python/typeshed
Typeshed
Typeshed is a collection of static type definitions and stubs for the Python standard library and third-party packages. It serves as a standardized resource for static analyzers and integrated development environments to validate code correctness and provide type-based code completion without modifying the original source code of the libraries.
The project focuses on the creation and maintenance of external type hint files that separate type annotations from runtime implementation. It utilizes a system for versioning and mapping these stubs to specific versions of runtime packages to maintain compatibility.
The repository includes a validation suite to ensure the accuracy of these definitions. This covers runtime-to-stub validation to identify mismatches between declared and actual types, directory structure verification, and regression testing to prevent the reintroduction of known type-checking bugs.
Features
- Type Stub Files - Maintains a comprehensive collection of .pyi files that separate type annotations from runtime Python implementation.
- Static Type Definitions - Provides a comprehensive collection of static type definitions for the Python standard library and third-party packages.
- Type Accuracy Validation - Provides tools to verify that static type declarations accurately match the runtime behavior of Python packages.
- Stub Version Mapping - Provides a mechanism to map specific type stub versions to corresponding runtime package versions for compatibility.
- Stub Versioning - Implements a system to ensure type stubs remain compatible with the specific versions of the installed runtime code.
- Python Library Stubbing - Creates and maintains type hint files for Python libraries that do not have native type annotations.
- External Library Definitions - Provides primary type mapping for third-party dependencies to enable static analysis of external Python code.
- Static Type Validation - Enforces type correctness by verifying that static definitions accurately match runtime package behavior.
- Python Type Stub Repositories - Provides a comprehensive collection of static type definitions for the Python standard library and third-party packages.
- Stub-to-Runtime Validations - Ships a validation system that compares static type definitions against live Python objects to identify mismatches.
- Python Type Checkers - Provides the foundational type definitions used by Python type checkers to identify inconsistencies in codebases.
- Static Type Checking - Provides the type definitions necessary for static analysis tools to verify API compatibility and code correctness without execution.
- Static Code Analysis - Serves as a standardized resource for static code analysis to detect bugs and maintain type safety in Python.
- Stub-to-Package Version Mapping - Maps specific versions of type stubs to corresponding versions of runtime packages to ensure compatibility.
- Utility Type Definitions - Provides standardized utility type annotations used across various stub files to ensure consistent type checking.
- Stub Validation Suites - Implements a validation suite to ensure type definitions accurately match the runtime behavior of Python packages.
- Stub Completeness Verifications - Runs static type checkers with varying strictness to identify incomplete stubs or missing type information.
- Regression Testing Suites - Provides a suite of tests to ensure that updates to type stubs do not reintroduce previously fixed type-checking bugs.
- Lint Regression Testing - Employs a verification system to detect regressions in type-checking behavior by comparing current output against baselines.
- Code Analysis - Listed in the “Code Analysis” section of the Awesome Python awesome list.
- Stub Packages - Centralized collection of library stubs for static analysis.
- Type Checking - Collection of library stubs for static type analysis.
Star history
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