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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](https://github.com/Pometry/Raphtory/issues), [bounty board](https://github.com/Raphtory/Raphtory/discussions/categories/bounty-board) or hit us up directly on [slack](https://join.slack.com/t/raphtory/shared_invite/zt-xbebws9j-VgPIFRleJFJBwmpf81tvxA). Successful contributions will be reward with swizzling swag!
## Running a basic example
```python
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")
```
```a
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
```
## Installing Raphtory
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.
```bash
pip install raphtory
```
## Examples and Notebooks
Check out Raphtory in action with our interactive Jupyter Notebook! Just click the badge below to launch a Raphtory sandbox online, no installation needed.
[](https://mybinder.org/v2/gh/Raphtory/Raphtory/master?labpath=examples%2Fpy%2Flotr%2Flotr.ipynb)
Want to give Raphtory a go on your laptop? You can checkout out the [latest documentation](https://docs.raphtory.com/) and [complete list of available algorithms](https://docs.raphtory.com/en/v0.2.0/api/_autosummary/raphtory.algorithms.html) or hop on our notebook based tutorials below!
#### Getting started
| Type | Description |
|----------|------------------------------------------------------------------------------------------|
| Tutorial | [Building your first graph](https://docs.raphtory.com/en/master/Introduction/ingestion.html) |
#### Developing an end-to-end application
| Type | Description |
| ------------- |---------------------------------------------------------------------------------------------------------------------------------------------------------------|
| Notebook | [Use our powerful time APIs to find pump and dump scams in popular NFTs](https://github.com/Raphtory/Raphtory/blob/master/examples/py/nft/nft_analysis.ipynb) |
# Benchmarks
We host a page which triggers and saves the result of two benchmarks upon every push to the master branch.
View this here [https://pometry.github.io/Raphtory/dev/bench/](https://pometry.github.io/Raphtory/dev/bench/)
# Bounty board
Raphtory is currently offering rewards for contributions, such as new features or algorithms. Contributors will receive swag and prizes!
To get started, check out our list of desired algorithms at https://github.com/Raphtory/Raphtory/discussions/categories/bounty-board which include some low hanging fruit (🍇) that are easy to implement.
# Community
Join the growing community of open-source enthusiasts using Raphtory to power their graph analysis projects!
- Follow [](https://twitter.com/raphtory) for the latest Raphtory news and development
- Join our [](https://join.slack.com/t/raphtory/shared_invite/zt-xbebws9j-VgPIFRleJFJBwmpf81tvxA) to chat with us and get answers to your questions!
## Contributors
Want to get involved? Please join the Raphtory [Slack](https://join.slack.com/t/raphtory/shared_invite/zt-xbebws9j-VgPIFRleJFJBwmpf81tvxA) group and speak with us on how you could pitch in!
## License
Raphtory is licensed under the terms of the GNU General Public License v3.0 (check out our LICENSE file).