PyCQA/pylint
Pylint
Pylint is a static code analysis tool for Python that checks source code for errors, coding standard violations, and code smells without executing the program. It parses code into an abstract syntax tree and walks the tree to detect issues, enforces configurable style rules and naming conventions, and identifies duplicate code blocks by comparing tokenised source sequences. The tool also includes an inference engine that deduces variable types by simulating code paths, enabling deeper analysis even in untyped code.
What distinguishes Pylint is its plugin-based checker architecture, which allows users to extend analysis by loading external Python modules that register custom checkers and inference rules at runtime. It supports configuration file layering, merging settings from multiple configuration files and command-line arguments so project-wide defaults can be overridden by local or plugin-specific options. Pylint also tracks code quality over time by comparing current analysis results against a stored baseline score, reporting improvement or regression in successive runs, and can generate UML class and package diagrams from the abstract syntax tree in Graphviz, PlantUML, or MermaidJS formats.
The tool integrates into continuous integration pipelines and pre-commit hooks to run checks across multiple Python interpreter versions automatically. It can be installed via pip, conda, or a system package manager, and offers optional spell-checking of code identifiers through the enchant library. Pylint also provides editor integration for environments such as Emacs and TextMate, and includes a message explanation viewer that prints the full description and context of any specific warning or error code directly from the command line.
Features
- Static Code Analysis - Scans Python source code without execution to detect errors, style violations, and code smells.
- Python Static Analyzers - Provides static analysis for Python source code, detecting errors, style violations, and code smells.
- Custom Lint Rule Plugins - Allows users to define custom naming conventions and write plugins for project-specific rules.
- Plugin-Based Checker Architectures - Ships a plugin-based checker architecture that loads external Python modules for custom rules.
- CI/CD Pipeline Integrations - Integrates into CI pipelines and pre-commit hooks to enforce code quality automatically.
- Coding Standards Enforcement - Checks code against configurable style rules to ensure consistent formatting and naming conventions.
- Third-Party Plugins - Loads user-written or third-party plugins to add project-specific or framework-specific checks.
- Plugin-Based Architectures - Extends analysis capabilities by loading external Python modules that register custom checkers and inference rules at runtime.
- Python Analyzers - Checks Python source code for errors, coding standard violations, and code smells without execution.
- Pattern Violation Scanning - Scans Python source files and reports coding standard violations, probable bugs, and refactoring opportunities.
- Custom Checker Registrations - Register a new rule that inspects code for problems and reports violations during analysis.
- Code Quality Checks - Enforces configurable style rules and naming conventions to ensure consistent formatting.
- Code Quality Tools - Integrates into CI pipelines and pre-commit hooks to enforce coding standards across Python versions.
- Static Analysis AST Parsing - Parses Python source code into an abstract syntax tree to detect errors and style violations without execution.
- Static Logic Error Detection - Analyzes Python source code without execution to find bugs, syntax mistakes, and runtime-like errors.
- Code Analysis and Refactoring - Identifies code smells and recommends structural changes to improve codebase maintainability.
- Layered Configuration Mergers - Merges settings from multiple configuration files and command-line arguments with layered override support.
- AST-Based Diagram Generators - Generates UML class and package diagrams from Python source code via the abstract syntax tree.
- AST-Based Generators - Produces class and package diagrams from Python source code to visualize project structure.
- Code Duplication Directory Scans - Scans Python source files for identical or near-identical code blocks and reports similarity percentages.
- Transformation Plugin Development - Modifies the inference engine to understand project-specific patterns or third-party libraries.
- Pre-commit Hooks - Configures the analyser to execute automatically before each commit to catch issues early.
- CI Pipeline Integrations - Runs static analysis across multiple Python interpreters during automated build pipelines to catch issues early.
- Continuous Integration Checks - Automatically executes linting and analysis on pushed code or pull requests as part of a build pipeline.
- Code Smell Detectors - Identifies problematic patterns and recommends improvements to make code cleaner and more maintainable.
- Type Inference Support - Deduces variable types by simulating code paths, enabling deeper analysis even in untyped Python code.
- Token-Based Duplication Detectors - Scans Python source files for identical or near-identical code blocks and reports their locations and similarity percentage.
- Plugin Configurations - Reads additional settings from a plugin after the main configuration is applied, allowing custom defaults.
- Regex-Based Customizations - Allows overriding default regular expressions for valid constant, variable, or function names.
- Quality - Tracks code quality scores over time, reporting improvement or regression between successive analysis runs.
- Type Inference Engines - Deduces variable types by simulating code paths and propagating type information through the internal program representation.
- Code Quality Tools - Analyzes Python code for errors and style.
- Linting And Formatting - Python static analysis and error checking.
