| Name | pandas JSON |
| Version |
2.3.2
JSON |
| download |
| home_page | None |
| Summary | Powerful data structures for data analysis, time series, and statistics |
| upload_time | 2025-08-21 10:28:29 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.9 |
| license | BSD 3-Clause License
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dateutil - Extensions to the standard Python datetime module.
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----------------------------------------------------------------------
Authors/contributors include:
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Portions of this software are derived from third-party works licensed
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The TRE regular expression implementation (src/regex/reg* and
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OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.A. HISTORY OF THE SOFTWARE
==========================
Python was created in the early 1990s by Guido van Rossum at Stichting
Mathematisch Centrum (CWI, see https://www.cwi.nl) in the Netherlands
as a successor of a language called ABC. Guido remains Python's
principal author, although it includes many contributions from others.
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in Reston, Virginia where he released several versions of the
software.
In May 2000, Guido and the Python core development team moved to
BeOpen.com to form the BeOpen PythonLabs team. In October of the same
year, the PythonLabs team moved to Digital Creations, which became
Zope Corporation. In 2001, the Python Software Foundation (PSF, see
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Release Derived Year Owner GPL-
from compatible? (1)
0.9.0 thru 1.2 1991-1995 CWI yes
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1.6 1.5.2 2000 CNRI no
2.0 1.6 2000 BeOpen.com no
1.6.1 1.6 2001 CNRI yes (2)
2.1 2.0+1.6.1 2001 PSF no
2.0.1 2.0+1.6.1 2001 PSF yes
2.1.1 2.1+2.0.1 2001 PSF yes
2.1.2 2.1.1 2002 PSF yes
2.1.3 2.1.2 2002 PSF yes
2.2 and above 2.1.1 2001-now PSF yes
Footnotes:
(1) GPL-compatible doesn't mean that we're distributing Python under
the GPL. All Python licenses, unlike the GPL, let you distribute
a modified version without making your changes open source. The
GPL-compatible licenses make it possible to combine Python with
other software that is released under the GPL; the others don't.
(2) According to Richard Stallman, 1.6.1 is not GPL-compatible,
because its license has a choice of law clause. According to
CNRI, however, Stallman's lawyer has told CNRI's lawyer that 1.6.1
is "not incompatible" with the GPL.
Thanks to the many outside volunteers who have worked under Guido's
direction to make these releases possible.
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===============================================================
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Portions of code from MODP_ASCII - Ascii transformations (upper/lower, etc)
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<div align="center">
<img src="https://pandas.pydata.org/static/img/pandas.svg"><br>
</div>
-----------------
# pandas: powerful Python data analysis toolkit
| | |
| --- | --- |
| Testing | [](https://github.com/pandas-dev/pandas/actions/workflows/unit-tests.yml) [](https://codecov.io/gh/pandas-dev/pandas) |
| Package | [](https://pypi.org/project/pandas/) [](https://pypi.org/project/pandas/) [](https://anaconda.org/conda-forge/pandas) [](https://anaconda.org/conda-forge/pandas) |
| Meta | [](https://numfocus.org) [](https://doi.org/10.5281/zenodo.3509134) [](https://github.com/pandas-dev/pandas/blob/main/LICENSE) [](https://pandas.pydata.org/docs/dev/development/community.html?highlight=slack#community-slack) |
## What is it?
**pandas** is a Python package that provides fast, flexible, and expressive data
structures designed to make working with "relational" or "labeled" data both
easy and intuitive. It aims to be the fundamental high-level building block for
doing practical, **real world** data analysis in Python. Additionally, it has
the broader goal of becoming **the most powerful and flexible open source data
analysis / manipulation tool available in any language**. It is already well on
its way towards this goal.
