causallib dependencies

Causallib is used in Python projects. A Python package for flexible and modular causal inference modeling It has 8 direct runtime dependencies. Check its dependency graph on PyDeps to understand the full transitive dependency tree, reverse dependents, known CVEs, and license compatibility before installing.

What is causallib?

A Python package for flexible and modular causal inference modeling

What are the dependencies of causallib?

causallib declares 8 direct runtime dependencies on PyPI. Each one is resolved into the full dependency tree below:

causallib transitive dependencies

Beyond its direct dependencies, causallib can pull in further packages through its dependency tree. PyDeps resolves the entire chain from PyPI and deps.dev so you can see every transitive (nested) dependency of causallib, expand any node on demand, and understand the full set of code that ships when you run pip install causallib.

Does causallib have known vulnerabilities (CVEs)?

PyDeps checks causallib and every package in its dependency tree against the OSV vulnerability database in real time. For each CVE you can see the severity, the affected version ranges, and the first fixed version, so you know exactly which causallib version is safe to install before you ship.

What license does causallib use?

causallib is distributed under the Apache License 2.0. PyDeps also shows the license of every dependency in the tree so you can audit license compatibility across your whole causallib install, not just the top-level package.

How to install causallib with all dependencies

Install from PyPI with pip install causallib. For offline or air-gapped environments, PyDeps can download causallib together with every resolved dependency as wheel files in a single bundle, matched to your target Python version and operating system.

Which packages depend on causallib?

Switch to the dependents view to see the reverse dependencies of causallib — the PyPI packages that list causallib as a requirement. Reverse dependencies are a strong signal of how widely a package is trusted and how disruptive a breaking change would be.

Packages related to causallib

PyDeps