [ "Development Status :: 5 - Production/Stable", "Framework :: AsyncIO", "Intended Audience :: Developers", "License :: OSI Approved :: Apache Software License", "Operating System :: POSIX", "Operating System :: MacOS :: MacOS X", "Operating System :: Microsoft :: Windows", "Programming Language :: Python", "Programming Language :: Python :: 3", "Programming Language :: Python :: 3.9", "Programming Language :: Python :: 3.10", "Programming Language :: Python :: 3.11", "Programming Language :: Python :: 3.12", "Programming Language :: Python :: 3.13", "Topic :: Internet :: WWW/HTTP" ], "requires_dist": [ "aiohappyeyeballs>=2.3.0", "aiosignal>=1.1.2", "async-timeout<6.0,>=4.0; python_version < \"3.11\"", "attrs>=17.3.0", "frozenlist>=1.1.1", "multidict<7.0,>=4.5", "propcache>=0.2.0", "yarl<2.0,>=1.17.0", "aiodns>=3.2.0; (sys_platform == \"linux\" or sys_platform == \"darwin\") and extra == \"speedups\"", "Brotli; platform_python_implementation == \"CPython\" and extra == \"speedups\"", "brotlicffi; platform_python_implementation != \"CPython\" and extra == \"speedups\"" ], "requires_python": ">=3.9", "project_url": [ "Chat: Matrix, https://matrix.to/#/#aio-libs:matrix.org", "Chat: Matrix Space, https://matrix.to/#/#aio-libs-space:matrix.org", "CI: GitHub Actions, https://github.com/aio-libs/aiohttp/actions?query=workflow%3ACI", "Coverage: codecov, https://codecov.io/github/aio-libs/aiohttp", "Docs: Changelog, https://docs.aiohttp.org/en/stable/changes.html", "Docs: RTD, https://docs.aiohttp.org", "GitHub: issues, https://github.com/aio-libs/aiohttp/issues", "GitHub: repo, https://github.com/aio-libs/aiohttp" ], "provides_extra": [ "speedups" ], "description": "==================================\nAsync http client/server framework\n==================================\n\n.. image:: https://raw.githubusercontent.com/aio-libs/aiohttp/master/docs/aiohttp-plain.svg\n :height: 64px\n :width: 64px\n :alt: aiohttp logo\n\n|\n\n.. image:: https://github.com/aio-libs/aiohttp/workflows/CI/badge.svg\n :target: https://github.com/aio-libs/aiohttp/actions?query=workflow%3ACI\n :alt: GitHub Actions status for master branch\n\n.. image:: https://codecov.io/gh/aio-libs/aiohttp/branch/master/graph/badge.svg\n :target: https://codecov.io/gh/aio-libs/aiohttp\n :alt: codecov.io status for master branch\n\n.. image:: https://img.shields.io/endpoint?url=https://codspeed.io/badge.json\n :target: https://codspeed.io/aio-libs/aiohttp\n :alt: Codspeed.io status for aiohttp\n\n.. image:: https://badge.fury.io/py/aiohttp.svg\n :target: https://pypi.org/project/aiohttp\n :alt: Latest PyPI package version\n\n.. image:: https://readthedocs.org/projects/aiohttp/badge/?version=latest\n :target: https://docs.aiohttp.org/\n :alt: Latest Read The Docs\n\n.. image:: https://img.shields.io/matrix/aio-libs:matrix.org?label=Discuss%20on%20Matrix%20at%20%23aio-libs%3Amatrix.org&logo=matrix&server_fqdn=matrix.org&style=flat\n :target: https://matrix.to/#/%23aio-libs:matrix.org\n :alt: Matrix Room — #aio-libs:matrix.org\n\n.. image:: https://img.shields.io/matrix/aio-libs-space:matrix.org?label=Discuss%20on%20Matrix%20at%20%23aio-libs-space%3Amatrix.org&logo=matrix&server_fqdn=matrix.org&style=flat\n :target: https://matrix.to/#/%23aio-libs-space:matrix.org\n :alt: Matrix Space — #aio-libs-space:matrix.org\n\n\nKey Features\n============\n\n- Supports both client and server side of HTTP protocol.\n- Supports both client and server Web-Sockets out-of-the-box and avoids\n Callback Hell.\n- Provides Web-server with middleware and pluggable routing.\n\n\nGetting started\n===============\n\nClient\n------\n\nTo get something from the web:\n\n.. code-block:: python\n\n import aiohttp\n import asyncio\n\n async def main():\n\n async with aiohttp.ClientSession() as session:\n async with session.get('http://python.org') as response:\n\n print(\"Status:\", response.status)\n print(\"Content-type:\", response.headers['content-type'])\n\n html = await response.text()\n print(\"Body:\", html[:15], \"...\")\n\n asyncio.run(main())\n\nThis prints:\n\n.. code-block::\n\n Status: 200\n Content-type: text/html; charset=utf-8\n Body: ...\n\nComing from `requests `_ ? Read `why we need so many lines `_.\n\nServer\n------\n\nAn example using a simple server:\n\n.. code-block:: python\n\n # examples/server_simple.py\n from aiohttp import web\n\n async def handle(request):\n name = request.match_info.get('name', \"Anonymous\")\n text = \"Hello, \" + name\n return web.Response(text=text)\n\n async def wshandle(request):\n ws = web.WebSocketResponse()\n await ws.prepare(request)\n\n async for msg in ws:\n if msg.type == web.WSMsgType.text:\n await ws.send_str(\"Hello, {}\".format(msg.data))\n elif msg.type == web.WSMsgType.binary:\n await ws.send_bytes(msg.data)\n elif msg.type == web.WSMsgType.close:\n break\n\n return ws\n\n\n app = web.Application()\n app.add_routes([web.get('/', handle),\n web.get('/echo', wshandle),\n web.get('/{name}', handle)])\n\n if __name__ == '__main__':\n web.run_app(app)\n\n\nDocumentation\n=============\n\nhttps://aiohttp.readthedocs.io/\n\n\nDemos\n=====\n\nhttps://github.com/aio-libs/aiohttp-demos\n\n\nExternal links\n==============\n\n* `Third party libraries\n `_\n* `Built with aiohttp\n `_\n* `Powered by aiohttp\n `_\n\nFeel free to make a Pull Request for adding your link to these pages!\n\n\nCommunication channels\n======================\n\n*aio-libs Discussions*: https://github.com/aio-libs/aiohttp/discussions\n\n*Matrix*: `#aio-libs:matrix.org `_\n\nWe support `Stack Overflow\n`_.\nPlease add *aiohttp* tag to your question there.\n\nRequirements\n============\n\n- attrs_\n- multidict_\n- yarl_\n- frozenlist_\n\nOptionally you may install the aiodns_ library (highly recommended for sake of speed).\n\n.. _aiodns: https://pypi.python.org/pypi/aiodns\n.. _attrs: https://github.com/python-attrs/attrs\n.. _multidict: https://pypi.python.org/pypi/multidict\n.. _frozenlist: https://pypi.org/project/frozenlist/\n.. _yarl: https://pypi.python.org/pypi/yarl\n.. _async-timeout: https://pypi.python.org/pypi/async_timeout\n\nLicense\n=======\n\n``aiohttp`` is offered under the Apache 2 license.\n\n\nKeepsafe\n========\n\nThe aiohttp community would like to thank Keepsafe\n(https://www.getkeepsafe.com) for its support in the early days of\nthe project.\n\n\nSource code\n===========\n\nThe latest developer version is available in a GitHub repository:\nhttps://github.com/aio-libs/aiohttp\n\nBenchmarks\n==========\n\nIf you are interested in efficiency, the AsyncIO community maintains a\nlist of benchmarks on the official wiki:\nhttps://github.com/python/asyncio/wiki/Benchmarks\n" }, "metadata_location": "/opt/conda/lib/python3.10/site-packages/aiohttp-3.11.8.dist-info", "installer": "pip", "requested": false }, { "metadata": { "metadata_version": "2.1", "name": "aiosignal", "version": "1.3.1", "summary": "aiosignal: a list of registered asynchronous callbacks", "description_content_type": "text/x-rst", "home_page": "https://github.com/aio-libs/aiosignal", "maintainer": "aiohttp team ", "maintainer_email": "team@aiohttp.org", "license": "Apache 2.0", "classifier": [ "License :: OSI Approved :: Apache Software License", "Intended Audience :: Developers", "Programming Language :: Python", "Programming Language :: Python :: 3", "Programming Language :: Python :: 3 :: Only", "Programming Language :: Python :: 3.7", "Programming Language :: Python :: 3.8", "Programming Language :: Python :: 3.9", "Programming Language :: Python :: 3.10", "Programming Language :: Python :: 3.11", "Development Status :: 5 - Production/Stable", "Operating System :: POSIX", "Operating System :: MacOS :: MacOS X", "Operating System :: Microsoft :: Windows", "Framework :: AsyncIO" ], "requires_dist": [ "frozenlist (>=1.1.0)" ], "requires_python": ">=3.7", "project_url": [ "Chat: Gitter, https://gitter.im/aio-libs/Lobby", "CI: GitHub Actions, https://github.com/aio-libs/aiosignal/actions", "Coverage: codecov, https://codecov.io/github/aio-libs/aiosignal", "Docs: RTD, https://docs.aiosignal.org", "GitHub: issues, https://github.com/aio-libs/aiosignal/issues", "GitHub: repo, https://github.com/aio-libs/aiosignal" ], "description": "=========\naiosignal\n=========\n\n.. image:: https://github.com/aio-libs/aiosignal/workflows/CI/badge.svg\n :target: https://github.com/aio-libs/aiosignal/actions?query=workflow%3ACI\n :alt: GitHub status for master branch\n\n.. image:: https://codecov.io/gh/aio-libs/aiosignal/branch/master/graph/badge.svg\n :target: https://codecov.io/gh/aio-libs/aiosignal\n :alt: codecov.io status for master branch\n\n.. image:: https://badge.fury.io/py/aiosignal.svg\n :target: https://pypi.org/project/aiosignal\n :alt: Latest PyPI package version\n\n.. image:: https://readthedocs.org/projects/aiosignal/badge/?version=latest\n :target: https://aiosignal.readthedocs.io/\n :alt: Latest Read The Docs\n\n.. image:: https://img.shields.io/discourse/topics?server=https%3A%2F%2Faio-libs.discourse.group%2F\n :target: https://aio-libs.discourse.group/\n :alt: Discourse group for io-libs\n\n.. image:: https://badges.gitter.im/Join%20Chat.svg\n :target: https://gitter.im/aio-libs/Lobby\n :alt: Chat on Gitter\n\nIntroduction\n============\n\nA project to manage callbacks in `asyncio` projects.\n\n``Signal`` is a list of registered asynchronous callbacks.\n\nThe signal's life-cycle has two stages: after creation its content\ncould be filled by using standard list operations: ``sig.append()``\netc.\n\nAfter you call ``sig.freeze()`` the signal is *frozen*: adding, removing\nand dropping callbacks is forbidden.\n\nThe only available operation is calling the previously registered\ncallbacks by using ``await sig.send(data)``.\n\nFor concrete usage examples see the `Signals\n\nsection of the `Web Server Advanced\n` chapter of the `aiohttp\ndocumentation`_.\n\n\nInstallation\n------------\n\n::\n\n $ pip install aiosignal\n\nThe library requires Python 3.6 or newer.\n\n\nDocumentation\n=============\n\nhttps://aiosignal.readthedocs.io/\n\nCommunication channels\n======================\n\n*gitter chat* https://gitter.im/aio-libs/Lobby\n\nRequirements\n============\n\n- Python >= 3.6\n- frozenlist >= 1.0.0\n\nLicense\n=======\n\n``aiosignal`` is offered under the Apache 2 license.\n\nSource code\n===========\n\nThe project is hosted on GitHub_\n\nPlease file an issue in the `bug tracker\n`_ if you have found a bug\nor have some suggestions to improve the library.