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Add pylint #4100

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Add pylint #4100

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1 change: 1 addition & 0 deletions py-polars/build.requirements.txt
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Original file line number Diff line number Diff line change
Expand Up @@ -20,6 +20,7 @@ isort~=5.10.1
mypy==0.961
ghp-import==2.1.0
flake8==4.0.1
pylint==2.14.5
sphinx==4.2.0
pydata-sphinx-theme==0.6.3
sphinx-panels==0.6.0
Expand Down
4 changes: 2 additions & 2 deletions py-polars/polars/__init__.py
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@@ -1,3 +1,4 @@
import os
import warnings

try:
Expand All @@ -10,7 +11,7 @@ def version() -> str:
# this is only useful for documentation
warnings.warn("polars binary missing!")

import polars.testing as testing
from polars import testing
from polars.cfg import Config, toggle_string_cache # We do not export in __all__
from polars.convert import (
from_arrow,
Expand Down Expand Up @@ -238,6 +239,5 @@ def version() -> str:

__version__ = version()

import os

os.environ["POLARS_ALLOW_EXTENSION"] = "true"
16 changes: 8 additions & 8 deletions py-polars/polars/convert.py
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Expand Up @@ -165,8 +165,8 @@ def from_records(
DeprecationWarning,
)
return DataFrame._from_numpy(data, columns=columns, orient=orient)
else:
return DataFrame._from_records(data, columns=columns, orient=orient)

return DataFrame._from_records(data, columns=columns, orient=orient)


def from_numpy(
Expand Down Expand Up @@ -281,10 +281,10 @@ def from_arrow(
raise ImportError("'pyarrow' is required when using from_arrow().")
if isinstance(a, pa.Table):
return DataFrame._from_arrow(a, rechunk=rechunk)
elif isinstance(a, (pa.Array, pa.ChunkedArray)):
if isinstance(a, (pa.Array, pa.ChunkedArray)):
return Series._from_arrow("", a, rechunk)
else:
raise ValueError(f"Expected Arrow Table or Array, got {type(a)}.")

raise ValueError(f"Expected Arrow Table or Array, got {type(a)}.")


@overload
Expand Down Expand Up @@ -369,7 +369,7 @@ def from_pandas(

if isinstance(df, (pd.Series, pd.DatetimeIndex)):
return Series._from_pandas("", df, nan_to_none=nan_to_none)
elif isinstance(df, pd.DataFrame):
if isinstance(df, pd.DataFrame):
return DataFrame._from_pandas(df, rechunk=rechunk, nan_to_none=nan_to_none)
else:
raise ValueError(f"Expected pandas DataFrame or Series, got {type(df)}.")

raise ValueError(f"Expected pandas DataFrame or Series, got {type(df)}.")
24 changes: 12 additions & 12 deletions py-polars/polars/datatypes.py
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Expand Up @@ -126,13 +126,13 @@ def __eq__(self, other: type[DataType]) -> bool: # type: ignore[override]
# List[i64] == List[f32] == False

# allow comparing object instances to class
if type(other) is type and issubclass(other, List):
if isinstance(other, type) and issubclass(other, List): # type: ignore[redundant-expr]
return True
if isinstance(other, List):
if self.inner is None or other.inner is None:
return True
else:
return self.inner == other.inner

return self.inner == other.inner
else:
return False

Expand Down Expand Up @@ -421,26 +421,26 @@ def dtype_to_ctype(dtype: PolarsDataType) -> type[_SimpleCData]:
try:
return _DTYPE_TO_CTYPE[dtype]
except KeyError: # pragma: no cover
raise NotImplementedError
raise NotImplementedError from None


def dtype_to_ffiname(dtype: PolarsDataType) -> str:
try:
return _DTYPE_TO_FFINAME[dtype]
except KeyError: # pragma: no cover
raise NotImplementedError
raise NotImplementedError from None


def dtype_to_py_type(dtype: PolarsDataType) -> type:
try:
return _DTYPE_TO_PY_TYPE[dtype]
except KeyError: # pragma: no cover
raise NotImplementedError
raise NotImplementedError from None


