semvec/pypi-packages huggingface dataset:
fixturebuilder_py 1.2.9
Build fixtures from a single source
License: MIT
Keywords: testing
fixture
test data

fixturebuilder_py
=================


Install
-------

.. code-block:: bash

    $ pip install fixturebuilder


Usage
-----

.. code-block:: python

    # define the data structure to be worked on
    start_data = {
        'prop1': 'value1',
        'prop2': 'value2',
        'dict1': {
            'dictprop1': 'dictvalue1'
        },
        'list1': [
            'listvalue1',
            'listvalue2'
        ],
        'list2': [
            {'listdictprop1': 'listdictprop1', 'listdictlist1': ['listdictlistvalue1']}
        ]
    }

    # initialize a new builder
    builder = FixtureBulder.create(start_data)

    # retrieve the data unchanged
    test_data1 = builder.data

    # set a new value on a property and retrieve the updated data
    test_data2 = builder.set('prop1', 1).data

    # do complex manipulation on the start_data and retrieve the modified data
    test_data3 = builder
        .with_dict('dict1')  # descend into 'dict1' and work on it's properties
            .set('dictprop1', 12)
            .set('newlist', ['value'])
            .add('newlist', 'additional value')  # add a new value to a list
            .set('newdict', {'someprop': 'some value'})
            .with_dict('newdict')
                .set('someprop', 'change previously created value')
            .done()  # finish working on 'newdict' and return to 'dict1'
        .done()  # finish working on 'dict1' and return to the root
        .data


    test_data4 = builder
        .duplicate_last_list_entry('list2')  # append a duplicated dict to the list
        .with_dict_list_element('list2')     # descend into the last list element to work on it's properties
            .add('listdictlist1', 'new value1')
            .set('listdictprop1', False)
        .done()  # finish working on the list element and return to the root
        .data

    # retrieve the original unmodified data
    original_data = builder.data

    # setting new property raises an error
    builder.set('newprop', 'newvalue')
turing-chatroom-bus 0.0.1.post0.dev12
Chatroom by Socket.IO
License: MIT

turing-chatroom-bus
------------------------------------------------

Response
================================================

Success
################################################

.. code-block:: json

    {
      "_uid": <The id of the request>,
      "success": <true or false>,
      "error": <[Optional] error message>
    }


Register
=================================================

client
#################################################

.. code-block:: json

    {
      "_uid": <uuid>,
      "path": <client path>
    }

RPC
=================================================

RPC Request
#################################################

.. code-block:: json

    {
      "_uid": <uuid>,
      "path": <target path>,
      "payload": {
        "id": <RPC request id>,
        "method": <method name>,
        "parameters": <parameters>
      }
    }

RPC Response
#################################################

.. code-block:: json

    {
      "_uid": <uuid>,
      "path": <RPC request source path>,
      "payload": {
        "id": <RPC request id>,
        "result": <RPC result>,
        "error": <error message>
      }
    }
scratch 1.0.0
Interface Python with MIT Scratch 1.3+ (not 2.x)
License: MIT
Keywords: Scratch education

This package enables communication between Python and Scratch 1.3+ (not 2.x) 
using the remote sensors feature of Scratch.

Remember to enable remote sensors in Scratch!  To do this:

1. Go to Sensing
2. Right-click on a 'sensor value'
3. Select 'enable remote sensor connections'

Example usage:

::

    import scratch
    s = scratch.Scratch()

    # to make a broadcast to scratch
    s.broadcast("from python")

    # to receive an update from scratch
    message = s.receive()
    # blocks until an update is received
    # message returned as  {'broadcast': [], 'sensor-update': {'scratchvar': '64'}}
    #                  or  {'broadcast': ['from scratch'], 'sensor-update': {}}
    # where scratchvar is the name of a variable in scratch
    # and 'from scratch' is the name of a scratch broadcast

    # send sensor updates to scratch
    data = {}
    data['pyvar'] = 123
    for data['pycounter'] in range(60):
        s.sensorupdate(data)

0.0.1a
------
Initial version

1.0.0
-----
First release - module unchanged from 0.0.1a
fileshelf 0.0.1
Organize and Search your Files.
License: MIT

.. image:: https://travis-ci.org/MacHu-GWU/fileshelf-project.svg?branch=master
    :target: https://travis-ci.org/MacHu-GWU/fileshelf-project?branch=master

.. image:: https://codecov.io/gh/MacHu-GWU/fileshelf-project/branch/master/graph/badge.svg
  :target: https://codecov.io/gh/MacHu-GWU/fileshelf-project

.. image:: https://img.shields.io/pypi/v/fileshelf.svg
    :target: https://pypi.python.org/pypi/fileshelf

.. image:: https://img.shields.io/pypi/l/fileshelf.svg
    :target: https://pypi.python.org/pypi/fileshelf

.. image:: https://img.shields.io/pypi/pyversions/fileshelf.svg
    :target: https://pypi.python.org/pypi/fileshelf

.. image:: https://img.shields.io/badge/Star_Me_on_GitHub!--None.svg?style=social
    :target: https://github.com/MacHu-GWU/fileshelf-project


Welcome to ``fileshelf`` Documentation
==============================================================================

A web app to organize and search your file in your own way.


