"""
pint.util
~~~~~~~~~
Miscellaneous functions for pint.
:copyright: 2016 by Pint Authors, see AUTHORS for more details.
:license: BSD, see LICENSE for more details.
"""
from __future__ import annotations
import logging
import math
import operator
import re
import tokenize
import types
from collections.abc import Callable, Generator, Hashable, Iterable, Iterator, Mapping
from fractions import Fraction
from functools import lru_cache, partial
from logging import NullHandler
from numbers import Number
from token import NAME, NUMBER
from typing import (
TYPE_CHECKING,
Any,
ClassVar,
TypeVar,
)
from . import pint_eval
from ._typing import Scalar
from .compat import NUMERIC_TYPES, Self
from .errors import DefinitionSyntaxError
from .pint_eval import build_eval_tree
if TYPE_CHECKING:
from ._typing import QuantityOrUnitLike
from .registry import UnitRegistry
logger = logging.getLogger(__name__)
logger.addHandler(NullHandler())
T = TypeVar("T")
TH = TypeVar("TH", bound=Hashable)
TT = TypeVar("TT", bound=type)
# TODO: Change when Python 3.10 becomes minimal version.
# ItMatrix: TypeAlias = Iterable[Iterable[PintScalar]]
# Matrix: TypeAlias = list[list[PintScalar]]
ItMatrix = Iterable[Iterable[Scalar]]
Matrix = list[list[Scalar]]
def _noop(x: T) -> T:
return x
[docs]
def matrix_to_string(
matrix: ItMatrix,
row_headers: Iterable[str] | None = None,
col_headers: Iterable[str] | None = None,
fmtfun: Callable[
[
Scalar,
],
str,
] = "{:0.0f}".format,
) -> str:
"""Return a string representation of a matrix.
Parameters
----------
matrix
A matrix given as an iterable of an iterable of numbers.
row_headers
An iterable of strings to serve as row headers.
(default = None, meaning no row headers are printed.)
col_headers
An iterable of strings to serve as column headers.
(default = None, meaning no col headers are printed.)
fmtfun
A callable to convert a number into string.
(default = `"{:0.0f}".format`)
Returns
-------
str
String representation of the matrix.
"""
ret: list[str] = []
if col_headers:
ret.append(("\t" if row_headers else "") + "\t".join(col_headers))
if row_headers:
ret += [
rh + "\t" + "\t".join(fmtfun(f) for f in row)
for rh, row in zip(row_headers, matrix)
]
else:
ret += ["\t".join(fmtfun(f) for f in row) for row in matrix]
return "\n".join(ret)
[docs]
def transpose(matrix: ItMatrix) -> Matrix:
"""Return the transposed version of a matrix.
Parameters
----------
matrix
A matrix given as an iterable of an iterable of numbers.
Returns
-------
Matrix
The transposed version of the matrix.
"""
return [list(val) for val in zip(*matrix)]
[docs]
def matrix_apply(
matrix: ItMatrix,
func: Callable[
[
Scalar,
],
Scalar,
],
) -> Matrix:
"""Apply a function to individual elements within a matrix.
Parameters
----------
matrix
A matrix given as an iterable of an iterable of numbers.
func
A callable that converts a number to another.
Returns
-------
A new matrix in which each element has been replaced by new one.
"""
return [[func(x) for x in row] for row in matrix]
[docs]
def pi_theorem(quantities: dict[str, Any], registry: UnitRegistry | None = None):
"""Builds dimensionless quantities using the Buckingham π theorem
Parameters
----------
quantities : dict
mapping between variable name and units
registry :
(default value = None)
Returns
-------
type
a list of dimensionless quantities expressed as dicts
"""
# Preprocess input and build the dimensionality Matrix
quant = []
dimensions = set()
if registry is None:
getdim = _noop
non_int_type = float
else:
getdim = registry.get_dimensionality
non_int_type = registry.non_int_type
for name, value in quantities.items():
if isinstance(value, str):
value = ParserHelper.from_string(value, non_int_type=non_int_type)
if isinstance(value, dict):
dims = getdim(registry.UnitsContainer(value))
elif not hasattr(value, "dimensionality"):
dims = getdim(value)
else:
dims = value.dimensionality
if not registry and any(not key.startswith("[") for key in dims):
logger.warning(
"A non dimension was found and a registry was not provided. "
"Assuming that it is a dimension name: {}.".format(dims)
)
quant.append((name, dims))
dimensions = dimensions.union(dims.keys())
dimensions = list(dimensions)
# Calculate dimensionless quantities
matrix = [
[dimensionality[dimension] for name, dimensionality in quant]
for dimension in dimensions
]
ech_matrix, id_matrix, pivot = column_echelon_form(matrix, transpose_result=False)
