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beartype
Runtime type-checking library for Python functions and methods.
Our View
Assess whether this fits the group’s research and teaching workflows. beartype gives fast feedback when function inputs or outputs do not match the types a project claims to support, which is useful for research code that handles many arrays, tables, and configuration objects.
Provisional positions are editorial proposals awaiting group review.
Teaching — Recorded in topic offerings; consult the dated event links for availability.
1 topics with recorded teaching · 0 past offerings · 1 upcoming offerings
Related themes: Scientific Computing
Related topics: Robust and Reusable Software
Common use cases
- Validate function boundaries while developing reusable analysis code
- Catch incorrect data types in scripts before they produce misleading results
- Complement static type checking with runtime checks
Getting started
beartype checks Python type hints while code is running. It can be added to selected functions to make assumptions about inputs and outputs executable, without requiring a large framework or a complete rewrite of existing code.
Why It Matters in Research Workflows
Research code often grows from small scripts into shared functions used by several people. Runtime type checks help catch mistakes at the moment data crosses an interface, such as when a path is passed where a table is expected or a list is passed where a NumPy array is required.
In Our Teaching
We present beartype as one option in the broader topic of runtime data validation. It pairs naturally with static tools such as mypy and with schema tools such as Pydantic and Pandera. See the course material on run-time data validation frameworks in Python.