\n\n.. _GitHub: https://github.com/aio-libs/aiosignal\n.. _aiohttp documentation: https://docs.aiohttp.org/\n" }, "metadata_location": "/opt/conda/lib/python3.10/site-packages/aiosignal-1.3.1.dist-info", "installer": "pip", "requested": false }, { "metadata": { "metadata_version": "2.1", "name": "alabaster", "version": "1.0.0", "summary": "A light, configurable Sphinx theme", "description_content_type": "text/x-rst", "maintainer": "Adam Turner", "maintainer_email": "Jeff Forcier ", "classifier": [ "Development Status :: 5 - Production/Stable", "Framework :: Sphinx", "Framework :: Sphinx :: Theme", "Intended Audience :: Developers", "License :: OSI Approved :: BSD License", "Operating System :: OS Independent", "Programming Language :: Python :: 3", "Programming Language :: Python :: 3 :: Only", "Programming Language :: Python :: 3.10", "Programming Language :: Python :: 3.11", "Programming Language :: Python :: 3.12", "Programming Language :: Python :: 3.13", "Programming Language :: Python :: Implementation :: CPython", "Programming Language :: Python :: Implementation :: PyPy", "Topic :: Documentation", "Topic :: Documentation :: Sphinx", "Topic :: Software Development :: Documentation" ], "requires_python": ">=3.10", "project_url": [ "Changelog, https://alabaster.readthedocs.io/en/latest/changelog.html", "Documentation, https://alabaster.readthedocs.io/", "Download, https://pypi.org/project/alabaster/", "Homepage, https://alabaster.readthedocs.io/", "Issue tracker, https://github.com/sphinx-doc/alabaster/issues", "Source, https://github.com/sphinx-doc/alabaster" ], "description": ".. image:: https://img.shields.io/pypi/v/alabaster.svg\n :target: https://pypi.org/project/alabaster/\n :alt: Package on PyPI\n\n.. image:: https://github.com/sphinx-doc/alabaster/actions/workflows/test.yml/badge.svg\n :target: https://github.com/sphinx-doc/alabaster/actions/workflows/test.yml\n :alt: CI Status\n\n.. image:: https://readthedocs.org/projects/alabaster/badge/\n :target: https://alabaster.readthedocs.io/\n :alt: Documentation Status\n\n.. image:: https://img.shields.io/badge/License-BSD%203--Clause-blue.svg\n :target: https://opensource.org/license/BSD-3-Clause\n :alt: BSD 3 Clause\n\n\nWhat is Alabaster?\n==================\n\nAlabaster is a visually (c)lean, responsive, configurable theme for the `Sphinx\n`_ documentation system.\nIt requires Python 3.10 or newer and Sphinx 6.2 or newer.\n\nIt began as a third-party theme, and is still maintained separately, but as of\nSphinx 1.3, Alabaster is an install-time dependency of Sphinx and is selected\nas the default theme.\n\nLive examples of this theme can be seen on `this project's own website\n`_, `paramiko.org `_,\n`fabfile.org `_ and `pyinvoke.org `_.\n\nFor more documentation, please see https://alabaster.readthedocs.io/.\n\n" }, "metadata_location": "/opt/conda/lib/python3.10/site-packages/alabaster-1.0.0.dist-info", "installer": "pip", "requested": false }, { "metadata": { "metadata_version": "2.1", "name": "anaconda-anon-usage", "version": "0.5.0", "summary": "basic anonymous telemetry for conda", "keywords": [ "anaconda-anon-usage" ], "home_page": "https://github.com/Anaconda-Platform/anaconda-anon-usage", "author": "Michael C. Grant", "author_email": "mgrant@anaconda.com", "license": "BSD", "classifier": [ "Programming Language :: Python :: 3", "Programming Language :: Python :: 3.7", "Programming Language :: Python :: 3.8", "Programming Language :: Python :: 3.9", "Programming Language :: Python :: 3.10", "Programming Language :: Python :: 3.11", "Programming Language :: Python :: 3.12" ], "requires_dist": [ "conda" ] }, "metadata_location": "/opt/conda/lib/python3.10/site-packages/anaconda_anon_usage-0.5.0.dist-info", "direct_url": { "url": "file:///croot/anaconda-anon-usage_1732732445543/work", "dir_info": {} }, "installer": "conda", "requested": true }, { "metadata": { "metadata_version": "2.4", "name": "annotated-doc", "version": "0.0.4", "summary": "Document parameters, class attributes, return types, and variables inline, with Annotated.", "description_content_type": "text/markdown", "author_email": "=?utf-8?q?Sebasti=C3=A1n_Ram=C3=ADrez?= ", "classifier": [ "Intended Audience :: Information Technology", "Intended Audience :: System Administrators", "Operating System :: OS Independent", "Programming Language :: Python :: 3", "Programming Language :: Python", "Topic :: Internet", "Topic :: Software Development :: Libraries :: Application Frameworks", "Topic :: Software Development :: Libraries :: Python Modules", "Topic :: Software Development :: Libraries", "Topic :: Software Development", "Typing :: Typed", "Development Status :: 4 - Beta", "Intended Audience :: Developers", "Programming Language :: Python :: 3 :: Only", "Programming Language :: Python :: 3.8", "Programming Language :: Python :: 3.9", "Programming Language :: Python :: 3.10", "Programming Language :: Python :: 3.11", "Programming Language :: Python :: 3.12", "Programming Language :: Python :: 3.13", "Programming Language :: Python :: 3.14" ], "requires_python": ">=3.8", "project_url": [ "Homepage, https://github.com/fastapi/annotated-doc", "Documentation, https://github.com/fastapi/annotated-doc", "Repository, https://github.com/fastapi/annotated-doc", "Issues, https://github.com/fastapi/annotated-doc/issues", "Changelog, https://github.com/fastapi/annotated-doc/release-notes.md" ], "description": "# Annotated Doc\n\nDocument parameters, class attributes, return types, and variables inline, with `Annotated`.\n\n\n \"Test\"\n\n\n \"Coverage\"\n\n\n \"Package\n\n\n \"Supported\n\n\n## Installation\n\n```bash\npip install annotated-doc\n```\n\nOr with `uv`:\n\n```Python\nuv add annotated-doc\n```\n\n## Usage\n\nImport `Doc` and pass a single literal string with the documentation for the specific parameter, class attribute, return type, or variable.\n\nFor example, to document a parameter `name` in a function `hi` you could do:\n\n```Python\nfrom typing import Annotated\n\nfrom annotated_doc import Doc\n\ndef hi(name: Annotated[str, Doc(\"Who to say hi to\")]) -> None:\n print(f\"Hi, {name}!\")\n```\n\nYou can also use it to document class attributes:\n\n```Python\nfrom typing import Annotated\n\nfrom annotated_doc import Doc\n\nclass User:\n name: Annotated[str, Doc(\"The user's name\")]\n age: Annotated[int, Doc(\"The user's age\")]\n```\n\nThe same way, you could document return types and variables, or anything that could have a type annotation with `Annotated`.\n\n## Who Uses This\n\n`annotated-doc` was made for:\n\n* [FastAPI](https://fastapi.tiangolo.com/)\n* [Typer](https://typer.tiangolo.com/)\n* [SQLModel](https://sqlmodel.tiangolo.com/)\n* [Asyncer](https://asyncer.tiangolo.com/)\n\n`annotated-doc` is supported by [griffe-typingdoc](https://github.com/mkdocstrings/griffe-typingdoc), which powers reference documentation like the one in the [FastAPI Reference](https://fastapi.tiangolo.com/reference/).\n\n## Reasons not to use `annotated-doc`\n\nYou are already comfortable with one of the existing docstring formats, like:\n\n* Sphinx\n* numpydoc\n* Google\n* Keras\n\nYour team is already comfortable using them.\n\nYou prefer having the documentation about parameters all together in a docstring, separated from the code defining them.\n\nYou care about a specific set of users, using one specific editor, and that editor already has support for the specific docstring format you use.\n\n## Reasons to use `annotated-doc`\n\n* No micro-syntax to learn for newcomers, it’s **just Python** syntax.\n* **Editing** would be already fully supported by default by any editor (current or future) supporting Python syntax, including syntax errors, syntax highlighting, etc.\n* **Rendering** would be relatively straightforward to implement by static tools (tools that don't need runtime execution), as the information can be extracted from the AST they normally already create.\n* **Deduplication of information**: the name of a parameter would be defined in a single place, not duplicated inside of a docstring.\n* **Elimination** of the possibility of having **inconsistencies** when removing a parameter or class variable and **forgetting to remove** its documentation.\n* **Minimization** of the probability of adding a new parameter or class variable and **forgetting to add its documentation**.\n* **Elimination** of the possibility of having **inconsistencies** between the **name** of a parameter in the **signature** and the name in the docstring when it is renamed.\n* **Access** to the documentation string for each symbol at **runtime**, including existing (older) Python versions.\n* A more formalized way to document other symbols, like type aliases, that could use Annotated.\n* **Support** for apps using FastAPI, Typer and others.\n* **AI Accessibility**: AI tools will have an easier way understanding each parameter as the distance from documentation to parameter is much closer.\n\n## History\n\nI ([@tiangolo](https://github.com/tiangolo)) originally wanted for this to be part of the Python standard library (in [PEP 727](https://peps.python.org/pep-0727/)), but the proposal was withdrawn as there was a fair amount of negative feedback and opposition.\n\nThe conclusion was that this was better done as an external effort, in a third-party library.\n\nSo, here it is, with a simpler approach, as a third-party library, in a way that can be used by others, starting with FastAPI and friends.\n\n## License\n\nThis project is licensed under the terms of the MIT license.\n" }, "metadata_location": "/opt/conda/lib/python3.10/site-packages/annotated_doc-0.0.4.dist-info", "installer": "pip", "requested": false }, { "metadata": { "metadata_version": "2.3", "name": "annotated-types", "version": "0.7.0", "summary": "Reusable constraint types to use with typing.Annotated", "description_content_type": "text/markdown", "author_email": "Adrian Garcia Badaracco <1755071+adriangb@users.noreply.github.com>, Samuel Colvin , Zac Hatfield-Dodds ", "classifier": [ "Development Status :: 4 - Beta", "Environment :: Console", "Environment :: MacOS X", "Intended Audience :: Developers", "Intended Audience :: Information Technology", "License :: OSI Approved :: MIT License", "Operating System :: POSIX :: Linux", "Operating System :: Unix", "Programming Language :: Python :: 3 :: Only", "Programming Language :: Python :: 3.8", "Programming Language :: Python :: 3.9", "Programming Language :: Python :: 3.10", "Programming Language :: Python :: 3.11", "Programming Language :: Python :: 3.12", "Topic :: Software Development :: Libraries :: Python Modules", "Typing :: Typed" ], "requires_dist": [ "typing-extensions>=4.0.0; python_version < '3.9'" ], "requires_python": ">=3.8", "project_url": [ "Homepage, https://github.com/annotated-types/annotated-types", "Source, https://github.com/annotated-types/annotated-types", "Changelog, https://github.com/annotated-types/annotated-types/releases" ], "description": "# annotated-types\n\n[![CI](https://github.com/annotated-types/annotated-types/workflows/CI/badge.svg?event=push)](https://github.com/annotated-types/annotated-types/actions?query=event%3Apush+branch%3Amain+workflow%3ACI)\n[![pypi](https://img.shields.io/pypi/v/annotated-types.svg)](https://pypi.python.org/pypi/annotated-types)\n[![versions](https://img.shields.io/pypi/pyversions/annotated-types.svg)](https://github.com/annotated-types/annotated-types)\n[![license](https://img.shields.io/github/license/annotated-types/annotated-types.svg)](https://github.com/annotated-types/annotated-types/blob/main/LICENSE)\n\n[PEP-593](https://peps.python.org/pep-0593/) added `typing.Annotated` as a way of\nadding context-specific metadata to existing types, and specifies that\n`Annotated[T, x]` _should_ be treated as `T` by any tool or library without special\nlogic for `x`.\n\nThis package provides metadata objects which can be used to represent common\nconstraints such as upper and lower bounds on scalar values and collection sizes,\na `Predicate` marker for runtime checks, and\ndescriptions of how we intend these metadata to be interpreted. In some cases,\nwe also note alternative representations which do not require this package.\n\n## Install\n\n```bash\npip install annotated-types\n```\n\n## Examples\n\n```python\nfrom typing import Annotated\nfrom annotated_types import Gt, Len, Predicate\n\nclass MyClass:\n age: Annotated[int, Gt(18)] # Valid: 19, 20, ...