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"""Experimental pipeline API functionality. Be careful with this API, it's subject to change.""" from __future__ import annotations import datetime import operator import re import sys from collections import deque from collections.abc import Container from dataclasses import dataclass from decimal import Decimal from functools import cached_property, partial from typing import TYPE_CHECKING, Any, Callable, Generic, Pattern, Protocol, TypeVar, Union, overload import annotated_types from typing_extensions import Annotated if TYPE_CHECKING: from pydantic_core import core_schema as cs from pydantic import GetCoreSchemaHandler from pydantic._internal._internal_dataclass import slots_true as _slots_true if sys.version_info < (3, 10): EllipsisType = type(Ellipsis) else: from types import EllipsisType __all__ = ['validate_as', 'validate_as_deferred', 'transform'] _slots_frozen = {**_slots_true, 'frozen': True} @dataclass(**_slots_frozen) class _ValidateAs: tp: type[Any] strict: bool = False @dataclass class _ValidateAsDefer: func: Callable[[], type[Any]] @cached_property def tp(self) -> type[Any]: return self.func() @dataclass(**_slots_frozen) class _Transform: func: Callable[[Any], Any] @dataclass(**_slots_frozen) class _PipelineOr: left: _Pipeline[Any, Any] right: _Pipeline[Any, Any] @dataclass(**_slots_frozen) class _PipelineAnd: left: _Pipeline[Any, Any] right: _Pipeline[Any, Any] @dataclass(**_slots_frozen) class _Eq: value: Any @dataclass(**_slots_frozen) class _NotEq: value: Any @dataclass(**_slots_frozen) class _In: values: Container[Any] @dataclass(**_slots_frozen) class _NotIn: values: Container[Any] _ConstraintAnnotation = Union[ annotated_types.Le, annotated_types.Ge, annotated_types.Lt, annotated_types.Gt, annotated_types.Len, annotated_types.MultipleOf, annotated_types.Timezone, annotated_types.Interval, annotated_types.Predicate, # common predicates not included in annotated_types _Eq, _NotEq, _In, _NotIn, # regular expressions Pattern[str], ] @dataclass(**_slots_frozen) class _Constraint: constraint: _ConstraintAnnotation _Step = Union[_ValidateAs, _ValidateAsDefer, _Transform, _PipelineOr, _PipelineAnd, _Constraint] _InT = TypeVar('_InT') _OutT = TypeVar('_OutT') _NewOutT = TypeVar('_NewOutT') class _FieldTypeMarker: pass # TODO: ultimately, make this public, see https://github.com/pydantic/pydantic/pull/9459#discussion_r1628197626 # Also, make this frozen eventually, but that doesn't work right now because of the generic base # Which attempts to modify __orig_base__ and such. # We could go with a manual freeze, but that seems overkill for now. @dataclass(**_slots_true) class _Pipeline(Generic[_InT, _OutT]): """Abstract representation of a chain of validation, transformation, and parsing steps.""" _steps: tuple[_Step, ...] def transform( self, func: Callable[[_OutT], _NewOutT], ) -> _Pipeline[_InT, _NewOutT]: """Transform the output of the previous step. If used as the first step in a pipeline, the type of the field is used. That is, the transformation is applied to after the value is parsed to the field's type. """ return _Pipeline[_InT, _NewOutT](self._steps + (_Transform(func),)) @overload def validate_as(self, tp: type[_NewOutT], *, strict: bool = ...) -> _Pipeline[_InT, _NewOutT]: ... @overload def validate_as(self, tp: EllipsisType, *, strict: bool = ...) -> _Pipeline[_InT, Any]: # type: ignore ... def validate_as(self, tp: type[_NewOutT] | EllipsisType, *, strict: bool = False) -> _Pipeline[_InT, Any]: # type: ignore """Validate / parse the input into a new type. If no type is provided, the type of the field is used. Types are parsed in Pydantic's `lax` mode by default, but you can enable `strict` mode by passing `strict=True`. """ if isinstance(tp, EllipsisType): return _Pipeline[_InT, Any](self._steps + (_ValidateAs(_FieldTypeMarker, strict=strict),)) return _Pipeline[_InT, _NewOutT](self._steps + (_ValidateAs(tp, strict=strict),)) def validate_as_deferred(self, func: Callable[[], type[_NewOutT]]) -> _Pipeline[_InT, _NewOutT]: """Parse the input into a new type, deferring resolution of the type until the current class is fully defined. This is useful when you need to reference the class in it's own type annotations. """ return _Pipeline[_InT, _NewOutT](self._steps + (_ValidateAsDefer(func),)) # constraints @overload def constrain(self: _Pipeline[_InT, _NewOutGe], constraint: annotated_types.Ge) -> _Pipeline[_InT, _NewOutGe]: ... @overload def constrain(self: _Pipeline[_InT, _NewOutGt], constraint: annotated_types.Gt) -> _Pipeline[_InT, _NewOutGt]: ... @overload def constrain(self: _Pipeline[_InT, _NewOutLe], constraint: annotated_types.Le) -> _Pipeline[_InT, _NewOutLe]: ... @overload def constrain(self: _Pipeline[_InT, _NewOutLt], constraint: annotated_types.Lt) -> _Pipeline[_InT, _NewOutLt]: ... @overload def constrain( self: _Pipeline[_InT, _NewOutLen], constraint: annotated_types.Len ) -> _Pipeline[_InT, _NewOutLen]: ... @overload def constrain( self: _Pipeline[_InT, _NewOutT], constraint: annotated_types.MultipleOf ) -> _Pipeline[_InT, _NewOutT]: ... @overload def constrain( self: _Pipeline[_InT, _NewOutDatetime], constraint: annotated_types.Timezone ) -> _Pipeline[_InT, _NewOutDatetime]: ... @overload def constrain(self: _Pipeline[_InT, _OutT], constraint: annotated_types.Predicate) -> _Pipeline[_InT, _OutT]: ... @overload def constrain( self: _Pipeline[_InT, _NewOutInterval], constraint: annotated_types.Interval ) -> _Pipeline[_InT, _NewOutInterval]: ... @overload def constrain(self: _Pipeline[_InT, _OutT], constraint: _Eq) -> _Pipeline[_InT, _OutT]: ... @overload def constrain(self: _Pipeline[_InT, _OutT], constraint: _NotEq) -> _Pipeline[_InT, _OutT]: ... @overload def constrain(self: _Pipeline[_InT, _OutT], constraint: _In) -> _Pipeline[_InT, _OutT]: ... @overload def constrain(self: _Pipeline[_InT, _OutT], constraint: _NotIn) -> _Pipeline[_InT, _OutT]: ... @overload def constrain(self: _Pipeline[_InT, _NewOutT], constraint: Pattern[str]) -> _Pipeline[_InT, _NewOutT]: ... def constrain(self, constraint: _ConstraintAnnotation) -> Any: """Constrain a value to meet a certain condition. We support most conditions from `annotated_types`, as well as regular expressions. Most of the time you'll be calling a shortcut method like `gt`, `lt`, `len`, etc so you don't need to call this directly. """ return _Pipeline[_InT, _OutT](self._steps + (_Constraint(constraint),)) def predicate(self: _Pipeline[_InT, _NewOutT], func: Callable[[_NewOutT], bool]) -> _Pipeline[_InT, _NewOutT]: """Constrain a value to meet a certain predicate.""" return self.constrain(annotated_types.Predicate(func)) def gt(self: _Pipeline[_InT, _NewOutGt], gt: _NewOutGt) -> _Pipeline[_InT, _NewOutGt]: """Constrain a value to be greater than a certain