AlkantarClanX12
Your IP : 3.129.45.144
# engine/result.py
# Copyright (C) 2005-2024 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
"""Define generic result set constructs."""
from __future__ import annotations
from enum import Enum
import functools
import itertools
import operator
import typing
from typing import Any
from typing import Callable
from typing import cast
from typing import Dict
from typing import Generic
from typing import Iterable
from typing import Iterator
from typing import List
from typing import Mapping
from typing import NoReturn
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 .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 HasMemoized_ro_memoized_attribute
from ..util import NONE_SET
from ..util._has_cy import HAS_CYEXTENSION
from ..util.typing import Literal
from ..util.typing import Self
if typing.TYPE_CHECKING or not HAS_CYEXTENSION:
from ._py_row import tuplegetter as tuplegetter
else:
from sqlalchemy.cyextension.resultproxy import tuplegetter as tuplegetter
if typing.TYPE_CHECKING:
from ..sql.schema import Column
from ..sql.type_api import _ResultProcessorType
_KeyType = Union[str, "Column[Any]"]
_KeyIndexType = Union[str, "Column[Any]", int]
# is overridden in cursor using _CursorKeyMapRecType
_KeyMapRecType = Any
_KeyMapType = Mapping[_KeyType, _KeyMapRecType]
_RowData = Union[Row[Any], 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"""
_RawRowType = Tuple[Any, ...]
"""represents the kind of row we get from a DBAPI cursor"""
_R = TypeVar("_R", bound=_RowData)
_T = TypeVar("_T", bound=Any)
_TP = TypeVar("_TP", bound=Tuple[Any, ...])
_InterimRowType = Union[_R, _RawRowType]
"""a catchall "anything" kind of return type that can be applied
across all the result types
"""
_InterimSupportsScalarsRowType = Union[Row[Any], Any]
_ProcessorsType = Sequence[Optional["_ResultProcessorType[Any]"]]
_TupleGetterType = Callable[[Sequence[Any]], Sequence[Any]]
_UniqueFilterType = Callable[[Any], Any]
_UniqueFilterStateType = Tuple[Set[Any], Optional[_UniqueFilterType]]
class ResultMetaData:
"""Base for metadata about result rows."""
__slots__ = ()
_tuplefilter: Optional[_TupleGetterType] = None
_translated_indexes: Optional[Sequence[int]] = None
_unique_filters: Optional[Sequence[Callable[[Any], Any]]] = None
_keymap: _KeyMapType
_keys: Sequence[str]
_processors: Optional[_ProcessorsType]
_key_to_index: Mapping[_KeyType, int]
@property
def keys(self) -> RMKeyView:
return RMKeyView(self)
def _has_key(self, key: object) -> bool:
raise NotImplementedError()
def _for_freeze(self) -> ResultMetaData:
raise NotImplementedError()
@overload
def _key_fallback(
self, key: Any, err: Optional[Exception], raiseerr: Literal[True] = ...
) -> NoReturn: ...
@overload
def _key_fallback(
self,
key: Any,
err: Optional[Exception],
raiseerr: Literal[False] = ...,
) -> None: ...
@overload
def _key_fallback(
self, key: Any, err: Optional[Exception], raiseerr: bool = ...
) -> Optional[NoReturn]: ...
def _key_fallback(
self, key: Any, err: Optional[Exception], raiseerr: bool = True
) -> Optional[NoReturn]:
assert raiseerr
raise KeyError(key) from err
def _raise_for_ambiguous_column_name(
self, rec: _KeyMapRecType
) -> NoReturn:
raise NotImplementedError(
"ambiguous column name logic is implemented for "
"CursorResultMetaData"
)
def _index_for_key(
self, key: _KeyIndexType, raiseerr: bool
) -> Optional[int]:
raise NotImplementedError()
def _indexes_for_keys(
self, keys: Sequence[_KeyIndexType]
) -> Sequence[int]:
raise NotImplementedError()
def _metadata_for_keys(
self, keys: Sequence[_KeyIndexType]
) -> Iterator[_KeyMapRecType]:
raise NotImplementedError()
def _reduce(self, keys: Sequence[_KeyIndexType]) -> ResultMetaData:
raise NotImplementedError()
def _getter(
self, key: Any, raiseerr: bool = True
) -> Optional[Callable[[Row[Any]], Any]]:
index = self._index_for_key(key, raiseerr)
if index is not None:
return operator.itemgetter(index)
else:
return None
def _row_as_tuple_getter(
self, keys: Sequence[_KeyIndexType]
) -> _TupleGetterType:
indexes = self._indexes_for_keys(keys)
return tuplegetter(*indexes)
def _make_key_to_index(
self, keymap: Mapping[_KeyType, Sequence[Any]], index: int
) -> Mapping[_KeyType, int]:
return {
key: rec[index]
for key, rec in keymap.items()
if rec[index] is not None
}
def _key_not_found(self, key: Any, attr_error: bool) -> NoReturn:
if key in self._keymap:
# the index must be none in this case
self._raise_for_ambiguous_column_name(self._keymap[key])
else:
# unknown key
if attr_error:
try:
self._key_fallback(key, None)
except KeyError as ke:
raise AttributeError(ke.args[0]) from ke
else:
self._key_fallback(key, None)
@property
def _effective_processors(self) -> Optional[_ProcessorsType]:
if not self._processors or NONE_SET.issuperset(self._processors):
return None
else:
return self._processors
class RMKeyView(typing.KeysView[Any]):
__slots__ = ("_parent", "_keys")
_parent: ResultMetaData
_keys: Sequence[str]
def __init__(self, parent: ResultMetaData):
self._parent = parent
self._keys = [k for k in parent._keys if k is not None]
def __len__(self) -> int:
return len(self._keys)
def __repr__(self) -> str:
return "{0.__class__.__name__}({0._keys!r})".format(self)
def __iter__(self) -> Iterator[str]:
return iter(self._keys)
def __contains__(self, item: Any) -> bool:
if isinstance(item, int):
return False
# note this also includes special key fallback behaviors
# which also don't seem to be tested in test_resultset right now
return self._parent._has_key(item)
def __eq__(self, other: Any) -> bool:
return list(other) == list(self)
def __ne__(self, other: Any) -> bool:
return list(other) != list(self)
class SimpleResultMetaData(ResultMetaData):
"""result metadata for in-memory collections."""