# Collect results
# Make all numbers integers and minimize the number of negative exponents.
# Remove zeros
results = []
for rowm, rowi in zip(ech_matrix, id_matrix):
if any(el != 0 for el in rowm):
continue
max_den = max(f.denominator for f in rowi)
neg = -1 if sum(f < 0 for f in rowi) > sum(f > 0 for f in rowi) else 1
results.append(
{
q[0]: neg * f.numerator * max_den / f.denominator
for q, f in zip(quant, rowi)
if f.numerator != 0
}
)
return results
[docs]
def solve_dependencies(
dependencies: dict[TH, set[TH]],
) -> Generator[set[TH], None, None]:
"""Solve a dependency graph.
Parameters
----------
dependencies :
dependency dictionary. For each key, the value is an iterable indicating its
dependencies.
Yields
------
set
iterator of sets, each containing keys of independents tasks dependent only of
the previous tasks in the list.
Raises
------
ValueError
if a cyclic dependency is found.
"""
while dependencies:
# values not in keys (items without dep)
t = {i for v in dependencies.values() for i in v} - dependencies.keys()
# and keys without value (items without dep)
t.update(k for k, v in dependencies.items() if not v)
# can be done right away
if not t:
raise ValueError(
"Cyclic dependencies exist among these items: {}".format(
", ".join(repr(x) for x in dependencies.items())
)
)
# and cleaned up
dependencies = {k: v - t for k, v in dependencies.items() if v}
yield t
[docs]
def find_shortest_path(
graph: dict[TH, set[TH]], start: TH, end: TH, path: list[TH] | None = None
):
"""Find shortest path between two nodes within a graph.
Parameters
----------
graph
A graph given as a mapping of nodes
to a set of all connected nodes to it.
start
Starting node.
end
End node.
path
Path to prepend to the one found.
(default = None, empty path.)
Returns
-------
list[TH]
The shortest path between two nodes.
"""
path = (path or []) + [start]
if start == end:
return path
# TODO: raise ValueError when start not in graph
if start not in graph:
return None
shortest = None
for node in graph[start]:
if node not in path:
newpath = find_shortest_path(graph, node, end, path)
if newpath:
if not shortest or len(newpath) < len(shortest):
shortest = newpath
return shortest
[docs]
def find_connected_nodes(
graph: dict[TH, set[TH]], start: TH, visited: set[TH] | None = None
) -> set[TH] | None:
"""Find all nodes connected to a start node within a graph.
Parameters
----------
graph
A graph given as a mapping of nodes
to a set of all connected nodes to it.
start
Starting node.
visited
Mutable set to collect visited nodes.
(default = None, empty set)
Returns
-------
set[TH]
The shortest path between two nodes.
"""
# TODO: raise ValueError when start not in graph
if start not in graph:
return None
visited = visited or set()
visited.add(start)
for node in graph[start]:
if node not in visited:
find_connected_nodes(graph, node, visited)
return visited
[docs]
class udict(dict[str, Scalar]):
"""Custom dict implementing __missing__."""
def __missing__(self, key: str):
return 0
[docs]
def copy(self: Self) -> Self:
return udict(self)
[docs]
class UnitsContainer(Mapping[str, Scalar]):
"""The UnitsContainer stores the product of units and their respective
exponent and implements the corresponding operations.
UnitsContainer is a read-only mapping. All operations (even in place ones)
return new instances.
Parameters
----------
non_int_type
Numerical type used for non integer values.
"""
__slots__ = ("_d", "_hash", "_one", "_non_int_type")
_d: udict
_hash: int | None
_one: Scalar
_non_int_type: type
def __init__(
self, *args: Any, non_int_type: type | None = None, **kwargs: Any
) -> None:
if args and isinstance(args[0], UnitsContainer):
default_non_int_type = args[0]._non_int_type
else:
default_non_int_type = float
self._non_int_type = non_int_type or default_non_int_type
if self._non_int_type is float:
self._one = 1
else:
self._one = self._non_int_type("1")
d = udict(*args, **kwargs)
self._d = d
for key, value in d.items():
if not isinstance(key, str):
raise TypeError(f"key must be a str, not {type(key)}")
if not isinstance(value, Number):
raise TypeError(f"value must be a number, not {type(value)}")
if not isinstance(value, int) and not isinstance(value, self._non_int_type):
d[key] = self._non_int_type(value)
self._hash = None
[docs]
def copy(self: Self) -> Self:
"""Create a copy of this UnitsContainer."""
return self.__copy__()
[docs]
def add(self: Self, key: str, value: Number) -> Self:
"""Create a new UnitsContainer adding value to
the value existing for a given key.