def is_polars_dtype(data_type: Any) -> bool:
return (
type(data_type) is type
isinstance(data_type, type)
and issubclass(data_type, DataType)
or isinstance(data_type, DataType)
)
Expand All @@ -453,7 +453,7 @@ def py_type_to_dtype(data_type: Any) -> type[DataType]:
try:
return _PY_TYPE_TO_DTYPE[data_type]
except KeyError: # pragma: no cover
raise NotImplementedError
raise NotImplementedError from None


def py_type_to_arrow_type(dtype: type[Any]) -> pa.lib.DataType:
Expand All @@ -463,7 +463,7 @@ def py_type_to_arrow_type(dtype: type[Any]) -> pa.lib.DataType:
try:
return _PY_TYPE_TO_ARROW_TYPE[dtype]
except KeyError: # pragma: no cover
raise ValueError(f"Cannot parse dtype {dtype} into Arrow dtype.")
raise ValueError(f"Cannot parse dtype {dtype} into Arrow dtype.") from None


def dtype_to_arrow_type(dtype: PolarsDataType) -> pa.lib.DataType:
Expand All @@ -473,7 +473,7 @@ def dtype_to_arrow_type(dtype: PolarsDataType) -> pa.lib.DataType:
try:
return _DTYPE_TO_ARROW_TYPE[dtype]
except KeyError: # pragma: no cover
raise ValueError(f"Cannot parse dtype {dtype} into Arrow dtype.")
raise ValueError(f"Cannot parse dtype {dtype} into Arrow dtype.") from None


def supported_numpy_char_code(dtype: str) -> bool:
Expand All @@ -484,7 +484,7 @@ def numpy_char_code_to_dtype(dtype: str) -> type[DataType]:
try:
return _NUMPY_CHAR_CODE_TO_DTYPE[dtype]
except KeyError: # pragma: no cover
raise NotImplementedError
raise NotImplementedError from None


def maybe_cast(
Expand All @@ -495,7 +495,7 @@ def maybe_cast(

if isinstance(el, datetime):
return _datetime_to_pl_timestamp(el, time_unit)
elif isinstance(el, timedelta):
if isinstance(el, timedelta):
return _timedelta_to_pl_timedelta(el, time_unit)
py_type = dtype_to_py_type(dtype)
if not isinstance(el, py_type):
Expand Down
6 changes: 3 additions & 3 deletions py-polars/polars/datatypes_constructor.py
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Expand Up @@ -73,7 +73,7 @@ def polars_type_to_constructor(
try:
return _POLARS_TYPE_TO_CONSTRUCTOR[dtype]
except KeyError: # pragma: no cover
raise ValueError(f"Cannot construct PySeries for type {dtype}.")
raise ValueError(f"Cannot construct PySeries for type {dtype}.") from None


if _NUMPY_AVAILABLE and not _DOCUMENTING:
Expand Down Expand Up @@ -101,8 +101,8 @@ def numpy_type_to_constructor(dtype: type[np.dtype]) -> Callable[..., PySeries]:
return _NUMPY_TYPE_TO_CONSTRUCTOR[dtype]
except KeyError:
return PySeries.new_object
except NameError: # pragma: no cover
raise ImportError("'numpy' is required for this functionality.")
except NameError as err: # pragma: no cover
raise ImportError("'numpy' is required for this functionality.") from err


if not _DOCUMENTING:
Expand Down
13 changes: 6 additions & 7 deletions py-polars/polars/io.py
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Expand Up @@ -4,8 +4,6 @@
from pathlib import Path
from typing import Any, BinaryIO, Callable, Mapping, TextIO, cast

from polars.utils import format_path, handle_projection_columns

try:
import pyarrow as pa

Expand All @@ -22,6 +20,7 @@
from polars.datatypes import DataType, Utf8
from polars.internals import DataFrame, LazyFrame, _scan_ds
from polars.internals.io import _prepare_file_arg
from polars.utils import format_path, handle_projection_columns

