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"""
This module contains essential stuff that should've come with Python itself ;)
"""
from __future__ import annotations
import gc
import inspect
import re
import sys
import warnings
import weakref
from collections.abc import AsyncIterator, Iterable, Mapping
from functools import partial, wraps
from itertools import chain
from typing import TYPE_CHECKING, Any, TypeVar, overload
from scrapy.exceptions import ScrapyDeprecationWarning
from scrapy.utils.asyncgen import as_async_generator
if TYPE_CHECKING:
from collections.abc import Callable, Iterator
from re import Pattern
# typing.Concatenate and typing.ParamSpec require Python 3.10
# typing.Self requires Python 3.11
from typing_extensions import Concatenate, ParamSpec, Self
_P = ParamSpec("_P")
_T = TypeVar("_T")
_KT = TypeVar("_KT")
_VT = TypeVar("_VT")
def flatten(x: Iterable[Any]) -> list[Any]:
"""flatten(sequence) -> list
Returns a single, flat list which contains all elements retrieved
from the sequence and all recursively contained sub-sequences
(iterables).
Examples:
>>> [1, 2, [3,4], (5,6)]
[1, 2, [3, 4], (5, 6)]
>>> flatten([[[1,2,3], (42,None)], [4,5], [6], 7, (8,9,10)])
[1, 2, 3, 42, None, 4, 5, 6, 7, 8, 9, 10]
>>> flatten(["foo", "bar"])
['foo', 'bar']
>>> flatten(["foo", ["baz", 42], "bar"])
['foo', 'baz', 42, 'bar']
"""
warnings.warn(
"The flatten function is deprecated and will be removed in a future version of Scrapy.",
category=ScrapyDeprecationWarning,
stacklevel=2,
)
return list(iflatten(x))
def iflatten(x: Iterable[Any]) -> Iterable[Any]:
"""iflatten(sequence) -> iterator
Similar to ``.flatten()``, but returns iterator instead"""
warnings.warn(
"The iflatten function is deprecated and will be removed in a future version of Scrapy.",
category=ScrapyDeprecationWarning,
stacklevel=2,
)
for el in x:
if is_listlike(el):
yield from iflatten(el)
else:
yield el
def is_listlike(x: Any) -> bool:
"""
>>> is_listlike("foo")
False
>>> is_listlike(5)
False
>>> is_listlike(b"foo")
False
>>> is_listlike([b"foo"])
True
>>> is_listlike((b"foo",))
True
>>> is_listlike({})
True
>>> is_listlike(set())
True
>>> is_listlike((x for x in range(3)))
True
>>> is_listlike(range(5))
True
"""
return hasattr(x, "__iter__") and not isinstance(x, (str, bytes))
def unique(list_: Iterable[_T], key: Callable[[_T], Any] = lambda x: x) -> list[_T]:
"""efficient function to uniquify a list preserving item order"""
seen = set()
result: list[_T] = []
for item in list_:
seenkey = key(item)
if seenkey in seen:
continue
seen.add(seenkey)
result.append(item)
return result
def to_unicode(
text: str | bytes, encoding: str | None = None, errors: str = "strict"
) -> str:
"""Return the unicode representation of a bytes object ``text``. If
``text`` is already an unicode object, return it as-is."""
if isinstance(text, str):
return text
if not isinstance(text, (bytes, str)):
raise TypeError(
f"to_unicode must receive a bytes or str object, got {type(text).__name__}"
)
if encoding is None:
encoding = "utf-8"
return text.decode(encoding, errors)
def to_bytes(
text: str | bytes, encoding: str | None = None, errors: str = "strict"
) -> bytes:
"""Return the binary representation of ``text``. If ``text``
is already a bytes object, return it as-is."""
if isinstance(text, bytes):
return text
if not isinstance(text, str):
raise TypeError(
f"to_bytes must receive a str or bytes object, got {type(text).__name__}"
)
if encoding is None:
encoding = "utf-8"
return text.encode(encoding, errors)
def re_rsearch(
pattern: str | Pattern[str], text: str, chunk_size: int = 1024
) -> tuple[int, int] | None:
"""
This function does a reverse search in a text using a regular expression
given in the attribute 'pattern'.
Since the re module does not provide this functionality, we have to find for
the expression into chunks of text extracted from the end (for the sake of efficiency).
At first, a chunk of 'chunk_size' kilobytes is extracted from the end, and searched for
the pattern. If the pattern is not found, another chunk is extracted, and another
search is performed.
This process continues until a match is found, or until the whole file is read.
In case the pattern wasn't found, None is returned, otherwise it returns a tuple containing
the start position of the match, and the ending (regarding the entire text).
"""
def _chunk_iter() -> Iterable[tuple[str, int]]:
offset = len(text)
while True:
offset -= chunk_size * 1024
if offset <= 0:
break
yield (text[offset:], offset)
yield (text, 0)
if isinstance(pattern, str):
pattern = re.compile(pattern)
for chunk, offset in _chunk_iter():
matches = list(pattern.finditer(chunk))
if matches:
start, end = matches[-1].span()
return offset + start, offset + end
return None
_SelfT = TypeVar("_SelfT")
def memoizemethod_noargs(
method: Callable[Concatenate[_SelfT, _P], _T],
) -> Callable[Concatenate[_SelfT, _P], _T]:
"""Decorator to cache the result of a method (without arguments) using a
weak reference to its object
"""
cache: weakref.WeakKeyDictionary[_SelfT, _T] = weakref.WeakKeyDictionary()
@wraps(method)
def new_method(self: _SelfT, *args: _P.args, **kwargs: _P.kwargs) -> _T:
if self not in cache:
cache[self] = method(self, *args, **kwargs)
return cache[self]
return new_method
_BINARYCHARS = {
i for i in range(32) if to_bytes(chr(i)) not in {b"\0", b"\t", b"\n", b"\r"}
}
def binary_is_text(data: bytes) -> bool:
"""Returns ``True`` if the given ``data`` argument (a ``bytes`` object)
does not contain unprintable control characters.