value.""" return self.constrain(annotated_types.Gt(gt)) def lt(self: _Pipeline[_InT, _NewOutLt], lt: _NewOutLt) -> _Pipeline[_InT, _NewOutLt]: """Constrain a value to be less than a certain value.""" return self.constrain(annotated_types.Lt(lt)) def ge(self: _Pipeline[_InT, _NewOutGe], ge: _NewOutGe) -> _Pipeline[_InT, _NewOutGe]: """Constrain a value to be greater than or equal to a certain value.""" return self.constrain(annotated_types.Ge(ge)) def le(self: _Pipeline[_InT, _NewOutLe], le: _NewOutLe) -> _Pipeline[_InT, _NewOutLe]: """Constrain a value to be less than or equal to a certain value.""" return self.constrain(annotated_types.Le(le)) def len(self: _Pipeline[_InT, _NewOutLen], min_len: int, max_len: int | None = None) -> _Pipeline[_InT, _NewOutLen]: """Constrain a value to have a certain length.""" return self.constrain(annotated_types.Len(min_len, max_len)) @overload def multiple_of(self: _Pipeline[_InT, _NewOutDiv], multiple_of: _NewOutDiv) -> _Pipeline[_InT, _NewOutDiv]: ... @overload def multiple_of(self: _Pipeline[_InT, _NewOutMod], multiple_of: _NewOutMod) -> _Pipeline[_InT, _NewOutMod]: ... def multiple_of(self: _Pipeline[_InT, Any], multiple_of: Any) -> _Pipeline[_InT, Any]: """Constrain a value to be a multiple of a certain number.""" return self.constrain(annotated_types.MultipleOf(multiple_of)) def eq(self: _Pipeline[_InT, _OutT], value: _OutT) -> _Pipeline[_InT, _OutT]: """Constrain a value to be equal to a certain value.""" return self.constrain(_Eq(value)) def not_eq(self: _Pipeline[_InT, _OutT], value: _OutT) -> _Pipeline[_InT, _OutT]: """Constrain a value to not be equal to a certain value.""" return self.constrain(_NotEq(value)) def in_(self: _Pipeline[_InT, _OutT], values: Container[_OutT]) -> _Pipeline[_InT, _OutT]: """Constrain a value to be in a certain set.""" return self.constrain(_In(values)) def not_in(self: _Pipeline[_InT, _OutT], values: Container[_OutT]) -> _Pipeline[_InT, _OutT]: """Constrain a value to not be in a certain set.""" return self.constrain(_NotIn(values)) # timezone methods def datetime_tz_naive(self: _Pipeline[_InT, datetime.datetime]) -> _Pipeline[_InT, datetime.datetime]: return self.constrain(annotated_types.Timezone(None)) def datetime_tz_aware(self: _Pipeline[_InT, datetime.datetime]) -> _Pipeline[_InT, datetime.datetime]: return self.constrain(annotated_types.Timezone(...)) def datetime_tz( self: _Pipeline[_InT, datetime.datetime], tz: datetime.tzinfo ) -> _Pipeline[_InT, datetime.datetime]: return self.constrain(annotated_types.Timezone(tz)) # type: ignore def datetime_with_tz( self: _Pipeline[_InT, datetime.datetime], tz: datetime.tzinfo | None ) -> _Pipeline[_InT, datetime.datetime]: return self.transform(partial(datetime.datetime.replace, tzinfo=tz)) # string methods def str_lower(self: _Pipeline[_InT, str]) -> _Pipeline[_InT, str]: return self.transform(str.lower) def str_upper(self: _Pipeline[_InT, str]) -> _Pipeline[_InT, str]: return self.transform(str.upper) def str_title(self: _Pipeline[_InT, str]) -> _Pipeline[_InT, str]: return self.transform(str.title) def str_strip(self: _Pipeline[_InT, str]) -> _Pipeline[_InT, str]: return self.transform(str.strip) def str_pattern(self: _Pipeline[_InT, str], pattern: str) -> _Pipeline[_InT, str]: return self.constrain(re.compile(pattern)) def str_contains(self: _Pipeline[_InT, str], substring: str) -> _Pipeline[_InT, str]: return self.predicate(lambda