semvec/pypi-packages huggingface dataset:
hexbytes 2.0.0b1
hexbytes: Python `bytes` subclass that decodes hex, with a readable console output
Requires Python: <4,>=3.10
Keywords: ethereum

# HexBytes

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[![Build Status](https://circleci.com/gh/ethereum/hexbytes.svg?style=shield)](https://circleci.com/gh/ethereum/hexbytes)
[![PyPI version](https://badge.fury.io/py/hexbytes.svg)](https://badge.fury.io/py/hexbytes)
[![Python versions](https://img.shields.io/pypi/pyversions/hexbytes.svg)](https://pypi.python.org/pypi/hexbytes)
[![Docs build](https://readthedocs.org/projects/hexbytes/badge/?version=latest)](https://hexbytes.readthedocs.io/en/latest/?badge=latest)

Python `bytes` subclass that decodes hex, with a readable console output

Read the [documentation](https://hexbytes.readthedocs.io/).

View the [change log](https://hexbytes.readthedocs.io/en/latest/release_notes.html).

## Installation

```sh
python -m pip install hexbytes
```
snakeoil 0.11.0
misc common functionality and useful optimizations
Requires Python: ~=3.11

|pypi| |test| |coverage|

========
snakeoil
========

snakeoil is a python library that implements optimized versions of common
python functionality. Some classes and functions have cython equivalents,
but they all have native python implementations too.

Installing
==========

Installing latest pypi release::

    pip install snakeoil

Installing from git::

    pip install https://github.com/pkgcore/snakeoil/archive/master.tar.gz

Installing from a tarball::

    pip install .

Tests
=====

Normal pytest is used, just execute::

    pytest

Using tox for all supported python versions::

    tox

Using tox for a specific python version::

    tox -e py311

Contact
=======

For bugs and feature requests please create an issue on Github_.


.. _Github: https://github.com/pkgcore/snakeoil/issues

.. |pypi| image:: https://img.shields.io/pypi/v/snakeoil.svg
    :target: https://pypi.python.org/pypi/snakeoil
.. |test| image:: https://github.com/pkgcore/snakeoil/workflows/test/badge.svg
    :target: https://github.com/pkgcore/snakeoil/actions?query=workflow%3A%22test%22
.. |coverage| image:: https://codecov.io/gh/pkgcore/snakeoil/branch/master/graph/badge.svg
    :target: https://codecov.io/gh/pkgcore/snakeoil
daops 0.16.0
Dataset-Aware Operations.
Requires Python: >=3.11
Keywords: daops

daops - data-aware operations
=============================

.. image:: https://img.shields.io/pypi/v/daops.svg
    :target: https://pypi.python.org/pypi/daops
    :alt: PyPI

.. image:: https://github.com/roocs/daops/workflows/build/badge.svg
    :target: https://github.com/roocs/daops/actions
    :alt: Build Status

.. image:: https://readthedocs.org/projects/daops/badge/?version=latest
    :target: https://daops.readthedocs.io/en/latest/?badge=latest
    :alt: Documentation

.. image:: https://img.shields.io/badge/code%20style-black-000000.svg
    :target: https://github.com/python/black
    :alt: Python Black

The ``daops`` library (pronounced "day-ops") provides a python interface to a
set of operations suitable for working with climate simulation outputs. It is
typically used with ESGF data sets that are described in NetCDF files. ``daops``
is unique in that it accesses a store of *fixes* defined for datasets that are
irregular when compared with others in their *population*.

When a ``daops`` operation, such as ``subset``\ , is requested, the library will look
up a database of known fixes before performing and calculations or transformations.
The data will be loaded and *fixed* using the `xarray <http://xarray.pydata.org/>`_
library before the any actual operations are sent to its sister library
`clisops <https://github.com/roocs/clisops>`_.

* Free software: BSD
* Documentation: https://daops.readthedocs.io

Features
--------

The package has the following features:

* Ability to run *data-reduction* operations on large climate data sets.
* Knowledge of irregularities/anomalies in some climate data sets.
* Ability to apply *fixes* to those data sets before operating on them.
  This process is called *normalisation* of the data sets.

Credits
=======

This package was created with ``Cookiecutter`` and the ``cedadev/cookiecutter-pypackage`` project template.

* Cookiecutter: https://github.com/audreyr/cookiecutter
* cookiecutter-pypackage: https://github.com/cedadev/cookiecutter-pypackage