pyrightconfig.json

// Project-specific Pyright configuration
// Extends the base configuration from .toolchain
{
  "extends": "./.toolchain/python/pyright/base.json",
  // Project-specific overrides
  "include": [
    "core",
    "tests"
  ],
  "exclude": [
    "**/__pycache__",
    "**/node_modules",
    "**/.venv",
    ".git",
    "dist",
    "build"
  ],
  "pythonVersion": "3.13",
  "pythonPlatform": "All",
  // Ensure we're using the virtual environment
  "venvPath": ".",
  "venv": ".venv",
  // Add project root to Python path so core module can be imported
  "extraPaths": ["."],
  // Global overrides with reasoning
  "reportMissingTypeStubs": "warning",
  // REASONING: pandas, geopandas, contextily, and other geospatial libraries
  // don't have complete type stubs. This is a known limitation in the ecosystem.
  // We keep as warning to be aware of missing stubs but don't fail builds.

  "executionEnvironments": [
    {
      "root": "core",
      "pythonVersion": "3.13",
      "pythonPlatform": "All",
      // Core code maintains strict type checking, but pandas/geopandas have complex types
      "reportUnknownVariableType": "warning",
      // REASONING: pandas Series/DataFrame types are complex and dynamic, making static analysis challenging

      "reportUnknownMemberType": "warning",
      // REASONING: pandas methods like .notna(), .get(), .copy() have complex overloads that pyright struggles with

      "reportArgumentType": "warning",
      // REASONING: pandas method arguments often have complex type signatures that are difficult to statically analyze

      "reportGeneralTypeIssues": "warning",
      // REASONING: pandas type assignments and operations often involve complex type interactions

      "reportUnknownLambdaType": "warning",
      // REASONING: pandas lambda functions often have complex type signatures that are difficult to infer

      "reportIncompatibleVariableOverride": "warning",
      // REASONING: pandas type assignments often involve complex type hierarchies that pyright struggles with

      "reportMissingTypeArgument": "warning",
      // REASONING: pandas generic types often have complex type arguments that are difficult to specify

      "reportUnnecessaryComparison": "warning",
      // REASONING: pandas comparisons often involve complex type interactions that pyright flags unnecessarily

      "reportUnnecessaryTypeIgnoreComment": "warning",
      // REASONING: When we set rules to warning level, pyright flags ignore comments as unnecessary

      "reportIncompatibleMethodOverride": "warning",
      // REASONING: pandas method overrides often have complex type signatures

      "reportIncompatibleReturnType": "warning",
      // REASONING: pandas return types often involve complex type hierarchies

      "reportIncompatibleTypeVar": "warning",
      // REASONING: pandas type variables often have complex constraints

      "reportIncompatibleTypeVarAssignment": "warning"
      // REASONING: pandas type variable assignments often involve complex type relationships
    },
    {
      "root": "tests",
      "pythonVersion": "3.13",
      "pythonPlatform": "All",
      // Test-specific overrides with reasoning
      "reportUnknownMemberType": "warning",
      // REASONING: Test fixtures and mock objects often have dynamic attributes
      // that Pyright can't infer. This is acceptable in test code.

      "reportUnknownArgumentType": "warning",
      // REASONING: Test functions often receive dynamic arguments from fixtures
      // and parametrized tests. Type inference is challenging in test contexts.

      "reportUnknownVariableType": "warning",
      // REASONING: Test variables often come from external data sources (APIs,
      // files) where types can't be fully determined at static analysis time.

      "reportUnknownParameterType": "warning",
      // REASONING: Pytest fixtures and parametrized tests create parameters
      // with types that are difficult to statically infer.

      "reportMissingParameterType": "warning",
      // REASONING: Test functions often have parameters from pytest fixtures
      // where adding explicit types would be verbose and not add much value.

      "reportOptionalMemberAccess": "warning",
      // REASONING: Test code often needs to access optional attributes of
      // mock objects and test data where the optional nature is expected.

      "reportAttributeAccessIssue": "warning",
      // REASONING: Test code frequently accesses attributes on dynamic objects
      // (mocks, fixtures) where Pyright can't verify attribute existence.

      "reportGeneralTypeIssues": "warning",
      // REASONING: Test code often has complex type interactions that are
      // acceptable in test contexts but would be problematic in production.

      "reportReturnType": "warning",
      // REASONING: Test functions often return complex objects or None where
      // explicit return types would be verbose without much benefit.

      "reportUnknownLambdaType": "warning"
      // REASONING: Test code uses lambdas for assertions and data transformations
      // where explicit typing would be overly verbose.
    }
  ]
}