\n # Invalid: 17, 18, \"19\", 19.0, ...\n factors: list[Annotated[int, Predicate(is_prime)]] # Valid: 2, 3, 5, 7, 11, ...\n # Invalid: 4, 8, -2, 5.0, \"prime\", ...\n\n my_list: Annotated[list[int], Len(0, 10)] # Valid: [], [10, 20, 30, 40, 50]\n # Invalid: (1, 2), [\"abc\"], [0] * 20\n```\n\n## Documentation\n\n_While `annotated-types` avoids runtime checks for performance, users should not\nconstruct invalid combinations such as `MultipleOf(\"non-numeric\")` or `Annotated[int, Len(3)]`.\nDownstream implementors may choose to raise an error, emit a warning, silently ignore\na metadata item, etc., if the metadata objects described below are used with an\nincompatible type - or for any other reason!_\n\n### Gt, Ge, Lt, Le\n\nExpress inclusive and/or exclusive bounds on orderable values - which may be numbers,\ndates, times, strings, sets, etc. Note that the boundary value need not be of the\nsame type that was annotated, so long as they can be compared: `Annotated[int, Gt(1.5)]`\nis fine, for example, and implies that the value is an integer x such that `x > 1.5`.\n\nWe suggest that implementors may also interpret `functools.partial(operator.le, 1.5)`\nas being equivalent to `Gt(1.5)`, for users who wish to avoid a runtime dependency on\nthe `annotated-types` package.\n\nTo be explicit, these types have the following meanings:\n\n* `Gt(x)` - value must be \"Greater Than\" `x` - equivalent to exclusive minimum\n* `Ge(x)` - value must be \"Greater than or Equal\" to `x` - equivalent to inclusive minimum\n* `Lt(x)` - value must be \"Less Than\" `x` - equivalent to exclusive maximum\n* `Le(x)` - value must be \"Less than or Equal\" to `x` - equivalent to inclusive maximum\n\n### Interval\n\n`Interval(gt, ge, lt, le)` allows you to specify an upper and lower bound with a single\nmetadata object. `None` attributes should be ignored, and non-`None` attributes\ntreated as per the single bounds above.\n\n### MultipleOf\n\n`MultipleOf(multiple_of=x)` might be interpreted in two ways:\n\n1. Python semantics, implying `value % multiple_of == 0`, or\n2. [JSONschema semantics](https://json-schema.org/draft/2020-12/json-schema-validation.html#rfc.section.6.2.1),\n where `int(value / multiple_of) == value / multiple_of`.\n\nWe encourage users to be aware of these two common interpretations and their\ndistinct behaviours, especially since very large or non-integer numbers make\nit easy to cause silent data corruption due to floating-point imprecision.\n\nWe encourage libraries to carefully document which interpretation they implement.\n\n### MinLen, MaxLen, Len\n\n`Len()` implies that `min_length <= len(value) <= max_length` - lower and upper bounds are inclusive.\n\nAs well as `Len()` which can optionally include upper and lower bounds, we also\nprovide `MinLen(x)` and `MaxLen(y)` which are equivalent to `Len(min_length=x)`\nand `Len(max_length=y)` respectively.\n\n`Len`, `MinLen`, and `MaxLen` may be used with any type which supports `len(value)`.\n\nExamples of usage:\n\n* `Annotated[list, MaxLen(10)]` (or `Annotated[list, Len(max_length=10))`) - list must have a length of 10 or less\n* `Annotated[str, MaxLen(10)]` - string must have a length of 10 or less\n* `Annotated[list, MinLen(3))` (or `Annotated[list, Len(min_length=3))`) - list must have a length of 3 or more\n* `Annotated[list, Len(4, 6)]` - list must have a length of 4, 5, or 6\n* `Annotated[list, Len(8, 8)]` - list must have a length of exactly 8\n\n#### Changed in v0.4.0\n\n* `min_inclusive` has been renamed to `min_length`, no change in meaning\n* `max_exclusive` has been renamed to `max_length`, upper bound is now **inclusive** instead of **exclusive**\n* The recommendation that slices are interpreted as `Len` has been removed due to ambiguity and different semantic\n meaning of the upper bound in slices vs. `Len`\n\nSee [issue #23](https://github.com/annotated-types/annotated-types/issues/23) for discussion.\n\n### Timezone\n\n`Timezone` can be used with a `datetime` or a `time` to express which timezones\nare allowed. `Annotated[datetime, Timezone(None)]` must be a naive datetime.\n`Timezone[...]` ([literal ellipsis](https://docs.python.org/3/library/constants.html#Ellipsis))\nexpresses that any timezone-aware datetime is allowed. You may also pass a specific\ntimezone string or [`tzinfo`](https://docs.python.org/3/library/datetime.html#tzinfo-objects)\nobject such as `Timezone(timezone.utc)` or `Timezone(\"Africa/Abidjan\")` to express that you only\nallow a specific timezone, though we note that this is often a symptom of fragile design.\n\n#### Changed in v0.x.x\n\n* `Timezone` accepts [`tzinfo`](https://docs.python.org/3/library/datetime.html#tzinfo-objects) objects instead of\n `timezone`, extending compatibility to [`zoneinfo`](https://docs.python.org/3/library/zoneinfo.html) and third party libraries.\n\n### Unit\n\n`Unit(unit: str)` expresses that the annotated numeric value is the magnitude of\na quantity with the specified unit. For example, `Annotated[float, Unit(\"m/s\")]`\nwould be a float representing a velocity in meters per second.\n\nPlease note that `annotated_types` itself makes no attempt to parse or validate\nthe unit string in any way. That is left entirely to downstream libraries,\nsuch as [`pint`](https://pint.readthedocs.io) or\n[`astropy.units`](https://docs.astropy.org/en/stable/units/).\n\nAn example of how a library might use this metadata:\n\n```python\nfrom annotated_types import Unit\nfrom typing import Annotated, TypeVar, Callable, Any, get_origin, get_args\n\n# given a type annotated with a unit:\nMeters = Annotated[float, Unit(\"m\")]\n\n\n# you can cast the annotation to a specific unit type with any\n# callable that accepts a string and returns the desired type\nT = TypeVar(\"T\")\ndef cast_unit(tp: Any, unit_cls: Callable[[str], T]) -> T | None:\n if get_origin(tp) is Annotated:\n for arg in get_args(tp):\n if isinstance(arg, Unit):\n return unit_cls(arg.unit)\n return None\n\n\n# using `pint`\nimport pint\npint_unit = cast_unit(Meters, pint.Unit)\n\n\n# using `astropy.units`\nimport astropy.units as u\nastropy_unit = cast_unit(Meters, u.Unit)\n```\n\n### Predicate\n\n`Predicate(func: Callable)` expresses that `func(value)` is truthy for valid values.\nUsers should prefer the statically inspectable metadata above, but if you need\nthe full power and flexibility of arbitrary runtime predicates... here it is.\n\nFor some common constraints, we provide generic types:\n\n* `IsLower = Annotated[T, Predicate(str.islower)]`\n* `IsUpper = Annotated[T, Predicate(str.isupper)]`\n* `IsDigit = Annotated[T, Predicate(str.isdigit)]`\n* `IsFinite = Annotated[T, Predicate(math.isfinite)]`\n* `IsNotFinite = Annotated[T, Predicate(Not(math.isfinite))]`\n* `IsNan = Annotated[T, Predicate(math.isnan)]`\n* `IsNotNan = Annotated[T, Predicate(Not(math.isnan))]`\n* `IsInfinite = Annotated[T, Predicate(math.isinf)]`\n* `IsNotInfinite = Annotated[T, Predicate(Not(math.isinf))]`\n\nso that you can write e.g. `x: IsFinite[float] = 2.0` instead of the longer\n(but exactly equivalent) `x: Annotated[float, Predicate(math.isfinite)] = 2.0`.\n\nSome libraries might have special logic to handle known or understandable predicates,\nfor example by checking for `str.isdigit` and using its presence to both call custom\nlogic to enforce digit-only strings, and customise some generated external schema.\nUsers are therefore encouraged to avoid indirection like `lambda s: s.lower()`, in\nfavor of introspectable methods such as `str.lower` or `re.compile(\"pattern\").search`.\n\nTo enable basic negation of commonly used predicates like `math.isnan` without introducing introspection that makes it impossible for implementers to introspect the predicate we provide a `Not` wrapper that simply negates the predicate in an introspectable manner. Several of the predicates listed above are created in this manner.\n\nWe do not specify what behaviour should be expected for predicates that raise\nan exception. For example `Annotated[int, Predicate(str.isdigit)]` might silently\nskip invalid constraints, or statically raise an error; or it might try calling it\nand then propagate or discard the resulting\n`TypeError: descriptor 'isdigit' for 'str' objects doesn't apply to a 'int' object`\nexception. We encourage libraries to document the behaviour they choose.\n\n### Doc\n\n`doc()` can be used to add documentation information in `Annotated`, for function and method parameters, variables, class attributes, return types, and any place where `Annotated` can be used.\n\nIt expects a value that can be statically analyzed, as the main use case is for static analysis, editors, documentation generators, and similar tools.\n\nIt returns a `DocInfo` class with a single attribute `documentation` containing the value passed to `doc()`.\n\nThis is the early adopter's alternative form of the [`typing-doc` proposal](https://github.com/tiangolo/fastapi/blob/typing-doc/typing_doc.md).\n\n### Integrating downstream types with `GroupedMetadata`\n\nImplementers may choose to provide a convenience wrapper that groups multiple pieces of metadata.\nThis can help reduce verbosity and cognitive overhead for users.\nFor example, an implementer like Pydantic might provide a `Field` or `Meta` type that accepts keyword arguments and transforms these into low-level metadata:\n\n```python\nfrom dataclasses import dataclass\nfrom typing import Iterator\nfrom annotated_types import GroupedMetadata, Ge\n\n@dataclass\nclass Field(GroupedMetadata):\n ge: int | None = None\n description: str | None = None\n\n def __iter__(self) -> Iterator[object]:\n # Iterating over a GroupedMetadata object should yield annotated-types\n # constraint metadata objects which describe it as fully as possible,\n # and may include other unknown objects too.\n if self.ge is not None:\n yield Ge(self.ge)\n if self.description is not None:\n yield Description(self.description)\n```\n\nLibraries consuming annotated-types constraints should check for `GroupedMetadata` and unpack it by iterating over the object and treating the results as if they had been \"unpacked\" in the `Annotated` type. The same logic should be applied to the [PEP 646 `Unpack` type](https://peps.python.org/pep-0646/), so that `Annotated[T, Field(...)]`, `Annotated[T, Unpack[Field(...)]]` and `Annotated[T, *Field(...)]` are all treated consistently.\n\nLibraries consuming annotated-types should also ignore any metadata they do not recongize that came from unpacking a `GroupedMetadata`, just like they ignore unrecognized metadata in `Annotated` itself.\n\nOur own `annotated_types.Interval` class is a `GroupedMetadata` which unpacks itself into `Gt`, `Lt`, etc., so this is not an abstract concern. Similarly, `annotated_types.Len` is a `GroupedMetadata` which unpacks itself into `MinLen` (optionally) and `MaxLen`.\n\n### Consuming metadata\n\nWe intend to not be prescriptive as to _how_ the metadata and constraints are used, but as an example of how one might parse constraints from types annotations see our [implementation in `test_main.py`](https://github.com/annotated-types/annotated-types/blob/f59cf6d1b5255a0fe359b93896759a180bec30ae/tests/test_main.py#L94-L103).\n\nIt is up to the implementer to determine how this metadata is used.\nYou could use the metadata for runtime type checking, for generating schemas or to generate example data, amongst other use cases.