Parameters
----------
key
unit to which the value will be added.
value
value to be added.
Returns
-------
UnitsContainer
A copy of this container.
"""
newval = self._d[key] + value
new = self.copy()
if newval:
new._d[key] = newval
else:
new._d.pop(key)
new._hash = None
return new
[docs]
def remove(self: Self, keys: Iterable[str]) -> Self:
"""Create a new UnitsContainer purged from given entries.
Parameters
----------
keys
Iterable of keys (units) to remove.
Returns
-------
UnitsContainer
A copy of this container.
"""
new = self.copy()
for k in keys:
new._d.pop(k)
new._hash = None
return new
[docs]
def rename(self: Self, oldkey: str, newkey: str) -> Self:
"""Create a new UnitsContainer in which an entry has been renamed.
Parameters
----------
oldkey
Existing key (unit).
newkey
New key (unit).
Returns
-------
UnitsContainer
A copy of this container.
"""
new = self.copy()
new._d[newkey] = new._d.pop(oldkey)
new._hash = None
return new
def unit_items(self) -> Iterable[tuple[str, Scalar]]:
return self._d.items()
def __iter__(self) -> Iterator[str]:
return iter(self._d)
def __len__(self) -> int:
return len(self._d)
def __getitem__(self, key: str) -> Scalar:
return self._d[key]
def __contains__(self, key: str) -> bool:
return key in self._d
def __hash__(self) -> int:
if self._hash is None:
self._hash = hash(frozenset(self._d.items()))
return self._hash
# Only needed by pickle protocol 0 and 1 (used by pytables)
def __getstate__(self) -> tuple[udict, Scalar, type]:
return self._d, self._one, self._non_int_type
def __setstate__(self, state: tuple[udict, Scalar, type]):
self._d, self._one, self._non_int_type = state
self._hash = None
def __eq__(self, other: Any) -> bool:
if isinstance(other, UnitsContainer):
# UnitsContainer.__hash__(self) is not the same as hash(self); see
# ParserHelper.__hash__ and __eq__.
# Different hashes guarantee that the actual contents are different, but
# identical hashes give no guarantee of equality.
# e.g. in CPython, hash(-1) == hash(-2)
if UnitsContainer.__hash__(self) != UnitsContainer.__hash__(other):
return False
other = other._d
elif isinstance(other, str):
try:
other = ParserHelper.from_string(other, self._non_int_type)
except DefinitionSyntaxError:
return False
other = other._d
return dict.__eq__(self._d, other)
def __str__(self) -> str:
return self.__format__("")
def __repr__(self) -> str:
tmp = "{%s}" % ", ".join(
[f"'{key}': {value}" for key, value in sorted(self._d.items())]
)
return f"<UnitsContainer({tmp})>"
def __format__(self, spec: str) -> str:
# TODO: provisional
from .formatting import format_unit
return format_unit(self, spec)
def format_babel(self, spec: str, registry=None, **kwspec) -> str:
# TODO: provisional
from .formatting import format_unit
return format_unit(self, spec, registry=registry, **kwspec)
def __copy__(self):
# Skip expensive health checks performed by __init__
out = object.__new__(self.__class__)
out._d = self._d.copy()
out._hash = self._hash
out._non_int_type = self._non_int_type
out._one = self._one
return out
def __mul__(self, other: Any):
if not isinstance(other, self.__class__):
err = "Cannot multiply UnitsContainer by {}"
raise TypeError(err.format(type(other)))
new = self.copy()
for key, value in other.items():
new._d[key] += value
if new._d[key] == 0:
del new._d[key]
new._hash = None
return new
__rmul__ = __mul__
def __pow__(self, other: Any):
if not isinstance(other, NUMERIC_TYPES):
err = "Cannot power UnitsContainer by {}"
raise TypeError(err.format(type(other)))
new = self.copy()
for key, value in new._d.items():
new._d[key] *= other
new._hash = None
return new
def __truediv__(self, other: Any):
if not isinstance(other, self.__class__):
err = "Cannot divide UnitsContainer by {}"
raise TypeError(err.format(type(other)))
new = self.copy()
for key, value in other.items():
new._d[key] -= value
if new._d[key] == 0:
del new._d[key]
new._hash = None
return new
def __rtruediv__(self, other: Any):
if not isinstance(other, self.__class__) and other != 1:
err = "Cannot divide {} by UnitsContainer"
raise TypeError(err.format(type(other)))
return self**-1
[docs]
class ParserHelper(UnitsContainer):
"""The ParserHelper stores in place the product of variables and
their respective exponent and implements the corresponding operations.
