csa-prediction-engine 2.4.2

The csa_prediction_engine library provides a suite of tools and functions for performing relevance-based predictions using the Cambridge Sports Analytics Prediction Engine API. The package is designed to facilitate single and multi-task predictions, allowing for flexible model evaluation and experimentation.

Cambridge Sports Analytics Prediction Engine

The CSA Prediction Engine is the official Python client for interacting with the Cambridge Sports Analytics (CSA) API. It enables relevance-based predictions using flexible configurations, including support for batch jobs, grid evaluations, and multi-task prediction workflows.

Source code: github.com/CambridgeSportsAnalytics/csa_prediction_engine

Key features

• Single task predictions: One dependent variable and one set of circumstances.
• Multi-y predictions: Multiple dependent variables with a single set of circumstances.
• Multi-theta predictions: One dependent variable with multiple sets of circumstances.
• Relevance-based grid predictions: Optimal composite prediction across thresholds and variable combinations.
• Grid singularity predictions: Highest adjusted-fit prediction from the grid.
• MaxFit predictions: Best-fit model from adjusted relevance.

Installation

Install from PyPI:

pip install csa-prediction-engine

Requires Python 3.11.

Package layout

csa_prediction_engine/
├── api_client.py                 # Public API: predict_*, decorators, quota helpers
├── bin/
│   ├── _workers.py               # Worker implementations for prediction tasks
│   └── single_tasks.py           # Single-task CLI-style entry helpers
├── helpers/
│   ├── _auth_manager.py          # API authentication
│   ├── _details_handler.py       # Model details retrieval and storage
│   ├── _payload_handler.py       # Request payloads and endpoint routing
│   ├── _postmaster.py            # Internal HTTP / communication helpers
│   └── _router.py                # Task routing from configuration
├── parallel/
│   ├── _dispatchers.py           # Parallel task dispatch
│   ├── _threaded_predictions.py  # Threaded async prediction runs
│   └── _workers.py               # Parallel worker processes
├── version.py                    # Package version string
└── __init__.py

Documentation and examples

For OpenAPI specs, quickstart examples, and tutorials, see the companion repository:

CSA Prediction Engine quickstart

Contributing

Bug reports and feature requests are welcome. Reach out to the team at [e-mail].

License

Copyright (c) 2023–2026 Cambridge Prediction Analytics, LLC. All rights reserved.