venv

1 files changed, 2178 insertions, 0 deletions

diff --git a/venv/lib/python3.11/site-packages/sqlalchemy/engine/cursor.py b/venv/lib/python3.11/site-packages/sqlalchemy/engine/cursor.py
new file mode 100644
index 0000000..71767db
--- /dev/null
+++ b/venv/lib/python3.11/site-packages/sqlalchemy/engine/cursor.py
@@ -0,0 +1,2178 @@
+# engine/cursor.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
+# mypy: allow-untyped-defs, allow-untyped-calls
+
+"""Define cursor-specific result set constructs including
+:class:`.CursorResult`."""
+
+
+from __future__ import annotations
+
+import collections
+import functools
+import operator
+import typing
+from typing import Any
+from typing import cast
+from typing import ClassVar
+from typing import Dict
+from typing import Iterator
+from typing import List
+from typing import Mapping
+from typing import NoReturn
+from typing import Optional
+from typing import Sequence
+from typing import Tuple
+from typing import TYPE_CHECKING
+from typing import TypeVar
+from typing import Union
+
+from .result import IteratorResult
+from .result import MergedResult
+from .result import Result
+from .result import ResultMetaData
+from .result import SimpleResultMetaData
+from .result import tuplegetter
+from .row import Row
+from .. import exc
+from .. import util
+from ..sql import elements
+from ..sql import sqltypes
+from ..sql import util as sql_util
+from ..sql.base import _generative
+from ..sql.compiler import ResultColumnsEntry
+from ..sql.compiler import RM_NAME
+from ..sql.compiler import RM_OBJECTS
+from ..sql.compiler import RM_RENDERED_NAME
+from ..sql.compiler import RM_TYPE
+from ..sql.type_api import TypeEngine
+from ..util import compat
+from ..util.typing import Literal
+from ..util.typing import Self
+
+
+if typing.TYPE_CHECKING:
+    from .base import Connection
+    from .default import DefaultExecutionContext
+    from .interfaces import _DBAPICursorDescription
+    from .interfaces import DBAPICursor
+    from .interfaces import Dialect
+    from .interfaces import ExecutionContext
+    from .result import _KeyIndexType
+    from .result import _KeyMapRecType
+    from .result import _KeyMapType
+    from .result import _KeyType
+    from .result import _ProcessorsType
+    from .result import _TupleGetterType
+    from ..sql.type_api import _ResultProcessorType
+
+
+_T = TypeVar("_T", bound=Any)
+
+
+# metadata entry tuple indexes.
+# using raw tuple is faster than namedtuple.
+# these match up to the positions in
+# _CursorKeyMapRecType
+MD_INDEX: Literal[0] = 0
+"""integer index in cursor.description
+
+"""
+
+MD_RESULT_MAP_INDEX: Literal[1] = 1
+"""integer index in compiled._result_columns"""
+
+MD_OBJECTS: Literal[2] = 2
+"""other string keys and ColumnElement obj that can match.
+
+This comes from compiler.RM_OBJECTS / compiler.ResultColumnsEntry.objects
+
+"""
+
+MD_LOOKUP_KEY: Literal[3] = 3
+"""string key we usually expect for key-based lookup
+
+this comes from compiler.RM_NAME / compiler.ResultColumnsEntry.name
+"""
+
+
+MD_RENDERED_NAME: Literal[4] = 4
+"""name that is usually in cursor.description
+
+this comes from compiler.RENDERED_NAME / compiler.ResultColumnsEntry.keyname
+"""
+
+
+MD_PROCESSOR: Literal[5] = 5
+"""callable to process a result value into a row"""
+
+MD_UNTRANSLATED: Literal[6] = 6
+"""raw name from cursor.description"""
+
+
+_CursorKeyMapRecType = Tuple[
+    Optional[int],  # MD_INDEX, None means the record is ambiguously named
+    int,  # MD_RESULT_MAP_INDEX
+    List[Any],  # MD_OBJECTS
+    str,  # MD_LOOKUP_KEY
+    str,  # MD_RENDERED_NAME
+    Optional["_ResultProcessorType[Any]"],  # MD_PROCESSOR
+    Optional[str],  # MD_UNTRANSLATED
+]
+
+_CursorKeyMapType = Mapping["_KeyType", _CursorKeyMapRecType]
+
+# same as _CursorKeyMapRecType except the MD_INDEX value is definitely
+# not None
+_NonAmbigCursorKeyMapRecType = Tuple[
+    int,
+    int,
+    List[Any],
+    str,
+    str,
+    Optional["_ResultProcessorType[Any]"],
+    str,
+]
+
+
+class CursorResultMetaData(ResultMetaData):
+    """Result metadata for DBAPI cursors."""
+
+    __slots__ = (
+        "_keymap",
+        "_processors",
+        "_keys",
+        "_keymap_by_result_column_idx",
+        "_tuplefilter",
+        "_translated_indexes",
+        "_safe_for_cache",
+        "_unpickled",
+        "_key_to_index",
+        # don't need _unique_filters support here for now.  Can be added
+        # if a need arises.
+    )
+
+    _keymap: _CursorKeyMapType
+    _processors: _ProcessorsType
+    _keymap_by_result_column_idx: Optional[Dict[int, _KeyMapRecType]]
+    _unpickled: bool
+    _safe_for_cache: bool
+    _translated_indexes: Optional[List[int]]
+
+    returns_rows: ClassVar[bool] = True
+
+    def _has_key(self, key: Any) -> bool:
+        return key in self._keymap
+
+    def _for_freeze(self) -> ResultMetaData:
+        return SimpleResultMetaData(
+            self._keys,
+            extra=[self._keymap[key][MD_OBJECTS] for key in self._keys],
+        )
+
+    def _make_new_metadata(
+        self,
+        *,
+        unpickled: bool,
+        processors: _ProcessorsType,
+        keys: Sequence[str],
+        keymap: _KeyMapType,
+        tuplefilter: Optional[_TupleGetterType],
+        translated_indexes: Optional[List[int]],
+        safe_for_cache: bool,
+        keymap_by_result_column_idx: Any,
+    ) -> CursorResultMetaData:
+        new_obj = self.__class__.__new__(self.__class__)
+        new_obj._unpickled = unpickled
+        new_obj._processors = processors
+        new_obj._keys = keys
+        new_obj._keymap = keymap
+        new_obj._tuplefilter = tuplefilter
+        new_obj._translated_indexes = translated_indexes
+        new_obj._safe_for_cache = safe_for_cache
+        new_obj._keymap_by_result_column_idx = keymap_by_result_column_idx
+        new_obj._key_to_index = self._make_key_to_index(keymap, MD_INDEX)
+        return new_obj
+
+    def _remove_processors(self) -> CursorResultMetaData:
+        assert not self._tuplefilter
+        return self._make_new_metadata(
+            unpickled=self._unpickled,
+            processors=[None] * len(self._processors),
+            tuplefilter=None,
+            translated_indexes=None,
+            keymap={
+                key: value[0:5] + (None,) + value[6:]
+                for key, value in self._keymap.items()
+            },
+            keys=self._keys,
+            safe_for_cache=self._safe_for_cache,
+            keymap_by_result_column_idx=self._keymap_by_result_column_idx,
+        )
+
+    def _splice_horizontally(
+        self, other: CursorResultMetaData
+    ) -> CursorResultMetaData:
+        assert not self._tuplefilter
+
+        keymap = dict(self._keymap)
+        offset = len(self._keys)
+        keymap.update(
+            {
+                key: (
+                    # int index should be None for ambiguous key
+                    (
+                        value[0] + offset
+                        if value[0] is not None and key not in keymap
+                        else None
+                    ),
+                    value[1] + offset,
+                    *value[2:],
+                )
+                for key, value in other._keymap.items()
+            }
+        )
+        return self._make_new_metadata(
+            unpickled=self._unpickled,
+            processors=self._processors + other._processors,  # type: ignore
+            tuplefilter=None,
+            translated_indexes=None,
+            keys=self._keys + other._keys,  # type: ignore
+            keymap=keymap,
+            safe_for_cache=self._safe_for_cache,
+            keymap_by_result_column_idx={
+                metadata_entry[MD_RESULT_MAP_INDEX]: metadata_entry
+                for metadata_entry in keymap.values()
+            },
+        )
+
+    def _reduce(self, keys: Sequence[_KeyIndexType]) -> ResultMetaData:
+        recs = list(self._metadata_for_keys(keys))
+
+        indexes = [rec[MD_INDEX] for rec in recs]
+        new_keys: List[str] = [rec[MD_LOOKUP_KEY] for rec in recs]
+
+        if self._translated_indexes:
+            indexes = [self._translated_indexes[idx] for idx in indexes]
+        tup = tuplegetter(*indexes)
+        new_recs = [(index,) + rec[1:] for index, rec in enumerate(recs)]
+
+        keymap = {rec[MD_LOOKUP_KEY]: rec for rec in new_recs}
+        # TODO: need unit test for:
+        # result = connection.execute("raw sql, no columns").scalars()
+        # without the "or ()" it's failing because MD_OBJECTS is None
+        keymap.update(
+            (e, new_rec)
+            for new_rec in new_recs
+            for e in new_rec[MD_OBJECTS] or ()
+        )
+
+        return self._make_new_metadata(
+            unpickled=self._unpickled,
+            processors=self._processors,
+            keys=new_keys,
+            tuplefilter=tup,
+            translated_indexes=indexes,
+            keymap=keymap,  # type: ignore[arg-type]
+            safe_for_cache=self._safe_for_cache,
+            keymap_by_result_column_idx=self._keymap_by_result_column_idx,
+        )
+
+    def _adapt_to_context(self, context: ExecutionContext) -> ResultMetaData:
+        """When using a cached Compiled construct that has a _result_map,
+        for a new statement that used the cached Compiled, we need to ensure
+        the keymap has the Column objects from our new statement as keys.
