Current File : //opt/cloudlinux/venv/lib64/python3.11/site-packages/sqlalchemy/engine/result.py
# engine/result.py
# Copyright (C) 2005-2021 the SQLAlchemy authors and contributors
# <see AUTHORS file>
#
# This module is part of SQLAlchemy and is released under
# the MIT License: http://www.opensource.org/licenses/mit-license.php
"""Define result set constructs including :class:`_engine.ResultProxy`
and :class:`.RowProxy`."""
import collections
import operator
from .. import exc
from .. import util
from ..sql import expression
from ..sql import sqltypes
from ..sql import util as sql_util
# This reconstructor is necessary so that pickles with the C extension or
# without use the same Binary format.
try:
# We need a different reconstructor on the C extension so that we can
# add extra checks that fields have correctly been initialized by
# __setstate__.
from sqlalchemy.cresultproxy import safe_rowproxy_reconstructor
# The extra function embedding is needed so that the
# reconstructor function has the same signature whether or not
# the extension is present.
def rowproxy_reconstructor(cls, state):
return safe_rowproxy_reconstructor(cls, state)
except ImportError:
def rowproxy_reconstructor(cls, state):
obj = cls.__new__(cls)
obj.__setstate__(state)
return obj
try:
from sqlalchemy.cresultproxy import BaseRowProxy
_baserowproxy_usecext = True
except ImportError:
_baserowproxy_usecext = False
class BaseRowProxy(object):
__slots__ = ("_parent", "_row", "_processors", "_keymap")
def __init__(self, parent, row, processors, keymap):
"""RowProxy objects are constructed by ResultProxy objects."""
self._parent = parent
self._row = row
self._processors = processors
self._keymap = keymap
def __reduce__(self):
return (
rowproxy_reconstructor,
(self.__class__, self.__getstate__()),
)
def values(self):
"""Return the values represented by this RowProxy as a list."""
return list(self)
def __iter__(self):
for processor, value in zip(self._processors, self._row):
if processor is None:
yield value
else:
yield processor(value)
def __len__(self):
return len(self._row)
def __getitem__(self, key):
try:
processor, obj, index = self._keymap[key]
except KeyError as err:
processor, obj, index = self._parent._key_fallback(key, err)
except TypeError:
if isinstance(key, slice):
l = []
for processor, value in zip(
self._processors[key], self._row[key]
):
if processor is None:
l.append(value)
else:
l.append(processor(value))
return tuple(l)
else:
raise
if index is None:
raise exc.InvalidRequestError(
"Ambiguous column name '%s' in "
"result set column descriptions" % obj
)
if processor is not None:
return processor(self._row[index])
else:
return self._row[index]
def __getattr__(self, name):
try:
return self[name]
except KeyError as e:
util.raise_(AttributeError(e.args[0]), replace_context=e)
class RowProxy(BaseRowProxy):
"""Represent a single result row.
The :class:`.RowProxy` object is retrieved from a database result, from the
:class:`_engine.ResultProxy` object using methods like
:meth:`_engine.ResultProxy.fetchall`.
The :class:`.RowProxy` object seeks to act mostly like a Python named
tuple, but also provides some Python dictionary behaviors at the same time.
.. seealso::
:ref:`coretutorial_selecting` - includes examples of selecting
rows from SELECT statements.
"""
__slots__ = ()
def __contains__(self, key):
return self._parent._has_key(key)
def __getstate__(self):
return {"_parent": self._parent, "_row": tuple(self)}
def __setstate__(self, state):
self._parent = parent = state["_parent"]
self._row = state["_row"]
self._processors = parent._processors
self._keymap = parent._keymap
__hash__ = None
def _op(self, other, op):
return (
op(tuple(self), tuple(other))
if isinstance(other, RowProxy)
else op(tuple(self), other)
)
def __lt__(self, other):
return self._op(other, operator.lt)
def __le__(self, other):
return self._op(other, operator.le)
def __ge__(self, other):
return self._op(other, operator.ge)
def __gt__(self, other):
return self._op(other, operator.gt)
def __eq__(self, other):
return self._op(other, operator.eq)
def __ne__(self, other):
return self._op(other, operator.ne)
def __repr__(self):
return repr(sql_util._repr_row(self))
def has_key(self, key):
"""Return True if this :class:`.RowProxy` contains the given key.
