semvec/pypi-packages huggingface dataset:
an_example_pypi_project 0.0.5
An demonstration of how to create, document, and publish to the cheese shop a5 pypi.org.
License: BSD
Keywords: example documentation tutorial

.. include globals.rst

.. an_example_pypi_project documentation master file, created by
   sphinx-quickstart on Thu Nov 05 22:55:49 2009.
   You can adapt this file completely to your liking, but it should at least
   contain the root `toctree` directive.

Welcome to an_example_pypi_project's documentation!
***************************************************

Introduction: This Package is a Tutorial
========================================

This is just a demonstration vehicle used to take you through the process 
-- start to finish -- of creating a Python project that can be:

	1. Uploaded to
	2. Distributed from 

	and 

	3. Documented on
	
the Python Package Index (aka pypi or the cheeseshop) at http://pypi.python.org/pypi. 
This project uses setuptools, sphinx, and the Sphinx-PyPI-upload
(http://pypi.python.org/pypi/Sphinx-PyPI-upload/0.2.1). 

This demonstration is not meant to be complete nor authoritative. It's just a 
recording of the steps I took to get some projects onto pypi and 
hopefully it might save someone some time from googling around.  To be sure, 
this is simply just *one* way to make a project, document it, and get it 
on pypi. 

NOTE: This was originally given as a talk to the Minnesota Python Users Group 
http://groups.google.com/group/pymntos/ and was developed for a 
spoken presentation format.
sphinxcontrib-sdedit 0.3
Sphinx extension for drawing sequence diagrams
License: BSD

This package contains the Sphinx_ extension for sdedit_.

.. _Sphinx: http://sphinx.pocoo.org/
.. _sdedit: http://sdedit.sourceforge.net/

This extension enable you to insert sequence diagrams of UML in your Sphinx docu
ment. Following code is sample::

   .. sequence-diagram::

      actor:Actor
      sphinx:Sphinx[a]
      dot:Graphviz
      sdedit:Quick Sequence Diagram Editor

      actor:sphinx.make html
      sphinx:dot.render_diagram()
      sphinx:sdedit.render_diagram()


This module needs sdedit_ and PIL.
simpletable 0.2.2
wrapper around pytables/hd5f to simplify using structured data
License: BSD
Keywords: hdf5 pytables tables numpy

SimpleTable: simple wrapper around `pytables`_ hdf5
------------------------------------------------------------------------------

.. _`pytables`: http://pytables.org

This module removes some of the boiler-plate code required to use the excellent 
`pytables`_
module to save and access structured data.

Example Usage::

  >>> from simpletable import SimpleTable
  >>> import tables

define a table as a subclass of simple table.

  >>> RGB = tables.Enum(list('RGB'))
  >>> class ATable(SimpleTable):
  ...     x = tables.Float32Col()
  ...     y = tables.Float32Col()
  ...     name = tables.StringCol(16)
  ...     color = tables.EnumCol(RGB, 'R', 'uint8')

instantiate with: args: filename, tablename

  >>> tbl = ATable('test_docs.h5', 'atable1')

insert as with pytables:

  >>> row = tbl.row
  >>> for i in range(50):
  ...    row['x'], row['y'] = i, i * 10
  ...    row['name'] = "name_%i" % i
  ...    # NOTE how we have to manually translate the enum column.
  ...    row['color'] = RGB['G']
  ...    row.append()
  >>> tbl.flush()

can have the enum cols automatically translated using `insert`

  >>> data = {'x': 1000, 'y': 2000, 'color': 'G', 'name': 'flintstone'}
  >>> tbl.insert(data, row)
  >>> row.append()
  >>> tbl.flush()

there is also `insert_many()` method with takes an iterable
of dicts with keys matching the colunns (x, y, name) in this
case.

query the data (query() alias of tables' readWhere()
note that pytables sends back the data with enum cols as they were
and does nothing to translate them to their original values.