\n\n## Design & History\n\nThis package was designed at the PyCon 2022 sprints by the maintainers of Pydantic\nand Hypothesis, with the goal of making it as easy as possible for end-users to\nprovide more informative annotations for use by runtime libraries.\n\nIt is deliberately minimal, and following PEP-593 allows considerable downstream\ndiscretion in what (if anything!) they choose to support. Nonetheless, we expect\nthat staying simple and covering _only_ the most common use-cases will give users\nand maintainers the best experience we can. If you'd like more constraints for your\ntypes - follow our lead, by defining them and documenting them downstream!\n" }, "metadata_location": "/opt/conda/lib/python3.10/site-packages/annotated_types-0.7.0.dist-info", "installer": "pip", "requested": false }, { "metadata": { "metadata_version": "2.1", "name": "antlr4-python3-runtime", "version": "4.9.3", "summary": "ANTLR 4.9.3 runtime for Python 3.7", "home_page": "http://www.antlr.org", "author": "Eric Vergnaud, Terence Parr, Sam Harwell", "author_email": "eric.vergnaud@wanadoo.fr", "license": "BSD", "requires_dist": [ "typing; python_version < \"3.5\"" ] }, "metadata_location": "/opt/conda/lib/python3.10/site-packages/antlr4_python3_runtime-4.9.3.dist-info", "installer": "pip", "requested": false }, { "metadata": { "metadata_version": "2.4", "name": "anyio", "version": "4.13.0", "dynamic": [ "license-file" ], "summary": "High-level concurrency and networking framework on top of asyncio or Trio", "description_content_type": "text/x-rst", "author_email": "Alex Grönholm ", "classifier": [ "Development Status :: 5 - Production/Stable", "Intended Audience :: Developers", "Framework :: AnyIO", "Typing :: Typed", "Programming Language :: Python", "Programming Language :: Python :: 3", "Programming Language :: Python :: 3.10", "Programming Language :: Python :: 3.11", "Programming Language :: Python :: 3.12", "Programming Language :: Python :: 3.13", "Programming Language :: Python :: 3.14" ], "requires_dist": [ "exceptiongroup>=1.0.2; python_version < \"3.11\"", "idna>=2.8", "typing_extensions>=4.5; python_version < \"3.13\"", "trio>=0.32.0; extra == \"trio\"" ], "requires_python": ">=3.10", "project_url": [ "Documentation, https://anyio.readthedocs.io/en/latest/", "Changelog, https://anyio.readthedocs.io/en/stable/versionhistory.html", "Source code, https://github.com/agronholm/anyio", "Issue tracker, https://github.com/agronholm/anyio/issues" ], "provides_extra": [ "trio" ], "description": ".. image:: https://github.com/agronholm/anyio/actions/workflows/test.yml/badge.svg\n :target: https://github.com/agronholm/anyio/actions/workflows/test.yml\n :alt: Build Status\n.. image:: https://coveralls.io/repos/github/agronholm/anyio/badge.svg?branch=master\n :target: https://coveralls.io/github/agronholm/anyio?branch=master\n :alt: Code Coverage\n.. image:: https://readthedocs.org/projects/anyio/badge/?version=latest\n :target: https://anyio.readthedocs.io/en/latest/?badge=latest\n :alt: Documentation\n.. image:: https://badges.gitter.im/gitterHQ/gitter.svg\n :target: https://gitter.im/python-trio/AnyIO\n :alt: Gitter chat\n.. image:: https://tidelift.com/badges/package/pypi/anyio\n :target: https://tidelift.com/subscription/pkg/pypi-anyio\n :alt: Tidelift\n\nAnyIO is an asynchronous networking and concurrency library that works on top of either asyncio_ or\nTrio_. It implements Trio-like `structured concurrency`_ (SC) on top of asyncio and works in harmony\nwith the native SC of Trio itself.\n\nApplications and libraries written against AnyIO's API will run unmodified on either asyncio_ or\nTrio_. AnyIO can also be adopted into a library or application incrementally – bit by bit, no full\nrefactoring necessary. It will blend in with the native libraries of your chosen backend.\n\nTo find out why you might want to use AnyIO's APIs instead of asyncio's, you can read about it\n`here `_.\n\nDocumentation\n-------------\n\nView full documentation at: https://anyio.readthedocs.io/\n\nFeatures\n--------\n\nAnyIO offers the following functionality:\n\n* Task groups (nurseries_ in trio terminology)\n* High-level networking (TCP, UDP and UNIX sockets)\n\n * `Happy eyeballs`_ algorithm for TCP connections (more robust than that of asyncio on Python\n 3.8)\n * async/await style UDP sockets (unlike asyncio where you still have to use Transports and\n Protocols)\n\n* A versatile API for byte streams and object streams\n* Inter-task synchronization and communication (locks, conditions, events, semaphores, object\n streams)\n* Worker threads\n* Subprocesses\n* Subinterpreter support for code parallelization (on Python 3.13 and later)\n* Asynchronous file I/O (using worker threads)\n* Signal handling\n* Asynchronous version of the functools_ module\n\nAnyIO also comes with its own pytest_ plugin which also supports asynchronous fixtures.\nIt even works with the popular Hypothesis_ library.\n\n.. _asyncio: https://docs.python.org/3/library/asyncio.html\n.. _Trio: https://github.com/python-trio/trio\n.. _structured concurrency: https://en.wikipedia.org/wiki/Structured_concurrency\n.. _nurseries: https://trio.readthedocs.io/en/stable/reference-core.html#nurseries-and-spawning\n.. _Happy eyeballs: https://en.wikipedia.org/wiki/Happy_Eyeballs\n.. _pytest: https://docs.pytest.org/en/latest/\n.. _functools: https://docs.python.org/3/library/functools.html\n.. _Hypothesis: https://hypothesis.works/\n\nSecurity contact information\n----------------------------\n\nTo report a security vulnerability, please use the `Tidelift security contact`_.\nTidelift will coordinate the fix and disclosure.\n\n.. _Tidelift security contact: https://tidelift.com/security\n" }, "metadata_location": "/opt/conda/lib/python3.10/site-packages/anyio-4.13.0.dist-info", "installer": "pip", "requested": false }, { "metadata": { "metadata_version": "2.1", "name": "apex", "version": "0.1", "summary": "PyTorch Extensions written by NVIDIA", "requires_dist": [ "packaging>20.6" ] }, "metadata_location": "/opt/conda/lib/python3.10/site-packages/apex-0.1.dist-info", "direct_url": { "url": "http://antsys-hcsfaas-images-dev.cn-heyuan-alipay-office.oss-alipay.aliyuncs.com/404089/apex-0.1-cp310-cp310-linux_x86_64.whl", "archive_info": { "hash": "sha256=b147b1c016e11badd6003e32df91810e7431bfda64afacdc3f6c9908daa23ddb", "hashes": { "sha256": "b147b1c016e11badd6003e32df91810e7431bfda64afacdc3f6c9908daa23ddb" } } }, "installer": "pip", "requested": true }, { "metadata": { "metadata_version": "2.1", "name": "archspec", "version": "0.2.3", "summary": "A library to query system architecture", "description_content_type": "text/markdown", "home_page": "https://github.com/archspec/archspec", "author": "archspec developers", "author_email": "maintainers@spack.io", "maintainer": "Greg Becker", "maintainer_email": "maintainers@spack.io", "license": "Apache-2.0 OR MIT", "classifier": [ "Development Status :: 3 - Alpha", "Intended Audience :: Developers", "Intended Audience :: Information Technology", "Intended Audience :: Science/Research", "License :: Other/Proprietary License", "Operating System :: MacOS", "Operating System :: POSIX :: Linux", "Operating System :: Unix", "Programming Language :: Python :: 3", "Programming Language :: Python :: 3.7", "Programming Language :: Python :: 3.8", "Programming Language :: Python :: 3.9", "Programming Language :: Python :: 3.10", "Programming Language :: Python :: 3.11" ], "requires_python": ">=3.6, !=2.7.*, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*", "project_url": [ "Documentation, https://archspec.readthedocs.io", "Repository, https://github.com/archspec/archspec.git" ], "description": "# Archspec (Python bindings)\n\n[![CI](https://github.com/archspec/archspec/workflows/Unit%20tests/badge.svg)](https://github.com/archspec/archspec/actions)\n[![CodeCov](https://codecov.io/gh/archspec/archspec/branch/master/graph/badge.svg)](https://codecov.io/gh/archspec/archspec)\n[![Documentation Status](https://readthedocs.org/projects/archspec/badge/?version=latest)](https://archspec.readthedocs.io/en/latest/?badge=latest)\n\nArchspec aims at providing a standard set of human-understandable labels for\nvarious aspects of a system architecture like CPU, network fabrics, etc. and\nAPIs to detect, query and compare them.\n\nThis project grew out of [Spack](https://spack.io/) and is currently under\nactive development. At present it supports APIs to detect and model\ncompatibility relationships among different CPU microarchitectures.\n\n## Getting started with development\n\nThe `archspec` Python package needs [poetry](https://python-poetry.org/) to\nbe installed from VCS sources. The preferred method to install it is via\nits custom installer outside of any virtual environment:\n\n```console\ncurl -sSL https://install.python-poetry.org | python3 -\n```\n\nYou can refer to [Poetry's documentation](https://python-poetry.org/docs/#installation)\nfor further details or for other methods to install this tool. You'll also need `tox`\nto run unit test:\n\n```console\npip install --user tox\n```\n\nFinally, you'll need to clone the repository:\n\n```console\ngit clone --recursive https://github.com/archspec/archspec.git\n```\n\n### Running unit tests\n\nOnce you have your environment ready you can run `archspec` unit tests\nusing ``tox`` from the root of the repository:\n\n```console\n$ tox\n [ ... ]\n py27: commands succeeded\n py35: commands succeeded\n py36: commands succeeded\n py37: commands succeeded\n py38: commands succeeded\n pylint: commands succeeded\n flake8: commands succeeded\n black: commands succeeded\n congratulations :)\n```\n\n## Citing Archspec\n\nIf you are referencing `archspec` in a publication, please cite the following\npaper:\n\n* Massimiliano Culpo, Gregory Becker, Carlos Eduardo Arango Gutierrez, Kenneth\n Hoste, and Todd Gamblin.\n [**`archspec`: A library for detecting, labeling, and reasoning about\n microarchitectures**](https://tgamblin.github.io/pubs/archspec-canopie-hpc-2020.pdf).\n In *2nd International Workshop on Containers and New Orchestration Paradigms\n for Isolated Environments in HPC (CANOPIE-HPC'20)*, Online Event, November\n 12, 2020.\n\n## License\n\nArchspec is distributed under the terms of both the MIT license and the\nApache License (Version 2.0). Users may choose either license, at their\noption.\n\nAll new contributions must be made under both the MIT and Apache-2.0\nlicenses.\n\nSee [LICENSE-MIT](https://github.com/archspec/archspec/blob/master/LICENSE-MIT),\n[LICENSE-APACHE](https://github.com/archspec/archspec/blob/master/LICENSE-APACHE),\n[COPYRIGHT](https://github.com/archspec/archspec/blob/master/COPYRIGHT), and\n[NOTICE](https://github.com/archspec/archspec/blob/master/NOTICE) for details.