Filterpy is used in Python projects. Kalman filtering and optimal estimation library It has no required runtime dependencies, making it lightweight to install. Check its dependency graph on PyDeps to understand the full transitive dependency tree, reverse dependents, known CVEs, and license compatibility before installing.
Kalman filtering and optimal estimation library
filterpy has no required runtime dependencies. Installing it adds no transitive packages to your environment, which keeps installs small and minimizes the supply-chain surface you need to audit.
Beyond its direct dependencies, filterpy 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 filterpy, expand any node on demand, and understand the full set of code that ships when you run pip install filterpy.
PyDeps checks filterpy 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 filterpy version is safe to install before you ship.
filterpy is distributed under the MIT license. PyDeps also shows the license of every dependency in the tree so you can audit license compatibility across your whole filterpy install, not just the top-level package.
Install from PyPI with pip install filterpy. For offline or air-gapped environments, PyDeps can download filterpy together with every resolved dependency as wheel files in a single bundle, matched to your target Python version and operating system.
Switch to the dependents view to see the reverse dependencies of filterpy — the PyPI packages that list filterpy as a requirement. Reverse dependencies are a strong signal of how widely a package is trusted and how disruptive a breaking change would be.