# Copyright 2017 Google LLC # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """Cursor for the Google BigQuery DB-API.""" from __future__ import annotations import collections from collections import abc as collections_abc import re from typing import Optional try: from google.cloud.bigquery_storage import ArrowSerializationOptions except ImportError: _ARROW_COMPRESSION_SUPPORT = False else: # Having BQ Storage available implies that pyarrow >=1.0.0 is available, too. _ARROW_COMPRESSION_SUPPORT = True from google.cloud.bigquery import job from google.cloud.bigquery.dbapi import _helpers from google.cloud.bigquery.dbapi import exceptions import google.cloud.exceptions # type: ignore # Per PEP 249: A 7-item sequence containing information describing one result # column. The first two items (name and type_code) are mandatory, the other # five are optional and are set to None if no meaningful values can be # provided. Column = collections.namedtuple( "Column", [ "name", "type_code", "display_size", "internal_size", "precision", "scale", "null_ok", ], ) @_helpers.raise_on_closed("Operating on a closed cursor.") class Cursor(object): """DB-API Cursor to Google BigQuery. Args: connection (google.cloud.bigquery.dbapi.Connection): A DB-API connection to Google BigQuery. """ def __init__(self, connection): self.connection = connection self.description = None # Per PEP 249: The attribute is -1 in case no .execute*() has been # performed on the cursor or the rowcount of the last operation # cannot be determined by the interface. self.rowcount = -1 # Per PEP 249: The arraysize attribute defaults to 1, meaning to fetch # a single row at a time. However, we deviate from that, and set the # default to None, allowing the backend to automatically determine the # most appropriate size. self.arraysize = None self._query_data = None self._query_rows = None self._closed = False @property def query_job(self) -> Optional[job.QueryJob]: """google.cloud.bigquery.job.query.QueryJob | None: The query job created by the last ``execute*()`` call, if a query job was created. .. note:: If the last ``execute*()`` call was ``executemany()``, this is the last job created by ``executemany()``.""" rows = self._query_rows if rows is None: return None job_id = rows.job_id project = rows.project location = rows.location client = self.connection._client if job_id is None: return None return client.get_job(job_id, location=location, project=project) def close(self): """Mark the cursor as closed, preventing its further use.""" self._closed = True def _set_description(self, schema): """Set description from schema. Args: schema (Sequence[google.cloud.bigquery.schema.SchemaField]): A description of fields in the schema. """ if schema is None: self.description = None return self.description = tuple( Column( name=field.name, type_code=field.field_type, display_size=None, internal_size=None, precision=None, scale=None, null_ok=field.is_nullable, ) for field in schema ) def _set_rowcount(self, rows): """Set the rowcount from a RowIterator. Normally, this sets rowcount to the number of rows returned by the query, but if it was a DML statement, it sets rowcount to the number of modified rows. Args: query_results (google.cloud.bigquery.query._QueryResults): Results of a query. """ total_rows = 0 num_dml_affected_rows = rows.num_dml_affected_rows if rows.total_rows is not None and rows.total_rows > 0: total_rows = rows.total_rows if num_dml_affected_rows is not None and num_dml_affected_rows > 0: total_rows = num_dml_affected_rows self.rowcount = total_rows def execute(self, operation, parameters=None, job_id=None, job_config=None): """Prepare and execute a database operation. .. note:: When setting query parameters, values which are "text" (``unicode`` in Python2, ``str`` in Python3) will use the 'STRING' BigQuery type. Values which are "bytes" (``str`` in Python2, ``bytes`` in Python3), will use using the 'BYTES' type. A `~datetime.datetime` parameter without timezone information uses the 'DATETIME' BigQuery type (example: Global Pi Day Celebration March 14, 2017 at 1:59pm). A `~datetime.datetime` parameter with timezone information uses the 'TIMESTAMP' BigQuery type (example: a wedding on April 29, 2011 at 11am, British Summer Time). For more information about BigQuery data types, see: https://cloud.google.com/bigquery/docs/reference/standard-sql/data-types ``STRUCT``/``RECORD`` and ``REPEATED`` query parameters are not yet supported. See: https://github.com/GoogleCloudPlatform/google-cloud-python/issues/3524 Args: operation (str): A Google BigQuery query string. parameters (Union[Mapping[str, Any], Sequence[Any]]): (Optional) dictionary or sequence of parameter values. job_id (str | None): (Optional and discouraged) The job ID to use when creating the query job. For best performance and reliability, manually setting a job ID is discouraged. job_config (google.cloud.bigquery.job.QueryJobConfig): (Optional) Extra configuration options for the query job. """ formatted_operation, parameter_types = _format_operation(operation, parameters) self._execute( formatted_operation, parameters, job_id, job_config, parameter_types ) def _execute( self, formatted_operation, parameters, job_id, job_config, parameter_types ): self._query_data = None self._query_results = None client = self.connection._client # The DB-API uses the pyformat formatting, since the way BigQuery does # query parameters was not one of the standard options. Convert both # the query and the parameters to the format expected by the client # libraries. query_parameters = _helpers.to_query_parameters(parameters, parameter_types) config = job_config or job.QueryJobConfig() config.query_parameters = query_parameters # Start the query and wait for the query to finish. try: if job_id is not None: rows = client.query( formatted_operation, job_config=job_config, job_id=job_id, ).result( page_size=self.arraysize, ) else: rows = client.query_and_wait( formatted_operation, job_config=config, page_size=self.arraysize, ) except google.cloud.exceptions.GoogleCloudError as exc: raise exceptions.DatabaseError(exc) self._query_rows = rows self._set_description(rows.schema) if config.dry_run: self.rowcount = 0 else: self._set_rowcount(rows) def executemany(self, operation, seq_of_parameters): """Prepare and execute a database operation multiple times. Args: operation (str): A Google BigQuery query string. seq_of_parameters (Union[Sequence[Mapping[str, Any], Sequence[Any]]]): Sequence of many sets of parameter values. """ if seq_of_parameters: rowcount = 0 # There's no reason to format the line more than once, as # the operation only barely depends on the parameters. So # we just use the first set of parameters. If there are # different numbers or types of parameters, we'll error # anyway. formatted_operation, parameter_types = _format_operation( operation, seq_of_parameters[0] ) for parameters in seq_of_parameters: self._execute( formatted_operation, parameters, None, None, parameter_types ) rowcount += self.rowcount self.rowcount = rowcount def _try_fetch(self, size=None): """Try to start fetching data, if not yet started. Mutates self to indicate that iteration has started. """ if self._query_data is not None: # Already started fetching the data. return rows = self._query_rows if rows is None: raise exceptions.InterfaceError( "No query results: execute() must be called before fetch." ) bqstorage_client = self.connection._bqstorage_client if rows._should_use_bqstorage( bqstorage_client, create_bqstorage_client=False, ): rows_iterable = self._bqstorage_fetch(bqstorage_client) self._query_data = _helpers.to_bq_table_rows(rows_iterable) return self._query_data = iter(rows) def _bqstorage_fetch(self, bqstorage_client): """Start fetching data with the BigQuery Storage API. The method assumes that the data about the relevant query job already exists internally. Args: bqstorage_client(\ google.cloud.bigquery_storage_v1.BigQueryReadClient \ ): A client tha know how to talk to the BigQuery Storage API. Returns: Iterable[Mapping]: A sequence of rows, represented as dictionaries. """ # Hitting this code path with a BQ Storage client instance implies that # bigquery_storage can indeed be imported here without errors. from google.cloud import bigquery_storage table_reference = self._query_rows._table requested_session = bigquery_storage.types.ReadSession( table=table_reference.to_bqstorage(), data_format=bigquery_storage.types.DataFormat.ARROW, ) if _ARROW_COMPRESSION_SUPPORT: requested_session.read_options.arrow_serialization_options.buffer_compression = ( ArrowSerializationOptions.CompressionCodec.LZ4_FRAME ) read_session = bqstorage_client.create_read_session( parent="projects/{}".format(table_reference.project), read_session=requested_session, # a single stream only, as DB API is not well-suited for multithreading max_stream_count=1, ) if not read_session.streams: return iter([]) # empty table, nothing to read stream_name = read_session.streams[0].name read_rows_stream = bqstorage_client.read_rows(stream_name) rows_iterable = read_rows_stream.rows(read_session) return rows_iterable def fetchone(self): """Fetch a single row from the results of the last ``execute*()`` call. .. note:: If a dry run query was executed, no rows are returned. Returns: Tuple: A tuple representing a row or ``None`` if no more data is available. Raises: google.cloud.bigquery.dbapi.InterfaceError: if called before ``execute()``. """ self._try_fetch() try: return next(self._query_data) except StopIteration: return None def fetchmany(self, size=None): """Fetch multiple results from the last ``execute*()`` call. .. note:: If a dry run query was executed, no rows are returned. .. note:: The size parameter is not used for the request/response size. Set the ``arraysize`` attribute before calling ``execute()`` to set the batch size. Args: size (int): (Optional) Maximum number of rows to return. Defaults to the ``arraysize`` property value. If ``arraysize`` is not set, it defaults to ``1``. Returns: List[Tuple]: A list of rows. Raises: google.cloud.bigquery.dbapi.InterfaceError: if called before ``execute()``. """ if size is None: # Since self.arraysize can be None (a deviation from PEP 249), # use an actual PEP 249 default of 1 in such case (*some* number # is