## Table of Contents
- [Main Features](#main-features)
- [Where to get it](#where-to-get-it)
- [Dependencies](#dependencies)
- [Installation from sources](#installation-from-sources)
- [License](#license)
- [Documentation](#documentation)
- [Background](#background)
- [Getting Help](#getting-help)
- [Discussion and Development](#discussion-and-development)
- [Contributing to pandas](#contributing-to-pandas)
## Main Features
Here are just a few of the things that pandas does well:
- Easy handling of [**missing data**][missing-data] (represented as
`NaN`, `NA`, or `NaT`) in floating point as well as non-floating point data
- Size mutability: columns can be [**inserted and
deleted**][insertion-deletion] from DataFrame and higher dimensional
objects
- Automatic and explicit [**data alignment**][alignment]: objects can
be explicitly aligned to a set of labels, or the user can simply
ignore the labels and let `Series`, `DataFrame`, etc. automatically
align the data for you in computations
- Powerful, flexible [**group by**][groupby] functionality to perform
split-apply-combine operations on data sets, for both aggregating
and transforming data
- Make it [**easy to convert**][conversion] ragged,
differently-indexed data in other Python and NumPy data structures
into DataFrame objects
- Intelligent label-based [**slicing**][slicing], [**fancy
indexing**][fancy-indexing], and [**subsetting**][subsetting] of
large data sets
- Intuitive [**merging**][merging] and [**joining**][joining] data
sets
- Flexible [**reshaping**][reshape] and [**pivoting**][pivot-table] of
data sets
- [**Hierarchical**][mi] labeling of axes (possible to have multiple
labels per tick)
- Robust IO tools for loading data from [**flat files**][flat-files]
(CSV and delimited), [**Excel files**][excel], [**databases**][db],
and saving/loading data from the ultrafast [**HDF5 format**][hdfstore]
- [**Time series**][timeseries]-specific functionality: date range
generation and frequency conversion, moving window statistics,
date shifting and lagging
[missing-data]: https://pandas.pydata.org/pandas-docs/stable/user_guide/missing_data.html
[insertion-deletion]: https://pandas.pydata.org/pandas-docs/stable/user_guide/dsintro.html#column-selection-addition-deletion
[alignment]: https://pandas.pydata.org/pandas-docs/stable/user_guide/dsintro.html?highlight=alignment#intro-to-data-structures
[groupby]: https://pandas.pydata.org/pandas-docs/stable/user_guide/groupby.html#group-by-split-apply-combine
[conversion]: https://pandas.pydata.org/pandas-docs/stable/user_guide/dsintro.html#dataframe
[slicing]: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#slicing-ranges
[fancy-indexing]: https://pandas.pydata.org/pandas-docs/stable/user_guide/advanced.html#advanced
[subsetting]: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#boolean-indexing
[merging]: https://pandas.pydata.org/pandas-docs/stable/user_guide/merging.html#database-style-dataframe-or-named-series-joining-merging
[joining]: https://pandas.pydata.org/pandas-docs/stable/user_guide/merging.html#joining-on-index
[reshape]: https://pandas.pydata.org/pandas-docs/stable/user_guide/reshaping.html
[pivot-table]: https://pandas.pydata.org/pandas-docs/stable/user_guide/reshaping.html
[mi]: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#hierarchical-indexing-multiindex
[flat-files]: https://pandas.pydata.org/pandas-docs/stable/user_guide/io.html#csv-text-files
[excel]: https://pandas.pydata.org/pandas-docs/stable/user_guide/io.html#excel-files
[db]: https://pandas.pydata.org/pandas-docs/stable/user_guide/io.html#sql-queries
[hdfstore]: https://pandas.pydata.org/pandas-docs/stable/user_guide/io.html#hdf5-pytables
[timeseries]: https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html#time-series-date-functionality
## Where to get it
The source code is currently hosted on GitHub at:
https://github.com/pandas-dev/pandas
Binary installers for the latest released version are available at the [Python
Package Index (PyPI)](https://pypi.org/project/pandas) and on [Conda](https://docs.conda.io/en/latest/).
```sh
# conda
conda install -c conda-forge pandas
```
```sh
# or PyPI
pip install pandas
```
The list of changes to pandas between each release can be found
[here](https://pandas.pydata.org/pandas-docs/stable/whatsnew/index.html). For full
details, see the commit logs at https://github.com/pandas-dev/pandas.
## Dependencies
- [NumPy - Adds support for large, multi-dimensional arrays, matrices and high-level mathematical functions to operate on these arrays](https://www.numpy.org)
- [python-dateutil - Provides powerful extensions to the standard datetime module](https://dateutil.readthedocs.io/en/stable/index.html)
- [pytz - Brings the Olson tz database into Python which allows accurate and cross platform timezone calculations](https://github.com/stub42/pytz)
See the [full installation instructions](https://pandas.pydata.org/pandas-docs/stable/install.html#dependencies) for minimum supported versions of required, recommended and optional dependencies.
## Installation from sources
To install pandas from source you need [Cython](https://cython.org/) in addition to the normal
dependencies above. Cython can be installed from PyPI:
```sh
pip install cython
```
In the `pandas` directory (same one where you found this file after
cloning the git repo), execute:
```sh
pip install .
```
or for installing in [development mode](https://pip.pypa.io/en/latest/cli/pip_install/#install-editable):
```sh
python -m pip install -ve . --no-build-isolation --config-settings=editable-verbose=true
```
See the full instructions for [installing from source](https://pandas.pydata.org/docs/dev/development/contributing_environment.html).
## License
[BSD 3](LICENSE)
## Documentation
The official documentation is hosted on [PyData.org](https://pandas.pydata.org/pandas-docs/stable/).
## Background
Work on ``pandas`` started at [AQR](https://www.aqr.com/) (a quantitative hedge fund) in 2008 and
has been under active development since then.
## Getting Help
For usage questions, the best place to go to is [StackOverflow](https://stackoverflow.com/questions/tagged/pandas).
Further, general questions and discussions can also take place on the [pydata mailing list](https://groups.google.com/forum/?fromgroups#!forum/pydata).
## Discussion and Development
Most development discussions take place on GitHub in this repo, via the [GitHub issue tracker](https://github.com/pandas-dev/pandas/issues).