Through the SQLAlchemy 1.x series, the ``__contains__()`` method
of :class:`.RowProxy` also links to :meth:`.RowProxy.has_key`, in that
an expression such as ::
"some_col" in row
Will return True if the row contains a column named ``"some_col"``,
in the way that a Python mapping works.
However, it is planned that the 2.0 series of SQLAlchemy will reverse
this behavior so that ``__contains__()`` will refer to a value being
present in the row, in the way that a Python tuple works.
"""
return self._parent._has_key(key)
def items(self):
"""Return a list of tuples, each tuple containing a key/value pair.
This method is analogous to the Python dictionary ``.items()`` method,
except that it returns a list, not an iterator.
"""
return [(key, self[key]) for key in self.keys()]
def keys(self):
"""Return the list of keys as strings represented by this
:class:`.RowProxy`.
This method is analogous to the Python dictionary ``.keys()`` method,
except that it returns a list, not an iterator.
"""
return self._parent.keys
def iterkeys(self):
"""Return a an iterator against the :meth:`.RowProxy.keys` method.
This method is analogous to the Python-2-only dictionary
``.iterkeys()`` method.
"""
return iter(self._parent.keys)
def itervalues(self):
"""Return a an iterator against the :meth:`.RowProxy.values` method.
This method is analogous to the Python-2-only dictionary
``.itervalues()`` method.
"""
return iter(self)
def values(self):
"""Return the values represented by this :class:`.RowProxy` as a list.
This method is analogous to the Python dictionary ``.values()`` method,
except that it returns a list, not an iterator.
"""
return super(RowProxy, self).values()
try:
# Register RowProxy with Sequence,
# so sequence protocol is implemented
util.collections_abc.Sequence.register(RowProxy)
except ImportError:
pass
class ResultMetaData(object):
"""Handle cursor.description, applying additional info from an execution
context."""
__slots__ = (
"_keymap",
"case_sensitive",
"matched_on_name",
"_processors",
"keys",
"_orig_processors",
)
def __init__(self, parent, cursor_description):
context = parent.context
dialect = context.dialect
self.case_sensitive = dialect.case_sensitive
self.matched_on_name = False
self._orig_processors = None
if context.result_column_struct:
(
result_columns,
cols_are_ordered,
textual_ordered,
) = context.result_column_struct
num_ctx_cols = len(result_columns)
else:
result_columns = (
cols_are_ordered
) = num_ctx_cols = 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,
)
self._keymap = {}
if not _baserowproxy_usecext:
# keymap indexes by integer index: this is only used
# in the pure Python BaseRowProxy.__getitem__
# implementation to avoid an expensive
# isinstance(key, util.int_types) in the most common
# case path
len_raw = len(raw)
self._keymap.update(
[(elem[0], (elem[3], elem[4], elem[0])) for elem in raw]
+ [
(elem[0] - len_raw, (elem[3], elem[4], elem[0]))
for elem in raw
]
)
# processors in key order for certain per-row
# views like __iter__ and slices
self._processors = [elem[3] for elem in raw]
# keymap by primary string...
by_key = dict([(elem[2], (elem[3], elem[4], elem[0])) for elem in raw])
