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utils.py
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utils.py
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import warnings
import weakref
from collections import OrderedDict, defaultdict, deque
from copy import deepcopy
from itertools import islice, zip_longest
from types import BuiltinFunctionType, CodeType, FunctionType, GeneratorType, LambdaType, ModuleType
from typing import (
TYPE_CHECKING,
AbstractSet,
Any,
Callable,
Dict,
Generator,
Iterable,
Iterator,
List,
Mapping,
Optional,
Set,
Tuple,
Type,
TypeVar,
Union,
no_type_check,
)
from .typing import GenericAlias, NoneType, display_as_type
from .version import version_info
if TYPE_CHECKING:
from inspect import Signature
from pathlib import Path
from .dataclasses import Dataclass # noqa: F401
from .fields import ModelField # noqa: F401
from .main import BaseConfig, BaseModel # noqa: F401
from .typing import AbstractSetIntStr, DictIntStrAny, IntStr, MappingIntStrAny, ReprArgs # noqa: F401
__all__ = (
'import_string',
'sequence_like',
'validate_field_name',
'lenient_issubclass',
'in_ipython',
'deep_update',
'update_not_none',
'almost_equal_floats',
'get_model',
'to_camel',
'is_valid_field',
'smart_deepcopy',
'PyObjectStr',
'Representation',
'GetterDict',
'ValueItems',
'version_info', # required here to match behaviour in v1.3
'ClassAttribute',
'path_type',
'ROOT_KEY',
)
ROOT_KEY = '__root__'
# these are types that are returned unchanged by deepcopy
IMMUTABLE_NON_COLLECTIONS_TYPES: Set[Type[Any]] = {
int,
float,
complex,
str,
bool,
bytes,
type,
NoneType,
FunctionType,
BuiltinFunctionType,
LambdaType,
weakref.ref,
CodeType,
# note: including ModuleType will differ from behaviour of deepcopy by not producing error.
# It might be not a good idea in general, but considering that this function used only internally
# against default values of fields, this will allow to actually have a field with module as default value
ModuleType,
NotImplemented.__class__,
Ellipsis.__class__,
}
# these are types that if empty, might be copied with simple copy() instead of deepcopy()
BUILTIN_COLLECTIONS: Set[Type[Any]] = {
list,
set,
tuple,
frozenset,
dict,
OrderedDict,
defaultdict,
deque,
}
def import_string(dotted_path: str) -> Any:
"""
Stolen approximately from django. Import a dotted module path and return the attribute/class designated by the
last name in the path. Raise ImportError if the import fails.
"""
from importlib import import_module
try:
module_path, class_name = dotted_path.strip(' ').rsplit('.', 1)
except ValueError as e:
raise ImportError(f'"{dotted_path}" doesn\'t look like a module path') from e
module = import_module(module_path)
try:
return getattr(module, class_name)
except AttributeError as e:
raise ImportError(f'Module "{module_path}" does not define a "{class_name}" attribute') from e
def truncate(v: Union[str], *, max_len: int = 80) -> str:
"""
Truncate a value and add a unicode ellipsis (three dots) to the end if it was too long
"""
warnings.warn('`truncate` is no-longer used by pydantic and is deprecated', DeprecationWarning)
if isinstance(v, str) and len(v) > (max_len - 2):
# -3 so quote + string + … + quote has correct length
return (v[: (max_len - 3)] + '…').__repr__()
try:
v = v.__repr__()
except TypeError:
v = v.__class__.__repr__(v) # in case v is a type
if len(v) > max_len:
v = v[: max_len - 1] + '…'
return v
def sequence_like(v: Type[Any]) -> bool:
return isinstance(v, (list, tuple, set, frozenset, GeneratorType, deque))
def validate_field_name(bases: List[Type['BaseModel']], field_name: str) -> None:
"""
Ensure that the field's name does not shadow an existing attribute of the model.
"""
for base in bases:
if getattr(base, field_name, None):
raise NameError(
f'Field name "{field_name}" shadows a BaseModel attribute; '
f'use a different field name with "alias=\'{field_name}\'".'
)
def lenient_issubclass(cls: Any, class_or_tuple: Union[Type[Any], Tuple[Type[Any], ...]]) -> bool:
try:
return isinstance(cls, type) and issubclass(cls, class_or_tuple)
except TypeError:
if isinstance(cls, GenericAlias):
return False
raise # pragma: no cover
def in_ipython() -> bool:
"""
Check whether we're in an ipython environment, including jupyter notebooks.