__slots__ = (
"_keys",
"_keymap",
"_processors",
"_tuplefilter",
"_translated_indexes",
"_unique_filters",
"_key_to_index",
)
_keys: Sequence[str]
def __init__(
self,
keys: Sequence[str],
extra: Optional[Sequence[Any]] = None,
_processors: Optional[_ProcessorsType] = None,
_tuplefilter: Optional[_TupleGetterType] = None,
_translated_indexes: Optional[Sequence[int]] = None,
_unique_filters: Optional[Sequence[Callable[[Any], Any]]] = None,
):
self._keys = list(keys)
self._tuplefilter = _tuplefilter
self._translated_indexes = _translated_indexes
self._unique_filters = _unique_filters
if extra:
recs_names = [
(
(name,) + (extras if extras else ()),
(index, name, extras),
)
for index, (name, extras) in enumerate(zip(self._keys, extra))
]
else:
recs_names = [
((name,), (index, name, ()))
for index, name in enumerate(self._keys)
]
self._keymap = {key: rec for keys, rec in recs_names for key in keys}
self._processors = _processors
self._key_to_index = self._make_key_to_index(self._keymap, 0)
def _has_key(self, key: object) -> bool:
return key in self._keymap
def _for_freeze(self) -> ResultMetaData:
unique_filters = self._unique_filters
if unique_filters and self._tuplefilter:
unique_filters = self._tuplefilter(unique_filters)
# TODO: are we freezing the result with or without uniqueness
# applied?
return SimpleResultMetaData(
self._keys,
extra=[self._keymap[key][2] for key in self._keys],
_unique_filters=unique_filters,
)
def __getstate__(self) -> Dict[str, Any]:
return {
"_keys": self._keys,
"_translated_indexes": self._translated_indexes,
}
def __setstate__(self, state: Dict[str, Any]) -> None:
if state["_translated_indexes"]:
_translated_indexes = state["_translated_indexes"]
_tuplefilter = tuplegetter(*_translated_indexes)
else:
_translated_indexes = _tuplefilter = None
self.__init__( # type: ignore
state["_keys"],
_translated_indexes=_translated_indexes,
_tuplefilter=_tuplefilter,
)
def _index_for_key(self, key: Any, raiseerr: bool = True) -> int:
if int in key.__class__.__mro__:
key = self._keys[key]
try:
rec = self._keymap[key]
except KeyError as ke:
rec = self._key_fallback(key, ke, raiseerr)
return rec[0] # type: ignore[no-any-return]
def _indexes_for_keys(self, keys: Sequence[Any]) -> Sequence[int]:
return [self._keymap[key][0] for key in keys]
def _metadata_for_keys(
self, keys: Sequence[Any]
) -> Iterator[_KeyMapRecType]:
for key in keys:
if int in key.__class__.__mro__:
key = self._keys[key]
try:
rec = self._keymap[key]
except KeyError as ke:
rec = self._key_fallback(key, ke, True)
yield rec
def _reduce(self, keys: Sequence[Any]) -> ResultMetaData:
try:
metadata_for_keys = [
self._keymap[
self._keys[key] if int in key.__class__.__mro__ else key
]
for key in keys
]
except KeyError as ke:
self._key_fallback(ke.args[0], ke, True)
indexes: Sequence[int]
new_keys: Sequence[str]
extra: Sequence[Any]
indexes, new_keys, extra = zip(*metadata_for_keys)
if self._translated_indexes:
indexes = [self._translated_indexes[idx] for idx in indexes]
tup = tuplegetter(*indexes)
new_metadata = SimpleResultMetaData(
new_keys,
extra=extra,
_tuplefilter=tup,
_translated_indexes=indexes,
_processors=self._processors,
_unique_filters=self._unique_filters,
)
return new_metadata
def result_tuple(
fields: Sequence[str], extra: Optional[Any] = None
) -> Callable[[Iterable[Any]], Row[Any]]:
parent = SimpleResultMetaData(fields, extra)
return functools.partial(
Row, parent, parent._effective_processors, parent._key_to_index
)
# 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]):
__slots__ = ()
_real_result: Optional[Result[Any]] = 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[Any]]]:
raise NotImplementedError()
def _fetchone_impl(
self, hard_close: bool = False
) -> Optional[_InterimRowType[Row[Any]]]:
raise NotImplementedError()
def _fetchmany_impl(
self, size: Optional[int] = None
) -> List[_InterimRowType[Row[Any]]]:
raise NotImplementedError()
def _fetchall_impl(self) -> List[_InterimRowType[Row[Any]]]:
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[Any] = (
self._real_result
if self._real_result
else cast("Result[Any]", 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: Mapping[_KeyType, int],
scalar_obj: Any,
) -> Row[Any]:
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[Any]]) -> _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[Any]]) -> _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[Any]) -> 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[Any]) -> 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[Any]) -> 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[Any]) -> 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[Any]", 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[Any]", 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,
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:
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:
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 = (
self._real_result
if self._real_result
else cast("Result[Any]", self)
)
if not real_result._source_supports_scalars or len(indexes) != 1:
self._metadata = self._metadata._reduce(indexes)
assert self._generate_rows
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[Any]", 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__ = ()
_metadata: ResultMetaData
# used mainly to share documentation on the keys method.
def keys(self) -> RMKeyView:
"""Return an iterable view which yields the string keys that would
be represented by each :class:`_engine.Row`.
The keys can represent the labels of the columns returned by a core
statement or the names of the orm classes returned by an orm
execution.
The view also can be tested for key containment using the Python
``in`` operator, which will test both for the string keys represented
in the view, as well as for alternate keys such as column objects.
.. versionchanged:: 1.4 a key view object is returned rather than a
plain list.
"""
return self._metadata.keys
class Result(_WithKeys, ResultInternal[Row[_TP]]):
"""Represent a set of database results.
.. versionadded:: 1.4 The :class:`_engine.Result` object provides a
completely updated usage model and calling facade for SQLAlchemy
Core and SQLAlchemy ORM. In Core, it forms the basis of the
:class:`_engine.CursorResult` object which replaces the previous
:class:`_engine.ResultProxy` interface. When using the ORM, a
higher level object called :class:`_engine.ChunkedIteratorResult`
is normally used.
.. note:: In SQLAlchemy 1.4 and above, this object is
used for ORM results returned by :meth:`_orm.Session.execute`, which can
yield instances of ORM mapped objects either individually or within
tuple-like rows. Note that the :class:`_engine.Result` object does not
deduplicate instances or rows automatically as is the case with the
legacy :class:`_orm.Query` object. For in-Python de-duplication of
instances or rows, use the :meth:`_engine.Result.unique` modifier
method.
