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numpy_engine.py
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numpy_engine.py
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"""Numpy engine and data types."""
# docstrings are inherited
# pylint:disable=missing-class-docstring,too-many-ancestors
import builtins
import dataclasses
import datetime
import inspect
import warnings
from typing import Any, Dict, Iterable, List, Optional, Union, cast
import numpy as np
from pandera import dtypes, errors
from pandera.dtypes import immutable
from pandera.engines import engine, utils
from pandera.engines.type_aliases import PandasObject
from pandera.system import FLOAT_128_AVAILABLE
@immutable(init=True)
class DataType(dtypes.DataType):
"""Base `DataType` for boxing Numpy data types."""
type: np.dtype = dataclasses.field(
default=np.dtype("object"), repr=False, init=False
)
"""Native numpy dtype boxed by the data type."""
def __init__(self, dtype: Any):
super().__init__()
object.__setattr__(self, "type", np.dtype(dtype))
dtype_cls = dtype if inspect.isclass(dtype) else dtype.__class__
warnings.warn(
f"'{dtype_cls}' support is not guaranteed.\n"
+ "Usage Tip: Consider writing a custom "
+ "pandera.dtypes.DataType or opening an issue at "
+ "https://github.com/pandera-dev/pandera"
)
def __post_init__(self):
# this method isn't called if __init__ is defined
object.__setattr__(
self, "type", np.dtype(self.type)
) # pragma: no cover
def coerce(
self, data_container: Union[PandasObject, np.ndarray]
) -> Union[PandasObject, np.ndarray]:
"""Pure coerce without catching exceptions."""
coerced = data_container.astype(self.type)
if type(data_container).__module__.startswith("modin.pandas"):
# NOTE: this is a hack to enable catching of errors in modin
coerced.__str__()
return coerced
def coerce_value(self, value: Any) -> Any:
"""Coerce an value to a particular type."""
return self.type.type(value)
def try_coerce(
self, data_container: Union[PandasObject, np.ndarray]
) -> Union[PandasObject, np.ndarray]:
try:
return self.coerce(cast(PandasObject, data_container))
except Exception as exc: # pylint:disable=broad-except
raise errors.ParserError(
f"Could not coerce {type(data_container)} data_container "
f"into type {self.type}",
failure_cases=utils.numpy_pandas_coerce_failure_cases(
data_container, self.type
),
) from exc
def __str__(self) -> str:
return self.type.name
def __repr__(self) -> str:
return f"DataType({self})"
class Engine( # pylint:disable=too-few-public-methods
metaclass=engine.Engine, base_pandera_dtypes=DataType
):
"""Numpy data type engine."""
@classmethod
def dtype(cls, data_type: Any) -> dtypes.DataType:
"""Convert input into a numpy-compatible
Pandera :class:`~pandera.dtypes.DataType` object."""
try:
return engine.Engine.dtype(cls, data_type)
except TypeError:
try:
np_dtype = np.dtype(data_type).type
except TypeError:
raise TypeError(
f"data type '{data_type}' not understood by "
f"{cls.__name__}."
) from None
try:
return engine.Engine.dtype(cls, np_dtype)
except TypeError:
return DataType(data_type)
###############################################################################
# boolean
###############################################################################
@Engine.register_dtype(
equivalents=["bool", bool, np.bool_, dtypes.Bool, dtypes.Bool()]
)
@immutable
class Bool(DataType, dtypes.Bool):
type = np.dtype("bool")
def _build_number_equivalents(
builtin_name: str, pandera_name: str, sizes: List[int]
) -> Dict[int, List[Union[type, str, np.dtype, dtypes.DataType]]]:
"""Return a dict of equivalent builtin, numpy, pandera dtypes
indexed by size in bit_width."""
builtin_type = getattr(builtins, builtin_name, None)
default_np_dtype = np.dtype(builtin_name)
default_size = int(default_np_dtype.name.replace(builtin_name, ""))
default_equivalents = [
# e.g.: np.int64
np.dtype(builtin_name).type,
# e.g: pandera.dtypes.Int
getattr(dtypes, pandera_name),
]
if builtin_type:
default_equivalents.append(builtin_type)
return {
bit_width: list(
set(
(
# e.g.: numpy.int64
getattr(np, f"{builtin_name}{bit_width}"),
# e.g.: pandera.dtypes.Int64
getattr(dtypes, f"{pandera_name}{bit_width}"),
getattr(dtypes, f"{pandera_name}{bit_width}")(),
# e.g.: pandera.dtypes.Int(64)
getattr(dtypes, pandera_name)(),
)
)
| set(default_equivalents if bit_width == default_size else [])
)
for bit_width in sizes
}
###############################################################################
# signed integer
###############################################################################
_int_equivalents = _build_number_equivalents(
builtin_name="int", pandera_name="Int", sizes=[64, 32, 16, 8]
)
@Engine.register_dtype(equivalents=_int_equivalents[64])
@immutable
class Int64(DataType, dtypes.Int64):
type = np.dtype("int64")
bit_width: int = 64
@Engine.register_dtype(equivalents=_int_equivalents[32])
@immutable
class Int32(Int64):
type = np.dtype("int32") # type: ignore
bit_width: int = 32
@Engine.register_dtype(equivalents=_int_equivalents[16])
@immutable
class Int16(Int32):
type = np.dtype("int16") # type: ignore
bit_width: int = 16
@Engine.register_dtype(equivalents=_int_equivalents[8])
@immutable
class Int8(Int16):
type = np.dtype("int8") # type: ignore
bit_width: int = 8
###############################################################################