\n\nSPDX-License-Identifier: (Apache-2.0 OR MIT)\n\nLLNL-CODE-811653\n\n" }, "metadata_location": "/opt/conda/lib/python3.10/site-packages/archspec-0.2.3.dist-info", "direct_url": { "url": "file:///croot/archspec_1709217642129/work", "dir_info": {} }, "installer": "conda", "requested": true }, { "metadata": { "metadata_version": "2.1", "name": "asttokens", "version": "2.0.5", "platform": [ "UNKNOWN" ], "summary": "Annotate AST trees with source code positions", "keywords": [ "code", "ast", "parse", "tokenize", "refactor" ], "home_page": "https://github.com/gristlabs/asttokens", "author": "Dmitry Sagalovskiy, Grist Labs", "author_email": "dmitry@getgrist.com", "license": "Apache 2.0", "classifier": [ "Development Status :: 5 - Production/Stable", "Intended Audience :: Developers", "Topic :: Software Development :: Libraries :: Python Modules", "Topic :: Software Development :: Code Generators", "Topic :: Software Development :: Compilers", "Topic :: Software Development :: Interpreters", "Topic :: Software Development :: Pre-processors", "Environment :: Console", "Operating System :: OS Independent", "Programming Language :: Python :: 2", "Programming Language :: Python :: 2.7", "Programming Language :: Python :: 3", "Programming Language :: Python :: 3.5", "Programming Language :: Python :: 3.6", "Programming Language :: Python :: 3.7", "Programming Language :: Python :: 3.8", "Programming Language :: Python :: 3.9", "Programming Language :: Python :: Implementation :: CPython", "Programming Language :: Python :: Implementation :: PyPy" ], "requires_dist": [ "six", "astroid ; extra == 'test'", "pytest ; extra == 'test'" ], "provides_extra": [ "test" ], "description": "ASTTokens\n=========\n\n.. image:: https://img.shields.io/pypi/v/asttokens.svg\n :target: https://pypi.python.org/pypi/asttokens/\n.. image:: https://img.shields.io/pypi/pyversions/asttokens.svg\n :target: https://pypi.python.org/pypi/asttokens/\n.. image:: https://travis-ci.org/gristlabs/asttokens.svg?branch=master\n :target: https://travis-ci.org/gristlabs/asttokens\n.. image:: https://readthedocs.org/projects/asttokens/badge/?version=latest\n :target: http://asttokens.readthedocs.io/en/latest/index.html\n.. image:: https://coveralls.io/repos/github/gristlabs/asttokens/badge.svg\n :target: https://coveralls.io/github/gristlabs/asttokens\n\n.. Start of user-guide\n\nThe ``asttokens`` module annotates Python abstract syntax trees (ASTs) with the positions of tokens\nand text in the source code that generated them.\n\nIt makes it possible for tools that work with logical AST nodes to find the particular text that\nresulted in those nodes, for example for automated refactoring or highlighting.\n\nInstallation\n------------\nasttokens is available on PyPI: https://pypi.python.org/pypi/asttokens/::\n\n pip install asttokens\n\nThe code is on GitHub: https://github.com/gristlabs/asttokens.\n\nThe API Reference is here: http://asttokens.readthedocs.io/en/latest/api-index.html.\n\nUsage\n-----\nASTTokens works with both Python2 and Python3.\n\nASTTokens can annotate both trees built by `ast `_,\nAND those built by `astroid `_.\n\nHere's an example:\n\n.. code-block:: python\n\n import asttokens, ast\n source = \"Robot('blue').walk(steps=10*n)\"\n atok = asttokens.ASTTokens(source, parse=True)\n\nOnce the tree has been marked, nodes get ``.first_token``, ``.last_token`` attributes, and\nthe ``ASTTokens`` object offers helpful methods:\n\n.. code-block:: python\n\n attr_node = next(n for n in ast.walk(atok.tree) if isinstance(n, ast.Attribute))\n print(atok.get_text(attr_node))\n start, end = attr_node.last_token.startpos, attr_node.last_token.endpos\n print(atok.text[:start] + 'RUN' + atok.text[end:])\n\nWhich produces this output:\n\n.. code-block:: text\n\n Robot('blue').walk\n Robot('blue').RUN(steps=10*n)\n\nThe ``ASTTokens`` object also offers methods to walk and search the list of tokens that make up\nthe code (or a particular AST node), which is more useful and powerful than dealing with the text\ndirectly.\n\n\nContribute\n----------\n\nTo contribute:\n\n1. Fork this repository, and clone your fork.\n2. Install the package with test dependencies (ideally in a virtualenv) with::\n\n pip install -e '.[test]'\n\n3. Run tests in your current interpreter with the command ``pytest`` or ``python -m pytest``.\n4. Run tests across all supported interpreters with the ``tox`` command. You will need to have the interpreters installed separately. We recommend ``pyenv`` for that. Use ``tox -p auto`` to run the tests in parallel.\n5. By default certain tests which take a very long time to run are skipped, but they are run on travis CI. To run them locally, set the environment variable ``ASTTOKENS_SLOW_TESTS``. For example run ``ASTTOKENS_SLOW_TESTS=1 tox`` to run the full suite of tests.\n\n\n" }, "metadata_location": "/opt/conda/lib/python3.10/site-packages/asttokens-2.0.5.dist-info", "direct_url": { "url": "file:///opt/conda/conda-bld/asttokens_1646925590279/work", "dir_info": {} }, "installer": "conda", "requested": true }, { "metadata": { "metadata_version": "2.1", "name": "async-timeout", "version": "5.0.1", "summary": "Timeout context manager for asyncio programs", "description_content_type": "text/x-rst", "home_page": "https://github.com/aio-libs/async-timeout", "author": "Andrew Svetlov ", "author_email": "andrew.svetlov@gmail.com", "license": "Apache 2", "classifier": [ "Development Status :: 5 - Production/Stable", "Topic :: Software Development :: Libraries", "Framework :: AsyncIO", "Intended Audience :: Developers", "License :: OSI Approved :: Apache Software License", "Programming Language :: Python", "Programming Language :: Python :: 3", "Programming Language :: Python :: 3 :: Only" ], "requires_python": ">=3.8", "project_url": [ "Chat: Gitter, https://gitter.im/aio-libs/Lobby", "CI: GitHub Actions, https://github.com/aio-libs/async-timeout/actions", "Coverage: codecov, https://codecov.io/github/aio-libs/async-timeout", "GitHub: issues, https://github.com/aio-libs/async-timeout/issues", "GitHub: repo, https://github.com/aio-libs/async-timeout" ], "description": "async-timeout\n=============\n.. image:: https://travis-ci.com/aio-libs/async-timeout.svg?branch=master\n :target: https://travis-ci.com/aio-libs/async-timeout\n.. image:: https://codecov.io/gh/aio-libs/async-timeout/branch/master/graph/badge.svg\n :target: https://codecov.io/gh/aio-libs/async-timeout\n.. image:: https://img.shields.io/pypi/v/async-timeout.svg\n :target: https://pypi.python.org/pypi/async-timeout\n.. image:: https://badges.gitter.im/Join%20Chat.svg\n :target: https://gitter.im/aio-libs/Lobby\n :alt: Chat on Gitter\n\nasyncio-compatible timeout context manager.\n\n\n\nDEPRECATED\n----------\n\nThis library has effectively been upstreamed into Python 3.11+.\n\nTherefore this library is considered deprecated and no longer actively supported.\n\nVersion 5.0+ provides dual-mode when executed on Python 3.11+:\n``asyncio_timeout.Timeout`` is fully compatible with ``asyncio.Timeout`` *and* old\nversions of the library.\n\nAnyway, using upstream is highly recommended. ``asyncio_timeout`` exists only for the\nsake of backward compatibility, easy supporting both old and new Python by the same\ncode, and easy misgration.\n\nIf rescheduling API is not important and only ``async with timeout(...): ...`` functionality is required,\na user could apply conditional import::\n\n if sys.version_info >= (3, 11):\n from asyncio import timeout, timeout_at\n else:\n from async_timeout import timeout, timeout_at\n\n\nUsage example\n-------------\n\n\nThe context manager is useful in cases when you want to apply timeout\nlogic around block of code or in cases when ``asyncio.wait_for()`` is\nnot suitable. Also it's much faster than ``asyncio.wait_for()``\nbecause ``timeout`` doesn't create a new task.\n\nThe ``timeout(delay, *, loop=None)`` call returns a context manager\nthat cancels a block on *timeout* expiring::\n\n from async_timeout import timeout\n async with timeout(1.5):\n await inner()\n\n1. If ``inner()`` is executed faster than in ``1.5`` seconds nothing\n happens.\n2. Otherwise ``inner()`` is cancelled internally by sending\n ``asyncio.CancelledError`` into but ``asyncio.TimeoutError`` is\n raised outside of context manager scope.\n\n*timeout* parameter could be ``None`` for skipping timeout functionality.\n\n\nAlternatively, ``timeout_at(when)`` can be used for scheduling\nat the absolute time::\n\n loop = asyncio.get_event_loop()\n now = loop.time()\n\n async with timeout_at(now + 1.5):\n await inner()\n\n\nPlease note: it is not POSIX time but a time with\nundefined starting base, e.g. the time of the system power on.\n\n\nContext manager has ``.expired()`` / ``.expired`` for check if timeout happens\nexactly in context manager::\n\n async with timeout(1.5) as cm:\n await inner()\n print(cm.expired()) # recommended api\n print(cm.expired) # compatible api\n\nThe property is ``True`` if ``inner()`` execution is cancelled by\ntimeout context manager.\n\nIf ``inner()`` call explicitly raises ``TimeoutError`` ``cm.expired``\nis ``False``.\n\nThe scheduled deadline time is available as ``.when()`` / ``.deadline``::\n\n async with timeout(1.5) as cm:\n cm.when() # recommended api\n cm.deadline # compatible api\n\nNot finished yet timeout can be rescheduled by ``shift()``\nor ``update()`` methods::\n\n async with timeout(1.5) as cm:\n # recommended api\n cm.reschedule(cm.when() + 1) # add another second on waiting\n # compatible api\n cm.shift(1) # add another second on waiting\n cm.update(loop.time() + 5) # reschedule to now+5 seconds\n\nRescheduling is forbidden if the timeout is expired or after exit from ``async with``\ncode block.\n\n\nDisable scheduled timeout::\n\n async with timeout(1.5) as cm:\n cm.reschedule(None) # recommended api\n cm.reject() # compatible api\n\n\n\nInstallation\n------------\n\n::\n\n $ pip install async-timeout\n\nThe library is Python 3 only!\n\n\n\nAuthors and License\n-------------------\n\nThe module is written by Andrew Svetlov.\n\nIt's *Apache 2* licensed and freely available.\n" }, "metadata_location": "/opt/conda/lib/python3.10/site-packages/async_timeout-5.0.1.dist-info", "installer": "pip", "requested": false }, { "metadata": { "metadata_version": "2.3", "name": "attrs", "version": "24.2.0", "summary": "Classes Without Boilerplate", "description_content_type": "text/markdown", "keywords": [ "attribute", "boilerplate", "class" ], "author_email": "Hynek Schlawack ", "classifier": [ "Development Status :: 5 - Production/Stable", "License :: OSI Approved :: MIT License", "Programming Language :: Python :: 3.7", "Programming Language :: Python :: 3.8", "Programming Language :: Python :: 3.9", "Programming Language :: Python :: 3.10", "Programming Language :: Python :: 3.11", "Programming Language :: Python :: 3.12", "Programming Language :: Python :: 3.13", "Programming Language :: Python :: Implementation :: CPython", "Programming Language :: Python :: Implementation :: PyPy", "Typing :: Typed" ], "requires_dist": [ "importlib-metadata; python_version < '3.8'", "cloudpickle; (platform_python_implementation == 'CPython') and extra == 'benchmark'", "hypothesis; extra == 'benchmark'", "mypy>=1.11.1; (platform_python_implementation == 'CPython' and python_version >= '3.9') and extra == 'benchmark'", "pympler; extra == 'benchmark'", "pytest-codspeed; extra == 'benchmark'", "pytest-mypy-plugins; (platform_python_implementation == 'CPython' and python_version >= '3.9' and python_version < '3.13') and extra == 'benchmark'", "pytest-xdist[psutil]; extra == 'benchmark'", "pytest>=4.3.0; extra == 'benchmark'", "cloudpickle; (platform_python_implementation == 'CPython') and extra == 'cov'", "coverage[toml]>=5.3; extra == 'cov'", "hypothesis; extra == 'cov'", "mypy>=1.11.1; (platform_python_implementation == 'CPython' and python_version >= '3.9') and extra == 'cov'", "pympler; extra == 'cov'", "pytest-mypy-plugins; (platform_python_implementation == 'CPython' and python_version >= '3.9' and python_version < '3.13') and extra == 'cov'", "pytest-xdist[psutil]; extra == 'cov'", "pytest>=4.3.0; extra == 'cov'", "cloudpickle; (platform_python_implementation == 'CPython') and extra == 'dev'", "hypothesis; extra == 'dev'", "mypy>=1.11.1; (platform_python_implementation == 'CPython' and python_version >= '3.9') and extra == 'dev'", "pre-commit; extra == 'dev'", "pympler; extra == 'dev'", "pytest-mypy-plugins; (platform_python_implementation == 'CPython' and python_version >= '3.9' and python_version < '3.13') and extra == 'dev'", "pytest-xdist[psutil]; extra == 'dev'", "pytest>=4.3.0; extra == 'dev'", "cogapp; extra == 'docs'", "furo; extra == 'docs'", "myst-parser; extra == 'docs'", "sphinx; extra == 'docs'", "sphinx-notfound-page; extra == 'docs'", "sphinxcontrib-towncrier; extra == 'docs'", "towncrier<24.7; extra == 'docs'", "cloudpickle; (platform_python_implementation == 'CPython') and extra == 'tests'", "hypothesis; extra == 'tests'", "mypy>=1.11.1; (platform_python_implementation == 'CPython' and python_version >= '3.9') and extra == 'tests'", "pympler; extra == 'tests'", "pytest-mypy-plugins; (platform_python_implementation == 'CPython' and python_version >= '3.9' and python_version < '3.13') and extra == 'tests'", "pytest-xdist[psutil]; extra == 'tests'", "pytest>=4.3.0; extra == 'tests'", "mypy>=1.11.1; (platform_python_implementation == 'CPython' and python_version >= '3.9') and extra == 'tests-mypy'", "pytest-mypy-plugins; (platform_python_implementation == 'CPython' and python_version >= '3.9' and python_version < '3.13') and extra == 'tests-mypy'" ], "requires_python": ">=3.7", "project_url": [ "Documentation, https://www.attrs.org/", "Changelog, https://www.attrs.org/en/stable/changelog.html", "GitHub, https://github.com/python-attrs/attrs", "Funding, https://github.com/sponsors/hynek", "Tidelift, https://tidelift.com/subscription/pkg/pypi-attrs?utm_source=pypi-attrs&utm_medium=pypi" ], "provides_extra": [ "benchmark", "cov", "dev", "docs", "tests", "tests-mypy" ], "description": "

\n \n \"attrs\"\n \n

\n\n\n*attrs* is the Python package that will bring back the **joy** of **writing classes** by relieving you from the drudgery of implementing object protocols (aka [dunder methods](https://www.attrs.org/en/latest/glossary.html#term-dunder-methods)).\n[Trusted by NASA](https://docs.github.com/en/account-and-profile/setting-up-and-managing-your-github-profile/customizing-your-profile/personalizing-your-profile#list-of-qualifying-repositories-for-mars-2020-helicopter-contributor-achievement) for Mars missions since 2020!\n\nIts main goal is to help you to write **concise** and **correct** software without slowing down your code.\n\n\n## Sponsors\n\n*attrs* would not be possible without our [amazing sponsors](https://github.com/sponsors/hynek).\nEspecially those generously supporting us at the *The Organization* tier and higher:\n\n\n\n

\n\n\n\n\n\n\n\n\n

\n\n\n\n

\n Please consider joining them to help make attrs’s maintenance more sustainable!\n

\n\n\n\n## Example\n\n*attrs* gives you a class decorator and a way to declaratively define the attributes on that class:\n\n\n\n```pycon\n>>> from attrs import asdict, define, make_class, Factory\n\n>>> @define\n... class SomeClass:\n... a_number: int = 42\n... list_of_numbers: list[int] = Factory(list)\n...\n... def hard_math(self, another_number):\n... return self.a_number + sum(self.list_of_numbers) * another_number\n\n\n>>> sc = SomeClass(1, [1, 2, 3])\n>>> sc\nSomeClass(a_number=1, list_of_numbers=[1, 2, 3])\n\n>>> sc.hard_math(3)\n19\n>>> sc == SomeClass(1, [1, 2, 3])\nTrue\n>>> sc != SomeClass(2, [3, 2, 1])\nTrue\n\n>>> asdict(sc)\n{'a_number': 1, 'list_of_numbers': [1, 2, 3]}\n\n>>> SomeClass()\nSomeClass(a_number=42, list_of_numbers=[])\n\n>>> C = make_class(\"C\", [\"a\", \"b\"])\n>>> C(\"foo\", \"bar\")\nC(a='foo', b='bar')\n```\n\nAfter *declaring* your attributes, *attrs* gives you:\n\n- a concise and explicit overview of the class's attributes,\n- a nice human-readable `__repr__`,\n- equality-checking methods,\n- an initializer,\n- and much more,\n\n*without* writing dull boilerplate code again and again and *without* runtime performance penalties.\n\n---\n\nThis example uses *attrs*'s modern APIs that have been introduced in version 20.1.0, and the *attrs* package import name that has been added in version 21.3.0.\nThe classic APIs (`@attr.s`, `attr.ib`, plus their serious-business aliases) and the `attr` package import name will remain **indefinitely**.\n\nCheck out [*On The Core API Names*](https://www.attrs.org/en/latest/names.html) for an in-depth explanation!\n\n\n### Hate Type Annotations!?\n\nNo problem!\nTypes are entirely **optional** with *attrs*.\nSimply assign `attrs.field()` to the attributes instead of annotating them with types:\n\n```python\nfrom attrs import define, field\n\n@define\nclass SomeClass:\n a_number = field(default=42)\n list_of_numbers = field(factory=list)\n```\n\n\n## Data Classes\n\nOn the tin, *attrs* might remind you of `dataclasses` (and indeed, `dataclasses` [are a descendant](https://hynek.me/articles/import-attrs/) of *attrs*).\nIn practice it does a lot more and is more flexible.\nFor instance, it allows you to define [special handling of NumPy arrays for equality checks](https://www.attrs.org/en/stable/comparison.html#customization), allows more ways to [plug into the initialization process](https://www.attrs.org/en/stable/init.html#hooking-yourself-into-initialization), has a replacement for `__init_subclass__`, and allows for stepping through the generated methods using a debugger.\n\nFor more details, please refer to our [comparison page](https://www.attrs.org/en/stable/why.html#data-classes), but generally speaking, we are more likely to commit crimes against nature to make things work that one would expect to work, but that are quite complicated in practice.\n\n\n## Project Information\n\n- [**Changelog**](https://www.attrs.org/en/stable/changelog.html)\n- [**Documentation**](https://www.attrs.org/)\n- [**PyPI**](https://pypi.org/project/attrs/)\n- [**Source Code**](https://github.com/python-attrs/attrs)\n- [**Contributing**](https://github.com/python-attrs/attrs/blob/main/.github/CONTRIBUTING.md)\n- [**Third-party Extensions**](https://github.com/python-attrs/attrs/wiki/Extensions-to-attrs)\n- **Get Help**: use the `python-attrs` tag on [Stack Overflow](https://stackoverflow.com/questions/tagged/python-attrs)\n\n\n### *attrs* for Enterprise\n\nAvailable as part of the Tidelift Subscription.\n\nThe maintainers of *attrs* and thousands of other packages are working with Tidelift to deliver commercial support and maintenance for the open source packages you use to build your applications.\nSave time, reduce risk, and improve code health, while paying the maintainers of the exact packages you use.\n[Learn more](https://tidelift.com/?utm_source=lifter&utm_medium=referral&utm_campaign=hynek).\n\n## Release Information\n\n### Deprecations\n\n- Given the amount of warnings raised in the broader ecosystem, we've decided to only soft-deprecate the *hash* argument to `@define` / `@attr.s`.\n Please don't use it in new code, but we don't intend to remove it anymore.\n [#1330](https://github.com/python-attrs/attrs/issues/1330)\n\n\n### Changes\n\n- `attrs.converters.pipe()` (and its syntactic sugar of passing a list for `attrs.field()`'s / `attr.ib()`'s *converter* argument) works again when passing `attrs.setters.convert` to *on_setattr* (which is default for `attrs.define`).\n [#1328](https://github.com/python-attrs/attrs/issues/1328)\n- Restored support for PEP [649](https://peps.python.org/pep-0649/) / [749](https://peps.python.org/pep-0749/)-implementing Pythons -- currently 3.14-dev.\n [#1329](https://github.com/python-attrs/attrs/issues/1329)\n\n\n\n---\n\n[Full changelog →](https://www.attrs.org/en/stable/changelog.html)\n" }, "metadata_location": "/opt/conda/lib/python3.10/site-packages/attrs-24.2.0.dist-info", "direct_url": { "url": "file:///croot/attrs_1729089401488/work", "dir_info": {} }, "installer": "conda", "requested": true }, { "metadata": { "metadata_version": "2.1", "name": "babel", "version": "2.16.0", "summary": "Internationalization utilities", "home_page": "https://babel.pocoo.org/", "author": "Armin Ronacher", "author_email": "armin.ronacher@active-4.com", "maintainer": "Aarni Koskela", "maintainer_email": "akx@iki.fi", "license": "BSD-3-Clause", "classifier": [ "Development Status :: 5 - Production/Stable", "Environment :: Web Environment", "Intended Audience :: Developers", "License :: OSI Approved :: BSD License", "Operating System :: OS Independent", "Programming Language :: Python", "Programming Language :: Python :: 3", "Programming Language :: Python :: 3 :: Only", "Programming Language :: Python :: 3.8", "Programming Language :: Python :: 3.9", "Programming Language :: Python :: 3.10", "Programming Language :: Python :: 3.11", "Programming Language :: Python :: 3.12", "Programming Language :: Python :: Implementation :: CPython", "Programming Language :: Python :: Implementation :: PyPy", "Topic :: Software Development :: Libraries :: Python Modules" ], "requires_dist": [ "pytz >=2015.7 ; python_version < \"3.9\"", "pytest >=6.0 ; extra == 'dev'", "pytest-cov ; extra == 'dev'", "freezegun ~=1.0 ; extra == 'dev'" ], "requires_python": ">=3.8", "project_url": [ "Source, https://github.com/python-babel/babel" ], "provides_extra": [ "dev" ], "description": "A collection of tools for internationalizing Python applications.\n" }, "metadata_location": "/opt/conda/lib/python3.10/site-packages/babel-2.16.0.dist-info", "installer": "pip", "requested": false }, { "metadata": { "metadata_version": "2.1", "name": "beautifulsoup4", "version": "4.12.3", "summary": "Screen-scraping library", "description_content_type": "text/markdown", "keywords": [ "HTML", "XML", "parse", "soup" ], "author_email": "Leonard Richardson ", "license": "MIT License", "classifier": [ "Development Status :: 5 - Production/Stable", "Intended Audience :: Developers", "License :: OSI Approved :: MIT License", "Programming Language :: Python", "Programming Language :: Python :: 3", "Topic :: Software Development :: Libraries :: Python Modules", "Topic :: Text Processing :: Markup :: HTML", "Topic :: Text Processing :: Markup :: SGML", "Topic :: Text Processing :: Markup :: XML" ], "requires_dist": [ "soupsieve>1.2", "cchardet; extra == 'cchardet'", "chardet; extra == 'chardet'", "charset-normalizer; extra == 'charset-normalizer'", "html5lib; extra == 'html5lib'", "lxml; extra == 'lxml'" ], "requires_python": ">=3.6.0", "project_url": [ "Download, https://www.crummy.com/software/BeautifulSoup/bs4/download/", "Homepage, https://www.crummy.com/software/BeautifulSoup/bs4/" ], "provides_extra": [ "cchardet", "chardet", "charset-normalizer", "html5lib", "lxml" ], "description": "Beautiful Soup is a library that makes it easy to scrape information\nfrom web pages. It sits atop an HTML or XML parser, providing Pythonic\nidioms for iterating, searching, and modifying the parse tree.\n\n# Quick start\n\n```\n>>> from bs4 import BeautifulSoup\n>>> soup = BeautifulSoup(\"

SomebadHTML\")\n>>> print(soup.prettify())\n\n \n

\n Some\n \n bad\n \n HTML\n \n \n