.. seealso::
:ref:`tutorial_fetching_rows` - in the :doc:`/tutorial/index`
"""
__slots__ = ("_metadata", "__dict__")
_row_logging_fn: Optional[Callable[[Row[Any]], Row[Any]]] = None
_source_supports_scalars: bool = False
_yield_per: Optional[int] = None
_attributes: util.immutabledict[Any, Any] = util.immutabledict()
def __init__(self, cursor_metadata: ResultMetaData):
self._metadata = cursor_metadata
def __enter__(self) -> Self:
return self
def __exit__(self, type_: Any, value: Any, traceback: Any) -> None:
self.close()
def close(self) -> None:
"""close this :class:`_engine.Result`.
The behavior of this method is implementation specific, and is
not implemented by default. The method should generally end
the resources in use by the result object and also cause any
subsequent iteration or row fetching to raise
:class:`.ResourceClosedError`.
.. versionadded:: 1.4.27 - ``.close()`` was previously not generally
available for all :class:`_engine.Result` classes, instead only
being available on the :class:`_engine.CursorResult` returned for
Core statement executions. As most other result objects, namely the
ones used by the ORM, are proxying a :class:`_engine.CursorResult`
in any case, this allows the underlying cursor result to be closed
from the outside facade for the case when the ORM query is using
the ``yield_per`` execution option where it does not immediately
exhaust and autoclose the database cursor.
"""
self._soft_close(hard=True)
@property
def _soft_closed(self) -> bool:
raise NotImplementedError()
@property
def closed(self) -> bool:
"""return ``True`` if this :class:`_engine.Result` reports .closed
.. versionadded:: 1.4.43
"""
raise NotImplementedError()
@_generative
def yield_per(self, num: int) -> Self:
"""Configure the row-fetching strategy to fetch ``num`` rows at a time.
This impacts the underlying behavior of the result when iterating over
the result object, or otherwise making use of methods such as
:meth:`_engine.Result.fetchone` that return one row at a time. Data
from the underlying cursor or other data source will be buffered up to
this many rows in memory, and the buffered collection will then be
yielded out one row at a time or as many rows are requested. Each time
the buffer clears, it will be refreshed to this many rows or as many
rows remain if fewer remain.
The :meth:`_engine.Result.yield_per` method is generally used in
conjunction with the
:paramref:`_engine.Connection.execution_options.stream_results`
execution option, which will allow the database dialect in use to make
use of a server side cursor, if the DBAPI supports a specific "server
side cursor" mode separate from its default mode of operation.
.. tip::
Consider using the
:paramref:`_engine.Connection.execution_options.yield_per`
execution option, which will simultaneously set
:paramref:`_engine.Connection.execution_options.stream_results`
to ensure the use of server side cursors, as well as automatically
invoke the :meth:`_engine.Result.yield_per` method to establish
a fixed row buffer size at once.
The :paramref:`_engine.Connection.execution_options.yield_per`
execution option is available for ORM operations, with
:class:`_orm.Session`-oriented use described at
:ref:`orm_queryguide_yield_per`. The Core-only version which works
with :class:`_engine.Connection` is new as of SQLAlchemy 1.4.40.
.. versionadded:: 1.4
:param num: number of rows to fetch each time the buffer is refilled.
If set to a value below 1, fetches all rows for the next buffer.
.. seealso::
:ref:`engine_stream_results` - describes Core behavior for
:meth:`_engine.Result.yield_per`
:ref:`orm_queryguide_yield_per` - in the :ref:`queryguide_toplevel`
"""
self._yield_per = num
return self
@_generative
def unique(self, strategy: Optional[_UniqueFilterType] = None) -> Self:
"""Apply unique filtering to the objects returned by this
:class:`_engine.Result`.
When this filter is applied with no arguments, the rows or objects
returned will filtered such that each row is returned uniquely. The
algorithm used to determine this uniqueness is by default the Python
hashing identity of the whole tuple. In some cases a specialized
per-entity hashing scheme may be used, such as when using the ORM, a
scheme is applied which works against the primary key identity of
returned objects.
The unique filter is applied **after all other filters**, which means
if the columns returned have been refined using a method such as the
:meth:`_engine.Result.columns` or :meth:`_engine.Result.scalars`
method, the uniquing is applied to **only the column or columns
returned**. This occurs regardless of the order in which these
methods have been called upon the :class:`_engine.Result` object.
The unique filter also changes the calculus used for methods like
:meth:`_engine.Result.fetchmany` and :meth:`_engine.Result.partitions`.
When using :meth:`_engine.Result.unique`, these methods will continue
to yield the number of rows or objects requested, after uniquing
has been applied. However, this necessarily impacts the buffering
behavior of the underlying cursor or datasource, such that multiple
underlying calls to ``cursor.fetchmany()`` may be necessary in order
to accumulate enough objects in order to provide a unique collection
of the requested size.
:param strategy: a callable that will be applied to rows or objects
being iterated, which should return an object that represents the
unique value of the row. A Python ``set()`` is used to store
these identities. If not passed, a default uniqueness strategy
is used which may have been assembled by the source of this
:class:`_engine.Result` object.
"""
self._unique_filter_state = (set(), strategy)
return self
def columns(self, *col_expressions: _KeyIndexType) -> Self:
r"""Establish the columns that should be returned in each row.
This method may be used to limit the columns returned as well
as to reorder them. The given list of expressions are normally
a series of integers or string key names. They may also be
appropriate :class:`.ColumnElement` objects which correspond to
a given statement construct.
.. versionchanged:: 2.0 Due to a bug in 1.4, the
:meth:`_engine.Result.columns` method had an incorrect behavior
where calling upon the method with just one index would cause the
:class:`_engine.Result` object to yield scalar values rather than
:class:`_engine.Row` objects. In version 2.0, this behavior
has been corrected such that calling upon
:meth:`_engine.Result.columns` with a single index will
produce a :class:`_engine.Result` object that continues
to yield :class:`_engine.Row` objects, which include
only a single column.
E.g.::
statement = select(table.c.x, table.c.y, table.c.z)
result = connection.execute(statement)
for z, y in result.columns('z', 'y'):
# ...
Example of using the column objects from the statement itself::
for z, y in result.columns(
statement.selected_columns.c.z,
statement.selected_columns.c.y
):
# ...
.. versionadded:: 1.4
:param \*col_expressions: indicates columns to be returned. Elements
may be integer row indexes, string column names, or appropriate
:class:`.ColumnElement` objects corresponding to a select construct.
:return: this :class:`_engine.Result` object with the modifications
given.
"""
return self._column_slices(col_expressions)
@overload
def scalars(self: Result[Tuple[_T]]) -> ScalarResult[_T]: ...
@overload
def scalars(
self: Result[Tuple[_T]], index: Literal[0]
) -> ScalarResult[_T]: ...