Further, the [pandas-dev mailing list](https://mail.python.org/mailman/listinfo/pandas-dev) can also be used for specialized discussions or design issues, and a [Slack channel](https://pandas.pydata.org/docs/dev/development/community.html?highlight=slack#community-slack) is available for quick development related questions.
There are also frequent [community meetings](https://pandas.pydata.org/docs/dev/development/community.html#community-meeting) for project maintainers open to the community as well as monthly [new contributor meetings](https://pandas.pydata.org/docs/dev/development/community.html#new-contributor-meeting) to help support new contributors.
Additional information on the communication channels can be found on the [contributor community](https://pandas.pydata.org/docs/development/community.html) page.
## Contributing to pandas
[](https://www.codetriage.com/pandas-dev/pandas)
All contributions, bug reports, bug fixes, documentation improvements, enhancements, and ideas are welcome.
A detailed overview on how to contribute can be found in the **[contributing guide](https://pandas.pydata.org/docs/dev/development/contributing.html)**.
If you are simply looking to start working with the pandas codebase, navigate to the [GitHub "issues" tab](https://github.com/pandas-dev/pandas/issues) and start looking through interesting issues. There are a number of issues listed under [Docs](https://github.com/pandas-dev/pandas/issues?labels=Docs&sort=updated&state=open) and [good first issue](https://github.com/pandas-dev/pandas/issues?labels=good+first+issue&sort=updated&state=open) where you could start out.
You can also triage issues which may include reproducing bug reports, or asking for vital information such as version numbers or reproduction instructions. If you would like to start triaging issues, one easy way to get started is to [subscribe to pandas on CodeTriage](https://www.codetriage.com/pandas-dev/pandas).
Or maybe through using pandas you have an idea of your own or are looking for something in the documentation and thinking ‘this can be improved’...you can do something about it!
Feel free to ask questions on the [mailing list](https://groups.google.com/forum/?fromgroups#!forum/pydata) or on [Slack](https://pandas.pydata.org/docs/dev/development/community.html?highlight=slack#community-slack).
As contributors and maintainers to this project, you are expected to abide by pandas' code of conduct. More information can be found at: [Contributor Code of Conduct](https://github.com/pandas-dev/.github/blob/master/CODE_OF_CONDUCT.md)
<hr>
[Go to Top](#table-of-contents)
Raw data
{
"_id": null,
"home_page": null,
"name": "pandas",
"maintainer": null,
"docs_url": null,
"requires_python": ">=3.9",
"maintainer_email": null,
"keywords": null,
"author": null,
"author_email": "The Pandas Development Team <pandas-dev@python.org>",
"download_url": "https://files.pythonhosted.org/packages/79/8e/0e90233ac205ad182bd6b422532695d2b9414944a280488105d598c70023/pandas-2.3.2.tar.gz",
"platform": null,
"description": "<div align=\"center\">\n <img src=\"https://pandas.pydata.org/static/img/pandas.svg\"><br>\n</div>\n\n-----------------\n\n# pandas: powerful Python data analysis toolkit\n\n| | |\n| --- | --- |\n| Testing | [](https://github.com/pandas-dev/pandas/actions/workflows/unit-tests.yml) [](https://codecov.io/gh/pandas-dev/pandas) |\n| Package | [](https://pypi.org/project/pandas/) [](https://pypi.org/project/pandas/) [](https://anaconda.org/conda-forge/pandas) [](https://anaconda.org/conda-forge/pandas) |\n| Meta | [](https://numfocus.org) [](https://doi.org/10.5281/zenodo.3509134) [](https://github.com/pandas-dev/pandas/blob/main/LICENSE) [](https://pandas.pydata.org/docs/dev/development/community.html?highlight=slack#community-slack) |\n\n\n## What is it?\n\n**pandas** is a Python package that provides fast, flexible, and expressive data\nstructures designed to make working with \"relational\" or \"labeled\" data both\neasy and intuitive. It aims to be the fundamental high-level building block for\ndoing practical, **real world** data analysis in Python. Additionally, it has\nthe broader goal of becoming **the most powerful and flexible open source data\nanalysis / manipulation tool available in any language**. It is already well on\nits way towards this goal.\n\n## Table of Contents\n\n- [Main Features](#main-features)\n- [Where to get it](#where-to-get-it)\n- [Dependencies](#dependencies)\n- [Installation from sources](#installation-from-sources)\n- [License](#license)\n- [Documentation](#documentation)\n- [Background](#background)\n- [Getting Help](#getting-help)\n- [Discussion and Development](#discussion-and-development)\n- [Contributing to pandas](#contributing-to-pandas)\n\n## Main Features\nHere are just a few of the things that pandas does well:\n\n - Easy handling of [**missing data**][missing-data] (represented as\n `NaN`, `NA`, or `NaT`) in floating point as well as non-floating point data\n - Size mutability: columns can be [**inserted and\n deleted**][insertion-deletion] from DataFrame and higher dimensional\n objects\n - Automatic and explicit [**data alignment**][alignment]: objects can\n be explicitly aligned to a set of labels, or the user can simply\n ignore the labels and let `Series`, `DataFrame`, etc. automatically\n align the data for you in computations\n - Powerful, flexible [**group by**][groupby] functionality to perform\n split-apply-combine operations on data sets, for both aggregating\n and transforming data\n - Make it [**easy to convert**][conversion] ragged,\n differently-indexed data in other Python and NumPy data structures\n into DataFrame objects\n - Intelligent label-based [**slicing**][slicing], [**fancy\n indexing**][fancy-indexing], and [**subsetting**][subsetting] of\n large data sets\n - Intuitive [**merging**][merging] and [**joining**][joining] data\n sets\n - Flexible [**reshaping**][reshape] and [**pivoting**][pivot-table] of\n data sets\n - [**Hierarchical**][mi] labeling of axes (possible to have multiple\n labels per tick)\n - Robust IO tools for loading data from [**flat files**][flat-files]\n (CSV and delimited), [**Excel files**][excel], [**databases**][db],\n and saving/loading data from the ultrafast [**HDF5 format**][hdfstore]\n - [**Time series**][timeseries]-specific functionality: date range\n generation and frequency conversion, moving window statistics,\n date shifting and lagging\n\n\n [missing-data]: https://pandas.pydata.org/pandas-docs/stable/user_guide/missing_data.html\n [insertion-deletion]: https://pandas.pydata.org/pandas-docs/stable/user_guide/dsintro.html#column-selection-addition-deletion\n [alignment]: https://pandas.pydata.org/pandas-docs/stable/user_guide/dsintro.html?highlight=alignment#intro-to-data-structures\n [groupby]: https://pandas.pydata.org/pandas-docs/stable/user_guide/groupby.html#group-by-split-apply-combine\n [conversion]: https://pandas.pydata.org/pandas-docs/stable/user_guide/dsintro.html#dataframe\n [slicing]: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#slicing-ranges\n [fancy-indexing]: https://pandas.pydata.org/pandas-docs/stable/user_guide/advanced.html#advanced\n [subsetting]: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#boolean-indexing\n [merging]: https://pandas.pydata.org/pandas-docs/stable/user_guide/merging.html#database-style-dataframe-or-named-series-joining-merging\n [joining]: https://pandas.pydata.org/pandas-docs/stable/user_guide/merging.html#joining-on-index\n [reshape]: https://pandas.pydata.org/pandas-docs/stable/user_guide/reshaping.html\n [pivot-table]: https://pandas.pydata.org/pandas-docs/stable/user_guide/reshaping.html\n [mi]: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#hierarchical-indexing-multiindex\n [flat-files]: https://pandas.pydata.org/pandas-docs/stable/user_guide/io.html#csv-text-files\n [excel]: https://pandas.pydata.org/pandas-docs/stable/user_guide/io.html#excel-files\n [db]: https://pandas.pydata.org/pandas-docs/stable/user_guide/io.html#sql-queries\n [hdfstore]: https://pandas.pydata.org/pandas-docs/stable/user_guide/io.html#hdf5-pytables\n [timeseries]: https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html#time-series-date-functionality\n\n## Where to get it\nThe source code is currently hosted on GitHub at:\nhttps://github.com/pandas-dev/pandas\n\nBinary installers for the latest released version are available at the [Python\nPackage Index (PyPI)](https://pypi.org/project/pandas) and on [Conda](https://docs.conda.io/en/latest/).\n\n```sh\n# conda\nconda install -c conda-forge pandas\n```\n\n```sh\n# or PyPI\npip install pandas\n```\n\nThe list of changes to pandas between each release can be found\n[here](https://pandas.pydata.org/pandas-docs/stable/whatsnew/index.html). For full\ndetails, see the commit logs at https://github.com/pandas-dev/pandas.\n\n## Dependencies\n- [NumPy - Adds support for large, multi-dimensional arrays, matrices and high-level mathematical functions to operate on these arrays](https://www.numpy.org)\n- [python-dateutil - Provides powerful extensions to the standard datetime module](https://dateutil.readthedocs.io/en/stable/index.html)\n- [pytz - Brings the Olson tz database into Python which allows accurate and cross platform timezone calculations](https://github.com/stub42/pytz)\n\nSee the [full installation instructions](https://pandas.pydata.org/pandas-docs/stable/install.html#dependencies) for minimum supported versions of required, recommended and optional dependencies.\n\n## Installation from sources\nTo install pandas from source you need [Cython](https://cython.org/) in addition to the normal\ndependencies above. Cython can be installed from PyPI:\n\n```sh\npip install cython\n```\n\nIn the `pandas` directory (same one where you found this file after\ncloning the git repo), execute:\n\n```sh\npip install .\n```\n\nor for installing in [development mode](https://pip.pypa.io/en/latest/cli/pip_install/#install-editable):\n\n\n```sh\npython -m pip install -ve . --no-build-isolation --config-settings=editable-verbose=true\n```\n\nSee the full instructions for [installing from source](https://pandas.pydata.org/docs/dev/development/contributing_environment.html).\n\n## License\n[BSD 3](LICENSE)\n\n## Documentation\nThe official documentation is hosted on [PyData.org](https://pandas.pydata.org/pandas-docs/stable/).\n\n## Background\nWork on ``pandas`` started at [AQR](https://www.aqr.com/) (a quantitative hedge fund) in 2008 and\nhas been under active development since then.\n\n## Getting Help\n\nFor usage questions, the best place to go to is [StackOverflow](https://stackoverflow.com/questions/tagged/pandas).\nFurther, general questions and discussions can also take place on the [pydata mailing list](https://groups.google.com/forum/?fromgroups#!forum/pydata).\n\n## Discussion and Development\nMost development discussions take place on GitHub in this repo, via the [GitHub issue tracker](https://github.com/pandas-dev/pandas/issues).