--- /dev/null
+# engine/_result_cy.py
+# Copyright (C) 2005-2025 the SQLAlchemy authors and contributors
+# <see AUTHORS file>
+#
+# This module is part of SQLAlchemy and is released under
+# the MIT License: https://www.opensource.org/licenses/mit-license.php
+# mypy: disable-error-code="misc,no-redef,type-arg,untyped-decorator"
+from __future__ import annotations
+
+from collections.abc import Callable
+from collections.abc import Iterator
+from collections.abc import Sequence
+from enum import Enum
+import operator
+from typing import Any
+from typing import Generic
+from typing import Literal
+from typing import overload
+from typing import TYPE_CHECKING
+from typing import TypeVar
+from typing import Union
+
+from .row import Row
+from .row import RowMapping
+from .. import exc
+from ..util import HasMemoized_ro_memoized_attribute
+from ..util.typing import Self
+from ..util.typing import TupleAny
+from ..util.typing import Unpack
+
+if TYPE_CHECKING:
+ from .result import _ProcessorsType
+ from .result import Result
+ from .result import ResultMetaData
+
+# START GENERATED CYTHON IMPORT
+# This section is automatically generated by the script tools/cython_imports.py
+try:
+ # NOTE: the cython compiler needs this "import cython" in the file, it
+ # can't be only "from sqlalchemy.util import cython" with the fallback
+ # in that module
+ import cython
+except ModuleNotFoundError:
+ from sqlalchemy.util import cython
+
+
+def _is_compiled() -> bool:
+ """Utility function to indicate if this module is compiled or not."""
+ return cython.compiled # type: ignore[no-any-return,unused-ignore]
+
+
+# END GENERATED CYTHON IMPORT
+
+if cython.compiled:
+ from cython.cimports.cpython import Py_INCREF
+ from cython.cimports.cpython import PyList_New
+ from cython.cimports.cpython import PyList_SET_ITEM
+ from cython.cimports.cpython import PyTuple_New
+ from cython.cimports.cpython import PyTuple_SET_ITEM
+
+
+_RowData = Row[Unpack[TupleAny]] | RowMapping | Any
+"""A generic form of "row" that accommodates for the different kinds of
+"rows" that different result objects return, including row, row mapping, and
+scalar values"""
+_R = TypeVar("_R", bound=_RowData)
+_T = TypeVar("_T", bound=Any)
+
+_InterimRowType = Union[_R, TupleAny]
+"""a catchall "anything" kind of return type that can be applied
+across all the result types
+
+"""
+
+_UniqueFilterType = Callable[[Any], Any]
+_UniqueFilterStateType = tuple[set[Any], _UniqueFilterType | None]
+
+_FLAG_SIMPLE = cython.declare(cython.char, 0)
+_FLAG_SCALAR_TO_TUPLE = cython.declare(cython.char, 1)
+_FLAG_TUPLE_FILTER = cython.declare(cython.char, 2)
+
+
+# a symbol that indicates to internal Result methods that
+# "no row is returned". We can't use None for those cases where a scalar
+# filter is applied to rows.
+class _NoRow(Enum):
+ _NO_ROW = 0
+
+
+_NO_ROW = _NoRow._NO_ROW
+
+
+class BaseResultInternal(Generic[_R]):
+ __slots__ = ()
+
+ _real_result: Result[Unpack[TupleAny]] | None = None
+ _generate_rows: bool = True
+ _row_logging_fn: Callable[[Any], Any] | None
+
+ _unique_filter_state: _UniqueFilterStateType | None = None
+ _post_creational_filter: Callable[[Any], Any] | None = None
+
+ _metadata: ResultMetaData
+
+ _source_supports_scalars: bool
+ _yield_per: int | None
+
+ def _fetchiter_impl(
+ self,
+ ) -> Iterator[_InterimRowType[Row[Unpack[TupleAny]]]]:
+ raise NotImplementedError()
+
+ def _fetchone_impl(
+ self, hard_close: bool = False
+ ) -> _InterimRowType[Row[Unpack[TupleAny]]] | None:
+ raise NotImplementedError()
+
+ def _fetchmany_impl(
+ self, size: int | None = None
+ ) -> list[_InterimRowType[Row[Unpack[TupleAny]]]]:
+ raise NotImplementedError()
+
+ def _fetchall_impl(
+ self,
+ ) -> list[_InterimRowType[Row[Unpack[TupleAny]]]]:
+ raise NotImplementedError()
+
+ def _soft_close(self, hard: bool = False) -> None:
+ raise NotImplementedError()
+
+ @HasMemoized_ro_memoized_attribute
+ def _row_getter(
+ self,
+ ) -> tuple[Callable[..., _R] | None, Callable[..., Sequence[_R]] | None]:
+ real_result = self if self._real_result is None else self._real_result
+
+ metadata = self._metadata
+ tuple_filters = metadata._tuplefilter
+ flag: cython.char = _FLAG_SIMPLE
+
+ if real_result._source_supports_scalars:
+ if not self._generate_rows:
+ return None, None
+ else:
+ flag = _FLAG_SCALAR_TO_TUPLE
+ elif tuple_filters is not None:
+ flag = _FLAG_TUPLE_FILTER
+
+ processors: tuple
+ proc_valid: tuple
+
+ if metadata._effective_processors is not None:
+ ep = metadata._effective_processors
+ if flag == _FLAG_TUPLE_FILTER:
+ ep = tuple_filters(ep)
+
+ processors = tuple(ep)
+ proc_valid = tuple(
+ [i for i, p in enumerate(processors) if p is not None]
+ )
+ else:
+ processors = ()
+ proc_valid = ()
+
+ proc_size: cython.Py_ssize_t = len(processors)
+ log_row = real_result._row_logging_fn
+ has_log_row: cython.bint = log_row is not None
+
+ key_to_index = metadata._key_to_index
+ _Row = Row
+
+ if flag == _FLAG_SIMPLE and proc_size == 0 and not has_log_row:
+ # just build the rows
+
+ def single_row_simple(input_row: Sequence[Any], /) -> Row:
+ return _Row(metadata, None, key_to_index, input_row)
+
+ if cython.compiled:
+
+ def many_rows_simple(rows: Sequence[Any], /) -> list[Any]:
+ size: cython.Py_hash_t = len(rows)
+ i: cython.Py_ssize_t
+ result: list = PyList_New(size)
+ for i in range(size):
+ row: object = _Row(
+ metadata, None, key_to_index, rows[i]
+ )
+ Py_INCREF(row)
+ PyList_SET_ITEM(result, i, row)
+ return result
+
+ else:
+
+ def many_rows_simple(rows: Sequence[Any], /) -> list[Any]:
+ return [
+ _Row(metadata, None, key_to_index, row) for row in rows
+ ]
+
+ return single_row_simple, many_rows_simple # type: ignore[return-value] # noqa: E501
+
+ first_row: cython.bint = True
+
+ def single_row(input_row: Sequence[Any], /) -> Row:
+ nonlocal first_row
+
+ if flag == _FLAG_SCALAR_TO_TUPLE:
+ input_row = (input_row,)
+ elif flag == _FLAG_TUPLE_FILTER:
+ input_row = tuple_filters(input_row)
+
+ if proc_size != 0:
+ if first_row:
