turbograph 0.6.1

A Library for Quick Dependency-based Computation

Quick Dependency-based Computation

📖 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 "turbograph[networkx]"


# Or with the iGraph backend
pip install "turbograph[igraph]"

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

Credits

The TurboGraph logo was created using the following fonts

• Speedway – dafont.com/speedway.font
• Speed Solid – dafont.com/speed-solid.font

The multi-versioning approach for this documentation was largely inspired by the implementation in this repository, which is licensed under the Apache-2.0 license. I sincerely appreciate the author for sharing their work!