Skip to main content

A Library for Quick Dependency-based Computation

Project description

TurboGraph logo

TurboGraph - Quick Dependency-based Computation

pipeline status test coverage latest release

📖 Documentation: https://turbograph.docs.cern.ch/master

TurboGraph is a lightweight Python library for defining and computing values based on dependencies.

It builds a directed dependency graph automatically—leveraging either the networkx or igraph backend—to ensure computations run in the correct order.

🚀 Quick Example

TurboGraph infers dependencies from function signatures:

from turbograph import compute

specifications = {
    "a": 2,
    "sum": lambda a, b: a + b,  # "sum" depends on "a" and "b"
}

result = compute(specifications, ["sum"], {"b": 3})
print(result)  # Output: {"sum": 5}

TurboGraph detects that "sum" depends on both "a" and "b" and executes the computations accordingly.

📌 Check out the Quick-Start Guide for more details.

📥 Installation

TurboGraph requires Python ≥ 3.11 and supports NetworkX (≥2.5) and iGraph (≥0.10.0) as graph backends.

# Install with NetworkX backend
pip install fastgraph[networkx]


# Or with the iGraph backend
pip install fastgraph[igraph]

📚 For more installation options, check out the Installation Guide or Development Guide.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

turbograph-0.5.0-py3-none-any.whl (35.2 kB view details)

Uploaded Python 3

File details

Details for the file turbograph-0.5.0-py3-none-any.whl.

File metadata

  • Download URL: turbograph-0.5.0-py3-none-any.whl
  • Upload date:
  • Size: 35.2 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.6.3

File hashes

Hashes for turbograph-0.5.0-py3-none-any.whl
Algorithm Hash digest
SHA256 b2c8ce9f7585afb33706c971f19699f49f359eff956e41252e538426f54bd30c
MD5 6d7f9e3a5295277aa9ceb695d5d61be8
BLAKE2b-256 c61b36f26a66d78ebed004ca3b0349ddbb1b2a6fb9da4400282448cff1c6c78c

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page