+        So here we rewrite keymap with new entries for the new columns
+        as matched to those of the cached statement.
+
+        """
+
+        if not context.compiled or not context.compiled._result_columns:
+            return self
+
+        compiled_statement = context.compiled.statement
+        invoked_statement = context.invoked_statement
+
+        if TYPE_CHECKING:
+            assert isinstance(invoked_statement, elements.ClauseElement)
+
+        if compiled_statement is invoked_statement:
+            return self
+
+        assert invoked_statement is not None
+
+        # this is the most common path for Core statements when
+        # caching is used.  In ORM use, this codepath is not really used
+        # as the _result_disable_adapt_to_context execution option is
+        # set by the ORM.
+
+        # make a copy and add the columns from the invoked statement
+        # to the result map.
+
+        keymap_by_position = self._keymap_by_result_column_idx
+
+        if keymap_by_position is None:
+            # first retrival from cache, this map will not be set up yet,
+            # initialize lazily
+            keymap_by_position = self._keymap_by_result_column_idx = {
+                metadata_entry[MD_RESULT_MAP_INDEX]: metadata_entry
+                for metadata_entry in self._keymap.values()
+            }
+
+        assert not self._tuplefilter
+        return self._make_new_metadata(
+            keymap=compat.dict_union(
+                self._keymap,
+                {
+                    new: keymap_by_position[idx]
+                    for idx, new in enumerate(
+                        invoked_statement._all_selected_columns
+                    )
+                    if idx in keymap_by_position
+                },
+            ),
+            unpickled=self._unpickled,
+            processors=self._processors,
+            tuplefilter=None,
+            translated_indexes=None,
+            keys=self._keys,
+            safe_for_cache=self._safe_for_cache,
+            keymap_by_result_column_idx=self._keymap_by_result_column_idx,
+        )
+
+    def __init__(
+        self,
+        parent: CursorResult[Any],
+        cursor_description: _DBAPICursorDescription,
+    ):
+        context = parent.context
+        self._tuplefilter = None
+        self._translated_indexes = None
+        self._safe_for_cache = self._unpickled = False
+
+        if context.result_column_struct:
+            (
+                result_columns,
+                cols_are_ordered,
+                textual_ordered,
+                ad_hoc_textual,
+                loose_column_name_matching,
+            ) = context.result_column_struct
+            num_ctx_cols = len(result_columns)
+        else:
+            result_columns = cols_are_ordered = (  # type: ignore
+                num_ctx_cols
+            ) = ad_hoc_textual = loose_column_name_matching = (
+                textual_ordered
+            ) = False
+
+        # merge cursor.description with the column info
+        # present in the compiled structure, if any
+        raw = self._merge_cursor_description(
+            context,
+            cursor_description,
+            result_columns,
+            num_ctx_cols,
+            cols_are_ordered,
+            textual_ordered,
+            ad_hoc_textual,
+            loose_column_name_matching,
+        )
+
+        # processors in key order which are used when building up
+        # a row
+        self._processors = [
+            metadata_entry[MD_PROCESSOR] for metadata_entry in raw
+        ]
+
+        # this is used when using this ResultMetaData in a Core-only cache
+        # retrieval context.  it's initialized on first cache retrieval
+        # when the _result_disable_adapt_to_context execution option
+        # (which the ORM generally sets) is not set.
+        self._keymap_by_result_column_idx = None
+
+        # for compiled SQL constructs, copy additional lookup keys into
+        # the key lookup map, such as Column objects, labels,
+        # column keys and other names
+        if num_ctx_cols:
+            # keymap by primary string...
+            by_key = {
+                metadata_entry[MD_LOOKUP_KEY]: metadata_entry
+                for metadata_entry in raw
+            }
+
+            if len(by_key) != num_ctx_cols:
+                # if by-primary-string dictionary smaller than
+                # number of columns, assume we have dupes; (this check
+                # is also in place if string dictionary is bigger, as
+                # can occur when '*' was used as one of the compiled columns,
+                # which may or may not be suggestive of dupes), rewrite
+                # dupe records with "None" for index which results in
+                # ambiguous column exception when accessed.
+                #
+                # this is considered to be the less common case as it is not
+                # common to have dupe column keys in a SELECT statement.
+                #
+                # new in 1.4: get the complete set of all possible keys,
+                # strings, objects, whatever, that are dupes across two
+                # different records, first.
+                index_by_key: Dict[Any, Any] = {}
+                dupes = set()
+                for metadata_entry in raw:
+                    for key in (metadata_entry[MD_RENDERED_NAME],) + (
+                        metadata_entry[MD_OBJECTS] or ()
+                    ):
+                        idx = metadata_entry[MD_INDEX]
+                        # if this key has been associated with more than one
+                        # positional index, it's a dupe
+                        if index_by_key.setdefault(key, idx) != idx:
+                            dupes.add(key)
+
+                # then put everything we have into the keymap excluding only
+                # those keys that are dupes.
+                self._keymap = {
+                    obj_elem: metadata_entry
+                    for metadata_entry in raw
+                    if metadata_entry[MD_OBJECTS]
+                    for obj_elem in metadata_entry[MD_OBJECTS]
+                    if obj_elem not in dupes
+                }
+
+                # then for the dupe keys, put the "ambiguous column"
+                # record into by_key.
+                by_key.update(
+                    {
+                        key: (None, None, [], key, key, None, None)
+                        for key in dupes
+                    }
+                )
+
+            else:
+                # no dupes - copy secondary elements from compiled
+                # columns into self._keymap.  this is the most common
+                # codepath for Core / ORM statement executions before the
+                # result metadata is cached
+                self._keymap = {
+                    obj_elem: metadata_entry
+                    for metadata_entry in raw
+                    if metadata_entry[MD_OBJECTS]
+                    for obj_elem in metadata_entry[MD_OBJECTS]
+                }
+            # update keymap with primary string names taking
+            # precedence
+            self._keymap.update(by_key)
+        else:
+            # no compiled objects to map, just create keymap by primary string
+            self._keymap = {
+                metadata_entry[MD_LOOKUP_KEY]: metadata_entry
+                for metadata_entry in raw
+            }
+
+        # update keymap with "translated" names.  In SQLAlchemy this is a
+        # sqlite only thing, and in fact impacting only extremely old SQLite
+        # versions unlikely to be present in modern Python versions.
+        # however, the pyhive third party dialect is
+        # also using this hook, which means others still might use it as well.
+        # I dislike having this awkward hook here but as long as we need
+        # to use names in cursor.description in some cases we need to have
+        # some hook to accomplish this.
+        if not num_ctx_cols and context._translate_colname:
+            self._keymap.update(
+                {
+                    metadata_entry[MD_UNTRANSLATED]: self._keymap[
+                        metadata_entry[MD_LOOKUP_KEY]
+                    ]
+                    for metadata_entry in raw
+                    if metadata_entry[MD_UNTRANSLATED]
+                }
+            )
+
+        self._key_to_index = self._make_key_to_index(self._keymap, MD_INDEX)
+
+    def _merge_cursor_description(
+        self,
+        context,
+        cursor_description,
+        result_columns,
+        num_ctx_cols,
+        cols_are_ordered,
+        textual_ordered,
+        ad_hoc_textual,
+        loose_column_name_matching,
+    ):
+        """Merge a cursor.description with compiled result column information.
+
+        There are at least four separate strategies used here, selected
+        depending on the type of SQL construct used to start with.
+
+        The most common case is that of the compiled SQL expression construct,
+        which generated the column names present in the raw SQL string and
+        which has the identical number of columns as were reported by
+        cursor.description.  In this case, we assume a 1-1 positional mapping
+        between the entries in cursor.description and the compiled object.
