Metadata-Version: 2.1
Name: pyarrow
Version: 0.12.1
Summary: Python library for Apache Arrow
Home-page: https://arrow.apache.org/
Maintainer: Apache Arrow Developers
Maintainer-email: dev@arrow.apache.org
License: Apache License, Version 2.0
Platform: UNKNOWN
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Description-Content-Type: text/markdown
Requires-Dist: numpy (>=1.14)
Requires-Dist: six (>=1.0.0)
Requires-Dist: futures; python_version < "3.2"

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## Python library for Apache Arrow

This library provides a Python API for functionality provided by the Arrow C++
libraries, along with tools for Arrow integration and interoperability with
pandas, NumPy, and other software in the Python ecosystem.

## Installing

Across platforms, you can install a recent version of pyarrow with the conda
package manager:

```shell
conda install pyarrow -c conda-forge
```

On Linux/macOS and Windows, you can also install binary wheels from PyPI with pip:

```shell
pip install pyarrow
```

## Development

### Coding Style

We follow a similar PEP8-like coding style to the [pandas project][3].

The code must pass `flake8` (available from pip or conda) or it will fail the
build. Check for style errors before submitting your pull request with:

```
flake8 .
flake8 --config=.flake8.cython .
```

### Building from Source

See the [Development][2] page in the documentation.

### Running the unit tests

We are using [pytest][4] to develop our unit test suite. After building the
project using `setup.py build_ext --inplace`, you can run its unit tests like
so:

```bash
pytest pyarrow
```

The project has a number of custom command line options for its test
suite. Some tests are disabled by default, for example. To see all the options,
run

```bash
pytest pyarrow --help
```

and look for the "custom options" section.

For running the benchmarks, see the [Sphinx documentation][5].

### Building the documentation

```bash
pip install -r ../docs/requirements.txt
python setup.py build_sphinx -s ../docs/source
```

[2]: https://github.com/apache/arrow/blob/master/docs/source/python/development.rst
[3]: https://github.com/pandas-dev/pandas
[4]: https://docs.pytest.org/en/latest/
[5]: https://arrow.apache.org/docs/latest/python/benchmarks.html