\n\nFurther, the [pandas-dev mailing list](https://mail.python.org/mailman/listinfo/pandas-dev) can also be used for specialized discussions or design issues, and a [Slack channel](https://pandas.pydata.org/docs/dev/development/community.html?highlight=slack#community-slack) is available for quick development related questions.\n\nThere are also frequent [community meetings](https://pandas.pydata.org/docs/dev/development/community.html#community-meeting) for project maintainers open to the community as well as monthly [new contributor meetings](https://pandas.pydata.org/docs/dev/development/community.html#new-contributor-meeting) to help support new contributors.\n\nAdditional information on the communication channels can be found on the [contributor community](https://pandas.pydata.org/docs/development/community.html) page.\n\n## Contributing to pandas\n\n[](https://www.codetriage.com/pandas-dev/pandas)\n\nAll contributions, bug reports, bug fixes, documentation improvements, enhancements, and ideas are welcome.\n\nA detailed overview on how to contribute can be found in the **[contributing guide](https://pandas.pydata.org/docs/dev/development/contributing.html)**.\n\nIf you are simply looking to start working with the pandas codebase, navigate to the [GitHub \"issues\" tab](https://github.com/pandas-dev/pandas/issues) and start looking through interesting issues. There are a number of issues listed under [Docs](https://github.com/pandas-dev/pandas/issues?labels=Docs&sort=updated&state=open) and [good first issue](https://github.com/pandas-dev/pandas/issues?labels=good+first+issue&sort=updated&state=open) where you could start out.\n\nYou can also triage issues which may include reproducing bug reports, or asking for vital information such as version numbers or reproduction instructions. If you would like to start triaging issues, one easy way to get started is to [subscribe to pandas on CodeTriage](https://www.codetriage.com/pandas-dev/pandas).\n\nOr maybe through using pandas you have an idea of your own or are looking for something in the documentation and thinking \u2018this can be improved\u2019...you can do something about it!\n\nFeel free to ask questions on the [mailing list](https://groups.google.com/forum/?fromgroups#!forum/pydata) or on [Slack](https://pandas.pydata.org/docs/dev/development/community.html?highlight=slack#community-slack).\n\nAs contributors and maintainers to this project, you are expected to abide by pandas' code of conduct. More information can be found at: [Contributor Code of Conduct](https://github.com/pandas-dev/.github/blob/master/CODE_OF_CONDUCT.md)\n\n<hr>\n\n[Go to Top](#table-of-contents)\n",
"bugtrack_url": null,
"license": "BSD 3-Clause License\n \n Copyright (c) 2008-2011, AQR Capital Management, LLC, Lambda Foundry, Inc. and PyData Development Team\n All rights reserved.\n \n Copyright (c) 2011-2023, Open source contributors.\n \n Redistribution and use in source and binary forms, with or without\n modification, are permitted provided that the following conditions are met:\n \n * Redistributions of source code must retain the above copyright notice, this\n list of conditions and the following disclaimer.\n \n * Redistributions in binary form must reproduce the above copyright notice,\n this list of conditions and the following disclaimer in the documentation\n and/or other materials provided with the distribution.\n \n * Neither the name of the copyright holder nor the names of its\n contributors may be used to endorse or promote products derived from\n this software without specific prior written permission.\n \n THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS \"AS IS\"\n AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE\n IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE\n DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE\n FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL\n DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR\n SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER\n CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,\n OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE\n OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.\n Copyright (c) 2010-2019 Keith Goodman\n Copyright (c) 2019 Bottleneck Developers\n All rights reserved.\n \n Redistribution and use in source and binary forms, with or without\n modification, are permitted provided that the following conditions are met:\n \n * Redistributions of source code must retain the above copyright notice,\n this list of conditions and the following disclaimer.\n \n * Redistributions in binary form must reproduce the above copyright\n notice, this list of conditions and the following disclaimer in the\n documentation and/or other materials provided with the distribution.\n \n THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS \"AS IS\"\n AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE\n IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE\n ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE\n LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR\n CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF\n SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS\n INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN\n CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)\n ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE\n POSSIBILITY OF SUCH DAMAGE.Copyright 2017- Paul Ganssle <paul@ganssle.io>\n Copyright 2017- dateutil contributors (see AUTHORS file)\n \n Licensed under the Apache License, Version 2.0 (the \"License\");\n you may not use this file except in compliance with the License.