+        This is also the most performant case as we disregard extracting /
+        decoding the column names present in cursor.description since we
+        already have the desired name we generated in the compiled SQL
+        construct.
+
+        The next common case is that of the completely raw string SQL,
+        such as passed to connection.execute().  In this case we have no
+        compiled construct to work with, so we extract and decode the
+        names from cursor.description and index those as the primary
+        result row target keys.
+
+        The remaining fairly common case is that of the textual SQL
+        that includes at least partial column information; this is when
+        we use a :class:`_expression.TextualSelect` construct.
+        This construct may have
+        unordered or ordered column information.  In the ordered case, we
+        merge the cursor.description and the compiled construct's information
+        positionally, and warn if there are additional description names
+        present, however we still decode the names in cursor.description
+        as we don't have a guarantee that the names in the columns match
+        on these.   In the unordered case, we match names in cursor.description
+        to that of the compiled construct based on name matching.
+        In both of these cases, the cursor.description names and the column
+        expression objects and names are indexed as result row target keys.
+
+        The final case is much less common, where we have a compiled
+        non-textual SQL expression construct, but the number of columns
+        in cursor.description doesn't match what's in the compiled
+        construct.  We make the guess here that there might be textual
+        column expressions in the compiled construct that themselves include
+        a comma in them causing them to split.  We do the same name-matching
+        as with textual non-ordered columns.
+
+        The name-matched system of merging is the same as that used by
+        SQLAlchemy for all cases up through the 0.9 series.   Positional
+        matching for compiled SQL expressions was introduced in 1.0 as a
+        major performance feature, and positional matching for textual
+        :class:`_expression.TextualSelect` objects in 1.1.
+        As name matching is no longer
+        a common case, it was acceptable to factor it into smaller generator-
+        oriented methods that are easier to understand, but incur slightly
+        more performance overhead.
+
+        """
+
+        if (
+            num_ctx_cols
+            and cols_are_ordered
+            and not textual_ordered
+            and num_ctx_cols == len(cursor_description)
+        ):
+            self._keys = [elem[0] for elem in result_columns]
+            # pure positional 1-1 case; doesn't need to read
+            # the names from cursor.description
+
+            # most common case for Core and ORM
+
+            # this metadata is safe to cache because we are guaranteed
+            # to have the columns in the same order for new executions
+            self._safe_for_cache = True
+            return [
+                (
+                    idx,
+                    idx,
+                    rmap_entry[RM_OBJECTS],
+                    rmap_entry[RM_NAME],
+                    rmap_entry[RM_RENDERED_NAME],
+                    context.get_result_processor(
+                        rmap_entry[RM_TYPE],
+                        rmap_entry[RM_RENDERED_NAME],
+                        cursor_description[idx][1],
+                    ),
+                    None,
+                )
+                for idx, rmap_entry in enumerate(result_columns)
+            ]
+        else:
+            # name-based or text-positional cases, where we need
+            # to read cursor.description names
+
+            if textual_ordered or (
+                ad_hoc_textual and len(cursor_description) == num_ctx_cols
+            ):
+                self._safe_for_cache = True
+                # textual positional case
+                raw_iterator = self._merge_textual_cols_by_position(
+                    context, cursor_description, result_columns
+                )
+            elif num_ctx_cols:
+                # compiled SQL with a mismatch of description cols
+                # vs. compiled cols, or textual w/ unordered columns
+                # the order of columns can change if the query is
+                # against a "select *", so not safe to cache
+                self._safe_for_cache = False
+                raw_iterator = self._merge_cols_by_name(
+                    context,
+                    cursor_description,
+                    result_columns,
+                    loose_column_name_matching,
+                )
+            else:
+                # no compiled SQL, just a raw string, order of columns
+                # can change for "select *"
+                self._safe_for_cache = False
+                raw_iterator = self._merge_cols_by_none(
+                    context, cursor_description
+                )
+
+            return [
+                (
+                    idx,
+                    ridx,
+                    obj,
+                    cursor_colname,
+                    cursor_colname,
+                    context.get_result_processor(
+                        mapped_type, cursor_colname, coltype
+                    ),
+                    untranslated,
+                )
+                for (
+                    idx,
+                    ridx,
+                    cursor_colname,
+                    mapped_type,
+                    coltype,
+                    obj,
+                    untranslated,
+                ) in raw_iterator
+            ]
+
+    def _colnames_from_description(self, context, cursor_description):
+        """Extract column names and data types from a cursor.description.
+
+        Applies unicode decoding, column translation, "normalization",
+        and case sensitivity rules to the names based on the dialect.
+
+        """
+
+        dialect = context.dialect
+        translate_colname = context._translate_colname
+        normalize_name = (
+            dialect.normalize_name if dialect.requires_name_normalize else None
+        )
+        untranslated = None
+
+        self._keys = []
+
+        for idx, rec in enumerate(cursor_description):
+            colname = rec[0]
+            coltype = rec[1]
+
+            if translate_colname:
+                colname, untranslated = translate_colname(colname)
+
+            if normalize_name:
+                colname = normalize_name(colname)
+
+            self._keys.append(colname)
+
+            yield idx, colname, untranslated, coltype
+
+    def _merge_textual_cols_by_position(
+        self, context, cursor_description, result_columns
+    ):
+        num_ctx_cols = len(result_columns)
+
+        if num_ctx_cols > len(cursor_description):
+            util.warn(
+                "Number of columns in textual SQL (%d) is "
+                "smaller than number of columns requested (%d)"
+                % (num_ctx_cols, len(cursor_description))
+            )
+        seen = set()
+        for (
+            idx,
+            colname,
+            untranslated,
+            coltype,
+        ) in self._colnames_from_description(context, cursor_description):
+            if idx < num_ctx_cols:
+                ctx_rec = result_columns[idx]
+                obj = ctx_rec[RM_OBJECTS]
+                ridx = idx
+                mapped_type = ctx_rec[RM_TYPE]
+                if obj[0] in seen:
+                    raise exc.InvalidRequestError(
+                        "Duplicate column expression requested "
+                        "in textual SQL: %r" % obj[0]
+                    )
+                seen.add(obj[0])
+            else:
+                mapped_type = sqltypes.NULLTYPE
+                obj = None
+                ridx = None
+            yield idx, ridx, colname, mapped_type, coltype, obj, untranslated
+
+    def _merge_cols_by_name(
+        self,
+        context,
+        cursor_description,
+        result_columns,
+        loose_column_name_matching,
+    ):
+        match_map = self._create_description_match_map(
+            result_columns, loose_column_name_matching
+        )
+        mapped_type: TypeEngine[Any]
+
+        for (
+            idx,
+            colname,
+            untranslated,
+            coltype,
+        ) in self._colnames_from_description(context, cursor_description):
+            try:
+                ctx_rec = match_map[colname]
+            except KeyError:
+                mapped_type = sqltypes.NULLTYPE
+                obj = None
+                result_columns_idx = None
+            else:
+                obj = ctx_rec[1]
+                mapped_type = ctx_rec[2]
+                result_columns_idx = ctx_rec[3]
+            yield (
+                idx,
+                result_columns_idx,
+                colname,
+                mapped_type,
+                coltype,
+                obj,
+                untranslated,
+            )
+
+    @classmethod
+    def _create_description_match_map(
+        cls,
+        result_columns: List[ResultColumnsEntry],
+        loose_column_name_matching: bool = False,
+    ) -> Dict[
+        Union[str, object], Tuple[str, Tuple[Any, ...], TypeEngine[Any], int]
+    ]:
+        """when matching cursor.description to a set of names that are present
+        in a Compiled object, as is the case with TextualSelect, get all the
+        names we expect might match those in cursor.description.
+        """
+
+        d: Dict[
+            Union[str, object],
+            Tuple[str, Tuple[Any, ...], TypeEngine[Any], int],
+        ] = {}
+        for ridx, elem in enumerate(result_columns):
+            key = elem[RM_RENDERED_NAME]
+            if key in d:
+                # conflicting keyname - just add the column-linked objects
+                # to the existing record.  if there is a duplicate column
+                # name in the cursor description, this will allow all of those
+                # objects to raise an ambiguous column error
+                e_name, e_obj, e_type, e_ridx = d[key]
+                d[key] = e_name, e_obj + elem[RM_OBJECTS], e_type, ridx
+            else:
+                d[key] = (elem[RM_NAME], elem[RM_OBJECTS], elem[RM_TYPE], ridx)
+
+            if loose_column_name_matching:
+                # when using a textual statement with an unordered set
+                # of columns that line up, we are expecting the user
+                # to be using label names in the SQL that match to the column
+                # expressions.  Enable more liberal matching for this case;
+                # duplicate keys that are ambiguous will be fixed later.