@overload
def scalars(self, index: _KeyIndexType = 0) -> ScalarResult[Any]: ...
def scalars(self, index: _KeyIndexType = 0) -> ScalarResult[Any]:
"""Return a :class:`_engine.ScalarResult` filtering object which
will return single elements rather than :class:`_row.Row` objects.
E.g.::
>>> result = conn.execute(text("select int_id from table"))
>>> result.scalars().all()
[1, 2, 3]
When results are fetched from the :class:`_engine.ScalarResult`
filtering object, the single column-row that would be returned by the
:class:`_engine.Result` is instead returned as the column's value.
.. versionadded:: 1.4
:param index: integer or row key indicating the column to be fetched
from each row, defaults to ``0`` indicating the first column.
:return: a new :class:`_engine.ScalarResult` filtering object referring
to this :class:`_engine.Result` object.
"""
return ScalarResult(self, index)
def _getter(
self, key: _KeyIndexType, raiseerr: bool = True
) -> Optional[Callable[[Row[Any]], Any]]:
"""return a callable that will retrieve the given key from a
:class:`_engine.Row`.
"""
if self._source_supports_scalars:
raise NotImplementedError(
"can't use this function in 'only scalars' mode"
)
return self._metadata._getter(key, raiseerr)
def _tuple_getter(self, keys: Sequence[_KeyIndexType]) -> _TupleGetterType:
"""return a callable that will retrieve the given keys from a
:class:`_engine.Row`.
"""
if self._source_supports_scalars:
raise NotImplementedError(
"can't use this function in 'only scalars' mode"
)
return self._metadata._row_as_tuple_getter(keys)
def mappings(self) -> MappingResult:
"""Apply a mappings filter to returned rows, returning an instance of
:class:`_engine.MappingResult`.
When this filter is applied, fetching rows will return
:class:`_engine.RowMapping` objects instead of :class:`_engine.Row`
objects.
.. versionadded:: 1.4
:return: a new :class:`_engine.MappingResult` filtering object
referring to this :class:`_engine.Result` object.
"""
return MappingResult(self)
@property
def t(self) -> TupleResult[_TP]:
"""Apply a "typed tuple" typing filter to returned rows.
The :attr:`_engine.Result.t` attribute is a synonym for
calling the :meth:`_engine.Result.tuples` method.
.. versionadded:: 2.0
"""
return self # type: ignore
def tuples(self) -> TupleResult[_TP]:
"""Apply a "typed tuple" typing filter to returned rows.
This method returns the same :class:`_engine.Result` object
at runtime,
however annotates as returning a :class:`_engine.TupleResult` object
that will indicate to :pep:`484` typing tools that plain typed
``Tuple`` instances are returned rather than rows. This allows
tuple unpacking and ``__getitem__`` access of :class:`_engine.Row`
objects to by typed, for those cases where the statement invoked
itself included typing information.
.. versionadded:: 2.0
:return: the :class:`_engine.TupleResult` type at typing time.
.. seealso::
:attr:`_engine.Result.t` - shorter synonym
:attr:`_engine.Row._t` - :class:`_engine.Row` version
"""
return self # type: ignore
def _raw_row_iterator(self) -> Iterator[_RowData]:
"""Return a safe iterator that yields raw row data.
This is used by the :meth:`_engine.Result.merge` method
to merge multiple compatible results together.
"""
raise NotImplementedError()
def __iter__(self) -> Iterator[Row[_TP]]:
return self._iter_impl()
def __next__(self) -> Row[_TP]:
return self._next_impl()
def partitions(
self, size: Optional[int] = None
) -> Iterator[Sequence[Row[_TP]]]:
"""Iterate through sub-lists of rows of the size given.
Each list will be of the size given, excluding the last list to
be yielded, which may have a small number of rows. No empty
lists will be yielded.
The result object is automatically closed when the iterator
is fully consumed.
Note that the backend driver will usually buffer the entire result
ahead of time unless the
:paramref:`.Connection.execution_options.stream_results` execution
option is used indicating that the driver should not pre-buffer
results, if possible. Not all drivers support this option and
the option is silently ignored for those who do not.
When using the ORM, the :meth:`_engine.Result.partitions` method
is typically more effective from a memory perspective when it is
combined with use of the
:ref:`yield_per execution option <orm_queryguide_yield_per>`,
which instructs both the DBAPI driver to use server side cursors,
if available, as well as instructs the ORM loading internals to only
build a certain amount of ORM objects from a result at a time before
yielding them out.
.. versionadded:: 1.4
:param size: indicate the maximum number of rows to be present
in each list yielded. If None, makes use of the value set by
the :meth:`_engine.Result.yield_per`, method, if it were called,
or the :paramref:`_engine.Connection.execution_options.yield_per`
execution option, which is equivalent in this regard. If
yield_per weren't set, it makes use of the
:meth:`_engine.Result.fetchmany` default, which may be backend
specific and not well defined.
:return: iterator of lists
.. seealso::
:ref:`engine_stream_results`
:ref:`orm_queryguide_yield_per` - in the :ref:`queryguide_toplevel`
"""
getter = self._manyrow_getter
while True:
partition = getter(self, size)
if partition:
yield partition
else:
break
def fetchall(self) -> Sequence[Row[_TP]]:
"""A synonym for the :meth:`_engine.Result.all` method."""
return self._allrows()
def fetchone(self) -> Optional[Row[_TP]]:
"""Fetch one row.
When all rows are exhausted, returns None.
This method is provided for backwards compatibility with
SQLAlchemy 1.x.x.
To fetch the first row of a result only, use the
:meth:`_engine.Result.first` method. To iterate through all
rows, iterate the :class:`_engine.Result` object directly.
:return: a :class:`_engine.Row` object if no filters are applied,
or ``None`` if no rows remain.
"""
row = self._onerow_getter(self)
if row is _NO_ROW:
return None
else:
return row
def fetchmany(self, size: Optional[int] = None) -> Sequence[Row[_TP]]:
"""Fetch many rows.
When all rows are exhausted, returns an empty sequence.
This method is provided for backwards compatibility with
SQLAlchemy 1.x.x.
To fetch rows in groups, use the :meth:`_engine.Result.partitions`
method.
:return: a sequence of :class:`_engine.Row` objects.
.. seealso::
:meth:`_engine.Result.partitions`
"""
return self._manyrow_getter(self, size)
def all(self) -> Sequence[Row[_TP]]:
"""Return all rows in a sequence.
Closes the result set after invocation. Subsequent invocations
will return an empty sequence.
.. versionadded:: 1.4
:return: a sequence of :class:`_engine.Row` objects.