# 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:
# if by-primary-string dictionary smaller (or bigger?!) than
# number of columns, assume we have dupes, rewrite
# dupe records with "None" for index which results in
# ambiguous column exception when accessed.
if len(by_key) != num_ctx_cols:
seen = set()
for rec in raw:
key = rec[1]
if key in seen:
# this is an "ambiguous" element, replacing
# the full record in the map
key = key.lower() if not self.case_sensitive else key
by_key[key] = (None, key, None)
seen.add(key)
# copy secondary elements from compiled columns
# into self._keymap, write in the potentially "ambiguous"
# element
self._keymap.update(
[
(obj_elem, by_key[elem[2]])
for elem in raw
if elem[4]
for obj_elem in elem[4]
]
)
# if we did a pure positional match, then reset the
# original "expression element" back to the "unambiguous"
# entry. This is a new behavior in 1.1 which impacts
# TextAsFrom but also straight compiled SQL constructs.
if not self.matched_on_name:
self._keymap.update(
[
(elem[4][0], (elem[3], elem[4], elem[0]))
for elem in raw
if elem[4]
]
)
else:
# no dupes - copy secondary elements from compiled
# columns into self._keymap
self._keymap.update(
[
(obj_elem, (elem[3], elem[4], elem[0]))
for elem in raw
if elem[4]
for obj_elem in elem[4]
]
)
# update keymap with primary string names taking
# precedence
self._keymap.update(by_key)
# update keymap with "translated" names (sqlite-only thing)
if not num_ctx_cols and context._translate_colname:
self._keymap.update(
[(elem[5], self._keymap[elem[2]]) for elem in raw if elem[5]]
)
def _merge_cursor_description(
self,
context,
cursor_description,
result_columns,
num_ctx_cols,
cols_are_ordered,
textual_ordered,
):
"""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:`.TextAsFrom` 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 te 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:`.TextAsFrom` 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.
"""
case_sensitive = context.dialect.case_sensitive
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
return [
(
idx,
key,
name.lower() if not case_sensitive else name,
context.get_result_processor(
type_, key, cursor_description[idx][1]
),
obj,
None,
)
for idx, (key, name, obj, type_) in enumerate(result_columns)
]
else:
# name-based or text-positional cases, where we need
# to read cursor.description names
if textual_ordered:
# 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
raw_iterator = self._merge_cols_by_name(
context, cursor_description, result_columns
)
else:
# no compiled SQL, just a raw string
raw_iterator = self._merge_cols_by_none(
context, cursor_description
)
return [
(
idx,
colname,
colname,
context.get_result_processor(
mapped_type, colname, coltype
),
obj,
untranslated,
)
for (
idx,
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
case_sensitive = dialect.case_sensitive
translate_colname = context._translate_colname
description_decoder = (
dialect._description_decoder
if dialect.description_encoding
else None
)
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 description_decoder:
colname = description_decoder(colname)
if translate_colname:
colname, untranslated = translate_colname(colname)
if normalize_name:
colname = normalize_name(colname)
self.keys.append(colname)
if not case_sensitive:
colname = colname.lower()
yield idx, colname, untranslated, coltype
def _merge_textual_cols_by_position(
self, context, cursor_description, result_columns
):
num_ctx_cols = len(result_columns) if result_columns else None
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[2]
mapped_type = ctx_rec[3]
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
yield idx, colname, mapped_type, coltype, obj, untranslated
def _merge_cols_by_name(self, context, cursor_description, result_columns):
dialect = context.dialect
case_sensitive = dialect.case_sensitive
result_map = self._create_result_map(result_columns, case_sensitive)
self.matched_on_name = True
for (
idx,
colname,
untranslated,
coltype,
) in self._colnames_from_description(context, cursor_description):
try:
ctx_rec = result_map[colname]
except KeyError:
mapped_type = sqltypes.NULLTYPE
obj = None
else:
obj = ctx_rec[1]
mapped_type = ctx_rec[2]
yield idx, colname, mapped_type, coltype, obj, untranslated
def _merge_cols_by_none(self, context, cursor_description):
for (
idx,
colname,
untranslated,
coltype,
) in self._colnames_from_description(context, cursor_description):
yield idx, colname, sqltypes.NULLTYPE, coltype, None, untranslated
@classmethod
def _create_result_map(cls, result_columns, case_sensitive=True):
d = {}
for elem in result_columns:
key, rec = elem[0], elem[1:]
if not case_sensitive:
key = key.lower()
if key in d:
# conflicting keyname, just double up the list
# of objects. this will cause an "ambiguous name"
# error if an attempt is made by the result set to
# access.
e_name, e_obj, e_type = d[key]
d[key] = e_name, e_obj + rec[1], e_type
else:
d[key] = rec
return d
def _key_fallback(self, key, err, raiseerr=True):
map_ = self._keymap
result = None
if isinstance(key, util.string_types):
result = map_.get(key if self.case_sensitive else key.lower())
# fallback for targeting a ColumnElement to a textual expression
# this is a rare use case which only occurs when matching text()
# or colummn('name') constructs to ColumnElements, or after a
# pickle/unpickle roundtrip
elif isinstance(key, expression.ColumnElement):
if (
key._label
and (key._label if self.case_sensitive else key._label.lower())
in map_
):
result = map_[
key._label if self.case_sensitive else key._label.lower()
]
elif (
hasattr(key, "name")
and (key.name if self.case_sensitive else key.name.lower())
in map_
):
# match is only on name.
result = map_[
key.name if self.case_sensitive else key.name.lower()
]
# search extra hard to make sure this
# isn't a column/label name overlap.
# this check isn't currently available if the row
# was unpickled.
if result is not None and result[1] is not None:
for obj in result[1]:
if key._compare_name_for_result(obj):
break
else:
result = None
if result is None:
if raiseerr:
util.raise_(
exc.NoSuchColumnError(
"Could not locate column in row for column '%s'"
% expression._string_or_unprintable(key)
),
replace_context=err,
)
else:
return None
else:
map_[key] = result
return result
def _has_key(self, key):
if key in self._keymap:
return True
else:
return self._key_fallback(key, None, False) is not None
def _getter(self, key, raiseerr=True):
if key in self._keymap:
processor, obj, index = self._keymap[key]
else:
ret = self._key_fallback(key, None, raiseerr)
if ret is None:
return None
processor, obj, index = ret
if index is None:
util.raise_(
exc.InvalidRequestError(
"Ambiguous column name '%s' in "
"result set column descriptions" % obj
),
from_=None,
)
return operator.itemgetter(index)
def __getstate__(self):
return {
"_pickled_keymap": dict(
(key, index)
for key, (processor, obj, index) in self._keymap.items()
if isinstance(key, util.string_types + util.int_types)
),
"keys": self.keys,
"case_sensitive": self.case_sensitive,
"matched_on_name": self.matched_on_name,
}
def __setstate__(self, state):
# the row has been processed at pickling time so we don't need any
# processor anymore
self._processors = [None for _ in range(len(state["keys"]))]
self._keymap = keymap = {}
for key, index in state["_pickled_keymap"].items():
# not preserving "obj" here, unfortunately our
# proxy comparison fails with the unpickle
keymap[key] = (None, None, index)
self.keys = state["keys"]
self.case_sensitive = state["case_sensitive"]
self.matched_on_name = state["matched_on_name"]
class ResultProxy(object):
"""A facade around a DBAPI cursor object.
Returns database rows via the :class:`.RowProxy` class, which provides
additional API features and behaviors on top of the raw data returned
by the DBAPI.
.. seealso::
:ref:`coretutorial_selecting` - introductory material for accessing
:class:`_engine.ResultProxy` and :class:`.RowProxy` objects.