+ first_row = False
+ assert len(input_row) == proc_size
+ input_row = _apply_processors(
+ processors, proc_size, proc_valid, input_row
+ )
+
+ row: Row = _Row(metadata, None, key_to_index, input_row)
+ if has_log_row:
+ row = log_row(row)
+ return row
+
+ if cython.compiled:
+
+ def many_rows(rows: Sequence[Any], /) -> list[Any]:
+ size: cython.Py_hash_t = len(rows)
+ i: cython.Py_ssize_t
+ result: list = PyList_New(size)
+ for i in range(size):
+ row: object = single_row(rows[i])
+ Py_INCREF(row)
+ PyList_SET_ITEM(result, i, row)
+ return result
+
+ else:
+
+ def many_rows(rows: Sequence[Any], /) -> list[Any]:
+ return [single_row(row) for row in rows]
+
+ return single_row, many_rows # type: ignore[return-value]
+
+ @HasMemoized_ro_memoized_attribute
+ def _iterator_getter(self) -> Callable[[], Iterator[_R]]:
+ make_row = self._row_getter[0]
+
+ post_creational_filter = self._post_creational_filter
+
+ if self._unique_filter_state is not None:
+ uniques: set
+ uniques, strategy = self._unique_strategy
+
+ def iterrows() -> Iterator[_R]:
+ for raw_row in self._fetchiter_impl():
+ row = (
+ make_row(raw_row) if make_row is not None else raw_row
+ )
+ hashed = strategy(row) if strategy is not None else row
+ if hashed in uniques:
+ continue
+ uniques.add(hashed)
+ if post_creational_filter is not None:
+ row = post_creational_filter(row)
+ yield row
+
+ else:
+
+ def iterrows() -> Iterator[_R]:
+ for raw_row in self._fetchiter_impl():
+ row = (
+ make_row(raw_row) if make_row is not None else raw_row
+ )
+ if post_creational_filter is not None:
+ row = post_creational_filter(row)
+ yield row
+
+ return iterrows
+
+ def _raw_all_rows(self) -> Sequence[_R]:
+ make_rows = self._row_getter[1]
+ assert make_rows is not None
+ return make_rows(self._fetchall_impl())
+
+ def _allrows(self) -> Sequence[_R]:
+ post_creational_filter = self._post_creational_filter
+
+ make_rows = self._row_getter[1]
+
+ rows = self._fetchall_impl()
+ made_rows: Sequence[_InterimRowType[_R]]
+ if make_rows is not None:
+ made_rows = make_rows(rows)
+ else:
+ made_rows = rows
+
+ interim_rows: Sequence[_R]
+
+ if self._unique_filter_state is not None:
+ uniques: set
+ uniques, strategy = self._unique_strategy
+ interim_rows = _apply_unique_strategy(
+ made_rows, [], uniques, strategy
+ )
+ else:
+ interim_rows = made_rows # type: ignore
+
+ if post_creational_filter is not None:
+ interim_rows = [
+ post_creational_filter(row) for row in interim_rows
+ ]
+ return interim_rows
+
+ @HasMemoized_ro_memoized_attribute
+ def _onerow_getter(
+ self,
+ ) -> Callable[[Self], Literal[_NoRow._NO_ROW] | _R]:
+ make_row = self._row_getter[0]
+
+ post_creational_filter = self._post_creational_filter
+
+ if self._unique_filter_state is not None:
+ uniques: set
+ uniques, strategy = self._unique_strategy
+
+ def onerow(self: Self) -> Literal[_NoRow._NO_ROW] | _R:
+ while True:
+ row = self._fetchone_impl()
+ if row is None:
+ return _NO_ROW
+ else:
+ obj: _InterimRowType[Any] = (
+ make_row(row) if make_row is not None else row
+ )
+ hashed = strategy(obj) if strategy is not None else obj
+ if hashed in uniques:
+ continue
+ uniques.add(hashed)
+ if post_creational_filter is not None:
+ obj = post_creational_filter(obj)
+ return obj # type: ignore
+
+ else:
+
+ def onerow(self: Self) -> Literal[_NoRow._NO_ROW] | _R:
+ row = self._fetchone_impl()
+ if row is None:
+ return _NO_ROW
+ else:
+ interim_row: _InterimRowType[Any] = (
+ make_row(row) if make_row is not None else row
+ )
+ if post_creational_filter is not None:
+ interim_row = post_creational_filter(interim_row)
+ return interim_row # type: ignore
+
+ return onerow
+
+ @HasMemoized_ro_memoized_attribute
+ def _manyrow_getter(self) -> Callable[[Self, int | None], Sequence[_R]]:
+ make_rows = self._row_getter[1]
+ real_result = self if self._real_result is None else self._real_result
+ yield_per = real_result._yield_per
+
+ post_creational_filter = self._post_creational_filter
+
+ if self._unique_filter_state:
+ uniques: set
+ uniques, strategy = self._unique_strategy
+
+ def manyrows(self: Self, num: int | None, /) -> Sequence[_R]:
+ made_rows: Sequence[Any]
+ collect: list[_R] = []
+
+ _manyrows = self._fetchmany_impl
+
+ if num is None:
+ # if None is passed, we don't know the default
+ # manyrows number, DBAPI has this as cursor.arraysize
+ # different DBAPIs / fetch strategies may be different.
+ # do a fetch to find what the number is. if there are
+ # only fewer rows left, then it doesn't matter.
+ if yield_per:
+ num_required = num = yield_per
+ else:
+ rows = _manyrows()
+ num = len(rows)
+ made_rows = (
+ rows if make_rows is None else make_rows(rows)
+ )
+ _apply_unique_strategy(
+ made_rows, collect, uniques, strategy
+ )
+ num_required = num - len(collect)
+ else:
+ num_required = num
+
+ assert num is not None
+
+ while num_required:
+ rows = _manyrows(num_required)
+ if not rows:
+ break
+
+ made_rows = rows if make_rows is None else make_rows(rows)
+ _apply_unique_strategy(
+ made_rows, collect, uniques, strategy
+ )
+ num_required = num - len(collect)
+
+ if post_creational_filter is not None:
+ collect = [post_creational_filter(row) for row in collect]
+ return collect
+
+ else:
+
+ def manyrows(self: Self, num: int | None, /) -> Sequence[_R]:
+ if num is None:
+ num = yield_per
+
+ rows: Sequence = self._fetchmany_impl(num)
+ if make_rows is not None:
+ rows = make_rows(rows)
+ if post_creational_filter is not None:
+ rows = [post_creational_filter(row) for row in rows]
+ return rows
+
+ return manyrows
+
+ @overload
+ def _only_one_row(
+ self: BaseResultInternal[Row[_T, Unpack[TupleAny]]],
+ raise_for_second_row: bool,
+ raise_for_none: bool,
+ scalar: Literal[True],
+ ) -> _T: ...
+
+ @overload
+ def _only_one_row(
+ self,
+ raise_for_second_row: bool,
+ raise_for_none: Literal[True],
+ scalar: bool,
+ ) -> _R: ...
+
+ @overload
+ def _only_one_row(
+ self,
+ raise_for_second_row: bool,
+ raise_for_none: bool,
+ scalar: bool,
+ ) -> _R | None: ...