.. seealso::
:ref:`engine_stream_results` - How to stream a large result set
without loading it completely in python.
"""
return self._allrows()
def first(self) -> Optional[Row[_TP]]:
"""Fetch the first row or ``None`` if no row is present.
Closes the result set and discards remaining rows.
.. note:: This method returns one **row**, e.g. tuple, by default.
To return exactly one single scalar value, that is, the first
column of the first row, use the
:meth:`_engine.Result.scalar` method,
or combine :meth:`_engine.Result.scalars` and
:meth:`_engine.Result.first`.
Additionally, in contrast to the behavior of the legacy ORM
:meth:`_orm.Query.first` method, **no limit is applied** to the
SQL query which was invoked to produce this
:class:`_engine.Result`;
for a DBAPI driver that buffers results in memory before yielding
rows, all rows will be sent to the Python process and all but
the first row will be discarded.
.. seealso::
:ref:`migration_20_unify_select`
:return: a :class:`_engine.Row` object, or None
if no rows remain.
.. seealso::
:meth:`_engine.Result.scalar`
:meth:`_engine.Result.one`
"""
return self._only_one_row(
raise_for_second_row=False, raise_for_none=False, scalar=False
)
def one_or_none(self) -> Optional[Row[_TP]]:
"""Return at most one result or raise an exception.
Returns ``None`` if the result has no rows.
Raises :class:`.MultipleResultsFound`
if multiple rows are returned.
.. versionadded:: 1.4
:return: The first :class:`_engine.Row` or ``None`` if no row
is available.
:raises: :class:`.MultipleResultsFound`
.. seealso::
:meth:`_engine.Result.first`
:meth:`_engine.Result.one`
"""
return self._only_one_row(
raise_for_second_row=True, raise_for_none=False, scalar=False
)
@overload
def scalar_one(self: Result[Tuple[_T]]) -> _T: ...
@overload
def scalar_one(self) -> Any: ...
def scalar_one(self) -> Any:
"""Return exactly one scalar result or raise an exception.
This is equivalent to calling :meth:`_engine.Result.scalars` and
then :meth:`_engine.Result.one`.
.. seealso::
:meth:`_engine.Result.one`
:meth:`_engine.Result.scalars`
"""
return self._only_one_row(
raise_for_second_row=True, raise_for_none=True, scalar=True
)
@overload
def scalar_one_or_none(self: Result[Tuple[_T]]) -> Optional[_T]: ...
@overload
def scalar_one_or_none(self) -> Optional[Any]: ...
def scalar_one_or_none(self) -> Optional[Any]:
"""Return exactly one scalar result or ``None``.
This is equivalent to calling :meth:`_engine.Result.scalars` and
then :meth:`_engine.Result.one_or_none`.
.. seealso::
:meth:`_engine.Result.one_or_none`
:meth:`_engine.Result.scalars`
"""
return self._only_one_row(
raise_for_second_row=True, raise_for_none=False, scalar=True
)
def one(self) -> Row[_TP]:
"""Return exactly one row or raise an exception.
Raises :class:`.NoResultFound` if the result returns no
rows, or :class:`.MultipleResultsFound` if multiple rows
would be returned.
.. note:: This method returns one **row**, e.g. tuple, by default.
To return exactly one single scalar value, that is, the first
column of the first row, use the
:meth:`_engine.Result.scalar_one` method, or combine
:meth:`_engine.Result.scalars` and
:meth:`_engine.Result.one`.
.. versionadded:: 1.4
:return: The first :class:`_engine.Row`.
:raises: :class:`.MultipleResultsFound`, :class:`.NoResultFound`
.. seealso::
:meth:`_engine.Result.first`
:meth:`_engine.Result.one_or_none`
:meth:`_engine.Result.scalar_one`
"""
return self._only_one_row(
raise_for_second_row=True, raise_for_none=True, scalar=False
)
@overload
def scalar(self: Result[Tuple[_T]]) -> Optional[_T]: ...
@overload
def scalar(self) -> Any: ...
def scalar(self) -> Any:
"""Fetch the first column of the first row, and close the result set.
Returns ``None`` if there are no rows to fetch.
No validation is performed to test if additional rows remain.
After calling this method, the object is fully closed,
e.g. the :meth:`_engine.CursorResult.close`
method will have been called.
:return: a Python scalar value, or ``None`` if no rows remain.
"""
return self._only_one_row(
raise_for_second_row=False, raise_for_none=False, scalar=True
)
def freeze(self) -> FrozenResult[_TP]:
"""Return a callable object that will produce copies of this
:class:`_engine.Result` when invoked.
The callable object returned is an instance of
:class:`_engine.FrozenResult`.
This is used for result set caching. The method must be called
on the result when it has been unconsumed, and calling the method
will consume the result fully. When the :class:`_engine.FrozenResult`
is retrieved from a cache, it can be called any number of times where
it will produce a new :class:`_engine.Result` object each time
against its stored set of rows.
.. seealso::
:ref:`do_orm_execute_re_executing` - example usage within the
ORM to implement a result-set cache.
"""
return FrozenResult(self)
def merge(self, *others: Result[Any]) -> MergedResult[_TP]:
"""Merge this :class:`_engine.Result` with other compatible result
objects.
The object returned is an instance of :class:`_engine.MergedResult`,
which will be composed of iterators from the given result
objects.
The new result will use the metadata from this result object.
The subsequent result objects must be against an identical
set of result / cursor metadata, otherwise the behavior is
undefined.
"""
return MergedResult(self._metadata, (self,) + others)
class FilterResult(ResultInternal[_R]):
"""A wrapper for a :class:`_engine.Result` that returns objects other than
:class:`_engine.Row` objects, such as dictionaries or scalar objects.
:class:`_engine.FilterResult` is the common base for additional result
APIs including :class:`_engine.MappingResult`,
:class:`_engine.ScalarResult` and :class:`_engine.AsyncResult`.
"""
__slots__ = (
"_real_result",
"_post_creational_filter",
"_metadata",
"_unique_filter_state",
"__dict__",
)
_post_creational_filter: Optional[Callable[[Any], Any]]
_real_result: Result[Any]
def __enter__(self) -> Self:
return self
def __exit__(self, type_: Any, value: Any, traceback: Any) -> None:
self._real_result.__exit__(type_, value, traceback)
@_generative
def yield_per(self, num: int) -> Self:
"""Configure the row-fetching strategy to fetch ``num`` rows at a time.
The :meth:`_engine.FilterResult.yield_per` method is a pass through
to the :meth:`_engine.Result.yield_per` method. See that method's
documentation for usage notes.