"""
_process_row = RowProxy
out_parameters = None
_autoclose_connection = False
_metadata = None
_soft_closed = False
closed = False
def __init__(self, context):
self.context = context
self.dialect = context.dialect
self.cursor = self._saved_cursor = context.cursor
self.connection = context.root_connection
self._echo = (
self.connection._echo and context.engine._should_log_debug()
)
self._init_metadata()
def _getter(self, key, raiseerr=True):
try:
getter = self._metadata._getter
except AttributeError as err:
return self._non_result(None, err)
else:
return getter(key, raiseerr)
def _has_key(self, key):
try:
has_key = self._metadata._has_key
except AttributeError as err:
return self._non_result(None, err)
else:
return has_key(key)
def _init_metadata(self):
cursor_description = self._cursor_description()
if cursor_description is not None:
if (
self.context.compiled
and "compiled_cache" in self.context.execution_options
):
if self.context.compiled._cached_metadata:
self._metadata = self.context.compiled._cached_metadata
else:
self._metadata = (
self.context.compiled._cached_metadata
) = ResultMetaData(self, cursor_description)
else:
self._metadata = ResultMetaData(self, cursor_description)
if self._echo:
self.context.engine.logger.debug(
"Col %r", tuple(x[0] for x in cursor_description)
)
def keys(self):
"""Return the list of string keys that would represented by each
:class:`.RowProxy`."""
if self._metadata:
return self._metadata.keys
else:
return []
@util.memoized_property
def rowcount(self):
"""Return the 'rowcount' for this result.
The 'rowcount' reports the number of rows *matched*
by the WHERE criterion of an UPDATE or DELETE statement.
.. note::
Notes regarding :attr:`_engine.ResultProxy.rowcount`:
* This attribute returns the number of rows *matched*,
which is not necessarily the same as the number of rows
that were actually *modified* - an UPDATE statement, for example,
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 by default to return the match
count in all cases.
* :attr:`_engine.ResultProxy.rowcount`
is *only* useful in conjunction
with an UPDATE or DELETE statement. Contrary to what the Python
DBAPI says, it does *not* return the
number of rows available from the results of a SELECT statement
as DBAPIs cannot support this functionality when rows are
unbuffered.
* :attr:`_engine.ResultProxy.rowcount`
may not be fully implemented by
all dialects. In particular, most DBAPIs do not support an
aggregate rowcount result from an executemany call.
The :meth:`_engine.ResultProxy.supports_sane_rowcount` and
:meth:`_engine.ResultProxy.supports_sane_multi_rowcount` methods
will report from the dialect if each usage is known to be
supported.
* Statements that use RETURNING may not return a correct
rowcount.
"""
try:
return self.context.rowcount
except BaseException as e:
self.connection._handle_dbapi_exception(
e, None, None, self.cursor, self.context
)
@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:`~ResultProxy.inserted_primary_key` attribute provides a
tuple of primary key values for a newly inserted row,
regardless of database backend.
"""
try:
return self._saved_cursor.lastrowid
except BaseException as e:
self.connection._handle_dbapi_exception(
e, None, None, self._saved_cursor, self.context
)
@property
def returns_rows(self):
"""True if this :class:`_engine.ResultProxy` returns rows.
I.e. if it is legal to call the methods
:meth:`_engine.ResultProxy.fetchone`,
:meth:`_engine.ResultProxy.fetchmany`
:meth:`_engine.ResultProxy.fetchall`.
"""
return self._metadata is not None
@property
def is_insert(self):
"""True if this :class:`_engine.ResultProxy` 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 _cursor_description(self):
"""May be overridden by subclasses."""
return self._saved_cursor.description
def _soft_close(self):
"""Soft close this :class:`_engine.ResultProxy`.
This releases all DBAPI cursor resources, but leaves the
ResultProxy "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.
.. versionadded:: 1.0.0
.. seealso::
:meth:`_engine.ResultProxy.close`
"""
if self._soft_closed:
return
self._soft_closed = True
cursor = self.cursor
self.connection._safe_close_cursor(cursor)
if self._autoclose_connection:
self.connection.close()
self.cursor = None
def close(self):
"""Close this ResultProxy.