try:
import connectorx as cx
Expand Down Expand Up @@ -967,10 +966,10 @@ def read_sql(
protocol=protocol,
)
return cast(DataFrame, from_arrow(tbl))
else:
raise ImportError(
"connectorx is not installed. Please run `pip install connectorx>=0.2.2`."
)

raise ImportError(
"connectorx is not installed. Please run `pip install connectorx>=0.2.2`."
)


def read_excel(
Expand Down Expand Up @@ -1060,7 +1059,7 @@ def read_excel(
except ImportError:
raise ImportError(
"xlsx2csv is not installed. Please run `pip install xlsx2csv`."
)
) from None

if isinstance(file, (str, Path)):
file = format_path(file)
Expand Down
42 changes: 21 additions & 21 deletions py-polars/polars/testing.py
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Expand Up @@ -275,11 +275,11 @@ def _getattr_multi(obj: object, op: str) -> Any:
get the attribute "str", and then the attribute "lengths"
"""
op_list = op.split(".")
return reduce(lambda o, m: getattr(o, m), op_list, obj)
return reduce(getattr, op_list, obj)


def verify_series_and_expr_api(
input: Series, expected: Series | None, op: str, *args: Any, **kwargs: Any
result: Series, expected: Series | None, op: str, *args: Any, **kwargs: Any
) -> None:
"""
Small helper function to test element-wise functions for both the series and expressions api.
Expand All @@ -291,8 +291,8 @@ def verify_series_and_expr_api(
>>> verify_series_and_expr_api(s, expected, "sort")
"""
expr = _getattr_multi(col("*"), op)(*args, **kwargs)
result_expr: Series = input.to_frame().select(expr)[:, 0] # type: ignore[assignment]
result_series = _getattr_multi(input, op)(*args, **kwargs)
result_expr: Series = result.to_frame().select(expr)[:, 0] # type: ignore[assignment]
result_series = _getattr_multi(result, op)(*args, **kwargs)
if expected is None:
assert_series_equal(result_series, result_expr)
else:
Expand All @@ -305,7 +305,7 @@ def is_categorical_dtype(data_type: Any) -> bool:
Check if the input is a polars Categorical dtype.
"""
return (
type(data_type) is type
isinstance(data_type, type)
and issubclass(data_type, Categorical)
or isinstance(data_type, Categorical)
)
Expand Down Expand Up @@ -409,23 +409,23 @@ def __post_init__(self) -> None:
raise InvalidArgument(
f"No strategy (currently) available for {self.dtype} type"
)

# given a custom strategy, but no explicit dtype. infer one
# from the first non-None value that the strategy produces.
with warnings.catch_warnings():
# note: usually you should not call "example()" outside of an interactive shell, hence
# the warning. however, here it is reasonable to do so, so we catch and ignore it
warnings.simplefilter("ignore", NonInteractiveExampleWarning)
sample_value_iter = (self.strategy.example() for _ in range(100)) # type: ignore[union-attr]
sample_value_type = type(
next(e for e in sample_value_iter if e is not None)
)
if sample_value_type is not None:
self.dtype = py_type_to_dtype(sample_value_type)
else:
# given a custom strategy, but no explicit dtype. infer one
# from the first non-None value that the strategy produces.
with warnings.catch_warnings():
# note: usually you should not call "example()" outside of an interactive shell, hence
# the warning. however, here it is reasonable to do so, so we catch and ignore it
warnings.simplefilter("ignore", NonInteractiveExampleWarning)
sample_value_iter = (self.strategy.example() for _ in range(100)) # type: ignore[union-attr]
sample_value_type = type(
next(e for e in sample_value_iter if e is not None)
)
if sample_value_type is not None:
self.dtype = py_type_to_dtype(sample_value_type)
else:
raise InvalidArgument(
f"Unable to determine dtype for strategy {self.dtype} type"
)
raise InvalidArgument(
f"Unable to determine dtype for strategy {self.dtype} type"
)

def columns(
cols: int | Sequence[str] | None = None,
Expand Down
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