"""
try:
eval('__IPYTHON__')
except NameError:
return False
else: # pragma: no cover
return True
KeyType = TypeVar('KeyType')
def deep_update(mapping: Dict[KeyType, Any], *updating_mappings: Dict[KeyType, Any]) -> Dict[KeyType, Any]:
updated_mapping = mapping.copy()
for updating_mapping in updating_mappings:
for k, v in updating_mapping.items():
if k in updated_mapping and isinstance(updated_mapping[k], dict) and isinstance(v, dict):
updated_mapping[k] = deep_update(updated_mapping[k], v)
else:
updated_mapping[k] = v
return updated_mapping
def update_not_none(mapping: Dict[Any, Any], **update: Any) -> None:
mapping.update({k: v for k, v in update.items() if v is not None})
def almost_equal_floats(value_1: float, value_2: float, *, delta: float = 1e-8) -> bool:
"""
Return True if two floats are almost equal
"""
return abs(value_1 - value_2) <= delta
def generate_model_signature(
init: Callable[..., None], fields: Dict[str, 'ModelField'], config: Type['BaseConfig']
) -> 'Signature':
"""
Generate signature for model based on its fields
"""
from inspect import Parameter, Signature, signature
present_params = signature(init).parameters.values()
merged_params: Dict[str, Parameter] = {}
var_kw = None
use_var_kw = False
for param in islice(present_params, 1, None): # skip self arg
if param.kind is param.VAR_KEYWORD:
var_kw = param
continue
merged_params[param.name] = param
if var_kw: # if custom init has no var_kw, fields which are not declared in it cannot be passed through
allow_names = config.allow_population_by_field_name
for field_name, field in fields.items():
param_name = field.alias
if field_name in merged_params or param_name in merged_params:
continue
elif not param_name.isidentifier():
if allow_names and field_name.isidentifier():
param_name = field_name
else:
use_var_kw = True
continue
# TODO: replace annotation with actual expected types once #1055 solved
kwargs = {'default': field.default} if not field.required else {}
merged_params[param_name] = Parameter(
param_name, Parameter.KEYWORD_ONLY, annotation=field.outer_type_, **kwargs
)
if config.extra is config.extra.allow:
use_var_kw = True
if var_kw and use_var_kw:
# Make sure the parameter for extra kwargs
# does not have the same name as a field
default_model_signature = [
('__pydantic_self__', Parameter.POSITIONAL_OR_KEYWORD),
('data', Parameter.VAR_KEYWORD),
]
if [(p.name, p.kind) for p in present_params] == default_model_signature:
# if this is the standard model signature, use extra_data as the extra args name
var_kw_name = 'extra_data'
else:
# else start from var_kw
var_kw_name = var_kw.name
# generate a name that's definitely unique
while var_kw_name in fields:
var_kw_name += '_'
merged_params[var_kw_name] = var_kw.replace(name=var_kw_name)
return Signature(parameters=list(merged_params.values()), return_annotation=None)
def get_model(obj: Union[Type['BaseModel'], Type['Dataclass']]) -> Type['BaseModel']:
from .main import BaseModel # noqa: F811
try:
model_cls = obj.__pydantic_model__ # type: ignore
except AttributeError:
model_cls = obj
if not issubclass(model_cls, BaseModel):
raise TypeError('Unsupported type, must be either BaseModel or dataclass')
return model_cls
def to_camel(string: str) -> str:
return ''.join(word.capitalize() for word in string.split('_'))
T = TypeVar('T')
def unique_list(input_list: Union[List[T], Tuple[T, ...]]) -> List[T]:
"""
Make a list unique while maintaining order.
"""
result = []
unique_set = set()
for v in input_list:
if v not in unique_set:
unique_set.add(v)
result.append(v)
return result
def update_normalized_all(
item: Union['AbstractSetIntStr', 'MappingIntStrAny'],
all_items: Union['AbstractSetIntStr', 'MappingIntStrAny'],
) -> Union['AbstractSetIntStr', 'MappingIntStrAny']:
"""
Update item based on what all items contains.
The update is done based on these cases:
- if both arguments are dicts then each key-value pair existing in ``all_items`` is merged into ``item``,
while the rest of the key-value pairs are updated recursively with this function.
- if both arguments are sets then they are just merged.
- if ``item`` is a dictionary and ``all_items`` is a set then all values of it are added to ``item`` as
``key: ...``.
- if ``item`` is set and ``all_items`` is a dictionary, then ``item`` is converted to a dictionary and then the
key-value pairs of ``all_items`` are merged in it.
During recursive calls, there is a case where ``all_items`` can be an Ellipsis, in which case the ``item`` is
returned as is.