\n \n\n>>> soup.find(text=\"bad\")\n'bad'\n>>> soup.i\nHTML\n#\n>>> soup = BeautifulSoup(\"SomebadXML\", \"xml\")\n#\n>>> print(soup.prettify())\n\n\n Some\n \n bad\n \n XML\n \n\n```\n\nTo go beyond the basics, [comprehensive documentation is available](https://www.crummy.com/software/BeautifulSoup/bs4/doc/).\n\n# Links\n\n* [Homepage](https://www.crummy.com/software/BeautifulSoup/bs4/)\n* [Documentation](https://www.crummy.com/software/BeautifulSoup/bs4/doc/)\n* [Discussion group](https://groups.google.com/group/beautifulsoup/)\n* [Development](https://code.launchpad.net/beautifulsoup/)\n* [Bug tracker](https://bugs.launchpad.net/beautifulsoup/)\n* [Complete changelog](https://bazaar.launchpad.net/~leonardr/beautifulsoup/bs4/view/head:/CHANGELOG)\n\n# Note on Python 2 sunsetting\n\nBeautiful Soup's support for Python 2 was discontinued on December 31,\n2020: one year after the sunset date for Python 2 itself. From this\npoint onward, new Beautiful Soup development will exclusively target\nPython 3. The final release of Beautiful Soup 4 to support Python 2\nwas 4.9.3.\n\n# Supporting the project\n\nIf you use Beautiful Soup as part of your professional work, please consider a\n[Tidelift subscription](https://tidelift.com/subscription/pkg/pypi-beautifulsoup4?utm_source=pypi-beautifulsoup4&utm_medium=referral&utm_campaign=readme).\nThis will support many of the free software projects your organization\ndepends on, not just Beautiful Soup.\n\nIf you use Beautiful Soup for personal projects, the best way to say\nthank you is to read\n[Tool Safety](https://www.crummy.com/software/BeautifulSoup/zine/), a zine I\nwrote about what Beautiful Soup has taught me about software\ndevelopment.\n\n# Building the documentation\n\nThe bs4/doc/ directory contains full documentation in Sphinx\nformat. Run `make html` in that directory to create HTML\ndocumentation.\n\n# Running the unit tests\n\nBeautiful Soup supports unit test discovery using Pytest:\n\n```\n$ pytest\n```\n\n" }, "metadata_location": "/opt/conda/lib/python3.10/site-packages/beautifulsoup4-4.12.3.dist-info", "direct_url": { "url": "file:///croot/beautifulsoup4-split_1718029820055/work", "dir_info": {} }, "installer": "conda", "requested": true }, { "metadata": { "metadata_version": "2.1", "name": "blosc", "version": "1.11.2", "platform": [ "any" ], "summary": "Blosc data compressor", "home_page": "https://github.com/blosc/python-blosc", "author": "The Blosc development team", "author_email": "blosc@blosc.org", "maintainer": "The Blosc development team", "maintainer_email": "blosc@blosc.org", "license": "https://opensource.org/licenses/BSD-3-Clause", "classifier": [ "Development Status :: 5 - Production/Stable", "Intended Audience :: Developers", "Intended Audience :: Information Technology", "Intended Audience :: Science/Research", "License :: OSI Approved :: BSD License", "Programming Language :: Python :: 3", "Programming Language :: Python :: 3.9", "Programming Language :: Python :: 3.10", "Programming Language :: Python :: 3.11", "Programming Language :: Python :: 3.12", "Programming Language :: Python :: 3 :: Only", "Topic :: Software Development :: Libraries :: Python Modules", "Topic :: System :: Archiving :: Compression", "Operating System :: Microsoft :: Windows", "Operating System :: Unix" ], "requires_python": ">=3.9", "description": "============\nPython-Blosc\n============\n\nA Python wrapper for the extremely fast Blosc compression library\n=================================================================\n\n:Author: The Blosc development team\n:Contact: blosc@blosc.org\n:Github: https://github.com/Blosc/python-blosc\n:URL: https://www.blosc.org/python-blosc/python-blosc.html\n:PyPi: |version|\n:Anaconda: |anaconda|\n:Gitter: |gitter|\n:Code of Conduct: |Contributor Covenant|\n\n.. |version| image:: https://img.shields.io/pypi/v/blosc.png\n :target: https://pypi.python.org/pypi/blosc\n.. |anaconda| image:: https://anaconda.org/conda-forge/python-blosc/badges/version.svg\n :target: https://anaconda.org/conda-forge/python-blosc\n.. |gitter| image:: https://badges.gitter.im/Blosc/c-blosc.svg\n :target: https://gitter.im/Blosc/c-blosc\n.. |Contributor Covenant| image:: https://img.shields.io/badge/Contributor%20Covenant-v2.0%20adopted-ff69b4.svg\n :target: https://github.com/Blosc/community/blob/master/code_of_conduct.md\n\n\nWhat it is\n==========\n\nBlosc (https://blosc.org) is a high performance compressor optimized for\nbinary data. It has been designed to transmit data to the processor\ncache faster than the traditional, non-compressed, direct memory fetch\napproach via a memcpy() OS call.\n\nBlosc works well for compressing numerical arrays that contains data\nwith relatively low entropy, like sparse data, time series, grids with\nregular-spaced values, etc.\n\npython-blosc a Python package that wraps Blosc. python-blosc supports\nPython 3.9 or higher versions.\n\n\nInstalling\n==========\n\n\nBlosc is now offering Python wheels for the main OS (Win, Mac and Linux) and platforms. You can install binary packages from PyPi using ``pip``:\n\n.. code-block:: console\n\n $ pip install blosc\n\n\nDocumentation\n=============\n\nThe Sphinx based documentation is here:\n\nhttps://blosc.org/python-blosc/python-blosc.html\n\nAlso, some examples are available on python-blosc wiki page:\n\nhttps://github.com/blosc/python-blosc/wiki\n\nLastly, here is the `recording\n`_\nand the `slides\n`_ from the talk\n\"Compress me stupid\" at the EuroPython 2014.\n\nBuilding\n========\n\nIf you need more control, there are different ways to compile python-blosc,\ndepending if you want to link with an already installed Blosc library or not.\n\n\nInstalling via setuptools\n-------------------------\n\n`python-blosc` comes with the Blosc sources with it and can be built with:\n\n.. code-block:: console\n\n $ python -m pip install -r requirements-dev.txt\n $ python setup.py build_ext --inplace\n\nAny codec can be enabled (`=1`) or disabled (`=0`) on this build-path with the appropriate\nOS environment variables `INCLUDE_LZ4`, `INCLUDE_SNAPPY`, `INCLUDE_ZLIB`, and\n`INCLUDE_ZSTD`. By default all the codecs in Blosc are enabled except Snappy\n(due to some issues with C++ with the `gcc` toolchain).\n\nCompiler specific optimisations are automatically enabled by inspecting\nthe CPU flags building Blosc. They can be manually disabled by setting\nthe following environmental variables: `DISABLE_BLOSC_SSE2` and\n`DISABLE_BLOSC_AVX2`.\n\n`setuptools` is limited to using the compiler specified in the environment\nvariable `CC` which on posix systems is usually `gcc`. This often causes\ntrouble with the Snappy codec, which is written in C++, and as a result Snappy\nis no longer compiled by default. This problem is not known to affect MSVC or\nclang. Snappy is considered optional in Blosc as its compression performance\nis below that of the other codecs.\n\nThat's all. You can proceed with testing section now.\n\n\nCompiling with an installed Blosc library\n-----------------------------------------\n\nThis approach uses pre-built, fully optimized versions of Blosc built via\nCMake.\n\nGo to https://github.com/Blosc/c-blosc/releases and download and install\nthe C-Blosc library. Then, you can tell python-blosc where is the\nC-Blosc library in a couple of ways:\n\nUsing an environment variable:\n\n.. code-block:: console\n\n $ export USE_SYSTEM_BLOSC=1 # or \"set USE_SYSTEM_BLOSC=1\" on Windows\n $ export Blosc_ROOT=/usr/local/customprefix # If you installed Blosc into a custom location\n $ python setup.py build_ext --inplace\n\nUsing flags:\n\n.. code-block:: console\n\n $ python setup.py build_ext --inplace -DUSE_SYSTEM_BLOSC:BOOL=YES -DBlosc_ROOT:PATH=/usr/local/customprefix\n\n\nTesting\n=======\n\nAfter compiling, you can quickly check that the package is sane by\nrunning the doctests in ``blosc/test.py``:\n\n.. code-block:: console\n\n $ python -m blosc.test (add -v for verbose mode)\n\nOnce installed, you can re-run the tests at any time with:\n\n.. code-block:: console\n\n $ python -c \"import blosc; blosc.test()\"\n\nBenchmarking\n============\n\nIf curious, you may want to run a small benchmark that compares a plain\nNumPy array copy against compression through different compressors in\nyour Blosc build:\n\n.. code-block:: console\n\n $ PYTHONPATH=. python bench/compress_ptr.py\n\nJust to whet your appetite, here are the results for an Intel Xeon\nE5-2695 v3 @ 2.30GHz, running Python 3.5, CentOS 7, but YMMV (and\nwill vary!)::\n\n -=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=\n python-blosc version: 1.5.1.dev0\n Blosc version: 1.11.2 ($Date:: 2017-01-27 #$)\n Compressors available: ['blosclz', 'lz4', 'lz4hc', 'snappy', 'zlib', 'zstd']\n Compressor library versions:\n BloscLZ: 1.0.5\n LZ4: 1.7.5\n Snappy: 1.1.1\n Zlib: 1.2.7\n Zstd: 1.1.2\n Python version: 3.5.2 |Continuum Analytics, Inc.| (default, Jul 2 2016, 17:53:06)\n [GCC 4.4.7 20120313 (Red Hat 4.4.7-1)]\n Platform: Linux-3.10.0-327.18.2.el7.x86_64-x86_64 (#1 SMP Thu May 12 11:03:55 UTC 2016)\n Linux dist: CentOS Linux 7.2.1511\n Processor: x86_64\n Byte-ordering: little\n Detected cores: 56\n Number of threads to use by default: 4\n -=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=\n Creating NumPy arrays with 10**8 int64/float64 elements:\n *** ctypes.memmove() *** Time for memcpy():\t0.276 s\t(2.70 GB/s)\n\n Times for compressing/decompressing with clevel=5 and 24 threads\n\n *** the arange linear distribution ***\n *** blosclz , noshuffle *** 0.382 s (1.95 GB/s) / 0.300 s (2.48 GB/s)\tCompr. ratio: 1.0x\n *** blosclz , shuffle *** 0.042 s (17.77 GB/s) / 0.027 s (27.18 GB/s)\tCompr. ratio: 57.1x\n *** blosclz , bitshuffle *** 0.094 s (7.94 GB/s) / 0.041 s (18.28 GB/s)\tCompr. ratio: 74.0x\n *** lz4 , noshuffle *** 0.156 s (4.79 GB/s) / 0.052 s (14.30 GB/s)\tCompr. ratio: 2.0x\n *** lz4 , shuffle *** 0.033 s (22.58 GB/s) / 0.034 s (22.03 GB/s)\tCompr. ratio: 68.6x\n *** lz4 , bitshuffle *** 0.059 s (12.63 GB/s) / 0.053 s (14.18 GB/s)\tCompr. ratio: 33.1x\n *** lz4hc , noshuffle *** 0.443 s (1.68 GB/s) / 0.070 s (10.62 GB/s)\tCompr. ratio: 2.0x\n *** lz4hc , shuffle *** 0.102 s (7.31 GB/s) / 0.029 s (25.42 GB/s)\tCompr. ratio: 97.5x\n *** lz4hc , bitshuffle *** 0.206 s (3.62 GB/s) / 0.038 s (19.85 GB/s)\tCompr. ratio: 180.5x\n *** snappy , noshuffle *** 0.154 s (4.84 GB/s) / 0.056 s (13.28 GB/s)\tCompr. ratio: 2.0x\n *** snappy , shuffle *** 0.044 s (16.89 GB/s) / 0.047 s (15.95 GB/s)\tCompr. ratio: 17.4x\n *** snappy , bitshuffle *** 0.064 s (11.58 GB/s) / 0.061 s (12.26 GB/s)\tCompr. ratio: 18.2x\n *** zlib , noshuffle *** 1.172 s (0.64 GB/s) / 0.135 s (5.50 GB/s)\tCompr. ratio: 5.3x\n *** zlib , shuffle *** 0.260 s (2.86 GB/s) / 0.086 s (8.67 GB/s)\tCompr. ratio: 120.8x\n *** zlib , bitshuffle *** 0.262 s (2.84 GB/s) / 0.094 s (7.96 GB/s)\tCompr. ratio: 260.1x\n *** zstd , noshuffle *** 0.973 s (0.77 GB/s) / 0.093 s (8.00 GB/s)\tCompr. ratio: 7.8x\n *** zstd , shuffle *** 0.093 s (7.97 GB/s) / 0.023 s (32.71 GB/s)\tCompr. ratio: 156.7x\n *** zstd , bitshuffle *** 0.115 s (6.46 GB/s) / 0.029 s (25.60 GB/s)\tCompr. ratio: 320.6x\n\n *** the linspace linear distribution ***\n *** blosclz , noshuffle *** 0.341 s (2.19 GB/s) / 0.291 s (2.56 GB/s)\tCompr. ratio: 1.0x\n *** blosclz , shuffle *** 0.132 s (5.65 GB/s) / 0.023 s (33.10 GB/s)\tCompr. ratio: 2.0x\n *** blosclz , bitshuffle *** 0.166 s (4.50 GB/s) / 0.036 s (20.89 GB/s)\tCompr. ratio: 2.8x\n *** lz4 , noshuffle *** 0.142 s (5.26 GB/s) / 0.028 s (27.07 GB/s)\tCompr. ratio: 1.0x\n *** lz4 , shuffle *** 0.093 s (8.01 GB/s) / 0.030 s (24.87 GB/s)\tCompr. ratio: 3.4x\n *** lz4 , bitshuffle *** 0.102 s (7.31 GB/s) / 0.039 s (19.13 