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Edit File: psycopg2.py
# postgresql/psycopg2.py # Copyright (C) 2005-2023 the SQLAlchemy authors and contributors # <see AUTHORS file> # # This module is part of SQLAlchemy and is released under # the MIT License: https://www.opensource.org/licenses/mit-license.php r""" .. dialect:: postgresql+psycopg2 :name: psycopg2 :dbapi: psycopg2 :connectstring: postgresql+psycopg2://user:password@host:port/dbname[?key=value&key=value...] :url: https://pypi.org/project/psycopg2/ psycopg2 Connect Arguments -------------------------- Keyword arguments that are specific to the SQLAlchemy psycopg2 dialect may be passed to :func:`_sa.create_engine()`, and include the following: * ``isolation_level``: This option, available for all PostgreSQL dialects, includes the ``AUTOCOMMIT`` isolation level when using the psycopg2 dialect. This option sets the **default** isolation level for the connection that is set immediately upon connection to the database before the connection is pooled. This option is generally superseded by the more modern :paramref:`_engine.Connection.execution_options.isolation_level` execution option, detailed at :ref:`dbapi_autocommit`. .. seealso:: :ref:`psycopg2_isolation_level` :ref:`dbapi_autocommit` * ``client_encoding``: sets the client encoding in a libpq-agnostic way, using psycopg2's ``set_client_encoding()`` method. .. seealso:: :ref:`psycopg2_unicode` * ``use_native_unicode``: Under Python 2 only, this can be set to False to disable the use of psycopg2's native Unicode support. .. seealso:: :ref:`psycopg2_disable_native_unicode` * ``executemany_mode``, ``executemany_batch_page_size``, ``executemany_values_page_size``: Allows use of psycopg2 extensions for optimizing "executemany"-style queries. See the referenced section below for details. .. seealso:: :ref:`psycopg2_executemany_mode` .. tip:: The above keyword arguments are **dialect** keyword arguments, meaning that they are passed as explicit keyword arguments to :func:`_sa.create_engine()`:: engine = create_engine( "postgresql+psycopg2://scott:tiger@localhost/test", isolation_level="SERIALIZABLE", ) These should not be confused with **DBAPI** connect arguments, which are passed as part of the :paramref:`_sa.create_engine.connect_args` dictionary and/or are passed in the URL query string, as detailed in the section :ref:`custom_dbapi_args`. .. _psycopg2_ssl: SSL Connections --------------- The psycopg2 module has a connection argument named ``sslmode`` for controlling its behavior regarding secure (SSL) connections. The default is ``sslmode=prefer``; it will attempt an SSL connection and if that fails it will fall back to an unencrypted connection. ``sslmode=require`` may be used to ensure that only secure connections are established. Consult the psycopg2 / libpq documentation for further options that are available. Note that ``sslmode`` is specific to psycopg2 so it is included in the connection URI:: engine = sa.create_engine( "postgresql+psycopg2://scott:tiger@192.168.0.199:5432/test?sslmode=require" ) Unix Domain Connections ------------------------ psycopg2 supports connecting via Unix domain connections. When the ``host`` portion of the URL is omitted, SQLAlchemy passes ``None`` to psycopg2, which specifies Unix-domain communication rather than TCP/IP communication:: create_engine("postgresql+psycopg2://user:password@/dbname") By default, the socket file used is to connect to a Unix-domain socket in ``/tmp``, or whatever socket directory was specified when PostgreSQL was built. This value can be overridden by passing a pathname to psycopg2, using ``host`` as an additional keyword argument:: create_engine("postgresql+psycopg2://user:password@/dbname?host=/var/lib/postgresql") .. seealso:: `PQconnectdbParams \ <https://www.postgresql.org/docs/current/static/libpq-connect.html#LIBPQ-PQCONNECTDBPARAMS>`_ .. _psycopg2_multi_host: Specifying multiple fallback hosts ----------------------------------- psycopg2 supports multiple connection points in the connection string. When the ``host`` parameter is used multiple times in the query section of the URL, SQLAlchemy will create a single string of the host and port information provided to make the connections. Tokens may consist of ``host::port`` or just ``host``; in the