Home
CSP (Composable Stream Processing) is a library for high-performance real-time event stream processing in Python.
- Powerful C++ Engine: Execute the graph using CSP's C++ Graph Processing Engine
- Simulation (i.e., offline) mode: Test workflows on historical data and quickly move to real-time data in deployment
- Infrastructure-agnostic: Connect to any data format or storage database, using built-in (Parquet, Kafka, etc.) or custom adapters
- Library of built-in operations: Write workflows quickly using CSP's built-in set of general, statistical, mathematical "nodes" that define common runtime computations
- Highly-customizable: Write your own input and output adapters for any data/storage formats, and real-time adapters for specific workflows
- PyData interoperability: Use your favorite libraries from the Scientific Python Ecosystem for numerical and statistical computations
- Functional/declarative style: Write concise and composable code for stream processing by building graphs in Python
- Install CSP and write your first CSP program
- Learn more about nodes, graphs, and execution modes
- Learn to extend CSP with adapters
| Real-time public transportation | Tracking Wikipedia page edits | Processing seismic waveforms | Visualizing global earthquakes |
|
|
|
|
Check out the examples directory for a comprehensive collection of CSP applications.
- Contribute to CSP and help improve the project
- Read about future plans in the project roadmap
Tip
Find relevant docs with GitHub’s search function, use repo:Point72/csp type:wiki <search terms> to search the documentation Wiki Pages.
CSP is licensed under the Apache 2.0 license. See the LICENSE file for details.