It also provides a scaling factor.
For example:
`3 * m ** 2` becomes ParserHelper(3, m=2)
Briefly is a UnitsContainer with a scaling factor.
ParserHelper is a read-only mapping. All operations (even in place ones)
return new instances.
WARNING : The hash value used does not take into account the scale
attribute so be careful if you use it as a dict key and then two unequal
object can have the same hash.
Parameters
----------
scale
Scaling factor.
(default = 1)
**kwargs
Used to populate the dict of units and exponents.
"""
__slots__ = ("scale",)
scale: Scalar
def __init__(self, scale: Scalar = 1, *args, **kwargs):
super().__init__(*args, **kwargs)
self.scale = scale
[docs]
@classmethod
def from_word(cls, input_word: str, non_int_type: type = float) -> ParserHelper:
"""Creates a ParserHelper object with a single variable with exponent one.
Equivalent to: ParserHelper(1, {input_word: 1})
Parameters
----------
input_word
non_int_type
Numerical type used for non integer values.
"""
if non_int_type is float:
return cls(1, [(input_word, 1)], non_int_type=non_int_type)
else:
ONE = non_int_type("1")
return cls(ONE, [(input_word, ONE)], non_int_type=non_int_type)
@classmethod
def eval_token(cls, token: tokenize.TokenInfo, non_int_type: type = float):
token_type = token.type
token_text = token.string
if token_type == NUMBER:
if non_int_type is float:
try:
return int(token_text)
except ValueError:
return float(token_text)
else:
return non_int_type(token_text)
elif token_type == NAME:
return ParserHelper.from_word(token_text, non_int_type=non_int_type)
else:
raise Exception("unknown token type")
[docs]
@classmethod
@lru_cache
def from_string(cls, input_string: str, non_int_type: type = float) -> ParserHelper:
"""Parse linear expression mathematical units and return a quantity object.
Parameters
----------
input_string
non_int_type
Numerical type used for non integer values.
"""
if not input_string:
return cls(non_int_type=non_int_type)
input_string = string_preprocessor(input_string)
if "[" in input_string:
input_string = input_string.replace("[", "__obra__").replace(
"]", "__cbra__"
)
reps = True
else:
reps = False
gen = pint_eval.tokenizer(input_string)
ret = build_eval_tree(gen).evaluate(
partial(cls.eval_token, non_int_type=non_int_type)
)
if isinstance(ret, Number):
return cls(ret, non_int_type=non_int_type)
if reps:
ret = cls(
ret.scale,
{
key.replace("__obra__", "[").replace("__cbra__", "]"): value
for key, value in ret.items()
},
non_int_type=non_int_type,
)
for k in list(ret):
if k.lower() == "nan":
del ret._d[k]
ret.scale = non_int_type(math.nan)
return ret
def __copy__(self):
new = super().__copy__()
new.scale = self.scale
return new
[docs]
def copy(self):
return self.__copy__()
def __hash__(self):
if self.scale != 1:
mess = "Only scale 1 ParserHelper instance should be considered hashable"
raise ValueError(mess)
return super().__hash__()
# Only needed by pickle protocol 0 and 1 (used by pytables)
def __getstate__(self):
return super().__getstate__() + (self.scale,)
def __setstate__(self, state):
super().__setstate__(state[:-1])
self.scale = state[-1]
def __eq__(self, other: Any) -> bool:
if isinstance(other, ParserHelper):
return self.scale == other.scale and super().__eq__(other)
elif isinstance(other, str):
return self == ParserHelper.from_string(other, self._non_int_type)
elif isinstance(other, Number):
return self.scale == other and not len(self._d)
return self.scale == 1 and super().__eq__(other)
def operate(self, items, op=operator.iadd, cleanup: bool = True):
d = udict(self._d)
for key, value in items:
d[key] = op(d[key], value)
if cleanup:
keys = [key for key, value in d.items() if value == 0]
for key in keys:
del d[key]