latter case, the default port is selected by libpq. In the example below, three host connections are specified, for ``HostA::PortA``, ``HostB`` connecting to the default port, and ``HostC::PortC``:: create_engine( "postgresql+psycopg2://user:password@/dbname?host=HostA:PortA&host=HostB&host=HostC:PortC" ) As an alternative, libpq query string format also may be used; this specifies ``host`` and ``port`` as single query string arguments with comma-separated lists - the default port can be chosen by indicating an empty value in the comma separated list:: create_engine( "postgresql+psycopg2://user:password@/dbname?host=HostA,HostB,HostC&port=PortA,,PortC" ) With either URL style, connections to each host is attempted based on a configurable strategy, which may be configured using the libpq ``target_session_attrs`` parameter. Per libpq this defaults to ``any`` which indicates a connection to each host is then attempted until a connection is successful. Other strategies include ``primary``, ``prefer-standby``, etc. The complete list is documented by PostgreSQL at `libpq connection strings <https://www.postgresql.org/docs/current/libpq-connect.html#LIBPQ-CONNSTRING>`_. For example, to indicate two hosts using the ``primary`` strategy:: create_engine( "postgresql+psycopg2://user:password@/dbname?host=HostA:PortA&host=HostB&host=HostC:PortC&target_session_attrs=primary" ) .. versionchanged:: 1.4.40 Port specification in psycopg2 multiple host format is repaired, previously ports were not correctly interpreted in this context. libpq comma-separated format is also now supported. .. versionadded:: 1.3.20 Support for multiple hosts in PostgreSQL connection string. .. seealso:: `libpq connection strings <https://www.postgresql.org/docs/current/libpq-connect.html#LIBPQ-CONNSTRING>`_ - please refer to this section in the libpq documentation for complete background on multiple host support. Empty DSN Connections / Environment Variable Connections --------------------------------------------------------- The psycopg2 DBAPI can connect to PostgreSQL by passing an empty DSN to the libpq client library, which by default indicates to connect to a localhost PostgreSQL database that is open for "trust" connections. This behavior can be further tailored using a particular set of environment variables which are prefixed with ``PG_...``, which are consumed by ``libpq`` to take the place of any or all elements of the connection string. For this form, the URL can be passed without any elements other than the initial scheme:: engine = create_engine('postgresql+psycopg2://') In the above form, a blank "dsn" string is passed to the ``psycopg2.connect()`` function which in turn represents an empty DSN passed to libpq. .. versionadded:: 1.3.2 support for parameter-less connections with psycopg2. .. seealso:: `Environment Variables\ <https://www.postgresql.org/docs/current/libpq-envars.html>`_ - PostgreSQL documentation on how to use ``PG_...`` environment variables for connections. .. _psycopg2_execution_options: Per-Statement/Connection Execution Options ------------------------------------------- The following DBAPI-specific options are respected when used with :meth:`_engine.Connection.execution_options`, :meth:`.Executable.execution_options`, :meth:`_query.Query.execution_options`, in addition to those not specific to DBAPIs: * ``isolation_level`` - Set the transaction isolation level for the lifespan of a :class:`_engine.Connection` (can only be set on a connection, not a statement or query). See :ref:`psycopg2_isolation_level`. * ``stream_results`` - Enable or disable usage of psycopg2 server side cursors - this feature makes use of "named" cursors in combination with special result handling methods so that result rows are not fully buffered. Defaults to False, meaning cursors are buffered by default. * ``max_row_buffer`` - when using ``stream_results``, an integer value that specifies the maximum number of rows to buffer at a time. This is interpreted by the :class:`.BufferedRowCursorResult`, and if omitted the buffer will grow to ultimately store 1000 rows at a time. .. versionchanged:: 1.4 The ``max_row_buffer`` size can now be greater than 1000, and the buffer will grow to that size. .. _psycopg2_batch_mode: .. _psycopg2_executemany_mode: Psycopg2 Fast Execution