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Raphtory is an in-memory graph tool written in Rust with friendly Python APIs on top. It is blazingly fast, scales to hundreds of millions of edges
on your laptop, and can be dropped into your existing pipelines with a simple pip install raphtory.
It supports time traveling, multilayer modelling, and advanced analytics beyond simple querying like community evolution, dynamic scoring, and mining temporal motifs.
If you wish to contribute, check out the open list of issues, bounty board or hit us up directly on slack. Successful contributions will be reward with swizzling swag!
from raphtory import Graph
import pandas as pd
# Create a new graph
graph = Graph()
# Add some data to your graph
graph.add_vertex(timestamp=1, id="Alice")
graph.add_vertex(timestamp=1, id="Bob")
graph.add_vertex(timestamp=1, id="Charlie")
graph.add_edge (timestamp=2, src="Bob", dst="Charlie", properties={"weight":5.0})
graph.add_edge (timestamp=3, src="Alice", dst="Bob", properties={"weight":10.0})
graph.add_edge (timestamp=3, src="Bob", dst="Charlie", properties={"weight":-15.0})
# Check the number of unique nodes/edges in the graph and earliest/latest time seen.
print(graph)
results = [["earliest_time", "name", "out_degree", "in_degree"]]
# Collect some simple vertex metrics Ran across the history of your graph with a rolling window
for graph_view in graph.rolling(window=1):
for v in graph_view.vertices():
results.append([graph_view.earliest_time(), v.name(), v.out_degree(), v.in_degree()])
# Print the results
print(pd.DataFrame(results[1:], columns=results[0]))
# Grab an edge, explore the history of its 'weight'
cb_edge = graph.edge("Bob","Charlie")
weight_history = cb_edge.property_history("weight")
print("The edge between Bob and Charlie has the following weight history:", weight_history)
# Compare this weight between time 2 and time 3
weight_change = cb_edge.at(2)["weight"] - cb_edge.at(3)["weight"]
print("The weight of the edge between Bob and Charlie has changed by",weight_change,"pts")Graph(number_of_edges=2, number_of_vertices=3, earliest_time=1, latest_time=3)
| | earliest_time | name | out_degree | in_degree |
|---|---------------|---------|------------|-----------|
| 0 | 1 | Alice | 0 | 0 |
| 1 | 1 | Bob | 0 | 0 |
| 2 | 1 | Charlie | 0 | 0 |
| 3 | 2 | Bob | 1 | 0 |
| 4 | 2 | Charlie | 0 | 1 |
| 5 | 3 | Alice | 1 | 0 |
| 6 | 3 | Bob | 1 | 1 |
| 7 | 3 | Charlie | 0 | 1 |
The edge between Bob and Charlie has the following weight history: [(2, 5.0), (3, -15.0)]
The weight of the edge between Bob and Charlie has changed by 20.0 pts
Raphtory is available for Python and Rust as of version 0.3.0. You should have Python version 3.10 or higher and it's a good idea to use conda, virtualenv, or pyenv.
pip install raphtoryCheck out Raphtory in action with our interactive Jupyter Notebook! Just click the badge below to launch a Raphtory sandbox online, no installation needed.
Want to give Raphtory a go on your laptop? You can checkout out the latest documentation and complete list of available algorithms or hop on our notebook based tutorials below!
| Type | Description |
|---|---|
| Tutorial | Building your first graph |
| Type | Description |
|---|---|
| Notebook | Use our powerful time APIs to find pump and dump scams in popular NFTs |
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Raphtory is licensed under the terms of the GNU General Public License v3.0 (check out our LICENSE file).