v: substring in v) def str_starts_with(self: _Pipeline[_InT, str], prefix: str) -> _Pipeline[_InT, str]: return self.predicate(lambda v: v.startswith(prefix)) def str_ends_with(self: _Pipeline[_InT, str], suffix: str) -> _Pipeline[_InT, str]: return self.predicate(lambda v: v.endswith(suffix)) # operators def otherwise(self, other: _Pipeline[_OtherIn, _OtherOut]) -> _Pipeline[_InT | _OtherIn, _OutT | _OtherOut]: """Combine two validation chains, returning the result of the first chain if it succeeds, and the second chain if it fails.""" return _Pipeline((_PipelineOr(self, other),)) __or__ = otherwise def then(self, other: _Pipeline[_OutT, _OtherOut]) -> _Pipeline[_InT, _OtherOut]: """Pipe the result of one validation chain into another.""" return _Pipeline((_PipelineAnd(self, other),)) __and__ = then def __get_pydantic_core_schema__(self, source_type: Any, handler: GetCoreSchemaHandler) -> cs.CoreSchema: from pydantic_core import core_schema as cs queue = deque(self._steps) s = None while queue: step = queue.popleft() s = _apply_step(step, s, handler, source_type) s = s or cs.any_schema() return s def __supports_type__(self, _: _OutT) -> bool: raise NotImplementedError validate_as = _Pipeline[Any, Any](()).validate_as validate_as_deferred = _Pipeline[Any, Any](()).validate_as_deferred transform = _Pipeline[Any, Any]((_ValidateAs(_FieldTypeMarker),)).transform def _check_func( func: Callable[[Any], bool], predicate_err: str | Callable[[], str], s: cs.CoreSchema | None ) -> cs.CoreSchema: from pydantic_core import core_schema as cs def handler(v: Any) -> Any: if func(v): return v raise ValueError(f'Expected {predicate_err if isinstance(predicate_err, str) else predicate_err()}') if s is None: return cs.no_info_plain_validator_function(handler) else: return cs.no_info_after_validator_function(handler, s) def _apply_step(step: _Step, s: cs.CoreSchema | None, handler: GetCoreSchemaHandler, source_type: Any) -> cs.CoreSchema: from pydantic_core import core_schema as cs if isinstance(step, _ValidateAs): s = _apply_parse(s, step.tp, step.strict, handler, source_type) elif isinstance(step, _ValidateAsDefer): s = _apply_parse(s, step.tp, False, handler, source_type) elif isinstance(step, _Transform): s = _apply_transform(s, step.func, handler) elif isinstance(step, _Constraint): s = _apply_constraint(s, step.constraint) elif isinstance(step, _PipelineOr): s = cs.union_schema([handler(step.left), handler(step.right)]) else: assert isinstance(step, _PipelineAnd) s = cs.chain_schema([handler(step.left), handler(step.right)]) return s def _apply_parse( s: cs.CoreSchema | None, tp: type[Any], strict: bool, handler: GetCoreSchemaHandler, source_type: Any, ) -> cs.CoreSchema: from pydantic_core import core_schema as cs from pydantic import Strict if tp is _FieldTypeMarker: return handler(source_type) if strict: tp = Annotated[tp, Strict()] # type: ignore if s and s['type'] == 'any': return handler(tp) else: return cs.chain_schema([s, handler(tp)]) if s else handler(tp) def _apply_transform( s: cs.CoreSchema | None, func: Callable[[Any], Any], handler: GetCoreSchemaHandler ) -> cs.CoreSchema: from pydantic_core import core_schema as cs if s is None: return cs.no_info_plain_validator_function(func) if s['type'] == 'str': if func is str.strip: s = s.copy() s['strip_whitespace'] = True return s elif func is str.lower: s = s.copy() s['to_lower'] = True return s elif