+                for r_key in elem[RM_OBJECTS]:
+                    d.setdefault(
+                        r_key,
+                        (elem[RM_NAME], elem[RM_OBJECTS], elem[RM_TYPE], ridx),
+                    )
+        return d
+
+    def _merge_cols_by_none(self, context, cursor_description):
+        for (
+            idx,
+            colname,
+            untranslated,
+            coltype,
+        ) in self._colnames_from_description(context, cursor_description):
+            yield (
+                idx,
+                None,
+                colname,
+                sqltypes.NULLTYPE,
+                coltype,
+                None,
+                untranslated,
+            )
+
+    if not TYPE_CHECKING:
+
+        def _key_fallback(
+            self, key: Any, err: Optional[Exception], raiseerr: bool = True
+        ) -> Optional[NoReturn]:
+            if raiseerr:
+                if self._unpickled and isinstance(key, elements.ColumnElement):
+                    raise exc.NoSuchColumnError(
+                        "Row was unpickled; lookup by ColumnElement "
+                        "is unsupported"
+                    ) from err
+                else:
+                    raise exc.NoSuchColumnError(
+                        "Could not locate column in row for column '%s'"
+                        % util.string_or_unprintable(key)
+                    ) from err
+            else:
+                return None
+
+    def _raise_for_ambiguous_column_name(self, rec):
+        raise exc.InvalidRequestError(
+            "Ambiguous column name '%s' in "
+            "result set column descriptions" % rec[MD_LOOKUP_KEY]
+        )
+
+    def _index_for_key(self, key: Any, raiseerr: bool = True) -> Optional[int]:
+        # TODO: can consider pre-loading ints and negative ints
+        # into _keymap - also no coverage here
+        if isinstance(key, int):
+            key = self._keys[key]
+
+        try:
+            rec = self._keymap[key]
+        except KeyError as ke:
+            x = self._key_fallback(key, ke, raiseerr)
+            assert x is None
+            return None
+
+        index = rec[0]
+
+        if index is None:
+            self._raise_for_ambiguous_column_name(rec)
+        return index
+
+    def _indexes_for_keys(self, keys):
+        try:
+            return [self._keymap[key][0] for key in keys]
+        except KeyError as ke:
+            # ensure it raises
+            CursorResultMetaData._key_fallback(self, ke.args[0], ke)
+
+    def _metadata_for_keys(
+        self, keys: Sequence[Any]
+    ) -> Iterator[_NonAmbigCursorKeyMapRecType]:
+        for key in keys:
+            if int in key.__class__.__mro__:
+                key = self._keys[key]
+
+            try:
+                rec = self._keymap[key]
+            except KeyError as ke:
+                # ensure it raises
+                CursorResultMetaData._key_fallback(self, ke.args[0], ke)
+
+            index = rec[MD_INDEX]
+
+            if index is None:
+                self._raise_for_ambiguous_column_name(rec)
+
+            yield cast(_NonAmbigCursorKeyMapRecType, rec)
+
+    def __getstate__(self):
+        # TODO: consider serializing this as SimpleResultMetaData
+        return {
+            "_keymap": {
+                key: (
+                    rec[MD_INDEX],
+                    rec[MD_RESULT_MAP_INDEX],
+                    [],
+                    key,
+                    rec[MD_RENDERED_NAME],
+                    None,
+                    None,
+                )
+                for key, rec in self._keymap.items()
+                if isinstance(key, (str, int))
+            },
+            "_keys": self._keys,
+            "_translated_indexes": self._translated_indexes,
+        }
+
+    def __setstate__(self, state):
+        self._processors = [None for _ in range(len(state["_keys"]))]
+        self._keymap = state["_keymap"]
+        self._keymap_by_result_column_idx = None
+        self._key_to_index = self._make_key_to_index(self._keymap, MD_INDEX)
+        self._keys = state["_keys"]
+        self._unpickled = True
+        if state["_translated_indexes"]:
+            self._translated_indexes = cast(
+                "List[int]", state["_translated_indexes"]
+            )
+            self._tuplefilter = tuplegetter(*self._translated_indexes)
+        else:
+            self._translated_indexes = self._tuplefilter = None
+
+
+class ResultFetchStrategy:
+    """Define a fetching strategy for a result object.
+
+
+    .. versionadded:: 1.4
+
+    """
+
+    __slots__ = ()
+
+    alternate_cursor_description: Optional[_DBAPICursorDescription] = None
+
+    def soft_close(
+        self, result: CursorResult[Any], dbapi_cursor: Optional[DBAPICursor]
+    ) -> None:
+        raise NotImplementedError()
+
+    def hard_close(
+        self, result: CursorResult[Any], dbapi_cursor: Optional[DBAPICursor]
+    ) -> None:
+        raise NotImplementedError()
+
+    def yield_per(
+        self,
+        result: CursorResult[Any],
+        dbapi_cursor: Optional[DBAPICursor],
+        num: int,
+    ) -> None:
+        return
+
+    def fetchone(
+        self,
+        result: CursorResult[Any],
+        dbapi_cursor: DBAPICursor,
+        hard_close: bool = False,
+    ) -> Any:
+        raise NotImplementedError()
+
+    def fetchmany(
+        self,
+        result: CursorResult[Any],
+        dbapi_cursor: DBAPICursor,
+        size: Optional[int] = None,
+    ) -> Any:
+        raise NotImplementedError()
+
+    def fetchall(
+        self,
+        result: CursorResult[Any],
+        dbapi_cursor: DBAPICursor,
+    ) -> Any:
+        raise NotImplementedError()
+
+    def handle_exception(
+        self,
+        result: CursorResult[Any],
+        dbapi_cursor: Optional[DBAPICursor],
+        err: BaseException,
+    ) -> NoReturn:
+        raise err
+
+
+class NoCursorFetchStrategy(ResultFetchStrategy):
+    """Cursor strategy for a result that has no open cursor.
+
+    There are two varieties of this strategy, one for DQL and one for
+    DML (and also DDL), each of which represent a result that had a cursor
+    but no longer has one.
+
+    """
+
+    __slots__ = ()
+
+    def soft_close(self, result, dbapi_cursor):
+        pass
+
+    def hard_close(self, result, dbapi_cursor):
+        pass
+
+    def fetchone(self, result, dbapi_cursor, hard_close=False):
+        return self._non_result(result, None)
+
+    def fetchmany(self, result, dbapi_cursor, size=None):
+        return self._non_result(result, [])
+
+    def fetchall(self, result, dbapi_cursor):
+        return self._non_result(result, [])
+
+    def _non_result(self, result, default, err=None):
+        raise NotImplementedError()
+
+
+class NoCursorDQLFetchStrategy(NoCursorFetchStrategy):
+    """Cursor strategy for a DQL result that has no open cursor.
+
+    This is a result set that can return rows, i.e. for a SELECT, or for an
+    INSERT, UPDATE, DELETE that includes RETURNING. However it is in the state
+    where the cursor is closed and no rows remain available.  The owning result
+    object may or may not be "hard closed", which determines if the fetch
+    methods send empty results or raise for closed result.
+
+    """
+
+    __slots__ = ()
+
+    def _non_result(self, result, default, err=None):
+        if result.closed:
+            raise exc.ResourceClosedError(
+                "This result object is closed."
+            ) from err
+        else:
+            return default
+
+
+_NO_CURSOR_DQL = NoCursorDQLFetchStrategy()
+
+
+class NoCursorDMLFetchStrategy(NoCursorFetchStrategy):
+    """Cursor strategy for a DML result that has no open cursor.
+
+    This is a result set that does not return rows, i.e. for an INSERT,
+    UPDATE, DELETE that does not include RETURNING.
+
+    """
+
+    __slots__ = ()
+
+    def _non_result(self, result, default, err=None):
+        # we only expect to have a _NoResultMetaData() here right now.
+        assert not result._metadata.returns_rows
+        result._metadata._we_dont_return_rows(err)
+
+
+_NO_CURSOR_DML = NoCursorDMLFetchStrategy()
+
+
+class CursorFetchStrategy(ResultFetchStrategy):
+    """Call fetch methods from a DBAPI cursor.
+
+    Alternate versions of this class may instead buffer the rows from
+    cursors or not use cursors at all.