+
+ def _only_one_row(
+ self,
+ raise_for_second_row: bool,
+ raise_for_none: bool,
+ scalar: bool,
+ ) -> _R | None:
+ onerow = self._fetchone_impl
+
+ row = onerow(hard_close=True)
+ if row is None:
+ if raise_for_none:
+ raise exc.NoResultFound(
+ "No row was found when one was required"
+ )
+ else:
+ return None
+
+ if scalar and self._source_supports_scalars:
+ self._generate_rows = False
+ make_row = None
+ else:
+ make_row = self._row_getter[0]
+
+ try:
+ row = make_row(row) if make_row is not None else row # type: ignore[assignment] # noqa: E501
+ except:
+ self._soft_close(hard=True)
+ raise
+
+ if raise_for_second_row:
+ if self._unique_filter_state:
+ # for no second row but uniqueness, need to essentially
+ # consume the entire result :(
+ strategy = self._unique_strategy[1]
+
+ existing_row_hash = (
+ strategy(row) if strategy is not None else row
+ )
+
+ while True:
+ next_row: Any = onerow(hard_close=True)
+ if next_row is None:
+ next_row = _NO_ROW
+ break
+
+ try:
+ next_row = (
+ make_row(next_row)
+ if make_row is not None
+ else next_row
+ )
+
+ if strategy is not None:
+ # assert next_row is not _NO_ROW
+ if existing_row_hash == strategy(next_row):
+ continue
+ elif row == next_row:
+ continue
+ # here, we have a row and it's different
+ break
+ except:
+ self._soft_close(hard=True)
+ raise
+ else:
+ next_row = onerow(hard_close=True)
+ if next_row is None:
+ next_row = _NO_ROW
+
+ if next_row is not _NO_ROW:
+ self._soft_close(hard=True)
+ raise exc.MultipleResultsFound(
+ "Multiple rows were found when exactly one was required"
+ if raise_for_none
+ else "Multiple rows were found when one or none "
+ "was required"
+ )
+ else:
+ next_row = _NO_ROW
+ # if we checked for second row then that would have
+ # closed us :)
+ self._soft_close(hard=True)
+
+ if not scalar:
+ post_creational_filter = self._post_creational_filter
+ if post_creational_filter is not None:
+ row = post_creational_filter(row)
+
+ if scalar and make_row is not None:
+ return row[0] # type: ignore
+ else:
+ return row # type: ignore
+
+ def _iter_impl(self) -> Iterator[_R]:
+ return self._iterator_getter()
+
+ def _next_impl(self) -> _R:
+ row = self._onerow_getter(self)
+ if row is _NO_ROW:
+ raise StopIteration()
+ else:
+ return row
+
+ @HasMemoized_ro_memoized_attribute
+ def _unique_strategy(self) -> _UniqueFilterStateType:
+ assert self._unique_filter_state is not None
+ uniques, strategy = self._unique_filter_state
+
+ if strategy is None and self._metadata._unique_filters is not None:
+ real_result = (
+ self if self._real_result is None else self._real_result
+ )
+ if (
+ real_result._source_supports_scalars
+ and not self._generate_rows
+ ):
+ strategy = self._metadata._unique_filters[0]
+ else:
+ filters = self._metadata._unique_filters
+ if self._metadata._tuplefilter is not None:
+ filters = self._metadata._tuplefilter(filters)
+
+ strategy = operator.methodcaller("_filter_on_values", filters)
+ return uniques, strategy
+
+
+if cython.compiled:
+
+ @cython.inline
+ @cython.cfunc
+ @cython.wraparound(False)
+ @cython.boundscheck(False)
+ def _apply_processors(
+ proc: tuple,
+ proc_size: cython.Py_ssize_t,
+ proc_valid: object, # used only by python impl
+ data: Sequence,
+ ) -> tuple[Any, ...]:
+ res: tuple = PyTuple_New(proc_size)
+ i: cython.Py_ssize_t
+ for i in range(proc_size):
+ p = proc[i]
+ if p is not None:
+ value = p(data[i])
+ else:
+ value = data[i]
+ Py_INCREF(value)
+ PyTuple_SET_ITEM(res, i, value)
+ return res
+
+else:
+
+ def _apply_processors(
+ proc: _ProcessorsType,
+ proc_size: int, # used only by cython impl
+ proc_valid: tuple[int, ...],
+ data: Sequence[Any],
+ ) -> tuple[Any, ...]:
+ res = list(data)
+ for i in proc_valid:
+ res[i] = proc[i](res[i])
+ return tuple(res)
+
+
+@cython.inline
+@cython.cfunc
+def _apply_unique_strategy(
+ rows: Sequence[Any],
+ destination: list[Any],
+ uniques: set[Any],
+ strategy: Callable[[Any], Any] | None,
+) -> list[Any]:
+ i: cython.Py_ssize_t
+ has_strategy: cython.bint = strategy is not None
+ for i in range(len(rows)):
+ row = rows[i]
+ hashed = strategy(row) if has_strategy else row
+ if hashed in uniques:
+ continue
+ uniques.add(hashed)
+ destination.append(row)
+ return destination
from __future__ import annotations
import collections
-import functools
import operator
import typing
from typing import Any
)
if cursor_description is not None:
- # inline of Result._row_getter(), set up an initial row
- # getter assuming no transformations will be called as this
- # is the most common case
-
- metadata = self._init_metadata(context, cursor_description)
-
- _make_row: Any
- proc = metadata._effective_processors
- tf = metadata._tuplefilter
- _make_row = functools.partial(
- Row,
- metadata,
- proc if tf is None or proc is None else tf(proc),
- metadata._key_to_index,
- )
- if tf is not None:
- _fixed_tf = tf # needed to make mypy happy...
-
- def _sliced_row(raw_data: Any) -> Any:
- return _make_row(_fixed_tf(raw_data))
-
- sliced_row = _sliced_row
- else:
- sliced_row = _make_row
+ self._init_metadata(context, cursor_description)
if echo:
log = self.context.connection._log_debug
self._row_logging_fn = _log_row
- def _make_row_2(row: Any) -> Any:
- return _log_row(sliced_row(row))
-
- make_row = _make_row_2
- else:
- make_row = sliced_row # type: ignore[assignment]
- self._set_memoized_attribute("_row_getter", make_row)
+ # call Result._row_getter to set up the row factory
+ self._row_getter
else:
assert context._num_sentinel_cols == 0
from __future__ import annotations
-from enum import Enum
import functools
import itertools
import operator
from typing import Optional
from typing import overload
from typing import Sequence
-from typing import Set
from typing import Tuple
from typing import TYPE_CHECKING
-from typing import TypeVar
from typing import Union
+from ._result_cy import _InterimRowType
+from ._result_cy import _NO_ROW as _NO_ROW
+from ._result_cy import _R as _R
+from ._result_cy import _RowData
+from ._result_cy import _T
+from ._result_cy import _UniqueFilterType as _UniqueFilterType
+from ._result_cy import BaseResultInternal
from ._util_cy import tuplegetter as tuplegetter
from .row import Row
from .row import RowMapping
from .. import exc
from .. import util
from ..sql.base import _generative
-from ..sql.base import HasMemoized
from ..sql.base import InPlaceGenerative
from ..util import deprecated
-from ..util import HasMemoized_ro_memoized_attribute
from ..util import NONE_SET
from ..util.typing import Self
from ..util.typing import TupleAny
_KeyMapType = Mapping[_KeyType, _KeyMapRecType]
-_RowData = Union[Row[Unpack[TupleAny]], RowMapping, Any]
-"""A generic form of "row" that accommodates for the different kinds of
-"rows" that different result objects return, including row, row mapping, and
-scalar values"""
-
-
-_R = TypeVar("_R", bound=_RowData)
-_T = TypeVar("_T", bound=Any)
_Ts = TypeVarTuple("_Ts")
-_InterimRowType = Union[_R, TupleAny]
-"""a catchall "anything" kind of return type that can be applied
-across all the result types
-
-"""
_InterimSupportsScalarsRowType = Union[Row[Unpack[TupleAny]], Any]
_ProcessorsType = Sequence[Optional["_ResultProcessorType[Any]"]]
_TupleGetterType = Callable[[Sequence[Any]], Sequence[Any]]
-_UniqueFilterType = Callable[[Any], Any]
-_UniqueFilterStateType = Tuple[Set[Any], Optional[_UniqueFilterType]]
class ResultMetaData:
)
-# a symbol that indicates to internal Result methods that
-# "no row is returned". We can't use None for those cases where a scalar
-# filter is applied to rows.