Helpers ------------------------------- Modern versions of psycopg2 include a feature known as `Fast Execution Helpers \ <https://initd.org/psycopg/docs/extras.html#fast-execution-helpers>`_, which have been shown in benchmarking to improve psycopg2's executemany() performance, primarily with INSERT statements, by multiple orders of magnitude. SQLAlchemy internally makes use of these extensions for ``executemany()`` style calls, which correspond to lists of parameters being passed to :meth:`_engine.Connection.execute` as detailed in :ref:`multiple parameter sets <tutorial_multiple_parameters>`. The ORM also uses this mode internally whenever possible. The two available extensions on the psycopg2 side are the ``execute_values()`` and ``execute_batch()`` functions. The psycopg2 dialect defaults to using the ``execute_values()`` extension for all qualifying INSERT statements. .. versionchanged:: 1.4 The psycopg2 dialect now defaults to a new mode ``"values_only"`` for ``executemany_mode``, which allows an order of magnitude performance improvement for INSERT statements, but does not include "batch" mode for UPDATE and DELETE statements which removes the ability of ``cursor.rowcount`` to function correctly. The use of these extensions is controlled by the ``executemany_mode`` flag which may be passed to :func:`_sa.create_engine`:: engine = create_engine( "postgresql+psycopg2://scott:tiger@host/dbname", executemany_mode='values_plus_batch') Possible options for ``executemany_mode`` include: * ``values_only`` - this is the default value. the psycopg2 execute_values() extension is used for qualifying INSERT statements, which rewrites the INSERT to include multiple VALUES clauses so that many parameter sets can be inserted with one statement. .. versionadded:: 1.4 Added ``"values_only"`` setting for ``executemany_mode`` which is also now the default. * ``None`` - No psycopg2 extensions are not used, and the usual ``cursor.executemany()`` method is used when invoking statements with multiple parameter sets. * ``'batch'`` - Uses ``psycopg2.extras.execute_batch`` for all qualifying INSERT, UPDATE and DELETE statements, so that multiple copies of a SQL query, each one corresponding to a parameter set passed to ``executemany()``, are joined into a single SQL string separated by a semicolon. When using this mode, the :attr:`_engine.CursorResult.rowcount` attribute will not contain a value for executemany-style executions. * ``'values_plus_batch'``- ``execute_values`` is used for qualifying INSERT statements, ``execute_batch`` is used for UPDATE and DELETE. When using this mode, the :attr:`_engine.CursorResult.rowcount` attribute will not contain a value for executemany-style executions against UPDATE and DELETE statements. By "qualifying statements", we mean that the statement being executed must be a Core :func:`_expression.insert`, :func:`_expression.update` or :func:`_expression.delete` construct, and not a plain textual SQL string or one constructed using :func:`_expression.text`. When using the ORM, all insert/update/delete statements used by the ORM flush process are qualifying. The "page size" for the "values" and "batch" strategies can be affected by using the ``executemany_batch_page_size`` and ``executemany_values_page_size`` engine parameters. These control how many parameter sets should be represented in each execution. The "values" page size defaults to 1000, which is different that psycopg2's default. The "batch" page size defaults to 100. These can be affected by passing new values to :func:`_engine.create_engine`:: engine = create_engine( "postgresql+psycopg2://scott:tiger@host/dbname", executemany_mode='values', executemany_values_page_size=10000, executemany_batch_page_size=500) .. versionchanged:: 1.4 The default for ``executemany_values_page_size`` is now 1000, up from 100. .. seealso:: :ref:`tutorial_multiple_parameters` - General information on using the :class:`_engine.Connection` object to execute statements in such a way as to make use of the DBAPI ``.executemany()`` method. .. _psycopg2_unicode: Unicode with Psycopg2 ---------------------- The psycopg2 DBAPI driver supports Unicode data transparently. Under Python 2 only, the SQLAlchemy psycopg2 dialect will enable the ``psycopg2.extensions.UNICODE`` extension by default