+
+    """
+
+    __slots__ = ()
+
+    def soft_close(
+        self, result: CursorResult[Any], dbapi_cursor: Optional[DBAPICursor]
+    ) -> None:
+        result.cursor_strategy = _NO_CURSOR_DQL
+
+    def hard_close(
+        self, result: CursorResult[Any], dbapi_cursor: Optional[DBAPICursor]
+    ) -> None:
+        result.cursor_strategy = _NO_CURSOR_DQL
+
+    def handle_exception(
+        self,
+        result: CursorResult[Any],
+        dbapi_cursor: Optional[DBAPICursor],
+        err: BaseException,
+    ) -> NoReturn:
+        result.connection._handle_dbapi_exception(
+            err, None, None, dbapi_cursor, result.context
+        )
+
+    def yield_per(
+        self,
+        result: CursorResult[Any],
+        dbapi_cursor: Optional[DBAPICursor],
+        num: int,
+    ) -> None:
+        result.cursor_strategy = BufferedRowCursorFetchStrategy(
+            dbapi_cursor,
+            {"max_row_buffer": num},
+            initial_buffer=collections.deque(),
+            growth_factor=0,
+        )
+
+    def fetchone(
+        self,
+        result: CursorResult[Any],
+        dbapi_cursor: DBAPICursor,
+        hard_close: bool = False,
+    ) -> Any:
+        try:
+            row = dbapi_cursor.fetchone()
+            if row is None:
+                result._soft_close(hard=hard_close)
+            return row
+        except BaseException as e:
+            self.handle_exception(result, dbapi_cursor, e)
+
+    def fetchmany(
+        self,
+        result: CursorResult[Any],
+        dbapi_cursor: DBAPICursor,
+        size: Optional[int] = None,
+    ) -> Any:
+        try:
+            if size is None:
+                l = dbapi_cursor.fetchmany()
+            else:
+                l = dbapi_cursor.fetchmany(size)
+
+            if not l:
+                result._soft_close()
+            return l
+        except BaseException as e:
+            self.handle_exception(result, dbapi_cursor, e)
+
+    def fetchall(
+        self,
+        result: CursorResult[Any],
+        dbapi_cursor: DBAPICursor,
+    ) -> Any:
+        try:
+            rows = dbapi_cursor.fetchall()
+            result._soft_close()
+            return rows
+        except BaseException as e:
+            self.handle_exception(result, dbapi_cursor, e)
+
+
+_DEFAULT_FETCH = CursorFetchStrategy()
+
+
+class BufferedRowCursorFetchStrategy(CursorFetchStrategy):
+    """A cursor fetch strategy with row buffering behavior.
+
+    This strategy buffers the contents of a selection of rows
+    before ``fetchone()`` is called.  This is to allow the results of
+    ``cursor.description`` to be available immediately, when
+    interfacing with a DB-API that requires rows to be consumed before
+    this information is available (currently psycopg2, when used with
+    server-side cursors).
+
+    The pre-fetching behavior fetches only one row initially, and then
+    grows its buffer size by a fixed amount with each successive need
+    for additional rows up the ``max_row_buffer`` size, which defaults
+    to 1000::
+
+        with psycopg2_engine.connect() as conn:
+
+            result = conn.execution_options(
+                stream_results=True, max_row_buffer=50
+                ).execute(text("select * from table"))
+
+    .. versionadded:: 1.4 ``max_row_buffer`` may now exceed 1000 rows.
+
+    .. seealso::
+
+        :ref:`psycopg2_execution_options`
+    """
+
+    __slots__ = ("_max_row_buffer", "_rowbuffer", "_bufsize", "_growth_factor")
+
+    def __init__(
+        self,
+        dbapi_cursor,
+        execution_options,
+        growth_factor=5,
+        initial_buffer=None,
+    ):
+        self._max_row_buffer = execution_options.get("max_row_buffer", 1000)
+
+        if initial_buffer is not None:
+            self._rowbuffer = initial_buffer
+        else:
+            self._rowbuffer = collections.deque(dbapi_cursor.fetchmany(1))
+        self._growth_factor = growth_factor
+
+        if growth_factor:
+            self._bufsize = min(self._max_row_buffer, self._growth_factor)
+        else:
+            self._bufsize = self._max_row_buffer
+
+    @classmethod
+    def create(cls, result):
+        return BufferedRowCursorFetchStrategy(
+            result.cursor,
+            result.context.execution_options,
+        )
+
+    def _buffer_rows(self, result, dbapi_cursor):
+        """this is currently used only by fetchone()."""
+
+        size = self._bufsize
+        try:
+            if size < 1:
+                new_rows = dbapi_cursor.fetchall()
+            else:
+                new_rows = dbapi_cursor.fetchmany(size)
+        except BaseException as e:
+            self.handle_exception(result, dbapi_cursor, e)
+
+        if not new_rows:
+            return
+        self._rowbuffer = collections.deque(new_rows)
+        if self._growth_factor and size < self._max_row_buffer:
+            self._bufsize = min(
+                self._max_row_buffer, size * self._growth_factor
+            )
+
+    def yield_per(self, result, dbapi_cursor, num):
+        self._growth_factor = 0
+        self._max_row_buffer = self._bufsize = num
+
+    def soft_close(self, result, dbapi_cursor):
+        self._rowbuffer.clear()
+        super().soft_close(result, dbapi_cursor)
+
+    def hard_close(self, result, dbapi_cursor):
+        self._rowbuffer.clear()
+        super().hard_close(result, dbapi_cursor)
+
+    def fetchone(self, result, dbapi_cursor, hard_close=False):
+        if not self._rowbuffer:
+            self._buffer_rows(result, dbapi_cursor)
+            if not self._rowbuffer:
+                try:
+                    result._soft_close(hard=hard_close)
+                except BaseException as e:
+                    self.handle_exception(result, dbapi_cursor, e)
+                return None
+        return self._rowbuffer.popleft()
+
+    def fetchmany(self, result, dbapi_cursor, size=None):
+        if size is None:
+            return self.fetchall(result, dbapi_cursor)
+
+        buf = list(self._rowbuffer)
+        lb = len(buf)
+        if size > lb:
+            try:
+                new = dbapi_cursor.fetchmany(size - lb)
+            except BaseException as e:
+                self.handle_exception(result, dbapi_cursor, e)
+            else:
+                if not new:
+                    result._soft_close()
+                else:
+                    buf.extend(new)
+
+        result = buf[0:size]
+        self._rowbuffer = collections.deque(buf[size:])
+        return result
+
+    def fetchall(self, result, dbapi_cursor):
+        try:
+            ret = list(self._rowbuffer) + list(dbapi_cursor.fetchall())
+            self._rowbuffer.clear()
+            result._soft_close()
+            return ret
+        except BaseException as e:
+            self.handle_exception(result, dbapi_cursor, e)
+
+
+class FullyBufferedCursorFetchStrategy(CursorFetchStrategy):
+    """A cursor strategy that buffers rows fully upon creation.
+
+    Used for operations where a result is to be delivered
+    after the database conversation can not be continued,
+    such as MSSQL INSERT...OUTPUT after an autocommit.
+
+    """
+
+    __slots__ = ("_rowbuffer", "alternate_cursor_description")
+
+    def __init__(
+        self, dbapi_cursor, alternate_description=None, initial_buffer=None
+    ):
+        self.alternate_cursor_description = alternate_description
+        if initial_buffer is not None:
+            self._rowbuffer = collections.deque(initial_buffer)
+        else:
+            self._rowbuffer = collections.deque(dbapi_cursor.fetchall())
+
+    def yield_per(self, result, dbapi_cursor, num):
+        pass
+
+    def soft_close(self, result, dbapi_cursor):
+        self._rowbuffer.clear()
+        super().soft_close(result, dbapi_cursor)
+
+    def hard_close(self, result, dbapi_cursor):
+        self._rowbuffer.clear()
+        super().hard_close(result, dbapi_cursor)
+
+    def fetchone(self, result, dbapi_cursor, hard_close=False):
+        if self._rowbuffer:
+            return self._rowbuffer.popleft()
+        else:
+            result._soft_close(hard=hard_close)
+            return None
+
+    def fetchmany(self, result, dbapi_cursor, size=None):
+        if size is None:
+            return self.fetchall(result, dbapi_cursor)
+
+        buf = list(self._rowbuffer)
+        rows = buf[0:size]
+        self._rowbuffer = collections.deque(buf[size:])
+        if not rows:
+            result._soft_close()
+        return rows
+
+    def fetchall(self, result, dbapi_cursor):
+        ret = self._rowbuffer
+        self._rowbuffer = collections.deque()
+        result._soft_close()
+        return ret
+
+
+class _NoResultMetaData(ResultMetaData):
+    __slots__ = ()
+
+    returns_rows = False
+
+    def _we_dont_return_rows(self, err=None):
+        raise exc.ResourceClosedError(
+            "This result object does not return rows. "
+            "It has been closed automatically."
+        ) from err
+
+    def _index_for_key(self, keys, raiseerr):
+        self._we_dont_return_rows()
+
+    def _metadata_for_keys(self, key):
+        self._we_dont_return_rows()
+
+    def _reduce(self, keys):
+        self._we_dont_return_rows()
+
+    @property
+    def _keymap(self):
+        self._we_dont_return_rows()
+
+    @property
+    def _key_to_index(self):
+        self._we_dont_return_rows()
+
+    @property
+    def _processors(self):
+        self._we_dont_return_rows()
+
+    @property
+    def keys(self):
+        self._we_dont_return_rows()
+
+
+_NO_RESULT_METADATA = _NoResultMetaData()
+
+
+def null_dml_result() -> IteratorResult[Any]:
+    it: IteratorResult[Any] = IteratorResult(_NoResultMetaData(), iter([]))
+    it._soft_close()
+    return it
+
+
+class CursorResult(Result[_T]):
+    """A Result that is representing state from a DBAPI cursor.