.. versionadded:: 1.4.40 - added :meth:`_engine.FilterResult.yield_per`
so that the method is available on all result set implementations
.. seealso::
:ref:`engine_stream_results` - describes Core behavior for
:meth:`_engine.Result.yield_per`
:ref:`orm_queryguide_yield_per` - in the :ref:`queryguide_toplevel`
"""
self._real_result = self._real_result.yield_per(num)
return self
def _soft_close(self, hard: bool = False) -> None:
self._real_result._soft_close(hard=hard)
@property
def _soft_closed(self) -> bool:
return self._real_result._soft_closed
@property
def closed(self) -> bool:
"""Return ``True`` if the underlying :class:`_engine.Result` reports
closed
.. versionadded:: 1.4.43
"""
return self._real_result.closed
def close(self) -> None:
"""Close this :class:`_engine.FilterResult`.
.. versionadded:: 1.4.43
"""
self._real_result.close()
@property
def _attributes(self) -> Dict[Any, Any]:
return self._real_result._attributes
def _fetchiter_impl(self) -> Iterator[_InterimRowType[Row[Any]]]:
return self._real_result._fetchiter_impl()
def _fetchone_impl(
self, hard_close: bool = False
) -> Optional[_InterimRowType[Row[Any]]]:
return self._real_result._fetchone_impl(hard_close=hard_close)
def _fetchall_impl(self) -> List[_InterimRowType[Row[Any]]]:
return self._real_result._fetchall_impl()
def _fetchmany_impl(
self, size: Optional[int] = None
) -> List[_InterimRowType[Row[Any]]]:
return self._real_result._fetchmany_impl(size=size)
class ScalarResult(FilterResult[_R]):
"""A wrapper for a :class:`_engine.Result` that returns scalar values
rather than :class:`_row.Row` values.
The :class:`_engine.ScalarResult` object is acquired by calling the
:meth:`_engine.Result.scalars` method.
A special limitation of :class:`_engine.ScalarResult` is that it has
no ``fetchone()`` method; since the semantics of ``fetchone()`` are that
the ``None`` value indicates no more results, this is not compatible
with :class:`_engine.ScalarResult` since there is no way to distinguish
between ``None`` as a row value versus ``None`` as an indicator. Use
``next(result)`` to receive values individually.
"""
__slots__ = ()
_generate_rows = False
_post_creational_filter: Optional[Callable[[Any], Any]]
def __init__(self, real_result: Result[Any], index: _KeyIndexType):
self._real_result = real_result
if real_result._source_supports_scalars:
self._metadata = real_result._metadata
self._post_creational_filter = None
else:
self._metadata = real_result._metadata._reduce([index])
self._post_creational_filter = operator.itemgetter(0)
self._unique_filter_state = real_result._unique_filter_state
def unique(self, strategy: Optional[_UniqueFilterType] = None) -> Self:
"""Apply unique filtering to the objects returned by this
:class:`_engine.ScalarResult`.
See :meth:`_engine.Result.unique` for usage details.
"""
self._unique_filter_state = (set(), strategy)
return self
def partitions(self, size: Optional[int] = None) -> Iterator[Sequence[_R]]:
"""Iterate through sub-lists of elements of the size given.
Equivalent to :meth:`_engine.Result.partitions` except that
scalar values, rather than :class:`_engine.Row` objects,
are returned.
"""
getter = self._manyrow_getter
while True:
partition = getter(self, size)
if partition:
yield partition
else:
break
def fetchall(self) -> Sequence[_R]:
"""A synonym for the :meth:`_engine.ScalarResult.all` method."""
return self._allrows()
def fetchmany(self, size: Optional[int] = None) -> Sequence[_R]:
"""Fetch many objects.
Equivalent to :meth:`_engine.Result.fetchmany` except that
scalar values, rather than :class:`_engine.Row` objects,
are returned.
"""
return self._manyrow_getter(self, size)
def all(self) -> Sequence[_R]:
"""Return all scalar values in a sequence.
Equivalent to :meth:`_engine.Result.all` except that
scalar values, rather than :class:`_engine.Row` objects,
are returned.
"""
return self._allrows()
def __iter__(self) -> Iterator[_R]:
return self._iter_impl()
def __next__(self) -> _R:
return self._next_impl()
def first(self) -> Optional[_R]:
"""Fetch the first object or ``None`` if no object is present.
Equivalent to :meth:`_engine.Result.first` except that
scalar values, rather than :class:`_engine.Row` objects,
are returned.
"""
return self._only_one_row(
raise_for_second_row=False, raise_for_none=False, scalar=False
)
def one_or_none(self) -> Optional[_R]:
"""Return at most one object or raise an exception.
Equivalent to :meth:`_engine.Result.one_or_none` except that
scalar values, rather than :class:`_engine.Row` objects,
are returned.
"""
return self._only_one_row(
raise_for_second_row=True, raise_for_none=False, scalar=False
)
def one(self) -> _R:
"""Return exactly one object or raise an exception.
Equivalent to :meth:`_engine.Result.one` except that
scalar values, rather than :class:`_engine.Row` objects,
are returned.
"""
return self._only_one_row(
raise_for_second_row=True, raise_for_none=True, scalar=False
)
class TupleResult(FilterResult[_R], util.TypingOnly):
"""A :class:`_engine.Result` that's typed as returning plain
Python tuples instead of rows.
Since :class:`_engine.Row` acts like a tuple in every way already,
this class is a typing only class, regular :class:`_engine.Result` is
still used at runtime.
"""
__slots__ = ()
if TYPE_CHECKING:
def partitions(
self, size: Optional[int] = None
) -> Iterator[Sequence[_R]]:
"""Iterate through sub-lists of elements of the size given.
Equivalent to :meth:`_engine.Result.partitions` except that
tuple values, rather than :class:`_engine.Row` objects,
are returned.
"""
...
def fetchone(self) -> Optional[_R]:
"""Fetch one tuple.
Equivalent to :meth:`_engine.Result.fetchone` except that
tuple values, rather than :class:`_engine.Row`
objects, are returned.
"""
...
def fetchall(self) -> Sequence[_R]:
"""A synonym for the :meth:`_engine.ScalarResult.all` method."""
...
def fetchmany(self, size: Optional[int] = None) -> Sequence[_R]:
"""Fetch many objects.
Equivalent to :meth:`_engine.Result.fetchmany` except that
tuple values, rather than :class:`_engine.Row` objects,
are returned.
"""
...
def all(self) -> Sequence[_R]: # noqa: A001
"""Return all scalar values in a sequence.
Equivalent to :meth:`_engine.Result.all` except that
tuple values, rather than :class:`_engine.Row` objects,
are returned.
