semvec/pypi-packages huggingface dataset:
PyOmics 0.0.1.dev6
A library for dealing with omic-data in the life sciences
License: MIT
Keywords: PyOmics bioinformatics omics science data analysis easy

PyOmics
=======

|Version| |Build Status|

**PyOmics - A library for dealing with omic-data in the life sciences**

Info
~~~~

Project has started in April 2017. So there are not a lot of things
online right now.

The goal of the project is to build some nice functionality for many
tasks with which scientists have to deal on a daily basis.

Feel free to make suggestions to the project and I'm looking forward to
any contributions.

Installation
~~~~~~~~~~~~

Simply use the Python package index to install PyOmics. This way is
recommended since it provides full pip functionality (upgrade,
uninstall).

.. code:: shell

    $ pip install PyOmics

Alternatively, you can clone the repository and manually run setup.py.
This will always give you the latest version of PyOmics, but might be
unstable at some point.

.. code:: shell

    $ git clone https://github.com/FloBay/PyOmics.git
    $ cd <path_to>/PyOmics
    $ python setup.py install

Documentation
~~~~~~~~~~~~~

There is no official documentation file available (so far). Sorry about
that !! At some point in the future, however, there will be one
available.

Meanwhile, PyOmics places a high premium on well documented source code
in compliance with several PEPs. Docstrings are written according to the
NumPy/SciPy Documentation formatting Guide.

.. |Version| image:: https://img.shields.io/pypi/v/PyOmics.svg
   :target: https://pypi.python.org/pypi/PyOmics
.. |Build Status| image:: https://travis-ci.org/FloBay/PyOmics.svg?branch=master
   :target: https://travis-ci.org/FloBay/PyOmics
kubetop 17.4.17.1
A top(1)-like tool for Kubernetes.
License: MIT

kubetop
=======

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

.. image:: https://travis-ci.org/LeastAuthority/kubetop.svg
   :target: https://travis-ci.org/LeastAuthority/kubetop
   :alt: CI status

.. image:: https://codecov.io/github/LeastAuthority/kubetop/coverage.svg
   :target: https://codecov.io/github/LeastAuthority/kubetop
   :alt: Coverage

What is this?
-------------

kubetop is a top(1)-like tool for `Kubernetes`_.

Usage Sample
------------

.. code-block:: sh

   $ kubetop

Output Sample
-------------

.. code-block::

   kubetop - 13:02:57
   Node 0 CPU%   9.80 MEM% 57.97 (   2 GiB/   4 GiB)  POD%  7.27 (  8/110) Ready
   Node 1 CPU%  21.20 MEM% 59.36 (   2 GiB/   4 GiB)  POD%  3.64 (  4/110) Ready
   Node 2 CPU%  99.90 MEM% 58.11 (   2 GiB/   4 GiB)  POD%  7.27 (  8/110) Ready
   Pods:       20 total        0 running        0 terminating        0 pending
                    POD               (CONTAINER)        %CPU         MEM   %MEM
   s4-infrastructure-3073578190-2k2vw                    75.5  782.05 MiB  20.76
                         (subscription-converger)        72.7  459.11 MiB
                                    (grid-router)         2.7   98.07 MiB
                                            (web)         0.1   67.61 MiB
                           (subscription-manager)         0.0   91.62 MiB
                          (foolscap-log-gatherer)         0.0   21.98 MiB
                                          (flapp)         0.0   21.46 MiB
                                 (wormhole-relay)         0.0   22.19 MiB

Installing
----------

To install the latest version of kubetop using pip::

  $ pip install kubetop

Testing
-------

kubetop uses pyunit-style tests.
After installing the development dependencies, you can run the test suite with trial::

  $ pip install kubetop[dev]
  $ trial kubetop

Version
-------

kubetop uses the `CalVer`_ versioning convention.
The first three segments of a kubetop version tell you the year (two digit), month, and day that version was released.
The fourth segment of a kubetop version is a bugfix release counter.
It is present if a new release is made that diffs from a previous release only by including one or more bug fixes.
For each bug fix release, the fourth segment is incremented.

License
-------

txkube is open source software released under the MIT License.
See the LICENSE file for more details.


.. _Kubernetes: https://kubernetes.io/
.. _CalVer: http://calver.org/
fjlc 1.0.3
A Python port of the Fredriksen-Jahren Lexicon Classifier
License: MIT
Keywords: twitter sentiment analysis lexicon

Lexicon Classifier
==================

Source code: https://github.com/draperunner/fjlc

This package is a Python port of the Lexicon Creator and Classifier of
Valerij Fredriksen and Brage Ekroll Jahren (2016). It is compatible with
Python version >= 3.

The original Java code is available here:
https://github.com/freva/Masteroppgave

If using this package in your publications, please cite > Valerij
Fredriksen and Brage Ekroll Jahren. Twitter Sentiment Analysis:
Exploring Automatic Creation of Sentiment Lexica. Master's thesis, 2016.

Installation
------------

.. code:: bash

    pip install fjlc

Lexicon Classifier
------------------

The ``LexiconClassifier`` uses the best performing lexicon of Fredriksen
and Jahren. You can specify your own lexicon, see Options below.

Usage
~~~~~

