Metadata-Version: 1.2
Name: graphscraper
Version: 0.5.0
Summary: Graph implementation that loads graph data (nodes and edges) from external sources and caches the loaded data in a database using sqlalchemy or flask-sqlalchemy.
Home-page: https://github.com/volfpeter/graphscraper
Author: Peter Volf
Author-email: do.volfp@gmail.com
License: MIT
Description: |Downloads|
        
        GraphScraper
        =================
        
        GraphScraper is a Python 3 library that contains a base graph implementation designed
        to be turned into a web scraper for graph data. It has two major features:
        
        1) The graph automatically manages a database (using either SQLAlchemy or
        Flask-SQLAlchemy) where it stores all the nodes and edges the graph has seen.
        
        2) The base graph implementation provides hook methods that, if implemented,
        turn the graph into a web scraper.
        
        Yet another graph implementation - why
        -------------------------------------------
        
        There are many excellent graph libraries available for different purposes. I started
        implementing this one because i haven't found a graph library that is dynamic (i don't
        need the whole graph in memory - or on disk - before i start working with it), that
        can be used as a web scraper (to seamlessly load nodes and edges from some remote
        data source when that piece of data is needed) and that keeps all data (the graph)
        automatically up-to-date on the disk. GraphScraper aims to satisfy these requirements.
        
        Examples
        ----------------------
        
        Besides the base graph implementation, the following working examples are also included
        in the library, that show you how you can implement and use an actual graph scraper:
        
        - `igraphwrapper`: Instead of web-scraping, this example is using an igraph_ graph
          instance as the "remote" source to scrape data from.
        - `spotifyartist`: This example is using the Spotify_ web API to load artists and
          edges are defined by Artist similarity.
        
        Dependencies
        -----------------
        
        If you wish to use one of the included graph implementations, then please read the
        corresponding module's description for additional requirements.
        
        Contribution
        -----------------
        
        Any form of constructive contribution (feedback, features, bug fixes, tests, additional
        documentation, etc.) is welcome.
        
        .. _igraph: http://igraph.org
        .. _Spotify: https://developer.spotify.com/web-api/
        .. |Downloads| image:: https://pepy.tech/badge/graphscraper
        
Keywords: graph network webscraping sqlalchemy database db caching
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Information Technology
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Database
Classifier: Topic :: Internet
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: Utilities
Requires-Python: >=3