+
+    .. versionchanged:: 1.4  The :class:`.CursorResult``
+       class replaces the previous :class:`.ResultProxy` interface.
+       This classes are based on the :class:`.Result` calling API
+       which provides an updated usage model and calling facade for
+       SQLAlchemy Core and SQLAlchemy ORM.
+
+    Returns database rows via the :class:`.Row` class, which provides
+    additional API features and behaviors on top of the raw data returned by
+    the DBAPI.   Through the use of filters such as the :meth:`.Result.scalars`
+    method, other kinds of objects may also be returned.
+
+    .. seealso::
+
+        :ref:`tutorial_selecting_data` - introductory material for accessing
+        :class:`_engine.CursorResult` and :class:`.Row` objects.
+
+    """
+
+    __slots__ = (
+        "context",
+        "dialect",
+        "cursor",
+        "cursor_strategy",
+        "_echo",
+        "connection",
+    )
+
+    _metadata: Union[CursorResultMetaData, _NoResultMetaData]
+    _no_result_metadata = _NO_RESULT_METADATA
+    _soft_closed: bool = False
+    closed: bool = False
+    _is_cursor = True
+
+    context: DefaultExecutionContext
+    dialect: Dialect
+    cursor_strategy: ResultFetchStrategy
+    connection: Connection
+
+    def __init__(
+        self,
+        context: DefaultExecutionContext,
+        cursor_strategy: ResultFetchStrategy,
+        cursor_description: Optional[_DBAPICursorDescription],
+    ):
+        self.context = context
+        self.dialect = context.dialect
+        self.cursor = context.cursor
+        self.cursor_strategy = cursor_strategy
+        self.connection = context.root_connection
+        self._echo = echo = (
+            self.connection._echo and context.engine._should_log_debug()
+        )
+
+        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
+            _make_row = functools.partial(
+                Row,
+                metadata,
+                metadata._effective_processors,
+                metadata._key_to_index,
+            )
+
+            if context._num_sentinel_cols:
+                sentinel_filter = operator.itemgetter(
+                    slice(-context._num_sentinel_cols)
+                )
+
+                def _sliced_row(raw_data):
+                    return _make_row(sentinel_filter(raw_data))
+
+                sliced_row = _sliced_row
+            else:
+                sliced_row = _make_row
+
+            if echo:
+                log = self.context.connection._log_debug
+
+                def _log_row(row):
+                    log("Row %r", sql_util._repr_row(row))
+                    return row
+
+                self._row_logging_fn = _log_row
+
+                def _make_row_2(row):
+                    return _log_row(sliced_row(row))
+
+                make_row = _make_row_2
+            else:
+                make_row = sliced_row
+            self._set_memoized_attribute("_row_getter", make_row)
+
+        else:
+            assert context._num_sentinel_cols == 0
+            self._metadata = self._no_result_metadata
+
+    def _init_metadata(self, context, cursor_description):
+        if context.compiled:
+            compiled = context.compiled
+
+            if compiled._cached_metadata:
+                metadata = compiled._cached_metadata
+            else:
+                metadata = CursorResultMetaData(self, cursor_description)
+                if metadata._safe_for_cache:
+                    compiled._cached_metadata = metadata
+
+            # result rewrite/ adapt step.  this is to suit the case
+            # when we are invoked against a cached Compiled object, we want
+            # to rewrite the ResultMetaData to reflect the Column objects
+            # that are in our current SQL statement object, not the one
+            # that is associated with the cached Compiled object.
+            # the Compiled object may also tell us to not
+            # actually do this step; this is to support the ORM where
+            # it is to produce a new Result object in any case, and will
+            # be using the cached Column objects against this database result
+            # so we don't want to rewrite them.
+            #
+            # Basically this step suits the use case where the end user
+            # is using Core SQL expressions and is accessing columns in the
+            # result row using row._mapping[table.c.column].
+            if (
+                not context.execution_options.get(
+                    "_result_disable_adapt_to_context", False
+                )
+                and compiled._result_columns
+                and context.cache_hit is context.dialect.CACHE_HIT
+                and compiled.statement is not context.invoked_statement
+            ):
+                metadata = metadata._adapt_to_context(context)
+
+            self._metadata = metadata
+
+        else:
+            self._metadata = metadata = CursorResultMetaData(
+                self, cursor_description
+            )
+        if self._echo:
+            context.connection._log_debug(
+                "Col %r", tuple(x[0] for x in cursor_description)
+            )
+        return metadata
+
+    def _soft_close(self, hard=False):
+        """Soft close this :class:`_engine.CursorResult`.
+
+        This releases all DBAPI cursor resources, but leaves the
+        CursorResult "open" from a semantic perspective, meaning the
+        fetchXXX() methods will continue to return empty results.
+
+        This method is called automatically when:
+
+        * all result rows are exhausted using the fetchXXX() methods.
+        * cursor.description is None.
+
+        This method is **not public**, but is documented in order to clarify
+        the "autoclose" process used.
+
+        .. seealso::
+
+            :meth:`_engine.CursorResult.close`
+
+
+        """
+
+        if (not hard and self._soft_closed) or (hard and self.closed):
+            return
+
+        if hard:
+            self.closed = True
+            self.cursor_strategy.hard_close(self, self.cursor)
+        else:
+            self.cursor_strategy.soft_close(self, self.cursor)
+
+        if not self._soft_closed:
+            cursor = self.cursor
+            self.cursor = None  # type: ignore
+            self.connection._safe_close_cursor(cursor)
+            self._soft_closed = True
+
+    @property
+    def inserted_primary_key_rows(self):
+        """Return the value of
+        :attr:`_engine.CursorResult.inserted_primary_key`
+        as a row contained within a list; some dialects may support a
+        multiple row form as well.
+
+        .. note:: As indicated below, in current SQLAlchemy versions this
+           accessor is only useful beyond what's already supplied by
+           :attr:`_engine.CursorResult.inserted_primary_key` when using the
+           :ref:`postgresql_psycopg2` dialect.   Future versions hope to
+           generalize this feature to more dialects.
+
+        This accessor is added to support dialects that offer the feature
+        that is currently implemented by the :ref:`psycopg2_executemany_mode`
+        feature, currently **only the psycopg2 dialect**, which provides
+        for many rows to be INSERTed at once while still retaining the
+        behavior of being able to return server-generated primary key values.
+
+        * **When using the psycopg2 dialect, or other dialects that may support
+          "fast executemany" style inserts in upcoming releases** : When
+          invoking an INSERT statement while passing a list of rows as the
+          second argument to :meth:`_engine.Connection.execute`, this accessor
+          will then provide a list of rows, where each row contains the primary
+          key value for each row that was INSERTed.
+
+        * **When using all other dialects / backends that don't yet support
+          this feature**: This accessor is only useful for **single row INSERT
+          statements**, and returns the same information as that of the
+          :attr:`_engine.CursorResult.inserted_primary_key` within a
+          single-element list. When an INSERT statement is executed in
+          conjunction with a list of rows to be INSERTed, the list will contain
+          one row per row inserted in the statement, however it will contain
+          ``None`` for any server-generated values.
+
+        Future releases of SQLAlchemy will further generalize the
+        "fast execution helper" feature of psycopg2 to suit other dialects,
+        thus allowing this accessor to be of more general use.
+
+        .. versionadded:: 1.4
+
+        .. seealso::
+
+            :attr:`_engine.CursorResult.inserted_primary_key`
+
+        """
+        if not self.context.compiled:
+            raise exc.InvalidRequestError(
+                "Statement is not a compiled expression construct."
+            )
+        elif not self.context.isinsert:
+            raise exc.InvalidRequestError(
+                "Statement is not an insert() expression construct."
+            )
+        elif self.context._is_explicit_returning:
+            raise exc.InvalidRequestError(
+                "Can't call inserted_primary_key "
+                "when returning() "
+                "is used."
+            )
+        return self.context.inserted_primary_key_rows
+
+    @property
+    def inserted_primary_key(self):
+        """Return the primary key for the row just inserted.
+
+        The return value is a :class:`_result.Row` object representing
+        a named tuple of primary key values in the order in which the
+        primary key columns are configured in the source
+        :class:`_schema.Table`.
+
+        .. versionchanged:: 1.4.8 - the
+           :attr:`_engine.CursorResult.inserted_primary_key`
+           value is now a named tuple via the :class:`_result.Row` class,
+           rather than a plain tuple.