GB/s)\tCompr. ratio: 5.3x\n *** lz4hc , noshuffle *** 0.700 s (1.06 GB/s) / 0.044 s (16.77 GB/s)\tCompr. ratio: 1.1x\n *** lz4hc , shuffle *** 0.203 s (3.67 GB/s) / 0.021 s (36.22 GB/s)\tCompr. ratio: 8.6x\n *** lz4hc , bitshuffle *** 0.342 s (2.18 GB/s) / 0.028 s (26.50 GB/s)\tCompr. ratio: 14.2x\n *** snappy , noshuffle *** 0.271 s (2.75 GB/s) / 0.274 s (2.72 GB/s)\tCompr. ratio: 1.0x\n *** snappy , shuffle *** 0.099 s (7.54 GB/s) / 0.042 s (17.55 GB/s)\tCompr. ratio: 4.2x\n *** snappy , bitshuffle *** 0.127 s (5.86 GB/s) / 0.043 s (17.20 GB/s)\tCompr. ratio: 6.1x\n *** zlib , noshuffle *** 1.525 s (0.49 GB/s) / 0.158 s (4.70 GB/s)\tCompr. ratio: 1.6x\n *** zlib , shuffle *** 0.346 s (2.15 GB/s) / 0.098 s (7.59 GB/s)\tCompr. ratio: 10.7x\n *** zlib , bitshuffle *** 0.420 s (1.78 GB/s) / 0.104 s (7.20 GB/s)\tCompr. ratio: 18.0x\n *** zstd , noshuffle *** 1.061 s (0.70 GB/s) / 0.096 s (7.79 GB/s)\tCompr. ratio: 1.9x\n *** zstd , shuffle *** 0.203 s (3.68 GB/s) / 0.052 s (14.21 GB/s)\tCompr. ratio: 14.2x\n *** zstd , bitshuffle *** 0.251 s (2.97 GB/s) / 0.047 s (15.84 GB/s)\tCompr. ratio: 22.2x\n\n *** the random distribution ***\n *** blosclz , noshuffle *** 0.340 s (2.19 GB/s) / 0.285 s (2.61 GB/s)\tCompr. ratio: 1.0x\n *** blosclz , shuffle *** 0.091 s (8.21 GB/s) / 0.017 s (44.29 GB/s)\tCompr. ratio: 3.9x\n *** blosclz , bitshuffle *** 0.080 s (9.27 GB/s) / 0.029 s (26.12 GB/s)\tCompr. ratio: 6.1x\n *** lz4 , noshuffle *** 0.150 s (4.95 GB/s) / 0.027 s (28.05 GB/s)\tCompr. ratio: 2.4x\n *** lz4 , shuffle *** 0.068 s (11.02 GB/s) / 0.029 s (26.03 GB/s)\tCompr. ratio: 4.5x\n *** lz4 , bitshuffle *** 0.063 s (11.87 GB/s) / 0.054 s (13.70 GB/s)\tCompr. ratio: 6.2x\n *** lz4hc , noshuffle *** 0.645 s (1.15 GB/s) / 0.019 s (39.22 GB/s)\tCompr. ratio: 3.5x\n *** lz4hc , shuffle *** 0.257 s (2.90 GB/s) / 0.022 s (34.62 GB/s)\tCompr. ratio: 5.1x\n *** lz4hc , bitshuffle *** 0.128 s (5.80 GB/s) / 0.029 s (25.52 GB/s)\tCompr. ratio: 6.2x\n *** snappy , noshuffle *** 0.164 s (4.54 GB/s) / 0.048 s (15.46 GB/s)\tCompr. ratio: 2.2x\n *** snappy , shuffle *** 0.082 s (9.09 GB/s) / 0.043 s (17.39 GB/s)\tCompr. ratio: 4.3x\n *** snappy , bitshuffle *** 0.071 s (10.48 GB/s) / 0.046 s (16.08 GB/s)\tCompr. ratio: 5.0x\n *** zlib , noshuffle *** 1.223 s (0.61 GB/s) / 0.093 s (7.97 GB/s)\tCompr. ratio: 4.0x\n *** zlib , shuffle *** 0.636 s (1.17 GB/s) / 0.126 s (5.89 GB/s)\tCompr. ratio: 5.5x\n *** zlib , bitshuffle *** 0.327 s (2.28 GB/s) / 0.109 s (6.81 GB/s)\tCompr. ratio: 6.2x\n *** zstd , noshuffle *** 1.432 s (0.52 GB/s) / 0.103 s (7.27 GB/s)\tCompr. ratio: 4.2x\n *** zstd , shuffle *** 0.388 s (1.92 GB/s) / 0.031 s (23.71 GB/s)\tCompr. ratio: 5.9x\n *** zstd , bitshuffle *** 0.127 s (5.86 GB/s) / 0.033 s (22.77 GB/s)\tCompr. ratio: 6.4x\n\n\nAlso, Blosc works quite well on ARM processors (even without NEON support yet)::\n\n -=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=\n python-blosc version: 1.4.4\n Blosc version: 1.11.2 ($Date:: 2017-01-27 #$)\n Compressors available: ['blosclz', 'lz4', 'lz4hc', 'snappy', 'zlib', 'zstd']\n Compressor library versions:\n BloscLZ: 1.0.5\n LZ4: 1.7.5\n Snappy: 1.1.1\n Zlib: 1.2.8\n Zstd: 1.1.2\n Python version: 3.6.0 (default, Dec 31 2016, 21:20:16)\n [GCC 4.9.2]\n Platform: Linux-3.4.113-sun8i-armv7l (#50 SMP PREEMPT Mon Nov 14 08:41:55 CET 2016)\n Linux dist: debian 9.0\n Processor: not recognized\n Byte-ordering: little\n Detected cores: 4\n Number of threads to use by default: 4\n -=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=\n *** ctypes.memmove() *** Time for memcpy(): 0.015 s (93.57 MB/s)\n\n Times for compressing/decompressing with clevel=5 and 4 threads\n\n *** user input ***\n *** blosclz , noshuffle *** 0.015 s (89.93 MB/s) / 0.010 s (138.32 MB/s) Compr. ratio: 2.7x\n *** blosclz , shuffle *** 0.023 s (60.25 MB/s) / 0.012 s (112.71 MB/s) Compr. ratio: 2.3x\n *** blosclz , bitshuffle *** 0.018 s (77.63 MB/s) / 0.021 s (66.76 MB/s) Compr. ratio: 7.3x\n *** lz4 , noshuffle *** 0.008 s (177.14 MB/s) / 0.009 s (159.00 MB/s) Compr. ratio: 3.6x\n *** lz4 , shuffle *** 0.010 s (131.29 MB/s) / 0.012 s (117.69 MB/s) Compr. ratio: 3.5x\n *** lz4 , bitshuffle *** 0.015 s (89.97 MB/s) / 0.022 s (63.62 MB/s) Compr. ratio: 8.4x\n *** lz4hc , noshuffle *** 0.071 s (19.30 MB/s) / 0.007 s (186.64 MB/s) Compr. ratio: 8.6x\n *** lz4hc , shuffle *** 0.079 s (17.30 MB/s) / 0.014 s (95.99 MB/s) Compr. ratio: 6.2x\n *** lz4hc , bitshuffle *** 0.062 s (22.23 MB/s) / 0.027 s (51.53 MB/s) Compr. ratio: 9.7x\n *** snappy , noshuffle *** 0.008 s (173.87 MB/s) / 0.009 s (148.77 MB/s) Compr. ratio: 4.4x\n *** snappy , shuffle *** 0.011 s (123.22 MB/s) / 0.016 s (85.16 MB/s) Compr. ratio: 4.4x\n *** snappy , bitshuffle *** 0.015 s (89.02 MB/s) / 0.021 s (64.87 MB/s) Compr. ratio: 6.2x\n *** zlib , noshuffle *** 0.047 s (29.26 MB/s) / 0.011 s (121.83 MB/s) Compr. ratio: 14.7x\n *** zlib , shuffle *** 0.080 s (17.20 MB/s) / 0.022 s (63.61 MB/s) Compr. ratio: 9.4x\n *** zlib , bitshuffle *** 0.059 s (23.50 MB/s) / 0.033 s (41.10 MB/s) Compr. ratio: 10.5x\n *** zstd , noshuffle *** 0.113 s (12.21 MB/s) / 0.011 s (124.64 MB/s) Compr. ratio: 15.6x\n *** zstd , shuffle *** 0.154 s (8.92 MB/s) / 0.026 s (52.56 MB/s) Compr. ratio: 9.9x\n *** zstd , bitshuffle *** 0.116 s (11.86 MB/s) / 0.036 s (38.40 MB/s) Compr. ratio: 11.4x\n\nFor details on the ARM benchmark see: https://github.com/Blosc/python-blosc/issues/105\n\nIn case you find your own results interesting, please report them back\nto the authors!\n\nLicense\n=======\n\nThe software is licensed under a 3-Clause BSD license. A copy of the\npython-blosc license can be found in\n`LICENSE.txt `_.\n\nMailing list\n============\n\nDiscussion about this module is welcome in the Blosc list:\n\nblosc@googlegroups.com\n\nhttps://groups.google.com/g/blosc\n\n----\n\n **Enjoy data!**\n\n\n.. Local Variables:\n.. mode: rst\n.. coding: utf-8\n.. fill-column: 72\n.. End:\n" }, "metadata_location": "/opt/conda/lib/python3.10/site-packages/blosc-1.11.2.dist-info", "installer": "pip", "requested": true }, { "metadata": { "metadata_version": "2.1", "name": "boltons", "version": "23.0.0", "platform": [ "any" ], "summary": "When they're not builtins, they're boltons.", "home_page": "https://github.com/mahmoud/boltons", "author": "Mahmoud Hashemi", "author_email": "mahmoud@hatnote.com", "license": "BSD", "classifier": [ "Topic :: Utilities", "Intended Audience :: Developers", "License :: OSI Approved :: BSD License", "Topic :: Software Development :: Libraries", "Development Status :: 5 - Production/Stable", "Operating System :: OS Independent", "Programming Language :: Python :: 2", "Programming Language :: Python :: 2.7", "Programming Language :: Python :: 3", "Programming Language :: Python :: 3.7", "Programming Language :: Python :: 3.8", "Programming Language :: Python :: 3.9", "Programming Language :: Python :: 3.10", "Programming Language :: Python :: 3.11", "Programming Language :: Python :: Implementation :: CPython", "Programming Language :: Python :: Implementation :: PyPy" ], "description": "Functionality that should be in the standard library. Like\nbuiltins, but Boltons.\n\nOtherwise known as, \"everyone's util.py,\" but cleaned up and\ntested.\n\nContains over 250 BSD-licensed utility types and functions that can be\nused as a package or independently. `Extensively documented on Read\nthe Docs `_.\n" }, "metadata_location": "/opt/conda/lib/python3.10/site-packages/boltons-23.0.0.dist-info", "direct_url": { "url": "file:///croot/boltons_1677628692245/work", "dir_info": {} }, "installer": "conda", "requested": true }, { "metadata": { "metadata_version": "2.1", "name": "build", "version": "1.2.2.post1", "summary": "A simple, correct Python build frontend", "description_content_type": "text/markdown", "author_email": "Filipe Laíns , Bernát Gábor , layday , Henry Schreiner ", "classifier": [ "License :: OSI Approved :: MIT License", "Programming Language :: Python :: 3", "Programming Language :: Python :: 3 :: Only", "Programming Language :: Python :: 3.8", "Programming Language :: Python :: 3.9", "Programming Language :: Python :: 3.10", "Programming Language :: Python :: 3.11", "Programming Language :: Python :: 3.12", "Programming Language :: Python :: 3.13", "Programming Language :: Python :: Implementation :: CPython", "Programming Language :: Python :: Implementation :: PyPy" ], "requires_dist": [ "packaging >= 19.1", "pyproject_hooks", "colorama; os_name == \"nt\"", "importlib-metadata >= 4.6; python_full_version < \"3.10.2\"", "tomli >= 1.1.0; python_version < \"3.11\"", "furo >= 2023.08.17 ; extra == \"docs\"", "sphinx ~= 7.0 ; extra == \"docs\"", "sphinx-argparse-cli >= 1.5 ; extra == \"docs\"", "sphinx-autodoc-typehints >= 1.10 ; extra == \"docs\"", "sphinx-issues >= 3.0.0 ; extra == \"docs\"", "build[uv, virtualenv] ; extra == \"test\"", "filelock >= 3 ; extra == \"test\"", "pytest >= 6.2.4 ; extra == \"test\"", "pytest-cov >= 2.12 ; extra == \"test\"", "pytest-mock >= 2 ; extra == \"test\"", "pytest-rerunfailures >= 9.1 ; extra == \"test\"", "pytest-xdist >= 1.34 ; extra == \"test\"", "wheel >= 0.36.0 ; extra == \"test\"", "setuptools >= 42.0.0 ; extra == \"test\" and ( python_version < \"3.10\")", "setuptools >= 56.0.0 ; extra == \"test\" and ( python_version == \"3.10\")", "setuptools >= 56.0.0 ; extra == \"test\" and ( python_version == \"3.11\")", "setuptools >= 67.8.0 ; extra == \"test\" and ( python_version >= \"3.12\")", "build[uv] ; extra == \"typing\"", "importlib-metadata >= 5.1 ; extra == \"typing\"", "mypy ~= 1.9.0 ; extra == \"typing\"", "tomli ; extra == \"typing\"", "typing-extensions >= 3.7.4.3 ; extra == \"typing\"", "uv >= 0.1.18 ; extra == \"uv\"", "virtualenv >= 20.0.35 ; extra == \"virtualenv\"" ], "requires_python": ">= 3.8", "project_url": [ "changelog, https://build.pypa.io/en/stable/changelog.html", "homepage, https://build.pypa.io", "issues, https://github.com/pypa/build/issues", "source, https://github.com/pypa/build" ], "provides_extra": [ "docs", "test", "typing", "uv", "virtualenv" ], "description": "# build\n\n[![pre-commit.ci status](https://results.pre-commit.ci/badge/github/pypa/build/main.svg)](https://results.pre-commit.ci/latest/github/pypa/build/main)\n[![CI test](https://github.com/pypa/build/actions/workflows/test.yml/badge.svg)](https://github.com/pypa/build/actions/workflows/test.yml)\n[![codecov](https://codecov.io/gh/pypa/build/branch/main/graph/badge.svg)](https://codecov.io/gh/pypa/build)\n\n[![Documentation Status](https://readthedocs.org/projects/pypa-build/badge/?version=latest)](https://build.pypa.io/en/latest/?badge=latest)\n[![PyPI version](https://badge.fury.io/py/build.svg)](https://pypi.org/project/build/)\n[![Discord](https://img.shields.io/discord/803025117553754132?label=Discord%20chat%20%23build)](https://discord.gg/pypa)\n\nA simple, correct Python build frontend.\n\nSee the [documentation](https://build.pypa.io) for more information.\n\n### Installation\n\n`build` can be installed via `pip` or an equivalent via:\n\n```console\n$ pip install build\n```\n\n### Usage\n\n```console\n$ python -m build\n```\n\nThis will build the package in an isolated environment, generating a\nsource-distribution and wheel in the directory `dist/`.\nSee the [documentation](https://build.pypa.io) for full information.\n\n### Common arguments\n\n- `--sdist` (`-s`): Produce just an SDist\n- `--wheel` (`-w`): Produce just a wheel\n- `-C