semvec/pypi-packages huggingface dataset:
GitFeed 0.1.9
Check your GitHub Newsfeed via the command-line.
License: MIT
Keywords: GitHub,news,feed,command-line,python

GitFeed
=======

|pypi.python.org| |build Status|

-  Check your GitHub Newsfeed via the command-line.

-  Newsfeed includes all the news from people you are following on
   GitHub, repositories you are watching, etc. All news you would find
   on your GitHub dashboard.

Screenshots
-----------

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

GitFeed can be installed from pypi.

For best results (compatibility with Pager), use Python3

::

    pip install gitfeed

or if you like to live on the bleeding edge

::

    git clone https://github.com/Ritiek/GitFeed
    cd GitFeed
    python setup.py install

Usage
-----

-  Run it using ``gitfeed``

-  The first time you launch ``gitfeed``, it will ask you for GitHub
   username and set it as the default username to fetch news for.

-  You can even fetch news for any other user provided you know their
   GitHub username.

-  Full list of supported options:

::

    usage: gitfeed [-h] [-u USER] [-p PAGES] [-q] [-nt] [-ns]

    Check your GitHub Newsfeed via the command-line.

    optional arguments:
      -h, --help            show this help message and exit
      -u USER, --user USER  GitHub username for the user to fetch newsfeed for
                            (default: <user>)
      -p PAGES, --pages PAGES
                            number of newsfeed pages to fetch (default: 1)
      -q, --quiet           hide comment body in issues & PRs (default: False)
      -nt, --no-time-stamp  hide time-stamp of events (default: False)
      -ns, --no-style       show plain white text with no colors or style
                            (default: False)

-  You can modify the default configuration by editing
   ``~/.gitfeed/gitfeed.ini``

License
-------

``The MIT License``

.. |pypi.python.org| image:: https://img.shields.io/pypi/v/GitFeed.svg
   :target: https://pypi.org/project/GitFeed/
.. |build Status| image:: https://travis-ci.org/ritiek/GitFeed.svg?branch=master
   :target: https://travis-ci.org/ritiek/GitFeed/
geoql 0.0.8.0
Library for performing queries and transformations on GeoJSON data (with emphasis on support for abstract graph representations).
License: MIT

=====
geoql
=====

Library for performing queries and transformations on GeoJSON data (with emphasis on support for abstract graph representations).

Package Installation and Usage
------------------------------

The package is available on PyPI::

    python -m pip install geoql

The library can be imported in the usual ways::

    import geoql
    from geoql import geoql

Examples
--------
An example of usage is provided  below::

    import geojson
    from geoql import geoql
    import geoleaflet
    import requests
    
    url = 'https://raw.githubusercontent.com/Data-Mechanics/geoql/master/examples/'
    
    # Boston ZIP Codes regions.
    z = geoql.loads(requests.get(url + 'example_zips.geojson').text, encoding="latin-1")
    
    # Extract of street data.
    g = geoql.loads(requests.get(url + 'example_extract.geojson').text, encoding="latin-1")
    
    g = g.properties_null_remove()\
         .tags_parse_str_to_dict()\
         .keep_by_property({"highway": {"$in": ["residential", "secondary", "tertiary"]}})
    g = g.keep_within_radius((42.3551, -71.0656), 0.75, 'miles') # 0.75 miles from Boston Common.
    g = g.keep_that_intersect(z) # Only those entries found in a Boston ZIP Code regions.
    g = g.node_edge_graph() # Converted into a graph with nodes and edges.
    g.dump(open('example_extract.geojson', 'w'))
    open('leaflet.html', 'w').write(geoleaflet.html(g)) # Create visualization.

An alternative example of usage is provided  below (the below usage is deprecated but will remain supported)::

    import geojson
    import geoql
    import geoleaflet
    import requests
    
    url = 'https://raw.githubusercontent.com/Data-Mechanics/geoql/master/examples/'
    
    # Boston ZIP Codes regions.
    z = geojson.loads(requests.get(url + 'example_zips.geojson').text, encoding="latin-1")
    
    # Extract of street data.
    g = geojson.loads(requests.get(url + 'example_extract.geojson').text, encoding="latin-1")
    
    g = geoql.features_properties_null_remove(g)
    g = geoql.features_tags_parse_str_to_dict(g)
    g = geoql.features_keep_by_property(g, {"highway": {"$in": ["residential", "secondary", "tertiary"]}})
    g = geoql.features_keep_within_radius(g, (42.3551, -71.0656), 0.75, 'miles') # Within 0.75 of Boston Common.
    g = geoql.features_keep_intersecting_features(g, z) # Only those entries found in a Boston ZIP Code regions.
    g = geoql.features_node_edge_graph(g) # Converted into a graph with nodes and edges.
    open('example_extract.geojson', 'w').write(geojson.dumps(g))
    open('leaflet.html', 'w').write(geoleaflet.html(g)) # Create visualization.