return self.__class__(self.scale, d, non_int_type=self._non_int_type)
def __str__(self):
tmp = "{%s}" % ", ".join(
[f"'{key}': {value}" for key, value in sorted(self._d.items())]
)
return f"{self.scale} {tmp}"
def __repr__(self):
tmp = "{%s}" % ", ".join(
[f"'{key}': {value}" for key, value in sorted(self._d.items())]
)
return f"<ParserHelper({self.scale}, {tmp})>"
def __mul__(self, other):
if isinstance(other, str):
new = self.add(other, self._one)
elif isinstance(other, Number):
new = self.copy()
new.scale *= other
elif isinstance(other, self.__class__):
new = self.operate(other.items())
new.scale *= other.scale
else:
new = self.operate(other.items())
return new
__rmul__ = __mul__
def __pow__(self, other):
d = self._d.copy()
for key in self._d:
d[key] *= other
return self.__class__(self.scale**other, d, non_int_type=self._non_int_type)
def __truediv__(self, other):
if isinstance(other, str):
new = self.add(other, -1)
elif isinstance(other, Number):
new = self.copy()
new.scale /= other
elif isinstance(other, self.__class__):
new = self.operate(other.items(), operator.sub)
new.scale /= other.scale
else:
new = self.operate(other.items(), operator.sub)
return new
__floordiv__ = __truediv__
def __rtruediv__(self, other):
new = self.__pow__(-1)
if isinstance(other, str):
new = new.add(other, self._one)
elif isinstance(other, Number):
new.scale *= other
elif isinstance(other, self.__class__):
new = self.operate(other.items(), operator.add)
new.scale *= other.scale
else:
new = new.operate(other.items(), operator.add)
return new
#: List of regex substitution pairs.
_subs_re_list = [
("\N{DEGREE SIGN}", "degree"),
(r"([\w\.\-\+\*\\\^])\s+", r"\1 "), # merge multiple spaces
(r"({}) squared", r"\1**2"), # Handle square and cube
(r"({}) cubed", r"\1**3"),
(r"cubic ({})", r"\1**3"),
(r"square ({})", r"\1**2"),
(r"sq ({})", r"\1**2"),
(
r"\b([0-9]+\.?[0-9]*)(?=[e|E][a-zA-Z]|[a-df-zA-DF-Z])",
r"\1*",
), # Handle numberLetter for multiplication
(r"([\w\.\)])\s+(?=[\w\(])", r"\1*"), # Handle space for multiplication
]
#: Compiles the regex and replace {} by a regex that matches an identifier.
_subs_re = [
(re.compile(a.format(r"[_a-zA-Z][_a-zA-Z0-9]*")), b) for a, b in _subs_re_list
]
_pretty_table = str.maketrans("⁰¹²³⁴⁵⁶⁷⁸⁹·⁻", "0123456789*-")
_pretty_exp_re = re.compile(r"(⁻?[⁰¹²³⁴⁵⁶⁷⁸⁹]+(?:\.[⁰¹²³⁴⁵⁶⁷⁸⁹]*)?)")
def string_preprocessor(input_string: str) -> str:
input_string = input_string.replace(",", "")
input_string = input_string.replace(" per ", "/")
for a, b in _subs_re:
input_string = a.sub(b, input_string)
input_string = _pretty_exp_re.sub(r"**(\1)", input_string)
# Replace pretty format characters
input_string = input_string.translate(_pretty_table)
# Handle caret exponentiation
input_string = input_string.replace("^", "**")
return input_string
def _is_dim(name: str) -> bool:
return name[0] == "[" and name[-1] == "]"
[docs]
class SharedRegistryObject:
"""Base class for object keeping a reference to the registree.
Such object are for now Quantity and Unit, in a number of places it is
that an object from this class has a '_units' attribute.
Parameters
----------
Returns
-------
"""
_REGISTRY: ClassVar[UnitRegistry]
_units: UnitsContainer
def __new__(cls, *args, **kwargs):
inst = object.__new__(cls)
if not hasattr(cls, "_REGISTRY"):
# Base class, not subclasses dynamically by
# UnitRegistry._init_dynamic_classes
from . import application_registry
inst._REGISTRY = application_registry.get()
return inst
def _check(self, other: Any) -> bool:
"""Check if the other object use a registry and if so that it is the
same registry.
Parameters
----------
other
Returns
-------
bool
Raises
------
ValueError
if other don't use the same unit registry.