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.ResultProxy`
exhausts all available rows. :meth:`_engine.ResultProxy.close`
is generally
an optional method except in the case when discarding a
:class:`_engine.ResultProxy`
that still has additional rows pending for fetch.
In the case of a result that is the product of
:ref:`connectionless execution <dbengine_implicit>`,
the underlying :class:`_engine.Connection` object is also closed,
which
:term:`releases` DBAPI connection resources.
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.
.. versionchanged:: 1.0.0 - the :meth:`_engine.ResultProxy.close`
method
has been separated out from the process that releases the underlying
DBAPI cursor resource. The "auto close" feature of the
:class:`_engine.Connection` now performs a so-called "soft close",
which
releases the underlying DBAPI cursor, but allows the
:class:`_engine.ResultProxy`
to still behave as an open-but-exhausted
result set; the actual :meth:`_engine.ResultProxy.close`
method is never
called. It is still safe to discard a
:class:`_engine.ResultProxy`
that has been fully exhausted without calling this method.
.. seealso::
:ref:`connections_toplevel`
"""
if not self.closed:
self._soft_close()
self.closed = True
def __iter__(self):
"""Implement iteration protocol."""
while True:
row = self.fetchone()
if row is None:
return
else:
yield row
def __next__(self):
"""Implement the Python next() protocol.
This method, mirrored as both ``.next()`` and ``.__next__()``, is part
of Python's API for producing iterator-like behavior.
.. versionadded:: 1.2
"""
row = self.fetchone()
if row is None:
raise StopIteration()
else:
return row
next = __next__
@util.memoized_property
def inserted_primary_key(self):
"""Return the primary key for the row just inserted.
The return value is a list of scalar values
corresponding to the list of primary key columns
in the target table.
This only applies to single row :func:`_expression.insert`
constructs which did not explicitly specify
:meth:`_expression.Insert.returning`.
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 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
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(self):
"""Return the values of default columns that were fetched using
the :meth:`.ValuesBase.return_defaults` feature.
The value is an instance of :class:`.RowProxy`, or ``None``
if :meth:`.ValuesBase.return_defaults` was not used or if the
backend does not support RETURNING.
.. versionadded:: 0.9.0
.. seealso::
:meth:`.ValuesBase.return_defaults`
"""
return self.context.returned_defaults
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.ResultProxy.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.ResultProxy.rowcount` for background.
"""
return self.dialect.supports_sane_multi_rowcount
def _fetchone_impl(self):
try:
return self.cursor.fetchone()
except AttributeError as err:
return self._non_result(None, err)
def _fetchmany_impl(self, size=None):
try:
if size is None:
return self.cursor.fetchmany()
else:
return self.cursor.fetchmany(size)
except AttributeError as err:
return self._non_result([], err)
def _fetchall_impl(self):
try:
return self.cursor.fetchall()
except AttributeError as err:
return self._non_result([], err)
def _non_result(self, default, err=None):
if self._metadata is None:
util.raise_(
exc.ResourceClosedError(
"This result object does not return rows. "
"It has been closed automatically."
),
replace_context=err,
)
elif self.closed:
util.raise_(
exc.ResourceClosedError("This result object is closed."),
replace_context=err,
)
else:
return default
def process_rows(self, rows):
process_row = self._process_row
metadata = self._metadata
keymap = metadata._keymap
processors = metadata._processors
if self._echo:
log = self.context.engine.logger.debug
l = []
for row in rows:
log("Row %r", sql_util._repr_row(row))
l.append(process_row(metadata, row, processors, keymap))
return l
else:
return [
process_row(metadata, row, processors, keymap) for row in rows
]
def fetchall(self):
"""Fetch all rows, just like DB-API ``cursor.fetchall()``.
After all rows have been exhausted, the underlying DBAPI
cursor resource is released, and the object may be safely
discarded.
Subsequent calls to :meth:`_engine.ResultProxy.fetchall` will return
an empty list. After the :meth:`_engine.ResultProxy.close` method is
called, the method will raise :class:`.ResourceClosedError`.