  >>> tbl.query('(x > 4) & (y < 70)') #doctest: +NORMALIZE_WHITESPACE
  array([(1, 'name_5', 5.0, 50.0), (1, 'name_6', 6.0, 60.0)],
         dtype=[('color', '|u1'), ('name', '|S16'), ('x', '<f4'), ('y', '<f4')])

get translated enumcols in an iterator with the .q  method.

  >>> r = tbl.q('x == 1000') # doctest: +NORMALIZE_WHITESPACE
  >>> r # doctest: +ELLIPSIS
  <generator ...>

  >>> list(r)
  [{'color': 'G', 'x': 1000.0, 'name': 'flintstone', 'y': 2000.0}]

or use the `translate_enum` method

  >>> for row_with_enum in tbl.query('(x > 4) & (y < 70)'):
  ...     tbl.translate_enum(row_with_enum)
  {'color': 'G', 'x': 5.0, 'name': 'name_5', 'y': 50.0}
  {'color': 'G', 'x': 6.0, 'name': 'name_6', 'y': 60.0}

Note that using `q` or `translate_enum` will affect performance.
spotimeta 0.2
"Library for querying the Spotify metadata service
License: BSD
Keywords: Spotify

.. -*- restructuredtext -*-

##############################################
Spotimeta - Spotify metadata search and lookup
##############################################

Introduction
------------

Spotimeta is a simple library for getting data from Spotify's metadata API.
Available functions is searching for artists, albums and tracks, as well
as looking up the same based on Spotify URIs. The data is returned as
simple python dictionaries.

NOTE:

This product uses a SPOTIFY API but is not endorsed, certified or otherwise 
approved in any way by Spotify. Spotify is the registered trade mark of the 
Spotify Group.

For more information about the metadata API, see
 http://developer.spotify.com/en/metadata-api/overview/

Examples
--------

>>> import spotimeta


Search for a track

>>> search = spotimeta.search_track("Trip back to childhood")
>>> search["total_results"]
1

Print the artist of that track

>>> artist = search["result"][0]["artist"]
>>> artist["name"]
u'St-Petersburg Ska-Jazz Review'

Look up more information about that artist:

>>> lookup = spotimeta.lookup(artist["href"], detail=1)
>>> for album in lookup["result"]["albums"]:
...     album["name"]
u'Too Good To Be True'
u'Too Good To Be True'
u'Live At The Red Club'

It's also possible to look up metadata using spotify URLs:

>>> track = spotimeta.lookup("http://open.spotify.com/track/3Z8cX6y0SeJIsI3yxoaQ8K")
>>> print track["result"]["artist"]["name"], "-", track["result"]["name"] 
Kings Of Leon - Closer

For anything but the simples use-cases one should use caching.
Caching is enabled by making a Metadata instance and passing it
something that is a mapping type. For instance a dictionary:

>>> metacache = {}
>>> metadata = spotimeta.Metadata(cache=metacache)

The metadata instance has exactly the same methods as the module itself.
Caching happens automatically as long as there is a cache object set.

>>> data = metadata.lookup("spotify:track:3kofFW93aMr28qx1BKps7A")
>>> data = metadata.lookup("spotify:track:3kofFW93aMr28qx1BKps7A")

This will only cause a single request. Data is cached for as long
as the Expiry header on the first request says it should.


Todo
----

- Sphinxify docs
- Testcases for search, not just search parser
- Deal with all the fixmes


Changelog
---------

See the CHANGELOG file

Contact
-------

The author is Rune Halvorsen <runefh@gmail.com>. The project resides at
http://bitbucket.org/runeh/spotimeta . If you find bugs, or have feature
requests, please report them in the project site issue tracker. Patches 
very welcome.

Also, see AUTHORS file for full list of contributors

License
-------

This software is licensed under the ``New BSD License``. See the ``LICENCE``
file in the top distribution directory for the full license text.