-class _NoRow(Enum):
- _NO_ROW = 0
-
-
-_NO_ROW = _NoRow._NO_ROW
-
-
-class ResultInternal(InPlaceGenerative, Generic[_R]):
+class ResultInternal(InPlaceGenerative, BaseResultInternal[_R]):
__slots__ = ()
-
- _real_result: Optional[Result[Unpack[TupleAny]]] = None
- _generate_rows: bool = True
- _row_logging_fn: Optional[Callable[[Any], Any]]
-
- _unique_filter_state: Optional[_UniqueFilterStateType] = None
- _post_creational_filter: Optional[Callable[[Any], Any]] = None
_is_cursor = False
- _metadata: ResultMetaData
-
- _source_supports_scalars: bool
-
- def _fetchiter_impl(
- self,
- ) -> Iterator[_InterimRowType[Row[Unpack[TupleAny]]]]:
- raise NotImplementedError()
-
- def _fetchone_impl(
- self, hard_close: bool = False
- ) -> Optional[_InterimRowType[Row[Unpack[TupleAny]]]]:
- raise NotImplementedError()
-
- def _fetchmany_impl(
- self, size: Optional[int] = None
- ) -> List[_InterimRowType[Row[Unpack[TupleAny]]]]:
- raise NotImplementedError()
-
- def _fetchall_impl(
- self,
- ) -> List[_InterimRowType[Row[Unpack[TupleAny]]]]:
- raise NotImplementedError()
-
- def _soft_close(self, hard: bool = False) -> None:
- raise NotImplementedError()
-
- @HasMemoized_ro_memoized_attribute
- def _row_getter(self) -> Optional[Callable[..., _R]]:
- real_result: Result[Unpack[TupleAny]] = (
- self._real_result
- if self._real_result
- else cast("Result[Unpack[TupleAny]]", self)
- )
-
- if real_result._source_supports_scalars:
- if not self._generate_rows:
- return None
- else:
- _proc = Row
-
- def process_row(
- metadata: ResultMetaData,
- processors: Optional[_ProcessorsType],
- key_to_index: Dict[_KeyType, int],
- scalar_obj: Any,
- ) -> Row[Unpack[TupleAny]]:
- return _proc(
- metadata, processors, key_to_index, (scalar_obj,)
- )
-
- else:
- process_row = Row # type: ignore
-
- metadata = self._metadata
-
- key_to_index = metadata._key_to_index
- processors = metadata._effective_processors
- tf = metadata._tuplefilter
-
- if tf and not real_result._source_supports_scalars:
- if processors:
- processors = tf(processors)
-
- _make_row_orig: Callable[..., _R] = functools.partial( # type: ignore # noqa E501
- process_row, metadata, processors, key_to_index
- )
-
- fixed_tf = tf
-
- def make_row(row: _InterimRowType[Row[Unpack[TupleAny]]]) -> _R:
- return _make_row_orig(fixed_tf(row))
-
- else:
- make_row = functools.partial( # type: ignore
- process_row, metadata, processors, key_to_index
- )
-
- if real_result._row_logging_fn:
- _log_row = real_result._row_logging_fn
- _make_row = make_row
-
- def make_row(row: _InterimRowType[Row[Unpack[TupleAny]]]) -> _R:
- return _log_row(_make_row(row)) # type: ignore
-
- return make_row
-
- @HasMemoized_ro_memoized_attribute
- def _iterator_getter(self) -> Callable[..., Iterator[_R]]:
- make_row = self._row_getter
-
- post_creational_filter = self._post_creational_filter
-
- if self._unique_filter_state:
- uniques, strategy = self._unique_strategy
-
- def iterrows(self: Result[Unpack[TupleAny]]) -> Iterator[_R]:
- for raw_row in self._fetchiter_impl():
- obj: _InterimRowType[Any] = (
- make_row(raw_row) if make_row else raw_row
- )
- hashed = strategy(obj) if strategy else obj
- if hashed in uniques:
- continue
- uniques.add(hashed)
- if post_creational_filter:
- obj = post_creational_filter(obj)
- yield obj # type: ignore
-
- else:
-
- def iterrows(self: Result[Unpack[TupleAny]]) -> Iterator[_R]:
- for raw_row in self._fetchiter_impl():
- row: _InterimRowType[Any] = (
- make_row(raw_row) if make_row else raw_row
- )
- if post_creational_filter:
- row = post_creational_filter(row)
- yield row # type: ignore
-
- return iterrows
-
- def _raw_all_rows(self) -> List[_R]:
- make_row = self._row_getter
- assert make_row is not None
- rows = self._fetchall_impl()
- return [make_row(row) for row in rows]
-
- def _allrows(self) -> List[_R]:
- post_creational_filter = self._post_creational_filter
-
- make_row = self._row_getter
-
- rows = self._fetchall_impl()
- made_rows: List[_InterimRowType[_R]]
- if make_row:
- made_rows = [make_row(row) for row in rows]
- else:
- made_rows = rows # type: ignore
-
- interim_rows: List[_R]
-
- if self._unique_filter_state:
- uniques, strategy = self._unique_strategy
-
- interim_rows = [
- made_row # type: ignore
- for made_row, sig_row in [
- (
- made_row,
- strategy(made_row) if strategy else made_row,
- )
- for made_row in made_rows
- ]
- if sig_row not in uniques and not uniques.add(sig_row) # type: ignore # noqa: E501
- ]
- else:
- interim_rows = made_rows # type: ignore
-
- if post_creational_filter:
- interim_rows = [
- post_creational_filter(row) for row in interim_rows
- ]
- return interim_rows
-
- @HasMemoized_ro_memoized_attribute
- def _onerow_getter(
- self,
- ) -> Callable[..., Union[Literal[_NoRow._NO_ROW], _R]]:
- make_row = self._row_getter
-
- post_creational_filter = self._post_creational_filter
-
- if self._unique_filter_state:
- uniques, strategy = self._unique_strategy
-
- def onerow(self: Result[Unpack[TupleAny]]) -> Union[_NoRow, _R]:
- _onerow = self._fetchone_impl
- while True:
- row = _onerow()
- if row is None:
- return _NO_ROW
- else:
- obj: _InterimRowType[Any] = (
- make_row(row) if make_row else row
- )
- hashed = strategy(obj) if strategy else obj
- if hashed in uniques:
- continue
- else:
- uniques.add(hashed)
- if post_creational_filter:
- obj = post_creational_filter(obj)
- return obj # type: ignore
-
- else:
-
- def onerow(self: Result[Unpack[TupleAny]]) -> Union[_NoRow, _R]:
- row = self._fetchone_impl()
- if row is None:
- return _NO_ROW
- else:
- interim_row: _InterimRowType[Any] = (
- make_row(row) if make_row else row
- )
- if post_creational_filter:
- interim_row = post_creational_filter(interim_row)
- return interim_row # type: ignore
-
- return onerow
-
- @HasMemoized_ro_memoized_attribute
- def _manyrow_getter(self) -> Callable[..., List[_R]]:
- make_row = self._row_getter
-
- post_creational_filter = self._post_creational_filter
-
- if self._unique_filter_state:
- uniques, strategy = self._unique_strategy
-
- def filterrows(
- make_row: Optional[Callable[..., _R]],
- rows: List[Any],
- strategy: Optional[Callable[[List[Any]], Any]],
- uniques: Set[Any],
- ) -> List[_R]:
- if make_row:
- rows = [make_row(row) for row in rows]
-
- if strategy:
- made_rows = (
- (made_row, strategy(made_row)) for made_row in rows
- )
- else:
- made_rows = ((made_row, made_row) for made_row in rows)
- return [
- made_row
- for made_row, sig_row in made_rows
- if sig_row not in uniques and not uniques.add(sig_row) # type: ignore # noqa: E501
- ]
-
- def manyrows(
- self: ResultInternal[_R], num: Optional[int]
- ) -> List[_R]:
- collect: List[_R] = []
-
- _manyrows = self._fetchmany_impl
-
- if num is None:
- # if None is passed, we don't know the default
- # manyrows number, DBAPI has this as cursor.arraysize
- # different DBAPIs / fetch strategies may be different.