# unsigned integer
###############################################################################
_uint_equivalents = _build_number_equivalents(
builtin_name="uint",
pandera_name="UInt",
sizes=[64, 32, 16, 8],
)
@Engine.register_dtype(equivalents=_uint_equivalents[64])
@immutable
class UInt64(DataType, dtypes.UInt64):
type = np.dtype("uint64")
bit_width: int = 64
@Engine.register_dtype(equivalents=_uint_equivalents[32])
@immutable
class UInt32(UInt64):
type = np.dtype("uint32") # type: ignore
bit_width: int = 32
@Engine.register_dtype(equivalents=_uint_equivalents[16])
@immutable
class UInt16(UInt32):
type = np.dtype("uint16") # type: ignore
bit_width: int = 16
@Engine.register_dtype(equivalents=_uint_equivalents[8])
@immutable
class UInt8(UInt16):
type = np.dtype("uint8") # type: ignore
bit_width: int = 8
###############################################################################
# float
###############################################################################
_float_equivalents = _build_number_equivalents(
builtin_name="float",
pandera_name="Float",
sizes=[128, 64, 32, 16] if FLOAT_128_AVAILABLE else [64, 32, 16],
)
if FLOAT_128_AVAILABLE:
# not supported in windows:
# https://github.com/winpython/winpython/issues/613
#
# or Mac M1:
# https://github.com/pandera-dev/pandera/issues/623
@Engine.register_dtype(equivalents=_float_equivalents[128])
@immutable
class Float128(DataType, dtypes.Float128):
type = np.dtype("float128")
bit_width: int = 128
@Engine.register_dtype(equivalents=_float_equivalents[64])
@immutable
class Float64(Float128):
type = np.dtype("float64")
bit_width: int = 64
else:
@Engine.register_dtype(equivalents=_float_equivalents[64])
@immutable
class Float64(DataType, dtypes.Float64): # type: ignore
type = np.dtype("float64")
bit_width: int = 64
@Engine.register_dtype(equivalents=_float_equivalents[32])
@immutable
class Float32(Float64):
type = np.dtype("float32") # type: ignore
bit_width: int = 32
@Engine.register_dtype(equivalents=_float_equivalents[16])
@immutable
class Float16(Float32):
type = np.dtype("float16") # type: ignore
bit_width: int = 16
###############################################################################
# complex
###############################################################################
_complex_equivalents = _build_number_equivalents(
builtin_name="complex",
pandera_name="Complex",
sizes=[256, 128, 64] if FLOAT_128_AVAILABLE else [128, 64],
)
if FLOAT_128_AVAILABLE:
# not supported in windows
# https://github.com/winpython/winpython/issues/613
@Engine.register_dtype(equivalents=_complex_equivalents[256])
@immutable
class Complex256(DataType, dtypes.Complex256):
type = np.dtype("complex256")
bit_width: int = 256
@Engine.register_dtype(equivalents=_complex_equivalents[128])
@immutable
class Complex128(Complex256):
type = np.dtype("complex128") # type: ignore
bit_width: int = 128
else:
@Engine.register_dtype(equivalents=_complex_equivalents[128])
@immutable
class Complex128(DataType, dtypes.Complex128): # type: ignore
type = np.dtype("complex128") # type: ignore
bit_width: int = 128
@Engine.register_dtype(equivalents=_complex_equivalents[64])
@immutable
class Complex64(Complex128):
type = np.dtype("complex64") # type: ignore
bit_width: int = 64
###############################################################################
# bytes
###############################################################################
@Engine.register_dtype(equivalents=["bytes", bytes, np.bytes_])
@immutable
class Bytes(DataType):
type = np.dtype("bytes")
###############################################################################
# string
###############################################################################
@Engine.register_dtype(equivalents=["str", "string", str, np.str_])
@immutable
class String(DataType, dtypes.String):
type = np.dtype("str")
def coerce(
self,
data_container: Union[PandasObject, np.ndarray],
) -> Union[PandasObject, np.ndarray]:
data_container = data_container.astype(object)
try:
notna = ~np.isnan(data_container)
except TypeError:
notna = np.ones_like(data_container).astype(bool)
data_container[notna] = data_container[notna].astype(str)
return data_container
def check(
self,
pandera_dtype: "dtypes.DataType",
data_container: Optional[PandasObject] = None,
) -> Union[bool, Iterable[bool]]:
return isinstance(pandera_dtype, (Object, type(self)))
###############################################################################
# object
###############################################################################
@Engine.register_dtype(equivalents=["object", "O", object, np.object_])
@immutable
class Object(DataType):
"""Semantic representation of a :class:`numpy.object_`."""
type = np.dtype("object")
###############################################################################
# time
###############################################################################
@Engine.register_dtype(
equivalents=[
datetime.datetime,
np.datetime64,
dtypes.Timestamp,
dtypes.Timestamp(),
]
)
@immutable
class DateTime64(DataType, dtypes.Timestamp):
type = np.dtype("datetime64")
@Engine.register_dtype(
equivalents=[
datetime.datetime,
np.timedelta64,
dtypes.Timedelta,
dtypes.Timedelta(),
]
)
@immutable
class Timedelta64(DataType, dtypes.Timedelta):
type = np.dtype("timedelta64[ns]")