Quick Links
------------------------------------------------------------------------------

- .. image:: https://img.shields.io/badge/Link-Document-red.svg
      :target: http://www.wbh-doc.com.s3.amazonaws.com/fileshelf/index.html

- .. image:: https://img.shields.io/badge/Link-API_Reference_and_Source_Code-red.svg
      :target: http://www.wbh-doc.com.s3.amazonaws.com/fileshelf/py-modindex.html

- .. image:: https://img.shields.io/badge/Link-Install-red.svg
      :target: `install`_

- .. image:: https://img.shields.io/badge/Link-GitHub-blue.svg
      :target: https://github.com/MacHu-GWU/fileshelf-project

- .. image:: https://img.shields.io/badge/Link-Submit_Issue_and_Feature_Request-blue.svg
      :target: https://github.com/MacHu-GWU/fileshelf-project/issues

- .. image:: https://img.shields.io/badge/Link-Download-blue.svg
      :target: https://pypi.python.org/pypi/fileshelf#downloads


.. _install:

Install
------------------------------------------------------------------------------

``fileshelf`` is released on PyPI, so all you need is:

.. code-block:: console

    $ pip install fileshelf

To upgrade to latest version:

.. code-block:: console

    $ pip install --upgrade fileshelf
WordEmbeddingLoader 0.2.1
Loaders and savers for different implentations of word embedding.
License: MIT

.. -*- coding: utf-8; -*-

Loaders and savers for different implentations of `word embedding <https://en.wikipedia.org/wiki/Word_embedding>`_. The motivation of this project is that it is cumbersome to write loaders for different pretrained word embedding files. This project provides a simple interface for loading pretrained word embedding files in different formats.

.. code:: python

   from word_embedding_loader import WordEmbedding

   # it will automatically determine format from content
   wv = WordEmbedding.load('path/to/embedding.bin')

   # This project provides minimum interface for word embedding
   print wv.vectors[wv.vocab['is']]

   # Modify and save word embedding file with arbitrary format
   wv.save('path/to/save.txt', 'word2vec', binary=False)


This project currently supports following formats:

* `GloVe <https://nlp.stanford.edu/projects/glove/>`_, Global Vectors for Word Representation, by Jeffrey Pennington, Richard Socher, Christopher D. Manning from Stanford NLP group.
* `word2vec <https://code.google.com/archive/p/word2vec/>`_, by Mikolov.
    - text (create with ``-binary 0`` option (the default))
    - binary (create with ``-binary 1`` option)
* `gensim <https://radimrehurek.com/gensim/>`_ 's ``models.word2vec`` module (coming)
* original HDFS format: a performance centric option for loading and saving word embedding (coming)


Sometimes, you want combine an external program with word embedding file of your own choice. This project also provides a simple executable to convert a word embedding format to another.

.. code:: bash

   # it will automatically determine the format from the content
   word-embedding-loader convert -t glove test/word_embedding_loader/word2vec.bin test.bin

   # Get help for command/subcommand
   word-embedding-loader --help
   word-embedding-loader convert --help

Issues with encoding
--------------------

This project does decode vocab. It is up to users to determine and decode bytes.

.. code:: python

    decoded_vocab = {k.decode('latin-1'): v for k, v in wv.vocab.iteritems()}


.. notes::

   Encoding of pretrained word2vec is latin-1. Encoding of pretrained
   glove is utf-8


Development
============

This project us Cython to build some modules, so you need Cython for development.

```bash
pip install -r requirements.txt
```

If environment variable ``DEVELOP_WE`` is set, it will try to rebuild ``.pyx`` modules.

```bash
DEVELOP_WE=1 python setup.py test
```
tinysumma 0.1.0
Summarize tinyletter statistics
License: MIT
Keywords: newsletter,tinyletter,command line,cli

tinysumma 0.1.0: summarize tinyletter statistics
================================================

Python package providing a friendly command-line interface to summarize tinyletter email newsletter statistics.

Built on top of `tinyapi`_, which wraps around TinyLetter's API, which is publicly accessible but undocumented—so, no guarantees.

.. _tinyapi: https://github.com/jsvine/tinyapi

Usage
-----

``tinysumma`` runs as a command-line script. Sample usage:

::

	>>tinysumma --help
	usage: tinysumma [-h] [-l] [-n NUMBEREDISSUE] [-u LETTERNAME]
					 [--datadir DATADIR]

	optional arguments:
	  -h, --help            show this help message and exit
	  -l, --latestissue     print stats latest issue
	  -n NUMBEREDISSUE, --numberedissue NUMBEREDISSUE
							print stats for numbered issue (first=1)
	  -u LETTERNAME, --updateletter LETTERNAME
							download latest stats to *.csv
	  --datadir DATADIR     data directory (if not current dir)

	>>tinysumma --updateletter mytinyletter
	Password:

	>>tinysumma --latestissue
	Your issue, 'Issue Title', was opened by 42 unique subscribers.
	That's a 75.0% open rate!
	The most popular url was https://github.com/awbirdsall/tinysumma,
	with 17 total clicks.
	A total of 9 urls were clicked.

Every time that ``tinysumma --updateletter mytinyletter`` is run, it writes three csv files: ``messages.csv``, ``urls.csv`` and ``subscribers.csv`` (default: current directory, unless other path passed in with ``--datadir`` flag). The command overwrites existing files with those names, without requiring confirmation! All summary data reported by other commands are taken from those files.

The csv files provide a lot more information than what ``tinysumma`` summarizes! A more in-depth analysis can always be performed outside of ``tinysumma`` (e.g., starting with ``pandas.read_csv()``).

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

Install using ``pip``.

Install from PyPI:

::

    pip install tinysumma

Install most recent Github commit (stability not guaranteed):

::

    pip install git+https://github.com/awbirdsall/tinysumma

Dependencies
------------

Tested on Python 3.5.

Requires ``tinyapi`` and ``pandas`` (installation of which should be automatically handled by ``pip``).

Running the tests requires ``pytest``.

Testing
-------

Tests are located in the ``tests/`` subfolder and can be run using ``py.test``.

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

Posting issues or pull requests to the `github page`_ is welcome!

.. _github page: https://github.com/awbirdsall/pyvap