Skip to content
GraphiPy: Universal Social Data Extractor
Python
Branch: master
Clone or download
shobeir Add Binder Badge
Note that the Binder copy wouldn't work without the following:
1. !pip install graphipy
2. entering the user's credentials
Latest commit 684d150 May 3, 2019
Permalink
Type Name Latest commit message Commit time
Failed to load latest commit information.
demo facebook demo update Nov 16, 2018
graphipy delete return graph Nov 29, 2018
.gitignore fixed neo4j bugs and added labels drawing Nov 14, 2018
LICENSE Create LICENSE Nov 27, 2018
README.md Add Binder Badge May 3, 2019
requirements.txt license and modify requirement Nov 28, 2018

README.md

GraphiPy

A Universal Social Data Extractor

PyPI version Downloads Binder

GraphiPy simplifies the extraction of data from different social media websites. Instead of having to study the different APIs of each website, just provide the API keys and use GraphiPy!

Currently, GraphiPy provides support to 7 different websites:

Installation

GraphiPy is uploaded on PyPI and can be found here.

To install GraphiPy, run pip install GraphiPy

Please note that GraphiPy does not support Python 2 and only works on Python 3.

Video Demonstration

GraphiPy Video

Data Strcuture

GraphiPy acts like a Graph in which all the different information are stored as nodes and connections between different nodes will be stored as edges.

Currently, we have 3 graph types:

All graph types are based on a class called BaseGraph

  • Dictionary Graph To provide easy access, the type of the nodes and edges are stored as keys while the rows of data are stored as values. The rows of data is also a dictionary, with the _id of the nodes and edges as keys (to avoid duplicate data) and the values would be the node and edge objects.

  • Pandas Graph Similar to the Dictionary Graph, the type of nodes and edges are stored as keys and the dataframes are stored as values. Since inserting rows one by one into the dataframe takes polynomial time, the implementation uses the help of Python's dictionary. After a certain number of elements are inside the dictionaries, all of them are converted into dataframes and appended into the existing dataframes.

  • Neo4j Graph GraphiPy directly connects and inserts to your Neo4j database. In order to avoid duplicate data, MERGE is used instead of CREATE. Thus, whenever an existing node _id is inserted, its attributes are updated instead of inserting a completely new node.

API Demos

For more information on how to use GraphiPy, please see one of the notebooks:

Data Exportation and Visualization with NetworkX

GraphiPy can also export data as CSV files and visualize the graphs using NetworkX. It is also possible to convert from one graph type to another (e.g. from Pandas to Neo4j and vice versa). For more information, see this notebook

  • Gephi Support: Gephi is an open-source software for network visualization and analysis. It helps data analysts to intuitively reveal patterns and trends, highlight outliers and tells stories with their data. The csv files exported from Graphify can be directly imported to Gephi. The below figure shows data visualization (via Gephi) of 20 youtube videos with keyword "dota2" extracted via GraphiPy Data of 20 youtube videos with keyword "dota2"

Folder Structure

.
├── demo
|   ├── DataExportDemo.ipynb
|   ├── FacebookDemo.ipynb
|   ├── LinkedinDemo.ipynb
|   ├── PinterestDemo.ipynb
|   ├── RedditDemo.ipynb
|   ├── TumblrDemo.ipynb
|   ├── TwitterDemo.ipynb
|   └── YoutubeDemo.ipynb
├── graphipy
|   ├── api
|   |   ├── _init_.py
|   |   ├── facebook_api.py	
|   |   ├── linkedin_api.py	
|   |   ├── pinterest_api.py
|   |   ├── reddit_api.py	
|   |   ├── tumblr_api.py	
|   |   ├── twitter_api.py	
|   |   └── youtube_api.py	
|   ├── graph
|   |   ├── _init_.py
|   |   ├── graph_base.py
|   |   ├── graph_dict.py
|   |   ├── graph_neo4j.py
|   |   └── graph_pandas.py
|   ├── _init_.py
|   ├── exportnx.py
|   └── graphipy.py
├── .gitignore 
├── README.md
└── requirements.txt
Folder/Filename Description
demo Jupyter notebooks explaining how to use the library in detail
graphipy The major directory of the library containing classes for all social media platforms, graph data structure and exporting functionalities
graphipy/api Class definitions for all social media platforms, including fetch functions and customized nodes and edges
graphipy/graph Definitions of the graph data structure implemented with dictionary, Pandas and Neo4J
requirements.txt All dependencies
You can’t perform that action at this time.