pyproject.toml

[build-system]
requires = [
    "setuptools",
    "wheel",
]


[tool.isort]
known_first_party = [
    "pl_examples",
    "pytorch_lightning",
    "tests_pytorch",
]
profile = "black"
line_length = 120
force_sort_within_sections = "False"
order_by_type = "False"
skip = ["_notebooks"]


[tool.black]
line-length = 120
exclude = '(_notebooks/.*)'


[tool.mypy]
files = [
    "src/pytorch_lightning",
    # TODO: Check typing in app source
    # "src/lightning_app",
]
install_types = "True"
non_interactive = "True"
disallow_untyped_defs = "True"
ignore_missing_imports = "True"
show_error_codes = "True"
warn_redundant_casts = "True"
warn_unused_configs = "True"
warn_unused_ignores = "True"
allow_redefinition = "True"
# disable this rule as the Trainer attributes are defined in the connectors, not in its __init__
disable_error_code = "attr-defined"
# style choices
warn_no_return = "False"

# Ignore mypy errors for these files
# TODO: the goal is for this to be empty
[[tool.mypy.overrides]]
# the list can be generated with:
# mypy --no-error-summary 2>&1 | tr ':' ' ' | awk '{print $1}' | sort | uniq | sed 's/\.py//g; s|src/||g;  s|\/|\.|g' | xargs -I {} echo '"{}",'
module = [
    "pytorch_lightning.callbacks.progress.rich_progress",
    "pytorch_lightning.callbacks.quantization",
    "pytorch_lightning.core.datamodule",
    "pytorch_lightning.core.decorators",
    "pytorch_lightning.core.module",
    "pytorch_lightning.core.saving",
    "pytorch_lightning.demos.boring_classes",
    "pytorch_lightning.demos.mnist_datamodule",
    "pytorch_lightning.profilers.base",
    "pytorch_lightning.profilers.pytorch",
    "pytorch_lightning.profilers.simple",
    "pytorch_lightning.strategies.ddp",
    "pytorch_lightning.strategies.sharded",
    "pytorch_lightning.strategies.sharded_spawn",
    "pytorch_lightning.trainer.callback_hook",
    "pytorch_lightning.trainer.connectors.callback_connector",
    "pytorch_lightning.trainer.connectors.data_connector",
    "pytorch_lightning.trainer.supporters",
    "pytorch_lightning.trainer.trainer",
    "pytorch_lightning.tuner.batch_size_scaling",
    "pytorch_lightning.utilities.auto_restart",
    "pytorch_lightning.utilities.data",
    "pytorch_lightning.utilities.meta",
]
ignore_errors = "True"