to ensure Unicode is handled properly; under Python 3, this is psycopg2's default behavior. The client character encoding can be controlled for the psycopg2 dialect in the following ways: * For PostgreSQL 9.1 and above, the ``client_encoding`` parameter may be passed in the database URL; this parameter is consumed by the underlying ``libpq`` PostgreSQL client library:: engine = create_engine("postgresql+psycopg2://user:pass@host/dbname?client_encoding=utf8") Alternatively, the above ``client_encoding`` value may be passed using :paramref:`_sa.create_engine.connect_args` for programmatic establishment with ``libpq``:: engine = create_engine( "postgresql+psycopg2://user:pass@host/dbname", connect_args={'client_encoding': 'utf8'} ) * For all PostgreSQL versions, psycopg2 supports a client-side encoding value that will be passed to database connections when they are first established. The SQLAlchemy psycopg2 dialect supports this using the ``client_encoding`` parameter passed to :func:`_sa.create_engine`:: engine = create_engine( "postgresql+psycopg2://user:pass@host/dbname", client_encoding="utf8" ) .. tip:: The above ``client_encoding`` parameter admittedly is very similar in appearance to usage of the parameter within the :paramref:`_sa.create_engine.connect_args` dictionary; the difference above is that the parameter is consumed by psycopg2 and is passed to the database connection using ``SET client_encoding TO 'utf8'``; in the previously mentioned style, the parameter is instead passed through psycopg2 and consumed by the ``libpq`` library. * A common way to set up client encoding with PostgreSQL databases is to ensure it is configured within the server-side postgresql.conf file; this is the recommended way to set encoding for a server that is consistently of one encoding in all databases:: # postgresql.conf file # client_encoding = sql_ascii # actually, defaults to database # encoding client_encoding = utf8 .. _psycopg2_disable_native_unicode: Disabling Native Unicode ^^^^^^^^^^^^^^^^^^^^^^^^ Under Python 2 only, SQLAlchemy can also be instructed to skip the usage of the psycopg2 ``UNICODE`` extension and to instead utilize its own unicode encode/decode services, which are normally reserved only for those DBAPIs that don't fully support unicode directly. Passing ``use_native_unicode=False`` to :func:`_sa.create_engine` will disable usage of ``psycopg2.extensions. UNICODE``. SQLAlchemy will instead encode data itself into Python bytestrings on the way in and coerce from bytes on the way back, using the value of the :func:`_sa.create_engine` ``encoding`` parameter, which defaults to ``utf-8``. SQLAlchemy's own unicode encode/decode functionality is steadily becoming obsolete as most DBAPIs now support unicode fully. Transactions ------------ The psycopg2 dialect fully supports SAVEPOINT and two-phase commit operations. .. _psycopg2_isolation_level: Psycopg2 Transaction Isolation Level ------------------------------------- As discussed in :ref:`postgresql_isolation_level`, all PostgreSQL dialects support setting of transaction isolation level both via the ``isolation_level`` parameter passed to :func:`_sa.create_engine` , as well as the ``isolation_level`` argument used by :meth:`_engine.Connection.execution_options`. When using the psycopg2 dialect , these options make use of psycopg2's ``set_isolation_level()`` connection method, rather than emitting a PostgreSQL directive; this is because psycopg2's API-level setting is always emitted at the start of each transaction in any case. The psycopg2 dialect supports these constants for isolation level: * ``READ COMMITTED`` * ``READ UNCOMMITTED`` * ``REPEATABLE READ`` * ``SERIALIZABLE`` * ``AUTOCOMMIT`` .. seealso:: :ref:`postgresql_isolation_level` :ref:`pg8000_isolation_level` NOTICE logging --------------- The psycopg2 dialect will log PostgreSQL NOTICE messages via the ``sqlalchemy.dialects.postgresql`` logger. When this logger is set to the ``logging.INFO`` level, notice messages will be logged:: import logging logging.getLogger('sqlalchemy.dialects.postgresql').setLevel(logging.INFO) Above, it is assumed that logging is configured externally. If this is not the case, configuration such as ``logging.basicConfig()`` must be utilized:: import logging logging.basicConfig() # log messages