func is str.upper: s = s.copy() s['to_upper'] = True return s return cs.no_info_after_validator_function(func, s) def _apply_constraint( # noqa: C901 s: cs.CoreSchema | None, constraint: _ConstraintAnnotation ) -> cs.CoreSchema: """Apply a single constraint to a schema.""" if isinstance(constraint, annotated_types.Gt): gt = constraint.gt if s and s['type'] in {'int', 'float', 'decimal'}: s = s.copy() if s['type'] == 'int' and isinstance(gt, int): s['gt'] = gt elif s['type'] == 'float' and isinstance(gt, float): s['gt'] = gt elif s['type'] == 'decimal' and isinstance(gt, Decimal): s['gt'] = gt else: def check_gt(v: Any) -> bool: return v > gt s = _check_func(check_gt, f'> {gt}', s) elif isinstance(constraint, annotated_types.Ge): ge = constraint.ge if s and s['type'] in {'int', 'float', 'decimal'}: s = s.copy() if s['type'] == 'int' and isinstance(ge, int): s['ge'] = ge elif s['type'] == 'float' and isinstance(ge, float): s['ge'] = ge elif s['type'] == 'decimal' and isinstance(ge, Decimal): s['ge'] = ge def check_ge(v: Any) -> bool: return v >= ge s = _check_func(check_ge, f'>= {ge}', s) elif isinstance(constraint, annotated_types.Lt): lt = constraint.lt if s and s['type'] in {'int', 'float', 'decimal'}: s = s.copy() if s['type'] == 'int' and isinstance(lt, int): s['lt'] = lt elif s['type'] == 'float' and isinstance(lt, float): s['lt'] = lt elif s['type'] == 'decimal' and isinstance(lt, Decimal): s['lt'] = lt def check_lt(v: Any) -> bool: return v < lt s = _check_func(check_lt, f'< {lt}', s) elif isinstance(constraint, annotated_types.Le): le = constraint.le if s and s['type'] in {'int', 'float', 'decimal'}: s = s.copy() if s['type'] == 'int' and isinstance(le, int): s['le'] = le elif s['type'] == 'float' and isinstance(le, float): s['le'] = le elif s['type'] == 'decimal' and isinstance(le, Decimal): s['le'] = le def check_le(v: Any) -> bool: return v <= le s = _check_func(check_le, f'<= {le}', s) elif isinstance(constraint, annotated_types.Len): min_len = constraint.min_length max_len = constraint.max_length if s and s['type'] in {'str', 'list', 'tuple', 'set', 'frozenset', 'dict'}: assert ( s['type'] == 'str' or s['type'] == 'list' or s['type'] == 'tuple' or s['type'] == 'set' or s['type'] == 'dict' or s['type'] == 'frozenset' ) s = s.copy() if min_len != 0: s['min_length'] = min_len if max_len is not None: s['max_length'] = max_len def check_len(v: Any) -> bool: if max_len is not None: return (min_len <= len(v)) and (len(v) <= max_len) return min_len <= len(v) s = _check_func(check_len, f'length >= {min_len} and length <= {max_len}', s) elif isinstance(constraint, annotated_types.MultipleOf): multiple_of = constraint.multiple_of if s and s['type'] in {'int', 'float', 'decimal'}: s = s.copy() if s['type'] == 'int' and isinstance(multiple_of, int): s['multiple_of'] = multiple_of elif s['type'] == 'float' and isinstance(multiple_of, float): s['multiple_of'] = multiple_of elif s['type'] == 'decimal' and isinstance(multiple_of, Decimal): s['multiple_of'] = multiple_of def check_multiple_of(v: Any) -> bool: return v % multiple_of == 0 s = _check_func(check_multiple_of, f'% {multiple_of} == 0', s) elif isinstance(constraint, annotated_types.Timezone): tz = constraint.tz if tz is ...: if s and s['type'] == 'datetime': s = s.copy() s['tz_constraint'] = 'aware' else: def check_tz_aware(v: object) -> bool: assert isinstance(v, datetime.datetime) return