\n You may obtain a copy of the License at\n \n http://www.apache.org/licenses/LICENSE-2.0\n \n Unless required by applicable law or agreed to in writing, software\n distributed under the License is distributed on an \"AS IS\" BASIS,\n WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n See the License for the specific language governing permissions and\n limitations under the License.\n \n The above license applies to all contributions after 2017-12-01, as well as\n all contributions that have been re-licensed (see AUTHORS file for the list of\n contributors who have re-licensed their code).\n --------------------------------------------------------------------------------\n dateutil - Extensions to the standard Python datetime module.\n \n Copyright (c) 2003-2011 - Gustavo Niemeyer <gustavo@niemeyer.net>\n Copyright (c) 2012-2014 - Tomi Pievil\u00e4inen <tomi.pievilainen@iki.fi>\n Copyright (c) 2014-2016 - Yaron de Leeuw <me@jarondl.net>\n Copyright (c) 2015- - Paul Ganssle <paul@ganssle.io>\n Copyright (c) 2015- - dateutil contributors (see AUTHORS file)\n \n All rights reserved.\n \n Redistribution and use in source and binary forms, with or without\n modification, are permitted provided that the following conditions are met:\n \n * Redistributions of source code must retain the above copyright notice,\n this list of conditions and the following disclaimer.\n * Redistributions in binary form must reproduce the above copyright notice,\n this list of conditions and the following disclaimer in the documentation\n and/or other materials provided with the distribution.\n * Neither the name of the copyright holder nor the names of its\n contributors may be used to endorse or promote products derived from\n this software without specific prior written permission.\n \n THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS\n \"AS IS\" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT\n LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR\n A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR\n CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,\n EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,\n PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR\n PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF\n LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING\n NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS\n SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.\n \n The above BSD License Applies to all code, even that also covered by Apache 2.0.# MIT License\n \n Copyright (c) 2019 Hadley Wickham; RStudio; and Evan Miller\n \n Permission is hereby granted, free of charge, to any person obtaining a copy\n of this software and associated documentation files (the \"Software\"), to deal\n in the Software without restriction, including without limitation the rights\n to use, copy, modify, merge, publish, distribute, sublicense, and/or sell\n copies of the Software, and to permit persons to whom the Software is\n furnished to do so, subject to the following conditions:\n \n The above copyright notice and this permission notice shall be included in all\n copies or substantial portions of the Software.\n \n THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\n AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\n OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE\n SOFTWARE.\n Based on http://opensource.org/licenses/MIT\n \n This is a template. Complete and ship as file LICENSE the following 2\n lines (only)\n \n YEAR:\n COPYRIGHT HOLDER:\n \n and specify as\n \n License: MIT + file LICENSE\n \n Copyright (c) <YEAR>, <COPYRIGHT HOLDER>\n \n Permission is hereby granted, free of charge, to any person obtaining\n a copy of this software and associated documentation files (the\n \"Software\"), to deal in the Software without restriction, including\n without limitation the rights to use, copy, modify, merge, publish,\n distribute, sublicense, and/or sell copies of the Software, and to\n permit persons to whom the Software is furnished to do so, subject to\n the following conditions:\n \n The above copyright notice and this permission notice shall be\n included in all copies or substantial portions of the Software.\n \n THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND,\n EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF\n MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND\n NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE\n LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION\n OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION\n WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.\n The MIT License\n \n Copyright (c) 2008- Attractive Chaos <attractor@live.co.uk>\n \n Permission is hereby granted, free of charge, to any person obtaining\n a copy of this software and associated documentation files (the\n \"Software\"), to deal in the Software without restriction, including\n without limitation the rights to use, copy, modify, merge, publish,\n distribute, sublicense, and/or sell copies of the Software, and to\n permit persons to whom the Software is furnished to do so, subject to\n the following conditions:\n \n The above copyright notice and this permission notice shall be\n included in all copies or substantial portions of the Software.