:return: a list of :class:`.RowProxy` objects
"""
try:
l = self.process_rows(self._fetchall_impl())
self._soft_close()
return l
except BaseException as e:
self.connection._handle_dbapi_exception(
e, None, None, self.cursor, self.context
)
def fetchmany(self, size=None):
"""Fetch many rows, just like DB-API
``cursor.fetchmany(size=cursor.arraysize)``.
After all rows have been exhausted, the underlying DBAPI
cursor resource is released, and the object may be safely
discarded.
Calls to :meth:`_engine.ResultProxy.fetchmany`
after all rows have been
exhausted will return
an empty list. After the :meth:`_engine.ResultProxy.close` method is
called, the method will raise :class:`.ResourceClosedError`.
:return: a list of :class:`.RowProxy` objects
"""
try:
l = self.process_rows(self._fetchmany_impl(size))
if len(l) == 0:
self._soft_close()
return l
except BaseException as e:
self.connection._handle_dbapi_exception(
e, None, None, self.cursor, self.context
)
def fetchone(self):
"""Fetch one row, just like DB-API ``cursor.fetchone()``.
After all rows have been exhausted, the underlying DBAPI
cursor resource is released, and the object may be safely
discarded.
Calls to :meth:`_engine.ResultProxy.fetchone` after all rows have
been exhausted will return ``None``.
After the :meth:`_engine.ResultProxy.close` method is
called, the method will raise :class:`.ResourceClosedError`.
:return: a :class:`.RowProxy` object, or None if no rows remain
"""
try:
row = self._fetchone_impl()
if row is not None:
return self.process_rows([row])[0]
else:
self._soft_close()
return None
except BaseException as e:
self.connection._handle_dbapi_exception(
e, None, None, self.cursor, self.context
)
def first(self):
"""Fetch the first row and then close the result set unconditionally.
After calling this method, the object is fully closed,
e.g. the :meth:`_engine.ResultProxy.close`
method will have been called.
:return: a :class:`.RowProxy` object, or None if no rows remain
"""
if self._metadata is None:
return self._non_result(None)
try:
row = self._fetchone_impl()
except BaseException as e:
self.connection._handle_dbapi_exception(
e, None, None, self.cursor, self.context
)
try:
if row is not None:
return self.process_rows([row])[0]
else:
return None
finally:
self.close()
def scalar(self):
"""Fetch the first column of the first row, and close the result set.
After calling this method, the object is fully closed,
e.g. the :meth:`_engine.ResultProxy.close`
method will have been called.
:return: a Python scalar value , or None if no rows remain
"""
row = self.first()
if row is not None:
return row[0]
else:
return None
class BufferedRowResultProxy(ResultProxy):
"""A ResultProxy with row buffering behavior.
``ResultProxy`` that 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 to a size of 1000.
The size argument is configurable using the ``max_row_buffer``
execution option::
with psycopg2_engine.connect() as conn:
result = conn.execution_options(
stream_results=True, max_row_buffer=50
).execute("select * from table")
.. versionadded:: 1.0.6 Added the ``max_row_buffer`` option.
.. seealso::
:ref:`psycopg2_execution_options`
"""
def _init_metadata(self):
self._max_row_buffer = self.context.execution_options.get(
"max_row_buffer", None
)
self.__buffer_rows()
super(BufferedRowResultProxy, self)._init_metadata()