"""
if not item:
return all_items
if isinstance(item, dict) and isinstance(all_items, dict):
item = dict(item)
item.update({k: update_normalized_all(item[k], v) for k, v in all_items.items() if k in item})
item.update({k: v for k, v in all_items.items() if k not in item})
return item
if isinstance(item, set) and isinstance(all_items, set):
item = set(item)
item.update(all_items)
return item
if isinstance(item, dict) and isinstance(all_items, set):
item = dict(item)
item.update({k: ... for k in all_items if k not in item})
return item
if isinstance(item, set) and isinstance(all_items, dict):
item = {k: ... for k in item}
item.update({k: v for k, v in all_items.items() if k not in item})
return item
# Case when item or all_items is ... (in recursive calls).
return item
class PyObjectStr(str):
"""
String class where repr doesn't include quotes. Useful with Representation when you want to return a string
representation of something that valid (or pseudo-valid) python.
"""
def __repr__(self) -> str:
return str(self)
class Representation:
"""
Mixin to provide __str__, __repr__, and __pretty__ methods. See #884 for more details.
__pretty__ is used by [devtools](https://python-devtools.helpmanual.io/) to provide human readable representations
of objects.
"""
__slots__: Tuple[str, ...] = tuple()
def __repr_args__(self) -> 'ReprArgs':
"""
Returns the attributes to show in __str__, __repr__, and __pretty__ this is generally overridden.
Can either return:
* name - value pairs, e.g.: `[('foo_name', 'foo'), ('bar_name', ['b', 'a', 'r'])]`
* or, just values, e.g.: `[(None, 'foo'), (None, ['b', 'a', 'r'])]`
"""
attrs = ((s, getattr(self, s)) for s in self.__slots__)
return [(a, v) for a, v in attrs if v is not None]
def __repr_name__(self) -> str:
"""
Name of the instance's class, used in __repr__.
"""
return self.__class__.__name__
def __repr_str__(self, join_str: str) -> str:
return join_str.join(repr(v) if a is None else f'{a}={v!r}' for a, v in self.__repr_args__())
def __pretty__(self, fmt: Callable[[Any], Any], **kwargs: Any) -> Generator[Any, None, None]:
"""
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
"""
yield self.__repr_name__() + '('
yield 1
for name, value in self.__repr_args__():
if name is not None:
yield name + '='
yield fmt(value)
yield ','
yield 0
yield -1
yield ')'
def __str__(self) -> str:
return self.__repr_str__(' ')
def __repr__(self) -> str:
return f'{self.__repr_name__()}({self.__repr_str__(", ")})'
class GetterDict(Representation):
"""
Hack to make object's smell just enough like dicts for validate_model.
We can't inherit from Mapping[str, Any] because it upsets cython so we have to implement all methods ourselves.
"""
__slots__ = ('_obj',)
def __init__(self, obj: Any):
self._obj = obj
def __getitem__(self, key: str) -> Any:
try:
return getattr(self._obj, key)
except AttributeError as e:
raise KeyError(key) from e
def get(self, key: Any, default: Any = None) -> Any:
return getattr(self._obj, key, default)
def extra_keys(self) -> Set[Any]:
"""
We don't want to get any other attributes of obj if the model didn't explicitly ask for them
"""
return set()
def keys(self) -> List[Any]:
"""
Keys of the pseudo dictionary, uses a list not set so order information can be maintained like python
dictionaries.
"""
return list(self)
def values(self) -> List[Any]:
return [self[k] for k in self]
def items(self) -> Iterator[Tuple[str, Any]]:
for k in self:
yield k, self.get(k)
def __iter__(self) -> Iterator[str]:
for name in dir(self._obj):
if not name.startswith('_'):
yield name
def __len__(self) -> int:
return sum(1 for _ in self)
def __contains__(self, item: Any) -> bool:
return item in self.keys()
def __eq__(self, other: Any) -> bool:
return dict(self) == dict(other.items())
def __repr_args__(self) -> 'ReprArgs':
return [(None, dict(self))]
def __repr_name__(self) -> str:
return f'GetterDict[{display_as_type(self._obj)}]'
class ValueItems(Representation):
"""
Class for more convenient calculation of excluded or included fields on values.
"""
__slots__ = ('_items', '_type')
def __init__(self, value: Any, items: Union['AbstractSetIntStr', 'MappingIntStrAny']) -> None:
if TYPE_CHECKING:
self._items: Union['AbstractSetIntStr', 'MappingIntStrAny']
self._type: Type[Union[set, dict]] # type: ignore
# For further type checks speed-up
if isinstance(items, Mapping):
self._type = dict
elif isinstance(items, AbstractSet):
self._type = set
else:
raise TypeError(f'Unexpected type of exclude value {items.__class__}')
if isinstance(value, (list, tuple)):
items = self._normalize_indexes(items, len(value))
self._items = items
@no_type_check
def is_excluded(self, item: Any) -> bool:
"""
Check if item is fully excluded
(value considered excluded if self._type is set and item contained in self._items
or self._type is dict and self._items.get(item) is ...
:param item: key or index of a value
"""
if self._type is set:
return item in self._items
return self._items.get(item) is ...