to stdout logging.getLogger('sqlalchemy.dialects.postgresql').setLevel(logging.INFO) .. seealso:: `Logging HOWTO <https://docs.python.org/3/howto/logging.html>`_ - on the python.org website .. _psycopg2_hstore: HSTORE type ------------ The ``psycopg2`` DBAPI includes an extension to natively handle marshalling of the HSTORE type. The SQLAlchemy psycopg2 dialect will enable this extension by default when psycopg2 version 2.4 or greater is used, and it is detected that the target database has the HSTORE type set up for use. In other words, when the dialect makes the first connection, a sequence like the following is performed: 1. Request the available HSTORE oids using ``psycopg2.extras.HstoreAdapter.get_oids()``. If this function returns a list of HSTORE identifiers, we then determine that the ``HSTORE`` extension is present. This function is **skipped** if the version of psycopg2 installed is less than version 2.4. 2. If the ``use_native_hstore`` flag is at its default of ``True``, and we've detected that ``HSTORE`` oids are available, the ``psycopg2.extensions.register_hstore()`` extension is invoked for all connections. The ``register_hstore()`` extension has the effect of **all Python dictionaries being accepted as parameters regardless of the type of target column in SQL**. The dictionaries are converted by this extension into a textual HSTORE expression. If this behavior is not desired, disable the use of the hstore extension by setting ``use_native_hstore`` to ``False`` as follows:: engine = create_engine("postgresql+psycopg2://scott:tiger@localhost/test", use_native_hstore=False) The ``HSTORE`` type is **still supported** when the ``psycopg2.extensions.register_hstore()`` extension is not used. It merely means that the coercion between Python dictionaries and the HSTORE string format, on both the parameter side and the result side, will take place within SQLAlchemy's own marshalling logic, and not that of ``psycopg2`` which may be more performant. """ # noqa from __future__ import absolute_import import decimal import logging import re from uuid import UUID as _python_UUID from .array import ARRAY as PGARRAY from .base import _ColonCast from .base import _DECIMAL_TYPES from .base import _FLOAT_TYPES from .base import _INT_TYPES from .base import ENUM from .base import PGCompiler from .base import PGDialect from .base import PGExecutionContext from .base import PGIdentifierPreparer from .base import UUID from .hstore import HSTORE from .json import JSON from .json import JSONB from ... import exc from ... import processors from ... import types as sqltypes from ... import util from ...engine import cursor as _cursor from ...util import collections_abc logger = logging.getLogger("sqlalchemy.dialects.postgresql") class _PGNumeric(sqltypes.Numeric): def bind_processor(self, dialect): return None def result_processor(self, dialect, coltype): if self.asdecimal: if coltype in _FLOAT_TYPES: return processors.to_decimal_processor_factory( decimal.Decimal, self._effective_decimal_return_scale ) elif coltype in _DECIMAL_TYPES or coltype in _INT_TYPES: # pg8000 returns Decimal natively for 1700 return None else: raise exc.InvalidRequestError( "Unknown PG numeric type: %d" % coltype ) else: if coltype in _FLOAT_TYPES: # pg8000 returns float natively for 701 return None elif coltype in _DECIMAL_TYPES or coltype in _INT_TYPES: return processors.to_float else: raise exc.InvalidRequestError( "Unknown PG numeric type: %d" % coltype ) class _PGEnum(ENUM): def result_processor(self, dialect, coltype): if util.py2k and self._expect_unicode is True: # for py2k, if the enum type needs unicode data (which is set up as # part of the Enum() constructor based on values passed as py2k # unicode objects) we have to use our own converters since # psycopg2's don't work, a rare exception to the "modern DBAPIs # support unicode everywhere" theme of deprecating # convert_unicode=True. Use the special "force_nocheck" directive # which forces unicode conversion to happen on the Python side # without an isinstance() check. in py3k psycopg2 does the right # thing automatically. self._expect_unicode = "force_nocheck" return super(_PGEnum, self).result_processor(dialect, coltype) class _PGHStore(HSTORE): def bind_processor(self, dialect): if dialect._has_native_hstore: return None else: return super(_PGHStore, self).bind_processor(dialect) def result_processor(self, dialect, coltype): if dialect._has_native_hstore: return None else: return super(_PGHStore, self).result_processor(dialect, coltype) class _PGARRAY(PGARRAY): def bind_expression(self, bindvalue): return _ColonCast(bindvalue, self) class _PGJSON(JSON): def result_processor(self, dialect, coltype): return None class _PGJSONB(JSONB): def result_processor(self, dialect, coltype): return None class _PGUUID(UUID): def bind_processor(self, dialect): if not self.as_uuid and dialect.use_native_uuid: def process(value): if value is not None: value = _python_UUID(value) return value return process def result_processor(self, dialect, coltype): if not self.as_uuid and dialect.use_native_uuid: def process(value): if value is not None: value = str(value) return value return process _server_side_id = util.counter() class PGExecutionContext_psycopg2(PGExecutionContext): _psycopg2_fetched_rows = None def create_server_side_cursor(self): # use server-side cursors: # https://lists.initd.org/pipermail/psycopg/2007-January/005251.html ident = "c_%s_%s" % (hex(id(self))[2:], hex(_server_side_id())[2:]) return self._dbapi_connection.cursor(ident) def post_exec(self): if ( self._psycopg2_fetched_rows and self.compiled and self.compiled.returning ): # psycopg2 execute_values will provide for a real cursor where # cursor.description works correctly. however, it executes the # INSERT statement multiple times for multiple pages of rows, so # while this cursor also supports calling .fetchall() directly, in # order to get the list of all rows inserted across multiple pages, # we have to retrieve the aggregated list from the execute_values() # function directly. strat_cls = _cursor.FullyBufferedCursorFetchStrategy self.cursor_fetch_strategy = strat_cls( self.cursor, initial_buffer=self._psycopg2_fetched_rows ) self._log_notices(self.cursor) def _log_notices(self, cursor): # check also that notices is an iterable, after it's already # established that we will be iterating through it. This is to get # around test suites such as SQLAlchemy's using a Mock object for # cursor if not cursor.connection.notices or not isinstance( cursor.connection.notices, collections_abc.Iterable ): return for notice in cursor.connection.notices: # NOTICE messages have a # newline character at the end logger.info(notice.rstrip()) cursor.connection.notices[:] = [] class PGCompiler_psycopg2(PGCompiler): pass class PGIdentifierPreparer_psycopg2(PGIdentifierPreparer): pass EXECUTEMANY_PLAIN = util.symbol("executemany_plain", canonical=0) EXECUTEMANY_BATCH = util.symbol("executemany_batch", canonical=1) EXECUTEMANY_VALUES = util.symbol("executemany_values", canonical=2) EXECUTEMANY_VALUES_PLUS_BATCH = util.symbol( "executemany_values_plus_batch", canonical=EXECUTEMANY_BATCH | EXECUTEMANY_VALUES, ) class PGDialect_psycopg2(PGDialect): driver = "psycopg2" supports_statement_cache = True if util.py2k: # turn off supports_unicode_statements for Python 2. psycopg2 supports # unicode statements in Py2K. But! it does not support unicode *bound # parameter names* because it uses the Python "%" operator to # interpolate these into the string, and this fails. So for Py2K, we # have to use full-on encoding for statements and parameters before # passing to cursor.execute(). supports_unicode_statements = False supports_server_side_cursors = True default_paramstyle = "pyformat" # set to true based on psycopg2 version supports_sane_multi_rowcount = False execution_ctx_cls = PGExecutionContext_psycopg2 statement_compiler = PGCompiler_psycopg2 preparer = PGIdentifierPreparer_psycopg2 psycopg2_version = (0, 0) _has_native_hstore = True engine_config_types = PGDialect.engine_config_types.union( {"use_native_unicode": util.asbool} ) colspecs = util.update_copy( PGDialect.colspecs, { sqltypes.Numeric: _PGNumeric, ENUM: _PGEnum, # needs force_unicode sqltypes.Enum: _PGEnum, # needs force_unicode HSTORE: _PGHStore, JSON: _PGJSON, sqltypes.JSON: _PGJSON, JSONB: _PGJSONB, UUID: _PGUUID, sqltypes.ARRAY: _PGARRAY, }, ) def __init__( self, use_native_unicode=True, client_encoding=None, use_native_hstore=True, use_native_uuid=True, executemany_mode="values_only", executemany_batch_page_size=100, executemany_values_page_size=1000, **kwargs ): PGDialect.