semvec/pypi-packages huggingface dataset:
BiblioPixel 3.4.46
BiblioPixel is a pure python library for manipulating a wide variety of LED strip based displays, both in strip and matrix form.
License: MIT

BiblioPixel: the light programming system
------------------------------------------

`Documentation <https://maniacallabs.github.io/BiblioPixel>`_...
---------------------------------------------------------------------

.. code-block:: yaml

       animation: $bpa.matrix.bloom
       shape: [64, 64]


.. image:: https://raw.githubusercontent.com/ManiacalLabs/DocsFiles/master/BiblioPixel/README.gif
   :target: https://raw.githubusercontent.com/ManiacalLabs/DocsFiles/master/BiblioPixel/README.gif
   :alt: Result
facebook-py-sdk 1.2.1
Facebook Python SDK
License: MIT

Facebook SDK Python
===================

.. image:: https://travis-ci.org/eventbrite/facebook-py-sdk.svg?branch=master
    :target: https://travis-ci.org/eventbrite/facebook-py-sdk
.. image:: https://coveralls.io/repos/github/eventbrite/facebook-py-sdk/badge.svg
    :target: https://coveralls.io/github/eventbrite/facebook-py-sdk

Facebook SDK Python is a python based implementation of `Facebook PHP SDK`_

.. contents:: Table of Contents


Installation
============

To install Facebook SDK Python, simply:

.. code-block:: bash

    $ pip install facebook-py-sdk

Usage
=====

Retrieve User Profile
---------------------

.. code-block:: python

    from facebook_sdk.exceptions import FacebookResponseException
    from facebook_sdk.facebook import Facebook

    facebook = Facebook(
        app_id='{app_id}',
        app_secret='{app_secret}',
        default_graph_version='v2.12',
    )

    facebook.set_default_access_token(access_token='{access_token}')

    try:
        response = facebook.get(endpoint='/me?fields=id,name')
    except FacebookResponseException as e:
        print(e.message)
    else:
        print('User id: %(name)s' % {'name': response.json_body.get('id')})
        print('User name: %(name)s' % {'name': response.json_body.get('name')})


Batch Upload Files
------------------

.. code-block:: python

    from facebook_sdk.exceptions import FacebookResponseException
    from facebook_sdk.facebook import Facebook

    facebook = Facebook(
        app_id='{app_id}',
        app_secret='{app_secret}',
    )

    facebook.set_default_access_token(access_token='{access_token}')

    batch = {
        'photo-one': facebook.request(
            endpoint='/me/photos',
            params={
                'message': 'Foo photo.',
                'source': facebook.file_to_upload('path/to/foo.jpg'),
            },
        ),
        'photo-two': facebook.request(
            endpoint='/me/photos',
            params={
                'message': 'Bar photo.',
                'source': facebook.file_to_upload('path/to/bar.jpg'),
            },
        ),
        'photo-three': facebook.request(
            endpoint='/me/photos',
            params={
                'message': 'Other photo.',
                'source': facebook.file_to_upload('path/to/other.jpg'),
            },
        )
    }

    try:
        responses = facebook.send_batch_request(requests=batch)
    except FacebookResponseException as e:
        print(e.message)


Dependencies
============

Dependencies that to use the application:

* requests_

.. _requests: http://docs.python-requests.org/en/latest/
.. _Facebook PHP SDK: https://developers.facebook.com/docs/reference/php/

Contributing
============

Please use github model by forking the repository and making Pull Requests.

Running tests
-------------

.. code-block:: bash

 ➜  facebook-python-sdk $ pip install -e .[testing]
 ➜  facebook-python-sdk $ pytest
mdsimseval 0.1.1
Collective analysis on a set of Molecular Dynamics simulations.
License: MIT
Requires Python: >=3.6.9,<4.0.0
Keywords: molecular-dynamics,RMSF

# MD Feature Extraction and Evaluation

**MDSimsEval** is a package we created as part of my undergraduate thesis that in a flexible way calculates useful
metrics from a collection of Molecular Dynamics (MD) simulations, stores them and provides a number of methods for
analysis and classification.  
  
More specifically the use case we developped this package for was to define and evaluate models used 
for discriminating agonist vs. antagonist ligands of the 5-HT2A receptor.

**Install**: `pip install mdsimseval`  
  
[More can be found on the docs](https://mikexydas.github.io/MDSimsEval/).

## Thesis Abstract

Molecular dynamics (MD) is a computer simulation method for analyzing the physical
movements of atoms and molecules. The atoms and molecules are allowed to interact
for a fixed period of time, giving a view of the dynamic &quot;evolution&quot; of the system. Then
the output of these simulations is analyzed in order to arrive to conclusions depending
on the use case.

In our use case we were provided with several simulations between ligands and the 5-HT2A 
receptor which is the main excitatory receptor subtype among the G protein-
coupled receptor (GPCRs) for serotonin and a target for many antipsychotic drugs. Our
simulations were of two classes. Some of the ligands were agonists meaning that they
activated the receptor, while the other were antagonists meaning that they blocked the
activation of the receptor.

Our goal was to find a set of features that was able to discriminate agonists from
antagonists with a degree of certainty. The small discriminative power of the currently
well-known descriptors of the simulations motivated us to dig deeper and extract a
custom-made feature set. We accomplished that by defining a method which is able to
find in a robust way, the residues of the receptor that had the most statistically
significant separability between the two classes.