\n \n THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND,\n EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF\n MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND\n NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS\n BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN\n ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN\n CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE\n SOFTWARE.musl as a whole is licensed under the following standard MIT license:\n \n ----------------------------------------------------------------------\n Copyright \u00a9 2005-2020 Rich Felker, et al.\n \n Permission is hereby granted, free of charge, to any person obtaining\n a copy of this software and associated documentation files (the\n \"Software\"), to deal in the Software without restriction, including\n without limitation the rights to use, copy, modify, merge, publish,\n distribute, sublicense, and/or sell copies of the Software, and to\n permit persons to whom the Software is furnished to do so, subject to\n the following conditions:\n \n The above copyright notice and this permission notice shall be\n included in all copies or substantial portions of the Software.\n \n THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND,\n EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF\n MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.\n IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY\n CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,\n TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE\n SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.\n ----------------------------------------------------------------------\n \n Authors/contributors include:\n \n A. Wilcox\n Ada Worcester\n Alex Dowad\n Alex Suykov\n Alexander Monakov\n Andre McCurdy\n Andrew Kelley\n Anthony G. Basile\n Aric Belsito\n Arvid Picciani\n Bartosz Brachaczek\n Benjamin Peterson\n Bobby Bingham\n Boris Brezillon\n Brent Cook\n Chris Spiegel\n Cl\u00e9ment Vasseur\n Daniel Micay\n Daniel Sabogal\n Daurnimator\n David Carlier\n David Edelsohn\n Denys Vlasenko\n Dmitry Ivanov\n Dmitry V. Levin\n Drew DeVault\n Emil Renner Berthing\n Fangrui Song\n Felix Fietkau\n Felix Janda\n Gianluca Anzolin\n Hauke Mehrtens\n He X\n Hiltjo Posthuma\n Isaac Dunham\n Jaydeep Patil\n Jens Gustedt\n Jeremy Huntwork\n Jo-Philipp Wich\n Joakim Sindholt\n John Spencer\n Julien Ramseier\n Justin Cormack\n Kaarle Ritvanen\n Khem Raj\n Kylie McClain\n Leah Neukirchen\n Luca Barbato\n Luka Perkov\n M Farkas-Dyck (Strake)\n Mahesh Bodapati\n Markus Wichmann\n Masanori Ogino\n Michael Clark\n Michael Forney\n Mikhail Kremnyov\n Natanael Copa\n Nicholas J. Kain\n orc\n Pascal Cuoq\n Patrick Oppenlander\n Petr Hosek\n Petr Skocik\n Pierre Carrier\n Reini Urban\n Rich Felker\n Richard Pennington\n Ryan Fairfax\n Samuel Holland\n Segev Finer\n Shiz\n sin\n Solar Designer\n Stefan Kristiansson\n Stefan O'Rear\n Szabolcs Nagy\n Timo Ter\u00e4s\n Trutz Behn\n Valentin Ochs\n Will Dietz\n William Haddon\n William Pitcock\n \n Portions of this software are derived from third-party works licensed\n under terms compatible with the above MIT license:\n \n The TRE regular expression implementation (src/regex/reg* and\n src/regex/tre*) is Copyright \u00a9 2001-2008 Ville Laurikari and licensed\n under a 2-clause BSD license (license text in the source files). The\n included version has been heavily modified by Rich Felker in 2012, in\n the interests of size, simplicity, and namespace cleanliness.\n \n Much of the math library code (src/math/* and src/complex/*) is\n Copyright \u00a9 1993,2004 Sun Microsystems or\n Copyright \u00a9 2003-2011 David Schultz or\n Copyright \u00a9 2003-2009 Steven G. Kargl or\n Copyright \u00a9 2003-2009 Bruce D. Evans or\n Copyright \u00a9 2008 Stephen L. Moshier or\n Copyright \u00a9 2017-2018 Arm Limited\n and labelled as such in comments in the individual source files. All\n have been licensed under extremely permissive terms.\n \n The ARM memcpy code (src/string/arm/memcpy.S) is Copyright \u00a9 2008\n The Android Open Source Project and is licensed under a two-clause BSD\n license. It was taken from Bionic libc, used on Android.\n \n The AArch64 memcpy and memset code (src/string/aarch64/*) are\n Copyright \u00a9 1999-2019, Arm Limited.\n \n The implementation of DES for crypt (src/crypt/crypt_des.c) is\n Copyright \u00a9 1994 David Burren. It is licensed under a BSD license.\n \n The implementation of blowfish crypt (src/crypt/crypt_blowfish.c) was\n originally written by Solar Designer and placed into the public\n domain. The code also comes with a fallback permissive license for use\n in jurisdictions that may not recognize the public domain.\n \n The smoothsort implementation (src/stdlib/qsort.c) is Copyright \u00a9 2011\n Valentin Ochs and is licensed under an MIT-style license.\n \n The x86_64 port was written by Nicholas J. Kain and is licensed under\n the standard MIT terms.\n \n The mips and microblaze ports were originally written by Richard\n Pennington for use in the ellcc project. The original code was adapted\n by Rich Felker for build system and code conventions during upstream\n integration. It is licensed under the standard MIT terms.\n \n The mips64 port was contributed by Imagination Technologies and is\n licensed under the standard MIT terms.\n \n The powerpc port was also originally written by Richard Pennington,\n and later supplemented and integrated by John Spencer. It is licensed\n under the standard MIT terms.