"""
...
def __iter__(self) -> Iterator[_R]: ...
def __next__(self) -> _R: ...
def first(self) -> Optional[_R]:
"""Fetch the first object or ``None`` if no object is present.
Equivalent to :meth:`_engine.Result.first` except that
tuple values, rather than :class:`_engine.Row` objects,
are returned.
"""
...
def one_or_none(self) -> Optional[_R]:
"""Return at most one object or raise an exception.
Equivalent to :meth:`_engine.Result.one_or_none` except that
tuple values, rather than :class:`_engine.Row` objects,
are returned.
"""
...
def one(self) -> _R:
"""Return exactly one object or raise an exception.
Equivalent to :meth:`_engine.Result.one` except that
tuple values, rather than :class:`_engine.Row` objects,
are returned.
"""
...
@overload
def scalar_one(self: TupleResult[Tuple[_T]]) -> _T: ...
@overload
def scalar_one(self) -> Any: ...
def scalar_one(self) -> Any:
"""Return exactly one scalar result or raise an exception.
This is equivalent to calling :meth:`_engine.Result.scalars`
and then :meth:`_engine.Result.one`.
.. seealso::
:meth:`_engine.Result.one`
:meth:`_engine.Result.scalars`
"""
...
@overload
def scalar_one_or_none(
self: TupleResult[Tuple[_T]],
) -> Optional[_T]: ...
@overload
def scalar_one_or_none(self) -> Optional[Any]: ...
def scalar_one_or_none(self) -> Optional[Any]:
"""Return exactly one or no scalar result.
This is equivalent to calling :meth:`_engine.Result.scalars`
and then :meth:`_engine.Result.one_or_none`.
.. seealso::
:meth:`_engine.Result.one_or_none`
:meth:`_engine.Result.scalars`
"""
...
@overload
def scalar(self: TupleResult[Tuple[_T]]) -> Optional[_T]: ...
@overload
def scalar(self) -> Any: ...
def scalar(self) -> Any:
"""Fetch the first column of the first row, and close the result
set.
Returns ``None`` if there are no rows to fetch.
No validation is performed to test if additional rows remain.
After calling this method, the object is fully closed,
e.g. the :meth:`_engine.CursorResult.close`
method will have been called.
:return: a Python scalar value , or ``None`` if no rows remain.
"""
...
class MappingResult(_WithKeys, FilterResult[RowMapping]):
"""A wrapper for a :class:`_engine.Result` that returns dictionary values
rather than :class:`_engine.Row` values.
The :class:`_engine.MappingResult` object is acquired by calling the
:meth:`_engine.Result.mappings` method.
"""
__slots__ = ()
_generate_rows = True
_post_creational_filter = operator.attrgetter("_mapping")
def __init__(self, result: Result[Any]):
self._real_result = result
self._unique_filter_state = result._unique_filter_state
self._metadata = result._metadata
if result._source_supports_scalars:
self._metadata = self._metadata._reduce([0])
def unique(self, strategy: Optional[_UniqueFilterType] = None) -> Self:
"""Apply unique filtering to the objects returned by this
:class:`_engine.MappingResult`.
See :meth:`_engine.Result.unique` for usage details.
"""
self._unique_filter_state = (set(), strategy)
return self
def columns(self, *col_expressions: _KeyIndexType) -> Self:
r"""Establish the columns that should be returned in each row."""
return self._column_slices(col_expressions)
def partitions(
self, size: Optional[int] = None
) -> Iterator[Sequence[RowMapping]]:
"""Iterate through sub-lists of elements of the size given.
Equivalent to :meth:`_engine.Result.partitions` except that
:class:`_engine.RowMapping` values, rather than :class:`_engine.Row`
objects, are returned.
"""
getter = self._manyrow_getter
while True:
partition = getter(self, size)
if partition:
yield partition
else:
break
def fetchall(self) -> Sequence[RowMapping]:
"""A synonym for the :meth:`_engine.MappingResult.all` method."""
return self._allrows()
def fetchone(self) -> Optional[RowMapping]:
"""Fetch one object.
Equivalent to :meth:`_engine.Result.fetchone` except that
:class:`_engine.RowMapping` values, rather than :class:`_engine.Row`
objects, are returned.
"""
row = self._onerow_getter(self)
if row is _NO_ROW:
return None
else:
return row
def fetchmany(self, size: Optional[int] = None) -> Sequence[RowMapping]:
"""Fetch many objects.
Equivalent to :meth:`_engine.Result.fetchmany` except that
:class:`_engine.RowMapping` values, rather than :class:`_engine.Row`
objects, are returned.
"""
return self._manyrow_getter(self, size)
def all(self) -> Sequence[RowMapping]:
"""Return all scalar values in a sequence.
Equivalent to :meth:`_engine.Result.all` except that
:class:`_engine.RowMapping` values, rather than :class:`_engine.Row`
objects, are returned.
"""
return self._allrows()
def __iter__(self) -> Iterator[RowMapping]:
return self._iter_impl()
def __next__(self) -> RowMapping:
return self._next_impl()
def first(self) -> Optional[RowMapping]:
"""Fetch the first object or ``None`` if no object is present.
Equivalent to :meth:`_engine.Result.first` except that
:class:`_engine.RowMapping` values, rather than :class:`_engine.Row`
objects, are returned.
"""
return self._only_one_row(
raise_for_second_row=False, raise_for_none=False, scalar=False
)
def one_or_none(self) -> Optional[RowMapping]:
"""Return at most one object or raise an exception.
Equivalent to :meth:`_engine.Result.one_or_none` except that
:class:`_engine.RowMapping` values, rather than :class:`_engine.Row`
objects, are returned.
"""
return self._only_one_row(
raise_for_second_row=True, raise_for_none=False, scalar=False
)
def one(self) -> RowMapping:
"""Return exactly one object or raise an exception.
Equivalent to :meth:`_engine.Result.one` except that
:class:`_engine.RowMapping` values, rather than :class:`_engine.Row`
objects, are returned.
"""
return self._only_one_row(
raise_for_second_row=True, raise_for_none=True, scalar=False
)
class FrozenResult(Generic[_TP]):
"""Represents a :class:`_engine.Result` object in a "frozen" state suitable
for caching.
The :class:`_engine.FrozenResult` object is returned from the
:meth:`_engine.Result.freeze` method of any :class:`_engine.Result`
object.
A new iterable :class:`_engine.Result` object is generated from a fixed
set of data each time the :class:`_engine.FrozenResult` is invoked as
a callable::
result = connection.execute(query)
frozen = result.freeze()
unfrozen_result_one = frozen()
for row in unfrozen_result_one:
print(row)
unfrozen_result_two = frozen()
rows = unfrozen_result_two.all()
# ... etc
.. versionadded:: 1.4
.. seealso::
:ref:`do_orm_execute_re_executing` - example usage within the
ORM to implement a result-set cache.