- # do a fetch to find what the number is. if there are
- # only fewer rows left, then it doesn't matter.
- real_result = (
- self._real_result
- if self._real_result
- else cast("Result[Unpack[TupleAny]]", self)
- )
- if real_result._yield_per:
- num_required = num = real_result._yield_per
- else:
- rows = _manyrows(num)
- num = len(rows)
- assert make_row is not None
- collect.extend(
- filterrows(make_row, rows, strategy, uniques)
- )
- num_required = num - len(collect)
- else:
- num_required = num
-
- assert num is not None
-
- while num_required:
- rows = _manyrows(num_required)
- if not rows:
- break
-
- collect.extend(
- filterrows(make_row, rows, strategy, uniques)
- )
- num_required = num - len(collect)
-
- if post_creational_filter:
- collect = [post_creational_filter(row) for row in collect]
- return collect
-
- else:
-
- def manyrows(
- self: ResultInternal[_R], num: Optional[int]
- ) -> List[_R]:
- if num is None:
- real_result = (
- self._real_result
- if self._real_result
- else cast("Result[Unpack[TupleAny]]", self)
- )
- num = real_result._yield_per
-
- rows: List[_InterimRowType[Any]] = self._fetchmany_impl(num)
- if make_row:
- rows = [make_row(row) for row in rows]
- if post_creational_filter:
- rows = [post_creational_filter(row) for row in rows]
- return rows # type: ignore
-
- return manyrows
-
- @overload
- def _only_one_row(
- self: ResultInternal[Row[_T, Unpack[TupleAny]]],
- raise_for_second_row: bool,
- raise_for_none: bool,
- scalar: Literal[True],
- ) -> _T: ...
-
- @overload
- def _only_one_row(
- self,
- raise_for_second_row: bool,
- raise_for_none: Literal[True],
- scalar: bool,
- ) -> _R: ...
-
- @overload
- def _only_one_row(
- self,
- raise_for_second_row: bool,
- raise_for_none: bool,
- scalar: bool,
- ) -> Optional[_R]: ...
-
- def _only_one_row(
- self,
- raise_for_second_row: bool,
- raise_for_none: bool,
- scalar: bool,
- ) -> Optional[_R]:
- onerow = self._fetchone_impl
-
- row: Optional[_InterimRowType[Any]] = onerow(hard_close=True)
- if row is None:
- if raise_for_none:
- raise exc.NoResultFound(
- "No row was found when one was required"
- )
- else:
- return None
-
- if scalar and self._source_supports_scalars:
- self._generate_rows = False
- make_row = None
- else:
- make_row = self._row_getter
-
- try:
- row = make_row(row) if make_row else row
- except:
- self._soft_close(hard=True)
- raise
-
- if raise_for_second_row:
- if self._unique_filter_state:
- # for no second row but uniqueness, need to essentially
- # consume the entire result :(
- uniques, strategy = self._unique_strategy
-
- existing_row_hash = strategy(row) if strategy else row
-
- while True:
- next_row: Any = onerow(hard_close=True)
- if next_row is None:
- next_row = _NO_ROW
- break
-
- try:
- next_row = make_row(next_row) if make_row else next_row
-
- if strategy:
- assert next_row is not _NO_ROW
- if existing_row_hash == strategy(next_row):
- continue
- elif row == next_row:
- continue
- # here, we have a row and it's different
- break
- except:
- self._soft_close(hard=True)
- raise
- else:
- next_row = onerow(hard_close=True)
- if next_row is None:
- next_row = _NO_ROW
-
- if next_row is not _NO_ROW:
- self._soft_close(hard=True)
- raise exc.MultipleResultsFound(
- "Multiple rows were found when exactly one was required"
- if raise_for_none
- else "Multiple rows were found when one or none "
- "was required"
- )
- else:
- # if we checked for second row then that would have
- # closed us :)
- self._soft_close(hard=True)
-
- if not scalar:
- post_creational_filter = self._post_creational_filter
- if post_creational_filter:
- row = post_creational_filter(row)
-
- if scalar and make_row:
- return row[0] # type: ignore
- else:
- return row # type: ignore
-
- def _iter_impl(self) -> Iterator[_R]:
- return self._iterator_getter(self)
-
- def _next_impl(self) -> _R:
- row = self._onerow_getter(self)
- if row is _NO_ROW:
- raise StopIteration()
- else:
- return row
-
@_generative
def _column_slices(self, indexes: Sequence[_KeyIndexType]) -> Self:
real_result = (
return self
- @HasMemoized.memoized_attribute
- def _unique_strategy(self) -> _UniqueFilterStateType:
- assert self._unique_filter_state is not None
- uniques, strategy = self._unique_filter_state
-
- real_result = (
- self._real_result
- if self._real_result is not None
- else cast("Result[Unpack[TupleAny]]", self)
- )
-
- if not strategy and self._metadata._unique_filters:
- if (
- real_result._source_supports_scalars
- and not self._generate_rows
- ):
- strategy = self._metadata._unique_filters[0]
- else:
- filters = self._metadata._unique_filters
- if self._metadata._tuplefilter:
- filters = self._metadata._tuplefilter(filters)
-
- strategy = operator.methodcaller("_filter_on_values", filters)
- return uniques, strategy
-
class _WithKeys:
__slots__ = ()
"against collections"
)
- result._unique_filter_state = (None, require_unique)
+ result._unique_filter_state = (set(), require_unique)
if context.yield_per:
result.yield_per(context.yield_per)
from . import _collections_cy
from . import _immutabledict_cy
from ..engine import _processors_cy
+ from ..engine import _result_cy
from ..engine import _row_cy
from ..engine import _util_cy as engine_util
from ..sql import _util_cy as sql_util
_collections_cy,
_immutabledict_cy,
_processors_cy,
+ _result_cy,
_row_cy,
engine_util,
sql_util,
# types
int = int # noqa: A001
+char = int
bint = bool
longlong = int
ulonglong = int
CYTHON_MODULES = (
"engine._processors_cy",
"engine._row_cy",
+ "engine._result_cy",
"engine._util_cy",
"sql._util_cy",
"util._collections_cy",
stmt = s.query(User).join(User.addresses).statement
- @assert_cycles(4)
+ @assert_cycles(8)
def go():
result = s.execute(stmt)
rows = result.fetchall() # noqa
stmt = s.query(User).join(User.addresses).statement
- @assert_cycles(4)
+ @assert_cycles(8)
def go():
result = s.execute(stmt)
for partition in result.partitions(3):
stmt = s.query(User).join(User.addresses).statement
- @assert_cycles(4)
+ @assert_cycles(8)
def go():
result = s.execute(stmt)
for partition in result.unique().partitions(3):
from collections import defaultdict
-import math
import re
from timeit import timeit
@classmethod
def _divide_results(cls, results, num, div, name):
"utility method to create ratios of two implementation"
- avg_str = "> mean of values"
if div in results and num in results:
num_dict = results[num]
div_dict = results[div]
- assert avg_str not in num_dict and avg_str not in div_dict
assert num_dict.keys() == div_dict.keys()
results[name] = {m: num_dict[m] / div_dict[m] for m in div_dict}
- not_na = [v for v in results[name].values() if not math.isnan(v)]
- avg = sum(not_na) / len(not_na)
- results[name][avg_str] = avg
@classmethod
def update_results(cls, results):
value = timeit(call, number=t_num)
print(".", end="", flush=True)
except Exception as e:
- fails.append(f"{name}::{m} error: {e}")
+ fails.append(f"{name}::{m} error: {e!r}")
print("x", end="", flush=True)
value = float("nan")
for f in fails:
print("\t", f)
+ before = set(results)
cls.update_results(results)