+
+        This accessor only applies to single row :func:`_expression.insert`
+        constructs which did not explicitly specify
+        :meth:`_expression.Insert.returning`.    Support for multirow inserts,
+        while not yet available for most backends, would be accessed using
+        the :attr:`_engine.CursorResult.inserted_primary_key_rows` accessor.
+
+        Note that primary key columns which specify a server_default clause, or
+        otherwise do not qualify as "autoincrement" columns (see the notes at
+        :class:`_schema.Column`), and were generated using the database-side
+        default, will appear in this list as ``None`` unless the backend
+        supports "returning" and the insert statement executed with the
+        "implicit returning" enabled.
+
+        Raises :class:`~sqlalchemy.exc.InvalidRequestError` if the executed
+        statement is not a compiled expression construct
+        or is not an insert() construct.
+
+        """
+
+        if self.context.executemany:
+            raise exc.InvalidRequestError(
+                "This statement was an executemany call; if primary key "
+                "returning is supported, please "
+                "use .inserted_primary_key_rows."
+            )
+
+        ikp = self.inserted_primary_key_rows
+        if ikp:
+            return ikp[0]
+        else:
+            return None
+
+    def last_updated_params(self):
+        """Return the collection of updated parameters from this
+        execution.
+
+        Raises :class:`~sqlalchemy.exc.InvalidRequestError` if the executed
+        statement is not a compiled expression construct
+        or is not an update() construct.
+
+        """
+        if not self.context.compiled:
+            raise exc.InvalidRequestError(
+                "Statement is not a compiled expression construct."
+            )
+        elif not self.context.isupdate:
+            raise exc.InvalidRequestError(
+                "Statement is not an update() expression construct."
+            )
+        elif self.context.executemany:
+            return self.context.compiled_parameters
+        else:
+            return self.context.compiled_parameters[0]
+
+    def last_inserted_params(self):
+        """Return the collection of inserted parameters from this
+        execution.
+
+        Raises :class:`~sqlalchemy.exc.InvalidRequestError` if the executed
+        statement is not a compiled expression construct
+        or is not an insert() construct.
+
+        """
+        if not self.context.compiled:
+            raise exc.InvalidRequestError(
+                "Statement is not a compiled expression construct."
+            )
+        elif not self.context.isinsert:
+            raise exc.InvalidRequestError(
+                "Statement is not an insert() expression construct."
+            )
+        elif self.context.executemany:
+            return self.context.compiled_parameters
+        else:
+            return self.context.compiled_parameters[0]
+
+    @property
+    def returned_defaults_rows(self):
+        """Return a list of rows each containing the values of default
+        columns that were fetched using
+        the :meth:`.ValuesBase.return_defaults` feature.
+
+        The return value is a list of :class:`.Row` objects.
+
+        .. versionadded:: 1.4
+
+        """
+        return self.context.returned_default_rows
+
+    def splice_horizontally(self, other):
+        """Return a new :class:`.CursorResult` that "horizontally splices"
+        together the rows of this :class:`.CursorResult` with that of another
+        :class:`.CursorResult`.
+
+        .. tip::  This method is for the benefit of the SQLAlchemy ORM and is
+           not intended for general use.
+
+        "horizontally splices" means that for each row in the first and second
+        result sets, a new row that concatenates the two rows together is
+        produced, which then becomes the new row.  The incoming
+        :class:`.CursorResult` must have the identical number of rows.  It is
+        typically expected that the two result sets come from the same sort
+        order as well, as the result rows are spliced together based on their
+        position in the result.
+
+        The expected use case here is so that multiple INSERT..RETURNING
+        statements (which definitely need to be sorted) against different
+        tables can produce a single result that looks like a JOIN of those two
+        tables.
+
+        E.g.::
+
+            r1 = connection.execute(
+                users.insert().returning(
+                    users.c.user_name,
+                    users.c.user_id,
+                    sort_by_parameter_order=True
+                ),
+                user_values
+            )
+
+            r2 = connection.execute(
+                addresses.insert().returning(
+                    addresses.c.address_id,
+                    addresses.c.address,
+                    addresses.c.user_id,
+                    sort_by_parameter_order=True
+                ),
+                address_values
+            )
+
+            rows = r1.splice_horizontally(r2).all()
+            assert (
+                rows ==
+                [
+                    ("john", 1, 1, "foo@bar.com", 1),
+                    ("jack", 2, 2, "bar@bat.com", 2),
+                ]
+            )
+
+        .. versionadded:: 2.0
+
+        .. seealso::
+
+            :meth:`.CursorResult.splice_vertically`
+
+
+        """
+
+        clone = self._generate()
+        total_rows = [
+            tuple(r1) + tuple(r2)
+            for r1, r2 in zip(
+                list(self._raw_row_iterator()),
+                list(other._raw_row_iterator()),
+            )
+        ]
+
+        clone._metadata = clone._metadata._splice_horizontally(other._metadata)
+
+        clone.cursor_strategy = FullyBufferedCursorFetchStrategy(
+            None,
+            initial_buffer=total_rows,
+        )
+        clone._reset_memoizations()
+        return clone
+
+    def splice_vertically(self, other):
+        """Return a new :class:`.CursorResult` that "vertically splices",
+        i.e. "extends", the rows of this :class:`.CursorResult` with that of
+        another :class:`.CursorResult`.
+
+        .. tip::  This method is for the benefit of the SQLAlchemy ORM and is
+           not intended for general use.
+
+        "vertically splices" means the rows of the given result are appended to
+        the rows of this cursor result. The incoming :class:`.CursorResult`
+        must have rows that represent the identical list of columns in the
+        identical order as they are in this :class:`.CursorResult`.
+
+        .. versionadded:: 2.0
+
+        .. seealso::
+
+            :meth:`.CursorResult.splice_horizontally`
+
+        """
+        clone = self._generate()
+        total_rows = list(self._raw_row_iterator()) + list(
+            other._raw_row_iterator()
+        )
+
+        clone.cursor_strategy = FullyBufferedCursorFetchStrategy(
+            None,
+            initial_buffer=total_rows,
+        )
+        clone._reset_memoizations()
+        return clone
+
+    def _rewind(self, rows):
+        """rewind this result back to the given rowset.
+
+        this is used internally for the case where an :class:`.Insert`
+        construct combines the use of
+        :meth:`.Insert.return_defaults` along with the
+        "supplemental columns" feature.
+
+        """
+
+        if self._echo:
+            self.context.connection._log_debug(
+                "CursorResult rewound %d row(s)", len(rows)
+            )
+
+        # the rows given are expected to be Row objects, so we
+        # have to clear out processors which have already run on these
+        # rows
+        self._metadata = cast(
+            CursorResultMetaData, self._metadata
+        )._remove_processors()
+
+        self.cursor_strategy = FullyBufferedCursorFetchStrategy(
+            None,
+            # TODO: if these are Row objects, can we save on not having to
+            # re-make new Row objects out of them a second time?  is that
+            # what's actually happening right now?  maybe look into this
+            initial_buffer=rows,
+        )
+        self._reset_memoizations()
+        return self
+
+    @property
+    def returned_defaults(self):
+        """Return the values of default columns that were fetched using
+        the :meth:`.ValuesBase.return_defaults` feature.
+
+        The value is an instance of :class:`.Row`, or ``None``
+        if :meth:`.ValuesBase.return_defaults` was not used or if the
+        backend does not support RETURNING.
+
+        .. seealso::
+
+            :meth:`.ValuesBase.return_defaults`
+
+        """
+
+        if self.context.executemany:
+            raise exc.InvalidRequestError(
+                "This statement was an executemany call; if return defaults "
+                "is supported, please use .returned_defaults_rows."
+            )
+
+        rows = self.context.returned_default_rows
+        if rows:
+            return rows[0]
+        else:
+            return None
+
+    def lastrow_has_defaults(self):
+        """Return ``lastrow_has_defaults()`` from the underlying
+        :class:`.ExecutionContext`.
+
+        See :class:`.ExecutionContext` for details.
+
+        """
+
+        return self.context.lastrow_has_defaults()
+
+    def postfetch_cols(self):
+        """Return ``postfetch_cols()`` from the underlying
+        :class:`.ExecutionContext`.
+
+        See :class:`.ExecutionContext` for details.
+
+        Raises :class:`~sqlalchemy.exc.InvalidRequestError` if the executed
+        statement is not a compiled expression construct
+        or is not an insert() or update() construct.
+
+        """
+
+        if not self.context.compiled:
+            raise exc.InvalidRequestError(
+                "Statement is not a compiled expression construct."
+            )
+        elif not self.context.isinsert and not self.context.isupdate:
+            raise exc.InvalidRequestError(
+                "Statement is not an insert() or update() "
+                "expression construct."
+            )
+        return self.context.postfetch_cols
+
+    def prefetch_cols(self):
+        """Return ``prefetch_cols()`` from the underlying
+        :class:`.ExecutionContext`.