__init__(self, **kwargs) self.use_native_unicode = use_native_unicode if not use_native_unicode and not util.py2k: raise exc.ArgumentError( "psycopg2 native_unicode mode is required under Python 3" ) if not use_native_hstore: self._has_native_hstore = False self.use_native_hstore = use_native_hstore self.use_native_uuid = use_native_uuid self.supports_unicode_binds = use_native_unicode self.client_encoding = client_encoding # Parse executemany_mode argument, allowing it to be only one of the # symbol names self.executemany_mode = util.symbol.parse_user_argument( executemany_mode, { EXECUTEMANY_PLAIN: [None], EXECUTEMANY_BATCH: ["batch"], EXECUTEMANY_VALUES: ["values_only"], EXECUTEMANY_VALUES_PLUS_BATCH: ["values_plus_batch", "values"], }, "executemany_mode", ) if self.executemany_mode & EXECUTEMANY_VALUES: self.insert_executemany_returning = True self.executemany_batch_page_size = executemany_batch_page_size self.executemany_values_page_size = executemany_values_page_size if self.dbapi and hasattr(self.dbapi, "__version__"): m = re.match(r"(\d+)\.(\d+)(?:\.(\d+))?", self.dbapi.__version__) if m: self.psycopg2_version = tuple( int(x) for x in m.group(1, 2, 3) if x is not None ) if self.psycopg2_version < (2, 7): raise ImportError( "psycopg2 version 2.7 or higher is required." ) def initialize(self, connection): super(PGDialect_psycopg2, self).initialize(connection) self._has_native_hstore = ( self.use_native_hstore and self._hstore_oids(connection.connection) is not None ) # PGDialect.initialize() checks server version for <= 8.2 and sets # this flag to False if so if not self.full_returning: self.insert_executemany_returning = False self.executemany_mode = EXECUTEMANY_PLAIN self.supports_sane_multi_rowcount = not ( self.executemany_mode & EXECUTEMANY_BATCH ) @classmethod def dbapi(cls): import psycopg2 return psycopg2 @classmethod def _psycopg2_extensions(cls): from psycopg2 import extensions return extensions @classmethod def _psycopg2_extras(cls): from psycopg2 import extras return extras @util.memoized_property def _isolation_lookup(self): extensions = self._psycopg2_extensions() return { "AUTOCOMMIT": extensions.ISOLATION_LEVEL_AUTOCOMMIT, "READ COMMITTED": extensions.ISOLATION_LEVEL_READ_COMMITTED, "READ UNCOMMITTED": extensions.ISOLATION_LEVEL_READ_UNCOMMITTED, "REPEATABLE READ": extensions.ISOLATION_LEVEL_REPEATABLE_READ, "SERIALIZABLE": extensions.ISOLATION_LEVEL_SERIALIZABLE, } def set_isolation_level(self, connection, level): try: level = self._isolation_lookup[level.replace("_", " ")] except KeyError as err: util.raise_( exc.ArgumentError( "Invalid value '%s' for isolation_level. " "Valid isolation levels for %s are %s" % (level, self.name, ", ".join(self._isolation_lookup)) ), replace_context=err, ) connection.set_isolation_level(level) def set_readonly(self, connection, value): connection.readonly = value def get_readonly(self, connection): return connection.readonly def set_deferrable(self, connection, value): connection.deferrable = value def get_deferrable(self, connection): return connection.deferrable def do_ping(self, dbapi_connection): cursor = None before_autocommit = dbapi_connection.autocommit try: if not before_autocommit: dbapi_connection.autocommit = True cursor = dbapi_connection.cursor() try: cursor.execute(self._dialect_specific_select_one) finally: cursor.close() if not before_autocommit and not dbapi_connection.closed: dbapi_connection.autocommit = before_autocommit except self.dbapi.Error as err: if self.is_disconnect(err, dbapi_connection, cursor): return False else: raise else: return True def on_connect(self): extras = self._psycopg2_extras() extensions = self._psycopg2_extensions() fns = [] if self.client_encoding is not None: def on_connect(conn): conn.set_client_encoding(self.client_encoding) fns.append(on_connect) if self.isolation_level is not None: def on_connect(conn): self.set_isolation_level(conn, self.isolation_level) fns.append(on_connect) if self.dbapi and self.use_native_uuid: def on_connect(conn): extras.register_uuid(None, conn) fns.append(on_connect) if util.py2k and self.dbapi and self.use_native_unicode: def on_connect(conn): extensions.register_type(extensions.UNICODE, conn) extensions.register_type(extensions.UNICODEARRAY, conn) fns.append(on_connect) if