- return results, [name for name, _ in objects]
+ after = set(results)
+ return results, [name for name, _ in objects], after - before
from collections import defaultdict
from datetime import datetime
+import math
import subprocess
import sqlalchemy as sa
else:
compare_by_meth = {}
- result_by_impl, impl_names = case.run_case(args.factor, args.filter)
+ result_by_impl, impl_names, computed = case.run_case(
+ args.factor, args.filter
+ )
+ add_mean = set(computed)
+ add_sum = set(impl_names)
result_by_method = defaultdict(dict)
all_impls = dict.fromkeys(result_by_impl)
+ sum_str = "> sum of values"
+ avg_str = "> mean of values"
for impl in result_by_impl:
for meth in result_by_impl[impl]:
meth_dict = result_by_method[meth]
meth_dict[impl] = result_by_impl[impl][meth]
if meth in compare_by_meth and impl in compare_by_meth[meth]:
cmp_impl = f"compare {impl}"
+ add_sum.add(cmp_impl)
over = f"{impl} / compare"
+ add_mean.add(over)
all_impls[cmp_impl] = None
all_impls[over] = None
meth_dict[cmp_impl] = compare_by_meth[meth][impl]
meth_dict[over] = meth_dict[impl] / meth_dict[cmp_impl]
+ for impl in add_sum | add_mean:
+ if impl in result_by_impl:
+ data = result_by_impl[impl]
+ else:
+ key = next(iter(result_by_method))
+ assert impl in result_by_method[key]
+ data = {
+ m: md[impl]
+ for m, md in result_by_method.items()
+ if impl in md
+ }
+
+ if impl in add_sum:
+ assert sum_str not in data
+ total = sum(data.values())
+ result_by_method[sum_str][impl] = total
+ if impl in add_mean:
+ assert avg_str not in data
+ not_na = [v for v in data.values() if not math.isnan(v)]
+ if not not_na:
+ continue
+ avg = sum(not_na) / len(not_na)
+ result_by_method[avg_str][impl] = avg
+
tabulate(list(all_impls), result_by_method)
if args.csv:
from dataclasses import dataclass
from itertools import product
from operator import itemgetter
+from types import FunctionType
from typing import Callable
from typing import Optional
from sqlalchemy.engine import cursor
from sqlalchemy.engine import result
from sqlalchemy.engine.default import DefaultExecutionContext
+from sqlalchemy.util.langhelpers import load_uncompiled_module
from .base import Case
from .base import test_case
class _CommonResult(Case):
+
+ @staticmethod
+ def _load_python_module():
+ from sqlalchemy.engine import _result_cy
+
+ py_result = load_uncompiled_module(_result_cy)
+ assert not py_result._is_compiled()
+ # NOTE: the enums must be couped over otherwise they are not the
+ # same object and `is` comparisons fail
+ py_result._NoRow = _result_cy._NoRow
+ py_result._NO_ROW = _result_cy._NO_ROW
+ return py_result
+
+ @staticmethod
+ def _make_subclass(
+ name: str, result_internal: type, base: type[result.Result]
+ ) -> type[result.Result]:
+ # Need to also create a python version of the scalar result
+ class PyScalarResult(result_internal, result.ScalarResult):
+ _fetchiter_impl = result.ScalarResult._fetchiter_impl
+ _fetchone_impl = result.ScalarResult._fetchone_impl
+ _fetchmany_impl = result.ScalarResult._fetchmany_impl
+ _fetchall_impl = result.ScalarResult._fetchall_impl
+ _soft_close = result.ScalarResult._soft_close
+
+ def scalars(self, index=0):
+ return PyScalarResult(self, index)
+
+ cls_dict = dict(
+ _fetchiter_impl=base._fetchiter_impl,
+ _fetchone_impl=base._fetchone_impl,
+ _fetchmany_impl=base._fetchmany_impl,
+ _fetchall_impl=base._fetchall_impl,
+ _soft_close=base._soft_close,
+ scalars=scalars,
+ )
+
+ return type(name, (result_internal, base), cls_dict)
+
+ @classmethod
+ def update_results(cls, results):
+ cls._divide_results(results, "cython", "python", "cy / py")
+
@classmethod
def init_class(cls):
# 3-col
impl: result.IteratorResult
@staticmethod
- def default():
- return cursor.IteratorResult
+ def python():
+ py_result = _CommonResult._load_python_module()
+
+ PyIteratorResult = _CommonResult._make_subclass(
+ "PyIteratorResult",
+ py_result.BaseResultInternal,
+ result.IteratorResult,
+ )
+
+ assert PyIteratorResult._allrows.__class__ is FunctionType
+ return PyIteratorResult
+
+ @staticmethod
+ def cython():
+ from sqlalchemy.engine import _result_cy
- IMPLEMENTATIONS = {"default": default.__func__}
+ assert _result_cy._is_compiled()
+
+ assert result.IteratorResult._allrows.__class__ is not FunctionType
+ return result.IteratorResult
+
+ IMPLEMENTATIONS = {
+ "python": python.__func__,
+ "cython": cython.__func__,
+ }
@classmethod
def get_init_args_callable(
impl: cursor.CursorResult
@staticmethod
- def default():
+ def python():
+ py_result = _CommonResult._load_python_module()
+
+ PyCursorResult = _CommonResult._make_subclass(
+ "PyCursorResult",
+ py_result.BaseResultInternal,
+ cursor.CursorResult,
+ )
+
+ return PyCursorResult
+
+ @staticmethod
+ def cython():
+ from sqlalchemy.engine import _result_cy
+
+ assert _result_cy._is_compiled()
+
+ assert cursor.CursorResult._allrows.__class__ is not FunctionType
return cursor.CursorResult
- IMPLEMENTATIONS = {"default": default.__func__}
+ IMPLEMENTATIONS = {
+ "python": python.__func__,
+ "cython": cython.__func__,
+ }
@classmethod
def get_init_args_callable(
# TEST: test.aaa_profiling.test_orm.DeferOptionsTest.test_baseline
-test.aaa_profiling.test_orm.DeferOptionsTest.test_baseline x86_64_linux_cpython_3.13_sqlite_pysqlite_dbapiunicode_cextensions 15356
+test.aaa_profiling.test_orm.DeferOptionsTest.test_baseline x86_64_linux_cpython_3.13_sqlite_pysqlite_dbapiunicode_cextensions 13312
test.aaa_profiling.test_orm.DeferOptionsTest.test_baseline x86_64_linux_cpython_3.13_sqlite_pysqlite_dbapiunicode_nocextensions 25384
-test.aaa_profiling.test_orm.DeferOptionsTest.test_baseline x86_64_linux_cpython_3.14_sqlite_pysqlite_dbapiunicode_cextensions 15358
+test.aaa_profiling.test_orm.DeferOptionsTest.test_baseline x86_64_linux_cpython_3.14_sqlite_pysqlite_dbapiunicode_cextensions 13347
test.aaa_profiling.test_orm.DeferOptionsTest.test_baseline x86_64_linux_cpython_3.14_sqlite_pysqlite_dbapiunicode_nocextensions 25386
# TEST: test.aaa_profiling.test_orm.DeferOptionsTest.test_defer_many_cols
-test.aaa_profiling.test_orm.DeferOptionsTest.test_defer_many_cols x86_64_linux_cpython_3.13_sqlite_pysqlite_dbapiunicode_cextensions 21463
+test.aaa_profiling.test_orm.DeferOptionsTest.test_defer_many_cols x86_64_linux_cpython_3.13_sqlite_pysqlite_dbapiunicode_cextensions 19455
test.aaa_profiling.test_orm.DeferOptionsTest.test_defer_many_cols x86_64_linux_cpython_3.13_sqlite_pysqlite_dbapiunicode_nocextensions 25491
-test.aaa_profiling.test_orm.DeferOptionsTest.test_defer_many_cols x86_64_linux_cpython_3.14_sqlite_pysqlite_dbapiunicode_cextensions 21465
+test.aaa_profiling.test_orm.DeferOptionsTest.test_defer_many_cols x86_64_linux_cpython_3.14_sqlite_pysqlite_dbapiunicode_cextensions 19454
test.aaa_profiling.test_orm.DeferOptionsTest.test_defer_many_cols x86_64_linux_cpython_3.14_sqlite_pysqlite_dbapiunicode_nocextensions 25493
# TEST: test.aaa_profiling.test_orm.JoinConditionTest.test_a_to_b_aliased
# TEST: test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[False-0]
-test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[False-0] x86_64_linux_cpython_3.13_mariadb_mysqldb_dbapiunicode_cextensions 18