"""
if not isinstance(data, bytes):
raise TypeError(f"data must be bytes, got '{type(data).__name__}'")
return all(c not in _BINARYCHARS for c in data)
def get_func_args(func: Callable[..., Any], stripself: bool = False) -> list[str]:
"""Return the argument name list of a callable object"""
if not callable(func):
raise TypeError(f"func must be callable, got '{type(func).__name__}'")
args: list[str] = []
try:
sig = inspect.signature(func)
except ValueError:
return args
if isinstance(func, partial):
partial_args = func.args
partial_kw = func.keywords
for name, param in sig.parameters.items():
if param.name in partial_args:
continue
if partial_kw and param.name in partial_kw:
continue
args.append(name)
else:
args = list(sig.parameters)
if stripself and args and args[0] == "self":
args = args[1:]
return args
def get_spec(func: Callable[..., Any]) -> tuple[list[str], dict[str, Any]]:
"""Returns (args, kwargs) tuple for a function
>>> import re
>>> get_spec(re.match)
(['pattern', 'string'], {'flags': 0})
>>> class Test:
... def __call__(self, val):
... pass
... def method(self, val, flags=0):
... pass
>>> get_spec(Test)
(['self', 'val'], {})
>>> get_spec(Test.method)
(['self', 'val'], {'flags': 0})
>>> get_spec(Test().method)
(['self', 'val'], {'flags': 0})
"""
if inspect.isfunction(func) or inspect.ismethod(func):
spec = inspect.getfullargspec(func)
elif hasattr(func, "__call__"): # noqa: B004
spec = inspect.getfullargspec(func.__call__)
else:
raise TypeError(f"{type(func)} is not callable")
defaults: tuple[Any, ...] = spec.defaults or ()
firstdefault = len(spec.args) - len(defaults)
args = spec.args[:firstdefault]
kwargs = dict(zip(spec.args[firstdefault:], defaults))
return args, kwargs
def equal_attributes(
obj1: Any, obj2: Any, attributes: list[str | Callable[[Any], Any]] | None
) -> bool:
"""Compare two objects attributes"""
warnings.warn(
"The equal_attributes function is deprecated and will be removed in a future version of Scrapy.",
category=ScrapyDeprecationWarning,
stacklevel=2,
)
# not attributes given return False by default
if not attributes:
return False
temp1, temp2 = object(), object()
for attr in attributes:
# support callables like itemgetter
if callable(attr):
if attr(obj1) != attr(obj2):
return False
elif getattr(obj1, attr, temp1) != getattr(obj2, attr, temp2):
return False
# all attributes equal
return True
@overload
def without_none_values(iterable: Mapping[_KT, _VT]) -> dict[_KT, _VT]: ...
@overload
def without_none_values(iterable: Iterable[_KT]) -> Iterable[_KT]: ...
def without_none_values(
iterable: Mapping[_KT, _VT] | Iterable[_KT],
) -> dict[_KT, _VT] | Iterable[_KT]:
"""Return a copy of ``iterable`` with all ``None`` entries removed.
If ``iterable`` is a mapping, return a dictionary where all pairs that have
value ``None`` have been removed.
"""
if isinstance(iterable, Mapping):
return {k: v for k, v in iterable.items() if v is not None}
# the iterable __init__ must take another iterable
return type(iterable)(v for v in iterable if v is not None) # type: ignore[call-arg]
def global_object_name(obj: Any) -> str:
"""Return the full import path of the given object.
>>> from scrapy import Request
>>> global_object_name(Request)
'scrapy.http.request.Request'
>>> global_object_name(Request.replace)
'scrapy.http.request.Request.replace'
"""
return f"{obj.__module__}.{obj.__qualname__}"
if hasattr(sys, "pypy_version_info"):
def garbage_collect() -> None:
# Collecting weakreferences can take two collections on PyPy.
gc.collect()
gc.collect()
else:
def garbage_collect() -> None:
gc.collect()
class MutableChain(Iterable[_T]):
"""
Thin wrapper around itertools.chain, allowing to add iterables "in-place"
"""
def __init__(self, *args: Iterable[_T]):
self.data: Iterator[_T] = chain.from_iterable(args)
def extend(self, *iterables: Iterable[_T]) -> None:
self.data = chain(self.data, chain.from_iterable(iterables))
def __iter__(self) -> Iterator[_T]:
return self
def __next__(self) -> _T:
return next(self.data)
async def _async_chain(
*iterables: Iterable[_T] | AsyncIterator[_T],
) -> AsyncIterator[_T]:
for it in iterables:
async for o in as_async_generator(it):
yield o
class MutableAsyncChain(AsyncIterator[_T]):
"""
Similar to MutableChain but for async iterables
"""
def __init__(self, *args: Iterable[_T] | AsyncIterator[_T]):
self.data: AsyncIterator[_T] = _async_chain(*args)
def extend(self, *iterables: Iterable[_T] | AsyncIterator[_T]) -> None:
self.data = _async_chain(self.data, _async_chain(*iterables))
def __aiter__(self) -> Self:
return self
async def __anext__(self) -> _T:
return await self.data.__anext__()
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