v.tzinfo is not None s = _check_func(check_tz_aware, 'timezone aware', s) elif tz is None: if s and s['type'] == 'datetime': s = s.copy() s['tz_constraint'] = 'naive' else: def check_tz_naive(v: object) -> bool: assert isinstance(v, datetime.datetime) return v.tzinfo is None s = _check_func(check_tz_naive, 'timezone naive', s) else: raise NotImplementedError('Constraining to a specific timezone is not yet supported') elif isinstance(constraint, annotated_types.Interval): if constraint.ge: s = _apply_constraint(s, annotated_types.Ge(constraint.ge)) if constraint.gt: s = _apply_constraint(s, annotated_types.Gt(constraint.gt)) if constraint.le: s = _apply_constraint(s, annotated_types.Le(constraint.le)) if constraint.lt: s = _apply_constraint(s, annotated_types.Lt(constraint.lt)) assert s is not None elif isinstance(constraint, annotated_types.Predicate): func = constraint.func if func.__name__ == '<lambda>': # attempt to extract the source code for a lambda function # to use as the function name in error messages # TODO: is there a better way? should we just not do this? import inspect try: # remove ')' suffix, can use removesuffix once we drop 3.8 source = inspect.getsource(func).strip() if source.endswith(')'): source = source[:-1] lambda_source_code = '`' + ''.join(''.join(source.split('lambda ')[1:]).split(':')[1:]).strip() + '`' except OSError: # stringified annotations lambda_source_code = 'lambda' s = _check_func(func, lambda_source_code, s) else: s = _check_func(func, func.__name__, s) elif isinstance(constraint, _NotEq): value = constraint.value def check_not_eq(v: Any) -> bool: return operator.__ne__(v, value) s = _check_func(check_not_eq, f'!= {value}', s) elif isinstance(constraint, _Eq): value = constraint.value def check_eq(v: Any) -> bool: return operator.__eq__(v, value) s = _check_func(check_eq, f'== {value}', s) elif isinstance(constraint, _In): values = constraint.values def check_in(v: Any) -> bool: return operator.__contains__(values, v) s = _check_func(check_in, f'in {values}', s) elif isinstance(constraint, _NotIn): values = constraint.values def check_not_in(v: Any) -> bool: return operator.__not__(operator.__contains__(values, v)) s = _check_func(check_not_in, f'not in {values}', s) else: assert isinstance(constraint, Pattern) if s and s['type'] == 'str': s = s.copy() s['pattern'] = constraint.pattern else: def check_pattern(v: object) -> bool: assert isinstance(v, str) return constraint.match(v) is not None s = _check_func(check_pattern, f'~ {constraint.pattern}', s) return s class _SupportsRange(annotated_types.SupportsLe, annotated_types.SupportsGe, Protocol): pass class _SupportsLen(Protocol): def __len__(self) -> int: ... _NewOutGt = TypeVar('_NewOutGt', bound=annotated_types.SupportsGt) _NewOutGe = TypeVar('_NewOutGe', bound=annotated_types.SupportsGe) _NewOutLt = TypeVar('_NewOutLt', bound=annotated_types.SupportsLt) _NewOutLe = TypeVar('_NewOutLe', bound=annotated_types.SupportsLe) _NewOutLen = TypeVar('_NewOutLen', bound=_SupportsLen) _NewOutDiv = TypeVar('_NewOutDiv', bound=annotated_types.SupportsDiv) _NewOutMod = TypeVar('_NewOutMod', bound=annotated_types.SupportsMod) _NewOutDatetime = TypeVar('_NewOutDatetime', bound=datetime.datetime) _NewOutInterval = TypeVar('_NewOutInterval', bound=_SupportsRange) _OtherIn = TypeVar('_OtherIn') _OtherOut = TypeVar('_OtherOut')
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