semvec/pypi-packages huggingface dataset:
madbot-extra 4
Framework to program bot. JSON backend. MIT license
License: MIT

MADBOT is a python3 framework to use if you want to program IRC or XMPP bot.

PROVIDES

| CLI, IRC and XMPP bot.
| REST server to serve objects of a bot.
| RSS fetcher are provided as well.
| custom written eventhandler.
| launch threads.
| sync objects to disk and back.

CONTACT

| Bart Thate
| botfather on #dunkbot irc.freenode.net
| bthate@dds.nl, thatebart@gmail.com


| MADBOT is code released onder een MIT compatible license.
| MADBOT is een event logger.
doublify-toolkit 0.5.2
Doublify API toolkit for Python
License: MIT
Keywords: doublify toolkit

Doublify API Toolkit
====================

|Travis| |PyPI| |RDT|

    Doublify API toolkit

Contribute
----------

PRs accepted.

License
-------

`MIT`_ (c) Doublify Technologies

.. |Travis| image:: https://travis-ci.org/doublifyapis/toolkit-python.svg?branch=master
    :target: https://travis-ci.org/doublifyapis/toolkit-python

.. |PyPI| image:: https://badge.fury.io/py/doublify-toolkit.svg
    :target: https://badge.fury.io/py/doublify-toolkit

.. |RDT| image:: https://readthedocs.org/projects/doublify-api-toolkit-for-python/badge/?version=latest
    :target: http://doublify-api-toolkit-for-python.readthedocs.io/en/latest/

.. _toolkit/filtering: /doublify/toolkit/filtering
.. _MIT: LICENSE
limix-inference 1.1.6
Fast inference for Generalized Linear Mixed Models.
License: MIT

limix-inference
===============

|PyPIl| |PyPIv| |Anaconda-Server Badge| |Documentation Status|

Fast inference for Generalized Linear Mixed Models.

Install
-------

The recommended way of installing it is via
`conda <http://conda.pydata.org/docs/index.html>`__

.. code:: bash

    conda install -c conda-forge limix-inference

An alternative way would be via
`pip <https://pypi.python.org/pypi/pip>`__. First you need to install
`liknorm <http://liknorm.readthedocs.io/en/latest/>`__ library and then

.. code:: bash

    pip install limix-inference

Refer to
`documentation <http://limix-inference.readthedocs.io/en/latest/>`__ for
more information.

Running the tests
-----------------

After installation, you can test it

::

    python -c "import limix_inference; limix_inference.test()"

as long as you have `pytest <http://docs.pytest.org/en/latest/>`__.

Authors
-------

-  **Danilo Horta** - https://github.com/Horta

License
-------

This project is licensed under the MIT License - see the
`LICENSE <LICENSE>`__ file for details

.. |PyPIl| image:: https://img.shields.io/pypi/l/limix-inference.svg?style=flat-square
   :target: https://pypi.python.org/pypi/limix-inference/
.. |PyPIv| image:: https://img.shields.io/pypi/v/limix-inference.svg?style=flat-square
   :target: https://pypi.python.org/pypi/limix-inference/
.. |Anaconda-Server Badge| image:: https://anaconda.org/conda-forge/limix-inference/badges/version.svg
   :target: https://anaconda.org/conda-forge/limix-inference
.. |Documentation Status| image:: https://readthedocs.org/projects/limix-inference/badge/?style=flat-square&version=latest
   :target: https://limix-inference.readthedocs.io/en/latest/
nfft 0.1
nfft: pure-python nonuniform fast Fourier transform
License: MIT

nfft
====
nfft is a pure-python implementation of the nonuniform fast Fourier transform.
Its performance is comparable to that of [pynfft](https://pypi.python.org/pypi/pyNFFT),
but it contains no compiled code and requires no links to external C libraries:
it depends only on [numpy](http://numpy.org) and [scipy](http://scipy.org).

For more information and links to usage examples, please see the
repository README_.

.. _README: https://github.com/jakevdp/nfft/blob/master/README.md

License
=======
``nfft`` is licensed under the terms of the MIT license. See the file
"LICENSE" for information on the history of this software, terms & conditions
for usage, and a DISCLAIMER OF ALL WARRANTIES.