+test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[False-0] x86_64_linux_cpython_3.13_mariadb_mysqldb_dbapiunicode_cextensions 17
test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[False-0] x86_64_linux_cpython_3.13_mariadb_mysqldb_dbapiunicode_nocextensions 18
-test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[False-0] x86_64_linux_cpython_3.13_mssql_pyodbc_dbapiunicode_cextensions 14
+test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[False-0] x86_64_linux_cpython_3.13_mssql_pyodbc_dbapiunicode_cextensions 13
test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[False-0] x86_64_linux_cpython_3.13_mssql_pyodbc_dbapiunicode_nocextensions 14
test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[False-0] x86_64_linux_cpython_3.13_oracle_oracledb_dbapiunicode_cextensions 21
test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[False-0] x86_64_linux_cpython_3.13_oracle_oracledb_dbapiunicode_nocextensions 19
-test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[False-0] x86_64_linux_cpython_3.13_postgresql_psycopg2_dbapiunicode_cextensions 14
+test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[False-0] x86_64_linux_cpython_3.13_postgresql_psycopg2_dbapiunicode_cextensions 13
test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[False-0] x86_64_linux_cpython_3.13_postgresql_psycopg2_dbapiunicode_nocextensions 14
-test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[False-0] x86_64_linux_cpython_3.13_sqlite_pysqlite_dbapiunicode_cextensions 14
+test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[False-0] x86_64_linux_cpython_3.13_sqlite_pysqlite_dbapiunicode_cextensions 13
test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[False-0] x86_64_linux_cpython_3.13_sqlite_pysqlite_dbapiunicode_nocextensions 14
test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[False-0] x86_64_linux_cpython_3.14_mariadb_mysqldb_dbapiunicode_cextensions 18
test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[False-0] x86_64_linux_cpython_3.14_mariadb_mysqldb_dbapiunicode_nocextensions 18
test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[False-0] x86_64_linux_cpython_3.14_oracle_oracledb_dbapiunicode_nocextensions 19
test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[False-0] x86_64_linux_cpython_3.14_postgresql_psycopg2_dbapiunicode_cextensions 14
test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[False-0] x86_64_linux_cpython_3.14_postgresql_psycopg2_dbapiunicode_nocextensions 14
-test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[False-0] x86_64_linux_cpython_3.14_sqlite_pysqlite_dbapiunicode_cextensions 14
+test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[False-0] x86_64_linux_cpython_3.14_sqlite_pysqlite_dbapiunicode_cextensions 13
test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[False-0] x86_64_linux_cpython_3.14_sqlite_pysqlite_dbapiunicode_nocextensions 14
# TEST: test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[False-1]
-test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[False-1] x86_64_linux_cpython_3.13_mariadb_mysqldb_dbapiunicode_cextensions 18
+test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[False-1] x86_64_linux_cpython_3.13_mariadb_mysqldb_dbapiunicode_cextensions 17
test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[False-1] x86_64_linux_cpython_3.13_mariadb_mysqldb_dbapiunicode_nocextensions 20
-test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[False-1] x86_64_linux_cpython_3.13_mssql_pyodbc_dbapiunicode_cextensions 14
+test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[False-1] x86_64_linux_cpython_3.13_mssql_pyodbc_dbapiunicode_cextensions 13
test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[False-1] x86_64_linux_cpython_3.13_mssql_pyodbc_dbapiunicode_nocextensions 16
test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[False-1] x86_64_linux_cpython_3.13_oracle_oracledb_dbapiunicode_cextensions 21
test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[False-1] x86_64_linux_cpython_3.13_oracle_oracledb_dbapiunicode_nocextensions 21
-test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[False-1] x86_64_linux_cpython_3.13_postgresql_psycopg2_dbapiunicode_cextensions 14
+test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[False-1] x86_64_linux_cpython_3.13_postgresql_psycopg2_dbapiunicode_cextensions 13
test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[False-1] x86_64_linux_cpython_3.13_postgresql_psycopg2_dbapiunicode_nocextensions 16
-test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[False-1] x86_64_linux_cpython_3.13_sqlite_pysqlite_dbapiunicode_cextensions 14
-test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[False-1] x86_64_linux_cpython_3.13_sqlite_pysqlite_dbapiunicode_nocextensions 17
+test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[False-1] x86_64_linux_cpython_3.13_sqlite_pysqlite_dbapiunicode_cextensions 13
+test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[False-1] x86_64_linux_cpython_3.13_sqlite_pysqlite_dbapiunicode_nocextensions 18
test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[False-1] x86_64_linux_cpython_3.14_mariadb_mysqldb_dbapiunicode_cextensions 18
test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[False-1] x86_64_linux_cpython_3.14_mariadb_mysqldb_dbapiunicode_nocextensions 20
test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[False-1] x86_64_linux_cpython_3.14_mssql_pyodbc_dbapiunicode_cextensions 14
test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[False-1] x86_64_linux_cpython_3.14_oracle_oracledb_dbapiunicode_nocextensions 21
test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[False-1] x86_64_linux_cpython_3.14_postgresql_psycopg2_dbapiunicode_cextensions 14
test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[False-1] x86_64_linux_cpython_3.14_postgresql_psycopg2_dbapiunicode_nocextensions 16
-test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[False-1] x86_64_linux_cpython_3.14_sqlite_pysqlite_dbapiunicode_cextensions 14
-test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[False-1] x86_64_linux_cpython_3.14_sqlite_pysqlite_dbapiunicode_nocextensions 17
+test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[False-1] x86_64_linux_cpython_3.14_sqlite_pysqlite_dbapiunicode_cextensions 13
+test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[False-1] x86_64_linux_cpython_3.14_sqlite_pysqlite_dbapiunicode_nocextensions 18
# TEST: test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[False-2]
-test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[False-2] x86_64_linux_cpython_3.13_mariadb_mysqldb_dbapiunicode_cextensions 18
+test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[False-2] x86_64_linux_cpython_3.13_mariadb_mysqldb_dbapiunicode_cextensions 17
test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[False-2] x86_64_linux_cpython_3.13_mariadb_mysqldb_dbapiunicode_nocextensions 20