"""
if self._REGISTRY is getattr(other, "_REGISTRY", None):
return True
elif isinstance(other, SharedRegistryObject):
mess = "Cannot operate with {} and {} of different registries."
raise ValueError(
mess.format(self.__class__.__name__, other.__class__.__name__)
)
else:
return False
[docs]
class PrettyIPython:
"""Mixin to add pretty-printers for IPython"""
default_format: str
def _repr_html_(self) -> str:
if "~" in self._REGISTRY.formatter.default_format:
return f"{self:~H}"
return f"{self:H}"
def _repr_latex_(self) -> str:
if "~" in self._REGISTRY.formatter.default_format:
return f"${self:~L}$"
return f"${self:L}$"
def _repr_pretty_(self, p, cycle: bool):
# if cycle:
if "~" in self._REGISTRY.formatter.default_format:
p.text(f"{self:~P}")
else:
p.text(f"{self:P}")
# else:
# p.pretty(self.magnitude)
# p.text(" ")
# p.pretty(self.units)
[docs]
def to_units_container(
unit_like: QuantityOrUnitLike, registry: UnitRegistry | None = None
) -> UnitsContainer:
"""Convert a unit compatible type to a UnitsContainer.
Parameters
----------
unit_like
Quantity or Unit to infer the plain units from.
registry
If provided, uses the registry's UnitsContainer and parse_unit_name. If None,
uses the registry attached to unit_like.
Returns
-------
UnitsContainer
"""
mro = type(unit_like).mro()
if UnitsContainer in mro:
return unit_like
elif SharedRegistryObject in mro:
return unit_like._units
elif str in mro:
if registry:
# TODO: document how to whether to lift preprocessing loop out to caller
for p in registry.preprocessors:
unit_like = p(unit_like)
return registry.parse_units_as_container(unit_like)
else:
return ParserHelper.from_string(unit_like)
elif dict in mro:
if registry:
return registry.UnitsContainer(unit_like)
else:
return UnitsContainer(unit_like)
[docs]
def infer_base_unit(
unit_like: QuantityOrUnitLike, registry: UnitRegistry | None = None
) -> UnitsContainer:
"""
Given a Quantity or UnitLike, give the UnitsContainer for it's plain units.
Parameters
----------
unit_like
Quantity or Unit to infer the plain units from.
registry
If provided, uses the registry's UnitsContainer and parse_unit_name. If None,
uses the registry attached to unit_like.
Returns
-------
UnitsContainer
Raises
------
ValueError
The unit_like did not reference a registry, and no registry was provided.
"""
d = udict()
original_units = to_units_container(unit_like, registry)
if registry is None and hasattr(unit_like, "_REGISTRY"):
registry = unit_like._REGISTRY
if registry is None:
raise ValueError("No registry provided.")
for unit_name, power in original_units.items():
candidates = registry.parse_unit_name(unit_name)
assert len(candidates) == 1
_, base_unit, _ = candidates[0]
d[base_unit] += power
# remove values that resulted in a power of 0
nonzero_dict = {k: v for k, v in d.items() if v != 0}
return registry.UnitsContainer(nonzero_dict)
[docs]
def getattr_maybe_raise(obj: Any, item: str):
"""Helper function invoked at start of all overridden ``__getattr__``.
Raise AttributeError if the user tries to ask for a _ or __ attribute,
*unless* it is immediately followed by a number, to enable units
encompassing constants, such as ``L / _100km``.
Parameters
----------
item
attribute to be found.
Raises
------
AttributeError
"""
# Double-underscore attributes are tricky to detect because they are
# automatically prefixed with the class name - which may be a subclass of obj
if (
item.endswith("__")
or len(item.lstrip("_")) == 0
or (item.startswith("_") and not item.lstrip("_")[0].isdigit())
):
raise AttributeError(f"{obj!r} object has no attribute {item!r}")
[docs]
def iterable(y: Any) -> bool:
"""Check whether or not an object can be iterated over."""
try:
iter(y)
except TypeError:
return False
return True
[docs]
def sized(y: Any) -> bool:
"""Check whether or not an object has a defined length."""
try:
len(y)
except TypeError:
return False
return True
[docs]
def create_class_with_registry(
registry: UnitRegistry, base_class: type[TT]
) -> type[TT]:
"""Create new class inheriting from base_class and
filling _REGISTRY class attribute with an actual instanced registry.
"""
class_body = {
"__module__": "pint",
"_REGISTRY": registry,
}
return types.new_class(
base_class.__name__,
bases=(base_class,),
exec_body=lambda ns: ns.update(class_body),
)