:func:`_orm.loading.merge_frozen_result` - ORM function to merge
a frozen result back into a :class:`_orm.Session`.
"""
data: Sequence[Any]
def __init__(self, result: Result[_TP]):
self.metadata = result._metadata._for_freeze()
self._source_supports_scalars = result._source_supports_scalars
self._attributes = result._attributes
if self._source_supports_scalars:
self.data = list(result._raw_row_iterator())
else:
self.data = result.fetchall()
def rewrite_rows(self) -> Sequence[Sequence[Any]]:
if self._source_supports_scalars:
return [[elem] for elem in self.data]
else:
return [list(row) for row in self.data]
def with_new_rows(
self, tuple_data: Sequence[Row[_TP]]
) -> FrozenResult[_TP]:
fr = FrozenResult.__new__(FrozenResult)
fr.metadata = self.metadata
fr._attributes = self._attributes
fr._source_supports_scalars = self._source_supports_scalars
if self._source_supports_scalars:
fr.data = [d[0] for d in tuple_data]
else:
fr.data = tuple_data
return fr
def __call__(self) -> Result[_TP]:
result: IteratorResult[_TP] = IteratorResult(
self.metadata, iter(self.data)
)
result._attributes = self._attributes
result._source_supports_scalars = self._source_supports_scalars
return result
class IteratorResult(Result[_TP]):
"""A :class:`_engine.Result` that gets data from a Python iterator of
:class:`_engine.Row` objects or similar row-like data.
.. versionadded:: 1.4
"""
_hard_closed = False
_soft_closed = False
def __init__(
self,
cursor_metadata: ResultMetaData,
iterator: Iterator[_InterimSupportsScalarsRowType],
raw: Optional[Result[Any]] = None,
_source_supports_scalars: bool = False,
):
self._metadata = cursor_metadata
self.iterator = iterator
self.raw = raw
self._source_supports_scalars = _source_supports_scalars
@property
def closed(self) -> bool:
"""Return ``True`` if this :class:`_engine.IteratorResult` has
been closed
.. versionadded:: 1.4.43
"""
return self._hard_closed
def _soft_close(self, hard: bool = False, **kw: Any) -> None:
if hard:
self._hard_closed = True
if self.raw is not None:
self.raw._soft_close(hard=hard, **kw)
self.iterator = iter([])
self._reset_memoizations()
self._soft_closed = True
def _raise_hard_closed(self) -> NoReturn:
raise exc.ResourceClosedError("This result object is closed.")
def _raw_row_iterator(self) -> Iterator[_RowData]:
return self.iterator
def _fetchiter_impl(self) -> Iterator[_InterimSupportsScalarsRowType]:
if self._hard_closed:
self._raise_hard_closed()
return self.iterator
def _fetchone_impl(
self, hard_close: bool = False
) -> Optional[_InterimRowType[Row[Any]]]:
if self._hard_closed:
self._raise_hard_closed()
row = next(self.iterator, _NO_ROW)
if row is _NO_ROW:
self._soft_close(hard=hard_close)
return None
else:
return row
def _fetchall_impl(self) -> List[_InterimRowType[Row[Any]]]:
if self._hard_closed:
self._raise_hard_closed()
try:
return list(self.iterator)
finally:
self._soft_close()
def _fetchmany_impl(
self, size: Optional[int] = None
) -> List[_InterimRowType[Row[Any]]]:
if self._hard_closed:
self._raise_hard_closed()
return list(itertools.islice(self.iterator, 0, size))
def null_result() -> IteratorResult[Any]:
return IteratorResult(SimpleResultMetaData([]), iter([]))
class ChunkedIteratorResult(IteratorResult[_TP]):
"""An :class:`_engine.IteratorResult` that works from an
iterator-producing callable.
The given ``chunks`` argument is a function that is given a number of rows
to return in each chunk, or ``None`` for all rows. The function should
then return an un-consumed iterator of lists, each list of the requested
size.
The function can be called at any time again, in which case it should
continue from the same result set but adjust the chunk size as given.
.. versionadded:: 1.4
"""
def __init__(
self,
cursor_metadata: ResultMetaData,
chunks: Callable[
[Optional[int]], Iterator[Sequence[_InterimRowType[_R]]]
],
source_supports_scalars: bool = False,
raw: Optional[Result[Any]] = None,
dynamic_yield_per: bool = False,
):
self._metadata = cursor_metadata
self.chunks = chunks
self._source_supports_scalars = source_supports_scalars
self.raw = raw
self.iterator = itertools.chain.from_iterable(self.chunks(None))
self.dynamic_yield_per = dynamic_yield_per
@_generative
def yield_per(self, num: int) -> Self:
# TODO: this throws away the iterator which may be holding
# onto a chunk. the yield_per cannot be changed once any
# rows have been fetched. either find a way to enforce this,
# or we can't use itertools.chain and will instead have to
# keep track.
self._yield_per = num
self.iterator = itertools.chain.from_iterable(self.chunks(num))
return self
def _soft_close(self, hard: bool = False, **kw: Any) -> None:
super()._soft_close(hard=hard, **kw)
self.chunks = lambda size: [] # type: ignore
def _fetchmany_impl(
self, size: Optional[int] = None
) -> List[_InterimRowType[Row[Any]]]:
if self.dynamic_yield_per:
self.iterator = itertools.chain.from_iterable(self.chunks(size))
return super()._fetchmany_impl(size=size)
class MergedResult(IteratorResult[_TP]):
"""A :class:`_engine.Result` that is merged from any number of
:class:`_engine.Result` objects.
Returned by the :meth:`_engine.Result.merge` method.
.. versionadded:: 1.4
"""
closed = False
rowcount: Optional[int]
def __init__(
self, cursor_metadata: ResultMetaData, results: Sequence[Result[_TP]]
):
self._results = results
super().__init__(
cursor_metadata,
itertools.chain.from_iterable(
r._raw_row_iterator() for r in results
),
)
self._unique_filter_state = results[0]._unique_filter_state
self._yield_per = results[0]._yield_per
# going to try something w/ this in next rev
self._source_supports_scalars = results[0]._source_supports_scalars
self._attributes = self._attributes.merge_with(
*[r._attributes for r in results]
)
def _soft_close(self, hard: bool = False, **kw: Any) -> None:
for r in self._results:
r._soft_close(hard=hard, **kw)
if hard:
self.closed = True