-test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[False-2] x86_64_linux_cpython_3.13_mssql_pyodbc_dbapiunicode_cextensions 14
+test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[False-2] x86_64_linux_cpython_3.13_mssql_pyodbc_dbapiunicode_cextensions 13
test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[False-2] x86_64_linux_cpython_3.13_mssql_pyodbc_dbapiunicode_nocextensions 16
test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[False-2] x86_64_linux_cpython_3.13_oracle_oracledb_dbapiunicode_cextensions 21
test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[False-2] x86_64_linux_cpython_3.13_oracle_oracledb_dbapiunicode_nocextensions 21
-test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[False-2] x86_64_linux_cpython_3.13_postgresql_psycopg2_dbapiunicode_cextensions 14
+test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[False-2] x86_64_linux_cpython_3.13_postgresql_psycopg2_dbapiunicode_cextensions 13
test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[False-2] x86_64_linux_cpython_3.13_postgresql_psycopg2_dbapiunicode_nocextensions 16
-test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[False-2] x86_64_linux_cpython_3.13_sqlite_pysqlite_dbapiunicode_cextensions 14
-test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[False-2] x86_64_linux_cpython_3.13_sqlite_pysqlite_dbapiunicode_nocextensions 17
+test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[False-2] x86_64_linux_cpython_3.13_sqlite_pysqlite_dbapiunicode_cextensions 13
+test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[False-2] x86_64_linux_cpython_3.13_sqlite_pysqlite_dbapiunicode_nocextensions 18
test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[False-2] x86_64_linux_cpython_3.14_mariadb_mysqldb_dbapiunicode_cextensions 18
test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[False-2] x86_64_linux_cpython_3.14_mariadb_mysqldb_dbapiunicode_nocextensions 20
test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[False-2] x86_64_linux_cpython_3.14_mssql_pyodbc_dbapiunicode_cextensions 14
test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[False-2] x86_64_linux_cpython_3.14_oracle_oracledb_dbapiunicode_nocextensions 21
test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[False-2] x86_64_linux_cpython_3.14_postgresql_psycopg2_dbapiunicode_cextensions 14
test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[False-2] x86_64_linux_cpython_3.14_postgresql_psycopg2_dbapiunicode_nocextensions 16
-test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[False-2] x86_64_linux_cpython_3.14_sqlite_pysqlite_dbapiunicode_cextensions 14
-test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[False-2] x86_64_linux_cpython_3.14_sqlite_pysqlite_dbapiunicode_nocextensions 17
+test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[False-2] x86_64_linux_cpython_3.14_sqlite_pysqlite_dbapiunicode_cextensions 13
+test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[False-2] x86_64_linux_cpython_3.14_sqlite_pysqlite_dbapiunicode_nocextensions 18
# TEST: test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[True-1]
test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[True-1] x86_64_linux_cpython_3.13_mariadb_mysqldb_dbapiunicode_cextensions 23
test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[True-1] x86_64_linux_cpython_3.13_mariadb_mysqldb_dbapiunicode_nocextensions 25
-test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[True-1] x86_64_linux_cpython_3.13_mssql_pyodbc_dbapiunicode_cextensions 17
+test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[True-1] x86_64_linux_cpython_3.13_mssql_pyodbc_dbapiunicode_cextensions 16
test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[True-1] x86_64_linux_cpython_3.13_mssql_pyodbc_dbapiunicode_nocextensions 19
test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[True-1] x86_64_linux_cpython_3.13_oracle_oracledb_dbapiunicode_cextensions 28
test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[True-1] x86_64_linux_cpython_3.13_oracle_oracledb_dbapiunicode_nocextensions 27
-test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[True-1] x86_64_linux_cpython_3.13_postgresql_psycopg2_dbapiunicode_cextensions 17
+test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[True-1] x86_64_linux_cpython_3.13_postgresql_psycopg2_dbapiunicode_cextensions 16
test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[True-1] x86_64_linux_cpython_3.13_postgresql_psycopg2_dbapiunicode_nocextensions 19
-test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[True-1] x86_64_linux_cpython_3.13_sqlite_pysqlite_dbapiunicode_cextensions 17
-test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[True-1] x86_64_linux_cpython_3.13_sqlite_pysqlite_dbapiunicode_nocextensions 19
+test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[True-1] x86_64_linux_cpython_3.13_sqlite_pysqlite_dbapiunicode_cextensions 16
+test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[True-1] x86_64_linux_cpython_3.13_sqlite_pysqlite_dbapiunicode_nocextensions 21
test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[True-1] x86_64_linux_cpython_3.14_mariadb_mysqldb_dbapiunicode_cextensions 23
test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[True-1] x86_64_linux_cpython_3.14_mariadb_mysqldb_dbapiunicode_nocextensions 25
test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[True-1] x86_64_linux_cpython_3.14_mssql_pyodbc_dbapiunicode_cextensions 17
test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[True-1] x86_64_linux_cpython_3.14_oracle_oracledb_dbapiunicode_nocextensions 27
test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[True-1] x86_64_linux_cpython_3.14_postgresql_psycopg2_dbapiunicode_cextensions 17
test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[True-1] x86_64_linux_cpython_3.14_postgresql_psycopg2_dbapiunicode_nocextensions 19
-test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[True-1] x86_64_linux_cpython_3.14_sqlite_pysqlite_dbapiunicode_cextensions 17
-test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[True-1] x86_64_linux_cpython_3.14_sqlite_pysqlite_dbapiunicode_nocextensions 19
+test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[True-1] x86_64_linux_cpython_3.14_sqlite_pysqlite_dbapiunicode_cextensions 16
+test.aaa_profiling.test_resultset.ResultSetTest.test_one_or_none[True-1] x86_64_linux_cpython_3.14_sqlite_pysqlite_dbapiunicode_nocextensions 21
# TEST: test.aaa_profiling.test_resultset.ResultSetTest.test_raw_string
content = section_re.sub(repl_fn, content)
if count == 0:
- raise ValueError(
- "Expected to find comment '# START GENERATED CYTHON IMPORT' "
- f"in cython file {file}, but none found"
- )
+ if content:
+ raise ValueError(
+ "Expected to find comment '# START GENERATED CYTHON IMPORT' "
+ f"in cython file {file}, but none found and the file is not "
+ "empty"
+ )
+ content = code
if count > 1:
raise ValueError(
"Expected to find a single comment '# START GENERATED CYTHON "
projects / thirdparty / sqlalchemy / sqlalchemy.git / commitdiff