\n \n All other files which have no copyright comments are original works\n produced specifically for use as part of this library, written either\n by Rich Felker, the main author of the library, or by one or more\n contibutors listed above. Details on authorship of individual files\n can be found in the git version control history of the project. The\n omission of copyright and license comments in each file is in the\n interest of source tree size.\n \n In addition, permission is hereby granted for all public header files\n (include/* and arch/*/bits/*) and crt files intended to be linked into\n applications (crt/*, ldso/dlstart.c, and arch/*/crt_arch.h) to omit\n the copyright notice and permission notice otherwise required by the\n license, and to use these files without any requirement of\n attribution. These files include substantial contributions from:\n \n Bobby Bingham\n John Spencer\n Nicholas J. Kain\n Rich Felker\n Richard Pennington\n Stefan Kristiansson\n Szabolcs Nagy\n \n all of whom have explicitly granted such permission.\n \n This file previously contained text expressing a belief that most of\n the files covered by the above exception were sufficiently trivial not\n to be subject to copyright, resulting in confusion over whether it\n negated the permissions granted in the license. 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HISTORY OF THE SOFTWARE\n ==========================\n \n Python was created in the early 1990s by Guido van Rossum at Stichting\n Mathematisch Centrum (CWI, see https://www.cwi.nl) in the Netherlands\n as a successor of a language called ABC. Guido remains Python's\n principal author, although it includes many contributions from others.\n \n In 1995, Guido continued his work on Python at the Corporation for\n National Research Initiatives (CNRI, see https://www.cnri.reston.va.us)\n in Reston, Virginia where he released several versions of the\n software.\n \n In May 2000, Guido and the Python core development team moved to\n BeOpen.com to form the BeOpen PythonLabs team. In October of the same\n year, the PythonLabs team moved to Digital Creations, which became\n Zope Corporation. In 2001, the Python Software Foundation (PSF, see\n https://www.python.org/psf/) was formed, a non-profit organization\n created specifically to own Python-related Intellectual Property.\n Zope Corporation was a sponsoring member of the PSF.\n \n All Python releases are Open Source (see https://opensource.org for\n the Open Source Definition). Historically, most, but not all, Python\n releases have also been GPL-compatible; the table below summarizes\n the various releases.\n \n Release Derived Year Owner GPL-\n from compatible? (1)\n \n 0.9.0 thru 1.2 1991-1995 CWI yes\n 1.3 thru 1.5.2 1.2 1995-1999 CNRI yes\n 1.6 1.5.2 2000 CNRI no\n 2.0 1.6 2000 BeOpen.com no\n 1.6.1 1.6 2001 CNRI yes (2)\n 2.1 2.0+1.6.1 2001 PSF no\n 2.0.1 2.0+1.6.1 2001 PSF yes\n 2.1.1 2.1+2.0.1 2001 PSF yes\n 2.1.2 2.1.1 2002 PSF yes\n 2.1.3 2.1.2 2002 PSF yes\n 2.2 and above 2.1.1 2001-now PSF yes\n \n Footnotes:\n \n (1) GPL-compatible doesn't mean that we're distributing Python under\n the GPL. All Python licenses, unlike the GPL, let you distribute\n a modified version without making your changes open source. The\n GPL-compatible licenses make it possible to combine Python with\n other software that is released under the GPL; the others don't.\n \n (2) According to Richard Stallman, 1.6.1 is not GPL-compatible,\n because its license has a choice of law clause. According to\n CNRI, however, Stallman's lawyer has told CNRI's lawyer that 1.6.1\n is \"not incompatible\" with the GPL.\n \n Thanks to the many outside volunteers who have worked under Guido's\n direction to make these releases possible.\n \n \n B. TERMS AND CONDITIONS FOR ACCESSING OR OTHERWISE USING PYTHON\n ===============================================================\n \n Python software and documentation are licensed under the\n Python Software Foundation License Version 2.\n \n Starting with Python 3.8.6, examples, recipes, and other code in\n the documentation are dual licensed under the PSF License Version 2\n and the Zero-Clause BSD license.\n \n Some software incorporated into Python is under different licenses.\n The licenses are listed with code falling under that license.\n \n \n PYTHON SOFTWARE FOUNDATION LICENSE VERSION 2\n --------------------------------------------\n \n 1. This LICENSE AGREEMENT is between the Python Software Foundation\n (\"PSF\"), and the Individual or Organization (\"Licensee\") accessing and\n otherwise using this software (\"Python\") in source or binary form and\n its associated documentation.\n \n 2. Subject to the terms and conditions of this License Agreement, PSF hereby\n grants Licensee a nonexclusive, royalty-free, world-wide license to reproduce,\n analyze, test, perform and/or display publicly, prepare derivative works,\n distribute, and otherwise use Python alone or in any derivative version,\n provided, however, that PSF's License Agreement and PSF's notice of copyright,\n i.e., \"Copyright (c) 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010,\n 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023 Python Software Foundation;\n All Rights Reserved\" are retained in Python alone or in any derivative version\n prepared by Licensee.\n \n 3. In the event Licensee prepares a derivative work that is based on\n or incorporates Python or any part thereof, and wants to make\n the derivative work available to others as provided herein, then\n Licensee hereby agrees to include in any such work a brief summary of\n the changes made to Python.\n \n 4. 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