self.dbapi and self.use_native_hstore: def on_connect(conn): hstore_oids = self._hstore_oids(conn) if hstore_oids is not None: oid, array_oid = hstore_oids kw = {"oid": oid} if util.py2k: kw["unicode"] = True kw["array_oid"] = array_oid extras.register_hstore(conn, **kw) fns.append(on_connect) if self.dbapi and self._json_deserializer: def on_connect(conn): extras.register_default_json( conn, loads=self._json_deserializer ) extras.register_default_jsonb( conn, loads=self._json_deserializer ) fns.append(on_connect) if fns: def on_connect(conn): for fn in fns: fn(conn) return on_connect else: return None def do_executemany(self, cursor, statement, parameters, context=None): if ( self.executemany_mode & EXECUTEMANY_VALUES and context and context.isinsert and context.compiled._is_safe_for_fast_insert_values_helper ): executemany_values = ( "(%s)" % context.compiled.insert_single_values_expr ) if not self.supports_unicode_statements: executemany_values = executemany_values.encode(self.encoding) # guard for statement that was altered via event hook or similar if executemany_values not in statement: executemany_values = None else: executemany_values = None if executemany_values: statement = statement.replace(executemany_values, "%s") if self.executemany_values_page_size: kwargs = {"page_size": self.executemany_values_page_size} else: kwargs = {} xtras = self._psycopg2_extras() context._psycopg2_fetched_rows = xtras.execute_values( cursor, statement, parameters, template=executemany_values, fetch=bool(context.compiled.returning), **kwargs ) elif self.executemany_mode & EXECUTEMANY_BATCH: if self.executemany_batch_page_size: kwargs = {"page_size": self.executemany_batch_page_size} else: kwargs = {} self._psycopg2_extras().execute_batch( cursor, statement, parameters, **kwargs ) else: cursor.executemany(statement, parameters) @util.memoized_instancemethod def _hstore_oids(self, conn): extras = self._psycopg2_extras() if hasattr(conn, "dbapi_connection"): conn = conn.dbapi_connection oids = extras.HstoreAdapter.get_oids(conn) if oids is not None and oids[0]: return oids[0:2] else: return None def create_connect_args(self, url): opts = url.translate_connect_args(username="user") is_multihost = False if "host" in url.query: is_multihost = isinstance(url.query["host"], (list, tuple)) if opts or url.query: if not opts: opts = {} if "port" in opts: opts["port"] = int(opts["port"]) opts.update(url.query) if is_multihost: hosts, ports = zip( *[ token.split(":") if ":" in token else (token, "") for token in url.query["host"] ] ) opts["host"] = ",".join(hosts) if "port" in opts: raise exc.ArgumentError( "Can't mix 'multihost' formats together; use " '"host=h1,h2,h3&port=p1,p2,p3" or ' '"host=h1:p1&host=h2:p2&host=h3:p3" separately' ) opts["port"] = ",".join(ports) return ([], opts) else: # no connection arguments whatsoever; psycopg2.connect() # requires that "dsn" be present as a blank string. return ([""], opts) def is_disconnect(self, e, connection, cursor): if isinstance(e, self.dbapi.Error): # check the "closed" flag. this might not be # present on old psycopg2 versions. Also, # this flag doesn't actually help in a lot of disconnect # situations, so don't rely on it. if getattr(connection, "closed", False): return True # checks based on strings. in the case that .closed # didn't cut it, fall back onto these. str_e = str(e).partition("\n")[0] for msg in [ # these error messages from libpq: interfaces/libpq/fe-misc.c # and interfaces/libpq/fe-secure.c. "terminating connection", "closed the connection", "connection not open", "could not receive data from server", "could not send data to server", # psycopg2 client errors, psycopg2/connection.h, # psycopg2/cursor.h "connection already closed", "cursor already closed", # not sure where this path is originally from, it may # be obsolete. It really says "losed", not "closed". "losed the connection unexpectedly", # these can occur in newer SSL "connection has been closed unexpectedly", "SSL error: decryption failed or bad record mac", "SSL SYSCALL error: Bad file descriptor", "SSL SYSCALL error: EOF detected", "SSL SYSCALL error: Operation timed out", "SSL SYSCALL error: Bad address", ]: idx = str_e.find(msg) if idx >= 0 and '"' not in str_e[:idx]: return True return False dialect = PGDialect_psycopg2