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# 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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