@no_type_check
def is_included(self, item: Any) -> bool:
"""
Check if value is contained in self._items
:param item: key or index of value
"""
return item in self._items
@no_type_check
def for_element(self, e: 'IntStr') -> Optional[Union['AbstractSetIntStr', 'MappingIntStrAny']]:
"""
:param e: key or index of element on value
:return: raw values for elemet if self._items is dict and contain needed element
"""
if self._type is dict:
item = self._items.get(e)
return item if item is not ... else None
return None
@no_type_check
def _normalize_indexes(
self, items: Union['AbstractSetIntStr', 'MappingIntStrAny'], v_length: int
) -> Union['AbstractSetIntStr', 'DictIntStrAny']:
"""
:param items: dict or set of indexes which will be normalized
:param v_length: length of sequence indexes of which will be
>>> self._normalize_indexes({0, -2, -1}, 4)
{0, 2, 3}
>>> self._normalize_indexes({'__all__'}, 4)
{0, 1, 2, 3}
"""
if any(not isinstance(i, int) and i != '__all__' for i in items):
raise TypeError(
'Excluding fields from a sequence of sub-models or dicts must be performed index-wise: '
'expected integer keys or keyword "__all__"'
)
if self._type is set:
if '__all__' in items:
if items != {'__all__'}:
raise ValueError('set with keyword "__all__" must not contain other elements')
return {i for i in range(v_length)}
return {v_length + i if i < 0 else i for i in items}
else:
all_items = items.get('__all__')
for i, v in items.items():
if not (isinstance(v, Mapping) or isinstance(v, AbstractSet) or v is ...):
raise TypeError(f'Unexpected type of exclude value for index "{i}" {v.__class__}')
normalized_items = {v_length + i if i < 0 else i: v for i, v in items.items() if i != '__all__'}
if all_items:
default: Type[Union[Set[Any], Dict[Any, Any]]]
if isinstance(all_items, Mapping):
default = dict
elif isinstance(all_items, AbstractSet):
default = set
else:
for i in range(v_length):
normalized_items.setdefault(i, ...)
return normalized_items
for i in range(v_length):
normalized_item = normalized_items.setdefault(i, default())
if normalized_item is not ...:
normalized_items[i] = update_normalized_all(normalized_item, all_items)
return normalized_items
def __repr_args__(self) -> 'ReprArgs':
return [(None, self._items)]
class ClassAttribute:
"""
Hide class attribute from its instances
"""
__slots__ = (
'name',
'value',
)
def __init__(self, name: str, value: Any) -> None:
self.name = name
self.value = value
def __get__(self, instance: Any, owner: Type[Any]) -> None:
if instance is None:
return self.value
raise AttributeError(f'{self.name!r} attribute of {owner.__name__!r} is class-only')
path_types = {
'is_dir': 'directory',
'is_file': 'file',
'is_mount': 'mount point',
'is_symlink': 'symlink',
'is_block_device': 'block device',
'is_char_device': 'char device',
'is_fifo': 'FIFO',
'is_socket': 'socket',
}
def path_type(p: 'Path') -> str:
"""
Find out what sort of thing a path is.
"""
assert p.exists(), 'path does not exist'
for method, name in path_types.items():
if getattr(p, method)():
return name
return 'unknown'
Obj = TypeVar('Obj')
def smart_deepcopy(obj: Obj) -> Obj:
"""
Return type as is for immutable built-in types
Use obj.copy() for built-in empty collections
Use copy.deepcopy() for non-empty collections and unknown objects
"""
obj_type = obj.__class__
if obj_type in IMMUTABLE_NON_COLLECTIONS_TYPES:
return obj # fastest case: obj is immutable and not collection therefore will not be copied anyway
elif not obj and obj_type in BUILTIN_COLLECTIONS:
# faster way for empty collections, no need to copy its members
return obj if obj_type is tuple else obj.copy() # type: ignore # tuple doesn't have copy method
return deepcopy(obj) # slowest way when we actually might need a deepcopy
def is_valid_field(name: str) -> bool:
if not name.startswith('_'):
return True
return ROOT_KEY == name
def is_valid_private_name(name: str) -> bool:
return not is_valid_field(name) and name not in {
'__annotations__',
'__classcell__',
'__doc__',
'__module__',
'__orig_bases__',
'__qualname__',
}
_EMPTY = object()
def all_identical(left: Iterable[Any], right: Iterable[Any]) -> bool:
"""
Check that the items of `left` are the same objects as those in `right`.
>>> a, b = object(), object()
>>> all_identical([a, b, a], [a, b, a])
True
>>> all_identical([a, b, [a]], [a, b, [a]]) # new list object, while "equal" is not "identical"
False
"""
for left_item, right_item in zip_longest(left, right, fillvalue=_EMPTY):
if left_item is not right_item:
return False
return True