needed here). size = self.arraysize if self.arraysize else 1 self._try_fetch(size=size) rows = [] for row in self._query_data: rows.append(row) if len(rows) >= size: break return rows def fetchall(self): """Fetch all remaining results from the last ``execute*()`` call. .. note:: If a dry run query was executed, no rows are returned. Returns: List[Tuple]: A list of all the rows in the results. Raises: google.cloud.bigquery.dbapi.InterfaceError: if called before ``execute()``. """ self._try_fetch() return list(self._query_data) def setinputsizes(self, sizes): """No-op, but for consistency raise an error if cursor is closed.""" def setoutputsize(self, size, column=None): """No-op, but for consistency raise an error if cursor is closed.""" def __iter__(self): self._try_fetch() return iter(self._query_data) def _format_operation_list(operation, parameters): """Formats parameters in operation in the way BigQuery expects. The input operation will be a query like ``SELECT %s`` and the output will be a query like ``SELECT ?``. Args: operation (str): A Google BigQuery query string. parameters (Sequence[Any]): Sequence of parameter values. Returns: str: A formatted query string. Raises: google.cloud.bigquery.dbapi.ProgrammingError: if a parameter used in the operation is not found in the ``parameters`` argument. """ formatted_params = ["?" for _ in parameters] try: return operation % tuple(formatted_params) except (TypeError, ValueError) as exc: raise exceptions.ProgrammingError(exc) def _format_operation_dict(operation, parameters): """Formats parameters in operation in the way BigQuery expects. The input operation will be a query like ``SELECT %(namedparam)s`` and the output will be a query like ``SELECT @namedparam``. Args: operation (str): A Google BigQuery query string. parameters (Mapping[str, Any]): Dictionary of parameter values. Returns: str: A formatted query string. Raises: google.cloud.bigquery.dbapi.ProgrammingError: if a parameter used in the operation is not found in the ``parameters`` argument. """ formatted_params = {} for name in parameters: escaped_name = name.replace("`", r"\`") formatted_params[name] = "@`{}`".format(escaped_name) try: return operation % formatted_params except (KeyError, ValueError, TypeError) as exc: raise exceptions.ProgrammingError(exc) def _format_operation(operation, parameters): """Formats parameters in operation in way BigQuery expects. Args: operation (str): A Google BigQuery query string. parameters (Union[Mapping[str, Any], Sequence[Any]]): Optional parameter values. Returns: str: A formatted query string. Raises: google.cloud.bigquery.dbapi.ProgrammingError: if a parameter used in the operation is not found in the ``parameters`` argument. """ if parameters is None or len(parameters) == 0: return operation.replace("%%", "%"), None # Still do percent de-escaping. operation, parameter_types = _extract_types(operation) if parameter_types is None: raise exceptions.ProgrammingError( f"Parameters were provided, but {repr(operation)} has no placeholders." ) if isinstance(parameters, collections_abc.Mapping): return _format_operation_dict(operation, parameters), parameter_types return _format_operation_list(operation, parameters), parameter_types def _extract_types( operation, extra_type_sub=re.compile( r""" (%*) # Extra %s. We'll deal with these in the replacement code % # Beginning of replacement, %s, %(...)s (?:\( # Begin of optional name and/or type ([^:)]*) # name (?:: # ':' introduces type ( # start of type group [a-zA-Z0-9_<>, ]+ # First part, no parens (?: # start sets of parens + non-paren text \([0-9 ,]+\) # comma-separated groups of digits in parens # (e.g. string(10)) (?=[, >)]) # Must be followed by ,>) or space [a-zA-Z0-9<>, ]* # Optional non-paren chars )* # Can be zero or more of parens and following text ) # end of type group )? # close type clause ":type" \))? # End of optional name and/or type s # End of replacement """, re.VERBOSE, ).sub, ): """Remove type information from parameter placeholders. For every parameter of the form %(name:type)s, replace with %(name)s and add the item name->type to dict that's returned. Returns operation without type information and a dictionary of names and types. """ parameter_types = None def repl(m): nonlocal parameter_types prefix, name, type_ = m.groups() if len(prefix) % 2: # The prefix has an odd number of %s, the last of which # escapes the % we're looking for, so we don't want to # change anything. return m.group(0) try: if name: if not parameter_types: parameter_types = {} if type_: if name in parameter_types: if type_ != parameter_types[name]: raise exceptions.ProgrammingError( f"Conflicting types for {name}: " f"{parameter_types[name]} and {type_}." ) else: parameter_types[name] = type_ else: if not isinstance(parameter_types, dict): raise TypeError() return f"{prefix}%({name})s" else: if parameter_types is None: parameter_types = [] parameter_types.append(type_) return f"{prefix}%s" except (AttributeError, TypeError): raise exceptions.ProgrammingError( f"{repr(operation)} mixes named and unamed parameters." ) return extra_type_sub(repl, operation), parameter_types