# this is a "growth chart" for the buffering of rows.
# each successive __buffer_rows call will use the next
# value in the list for the buffer size until the max
# is reached
size_growth = {
1: 5,
5: 10,
10: 20,
20: 50,
50: 100,
100: 250,
250: 500,
500: 1000,
}
def __buffer_rows(self):
if self.cursor is None:
return
size = getattr(self, "_bufsize", 1)
self.__rowbuffer = collections.deque(self.cursor.fetchmany(size))
self._bufsize = self.size_growth.get(size, size)
if self._max_row_buffer is not None:
self._bufsize = min(self._max_row_buffer, self._bufsize)
def _soft_close(self, **kw):
self.__rowbuffer.clear()
super(BufferedRowResultProxy, self)._soft_close(**kw)
def _fetchone_impl(self):
if self.cursor is None:
return self._non_result(None)
if not self.__rowbuffer:
self.__buffer_rows()
if not self.__rowbuffer:
return None
return self.__rowbuffer.popleft()
def _fetchmany_impl(self, size=None):
if size is None:
return self._fetchall_impl()
result = []
for x in range(0, size):
row = self._fetchone_impl()
if row is None:
break
result.append(row)
return result
def _fetchall_impl(self):
if self.cursor is None:
return self._non_result([])
self.__rowbuffer.extend(self.cursor.fetchall())
ret = self.__rowbuffer
self.__rowbuffer = collections.deque()
return ret
class FullyBufferedResultProxy(ResultProxy):
"""A result proxy 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.
"""
def _init_metadata(self):
super(FullyBufferedResultProxy, self)._init_metadata()
self.__rowbuffer = self._buffer_rows()
def _buffer_rows(self):
return collections.deque(self.cursor.fetchall())
def _soft_close(self, **kw):
self.__rowbuffer.clear()
super(FullyBufferedResultProxy, self)._soft_close(**kw)
def _fetchone_impl(self):
if self.__rowbuffer:
return self.__rowbuffer.popleft()
else:
return self._non_result(None)
def _fetchmany_impl(self, size=None):
if size is None:
return self._fetchall_impl()
result = []
for x in range(0, size):
row = self._fetchone_impl()
if row is None:
break
result.append(row)
return result
def _fetchall_impl(self):
if not self.cursor:
return self._non_result([])
ret = self.__rowbuffer
self.__rowbuffer = collections.deque()
return ret
class BufferedColumnRow(RowProxy):
def __init__(self, parent, row, processors, keymap):
# preprocess row
row = list(row)
# this is a tad faster than using enumerate
index = 0
for processor in parent._orig_processors:
if processor is not None:
row[index] = processor(row[index])
index += 1
row = tuple(row)
super(BufferedColumnRow, self).__init__(
parent, row, processors, keymap
)
class BufferedColumnResultProxy(ResultProxy):
"""A ResultProxy with column buffering behavior.
``ResultProxy`` that loads all columns into memory each time
fetchone() is called. If fetchmany() or fetchall() are called,
the full grid of results is fetched. This is to operate with
databases where result rows contain "live" results that fall out
of scope unless explicitly fetched.
.. versionchanged:: 1.2 This :class:`_engine.ResultProxy` is not used by
any SQLAlchemy-included dialects.
"""
_process_row = BufferedColumnRow
def _init_metadata(self):
super(BufferedColumnResultProxy, self)._init_metadata()
metadata = self._metadata
# don't double-replace the processors, in the case
# of a cached ResultMetaData
if metadata._orig_processors is None:
# orig_processors will be used to preprocess each row when
# they are constructed.
metadata._orig_processors = metadata._processors
# replace the all type processors by None processors.
metadata._processors = [None for _ in range(len(metadata.keys))]
keymap = {}
for k, (func, obj, index) in metadata._keymap.items():
keymap[k] = (None, obj, index)
metadata._keymap = keymap
def fetchall(self):
# can't call cursor.fetchall(), since rows must be
# fully processed before requesting more from the DBAPI.
l = []
while True:
row = self.fetchone()
if row is None:
break
l.append(row)
return l
def fetchmany(self, size=None):
# can't call cursor.fetchmany(), since rows must be
# fully processed before requesting more from the DBAPI.
if size is None:
return self.fetchall()
l = []
for i in range(size):
row = self.fetchone()
if row is None:
break
l.append(row)
return l
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