+
+        See :class:`.ExecutionContext` for details.
+
+        Raises :class:`~sqlalchemy.exc.InvalidRequestError` if the executed
+        statement is not a compiled expression construct
+        or is not an insert() or update() construct.
+
+        """
+
+        if not self.context.compiled:
+            raise exc.InvalidRequestError(
+                "Statement is not a compiled expression construct."
+            )
+        elif not self.context.isinsert and not self.context.isupdate:
+            raise exc.InvalidRequestError(
+                "Statement is not an insert() or update() "
+                "expression construct."
+            )
+        return self.context.prefetch_cols
+
+    def supports_sane_rowcount(self):
+        """Return ``supports_sane_rowcount`` from the dialect.
+
+        See :attr:`_engine.CursorResult.rowcount` for background.
+
+        """
+
+        return self.dialect.supports_sane_rowcount
+
+    def supports_sane_multi_rowcount(self):
+        """Return ``supports_sane_multi_rowcount`` from the dialect.
+
+        See :attr:`_engine.CursorResult.rowcount` for background.
+
+        """
+
+        return self.dialect.supports_sane_multi_rowcount
+
+    @util.memoized_property
+    def rowcount(self) -> int:
+        """Return the 'rowcount' for this result.
+
+        The primary purpose of 'rowcount' is to report the number of rows
+        matched by the WHERE criterion of an UPDATE or DELETE statement
+        executed once (i.e. for a single parameter set), which may then be
+        compared to the number of rows expected to be updated or deleted as a
+        means of asserting data integrity.
+
+        This attribute is transferred from the ``cursor.rowcount`` attribute
+        of the DBAPI before the cursor is closed, to support DBAPIs that
+        don't make this value available after cursor close.   Some DBAPIs may
+        offer meaningful values for other kinds of statements, such as INSERT
+        and SELECT statements as well.  In order to retrieve ``cursor.rowcount``
+        for these statements, set the
+        :paramref:`.Connection.execution_options.preserve_rowcount`
+        execution option to True, which will cause the ``cursor.rowcount``
+        value to be unconditionally memoized before any results are returned
+        or the cursor is closed, regardless of statement type.
+
+        For cases where the DBAPI does not support rowcount for a particular
+        kind of statement and/or execution, the returned value will be ``-1``,
+        which is delivered directly from the DBAPI and is part of :pep:`249`.
+        All DBAPIs should support rowcount for single-parameter-set
+        UPDATE and DELETE statements, however.
+
+        .. note::
+
+           Notes regarding :attr:`_engine.CursorResult.rowcount`:
+
+
+           * This attribute returns the number of rows *matched*,
+             which is not necessarily the same as the number of rows
+             that were actually *modified*. For example, an UPDATE statement
+             may have no net change on a given row if the SET values
+             given are the same as those present in the row already.
+             Such a row would be matched but not modified.
+             On backends that feature both styles, such as MySQL,
+             rowcount is configured to return the match
+             count in all cases.
+
+           * :attr:`_engine.CursorResult.rowcount` in the default case is
+             *only* useful in conjunction with an UPDATE or DELETE statement,
+             and only with a single set of parameters. For other kinds of
+             statements, SQLAlchemy will not attempt to pre-memoize the value
+             unless the
+             :paramref:`.Connection.execution_options.preserve_rowcount`
+             execution option is used.  Note that contrary to :pep:`249`, many
+             DBAPIs do not support rowcount values for statements that are not
+             UPDATE or DELETE, particularly when rows are being returned which
+             are not fully pre-buffered.   DBAPIs that dont support rowcount
+             for a particular kind of statement should return the value ``-1``
+             for such statements.
+
+           * :attr:`_engine.CursorResult.rowcount` may not be meaningful
+             when executing a single statement with multiple parameter sets
+             (i.e. an :term:`executemany`). Most DBAPIs do not sum "rowcount"
+             values across multiple parameter sets and will return ``-1``
+             when accessed.
+
+           * SQLAlchemy's :ref:`engine_insertmanyvalues` feature does support
+             a correct population of :attr:`_engine.CursorResult.rowcount`
+             when the :paramref:`.Connection.execution_options.preserve_rowcount`
+             execution option is set to True.
+
+           * Statements that use RETURNING may not support rowcount, returning
+             a ``-1`` value instead.
+
+        .. seealso::
+
+            :ref:`tutorial_update_delete_rowcount` - in the :ref:`unified_tutorial`
+
+            :paramref:`.Connection.execution_options.preserve_rowcount`
+
+        """  # noqa: E501
+        try:
+            return self.context.rowcount
+        except BaseException as e:
+            self.cursor_strategy.handle_exception(self, self.cursor, e)
+            raise  # not called
+
+    @property
+    def lastrowid(self):
+        """Return the 'lastrowid' accessor on the DBAPI cursor.
+
+        This is a DBAPI specific method and is only functional
+        for those backends which support it, for statements
+        where it is appropriate.  It's behavior is not
+        consistent across backends.
+
+        Usage of this method is normally unnecessary when
+        using insert() expression constructs; the
+        :attr:`~CursorResult.inserted_primary_key` attribute provides a
+        tuple of primary key values for a newly inserted row,
+        regardless of database backend.
+
+        """
+        try:
+            return self.context.get_lastrowid()
+        except BaseException as e:
+            self.cursor_strategy.handle_exception(self, self.cursor, e)
+
+    @property
+    def returns_rows(self):
+        """True if this :class:`_engine.CursorResult` returns zero or more
+        rows.
+
+        I.e. if it is legal to call the methods
+        :meth:`_engine.CursorResult.fetchone`,
+        :meth:`_engine.CursorResult.fetchmany`
+        :meth:`_engine.CursorResult.fetchall`.
+
+        Overall, the value of :attr:`_engine.CursorResult.returns_rows` should
+        always be synonymous with whether or not the DBAPI cursor had a
+        ``.description`` attribute, indicating the presence of result columns,
+        noting that a cursor that returns zero rows still has a
+        ``.description`` if a row-returning statement was emitted.
+
+        This attribute should be True for all results that are against
+        SELECT statements, as well as for DML statements INSERT/UPDATE/DELETE
+        that use RETURNING.   For INSERT/UPDATE/DELETE statements that were
+        not using RETURNING, the value will usually be False, however
+        there are some dialect-specific exceptions to this, such as when
+        using the MSSQL / pyodbc dialect a SELECT is emitted inline in
+        order to retrieve an inserted primary key value.
+
+
+        """
+        return self._metadata.returns_rows
+
+    @property
+    def is_insert(self):
+        """True if this :class:`_engine.CursorResult` is the result
+        of a executing an expression language compiled
+        :func:`_expression.insert` construct.
+
+        When True, this implies that the
+        :attr:`inserted_primary_key` attribute is accessible,
+        assuming the statement did not include
+        a user defined "returning" construct.
+
+        """
+        return self.context.isinsert
+
+    def _fetchiter_impl(self):
+        fetchone = self.cursor_strategy.fetchone
+
+        while True:
+            row = fetchone(self, self.cursor)
+            if row is None:
+                break
+            yield row
+
+    def _fetchone_impl(self, hard_close=False):
+        return self.cursor_strategy.fetchone(self, self.cursor, hard_close)
+
+    def _fetchall_impl(self):
+        return self.cursor_strategy.fetchall(self, self.cursor)
+
+    def _fetchmany_impl(self, size=None):
+        return self.cursor_strategy.fetchmany(self, self.cursor, size)
+
+    def _raw_row_iterator(self):
+        return self._fetchiter_impl()
+
+    def merge(self, *others: Result[Any]) -> MergedResult[Any]:
+        merged_result = super().merge(*others)
+        if self.context._has_rowcount:
+            merged_result.rowcount = sum(
+                cast("CursorResult[Any]", result).rowcount
+                for result in (self,) + others
+            )
+        return merged_result
+
+    def close(self) -> Any:
+        """Close this :class:`_engine.CursorResult`.
+
+        This closes out the underlying DBAPI cursor corresponding to the
+        statement execution, if one is still present.  Note that the DBAPI
+        cursor is automatically released when the :class:`_engine.CursorResult`
+        exhausts all available rows.  :meth:`_engine.CursorResult.close` is
+        generally an optional method except in the case when discarding a
+        :class:`_engine.CursorResult` that still has additional rows pending
+        for fetch.
+
+        After this method is called, it is no longer valid to call upon
+        the fetch methods, which will raise a :class:`.ResourceClosedError`
+        on subsequent use.
+
+        .. seealso::
+
+            :ref:`connections_toplevel`
+
+        """
+        self._soft_close(hard=True)
+
+    @_generative
+    def yield_per(self, num: int) -> Self:
+        self._yield_per = num
+        self.cursor_strategy.yield_per(self, self.cursor, num)
+        return self
+
+
+ResultProxy = CursorResult