Network analysis with Python, using state-of-the-art research findings that cover a series of advanced network analysis algorithms. Designed to scale on million-node datasets and largely reduce computation time.
Why EasyGraph?
Algorithm
The first open source library to cover the most complete SH Spanner detection methods and network representation learning.
→ More about EasyGraph functions
Optimization
Scalable functions with parallel, concurrent, or hybrid computing to achieve high efficiency.
→ More about EasyGraph performance
Visualization
Presentable drawings of the complete network with SH Spanner marks, CDF curves, and node positioning.
→ More about drawing with EasyGraph
Usability
Starter-friendly APIs. Able to analyze the network for SHS and export drawing and CDF curve with 6 lines of Python.
→ Check the code examples.
Advancement
Backed by world-class researchers with collective cutting-edge studies in interdisciplinary network analysis.
→ Meet the FudanDataNET team