.. code:: python

    from fjlc import LexiconClassifier
    lc = LexiconClassifier()

You can classify a single tweet or a list of tweets:

::

    >>> lc.classify("I am happy!")
    'POSITIVE'
    >>> lc.classify(["I am happy!", "I hate rain"])
    ['POSITIVE', 'NEGATIVE']

You can get the sentiment value of a single tweet or multiple tweets

::

    >>> lc.classify("I am happy!")
    5.599244615570646
    >>> lc.classify(["I am happy!", "I hate rain"])
    [5.599244615570646, -2.767224666516315]

Options
~~~~~~~

The ``LexiconClassifier`` takes three options: \* ``lexicon``: Path to
sentiment lexicon file \* ``options``: Path to options file \*
``dictionary``: Path to canonical dictionary

Lexicon Creator
---------------

Usage
~~~~~

.. code:: python

    from fjlc import LexiconCreator
    lc = LexiconCreator()

Incomplete, untested.
humilis-es 0.0.6
Humilis plug-in to create an Elasticsearch domain
License: MIT

Humilis plug-in to deploy an Elasticsearch domain
=================================================

|PyPI|

A `humilis <https://github.com//humilis/blob/master/README.md>`__
plug-in layer that provides support for layer type ``es``, which deploys
an `Elasticsearch <https://aws.amazon.com/elasticsearch-service/>`__
domain into a humilis environment.

Installation
------------

::

    pip install humilis-es

To install the development version:

::

    pip install git+https://github.com/humilis/humilis-es

Development
-----------

Assuming you have
`virtualenv <https://virtualenv.readthedocs.org/en/latest/>`__
installed:

::

    make develop

Configure humilis:

::

    make configure

Testing
-------

There is no logic in this layer beyond the deployment of AWS resources
so there is no unit test suite. You can test the deployment of a dummy
ES domain with:

::

    make testi

Layer parameters
----------------

Layer type ``es`` accepts the following parameters.

Required
~~~~~~~~

-  ``domain_name``: The actual name will be
   ``[envname]-[stage]-[domain_name]``

Optional
~~~~~~~~

-  ``whitelisted_ips``: A list of whitelisted CIDRs or IPs.
-  ``iam_users_arns``: These users will be given full access to the ES
   domain.
-  ``iam_roles_arns``: These roles will be given full access to the ES
   domain.

More information
----------------

See `humilis <https://github.com//humilis/blob/master/README.md>`__
documentation.

Contact
-------

If you have questions, bug reports, suggestions, etc. please create an
issue on the `GitHub project
page <http://github.com/humilis/humilis-es>`__.

License
-------

This software is licensed under the `MIT
license <http://en.wikipedia.org/wiki/MIT_License>`__.

See `License
file <https://github.com/humilis/humilis-es/blob/master/LICENSE.txt>`__.

© 2016 German Gomez-Herrero, `Find
Hotel <http://company.findhotel.net>`__ and others.

.. |PyPI| image:: https://img.shields.io/pypi/v/humilis-es.svg?style=flat
   :target: https://pypi.python.org/pypi/humilis-es