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Qichao
2023-10-08 20:59:00 +08:00
parent b494be364b
commit 1dac226337
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lib/sqlalchemy/dialects/mssql/__init__.py Normal file
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# mssql/__init__.py
# Copyright (C) 2005-2022 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
from . import base # noqa
from . import mxodbc # noqa
from . import pymssql # noqa
from . import pyodbc # noqa
from .base import BIGINT
from .base import BINARY
from .base import BIT
from .base import CHAR
from .base import DATE
from .base import DATETIME
from .base import DATETIME2
from .base import DATETIMEOFFSET
from .base import DECIMAL
from .base import FLOAT
from .base import IMAGE
from .base import INTEGER
from .base import JSON
from .base import MONEY
from .base import NCHAR
from .base import NTEXT
from .base import NUMERIC
from .base import NVARCHAR
from .base import REAL
from .base import ROWVERSION
from .base import SMALLDATETIME
from .base import SMALLINT
from .base import SMALLMONEY
from .base import SQL_VARIANT
from .base import TEXT
from .base import TIME
from .base import TIMESTAMP
from .base import TINYINT
from .base import try_cast
from .base import UNIQUEIDENTIFIER
from .base import VARBINARY
from .base import VARCHAR
from .base import XML
base.dialect = dialect = pyodbc.dialect
__all__ = (
"JSON",
"INTEGER",
"BIGINT",
"SMALLINT",
"TINYINT",
"VARCHAR",
"NVARCHAR",
"CHAR",
"NCHAR",
"TEXT",
"NTEXT",
"DECIMAL",
"NUMERIC",
"FLOAT",
"DATETIME",
"DATETIME2",
"DATETIMEOFFSET",
"DATE",
"TIME",
"SMALLDATETIME",
"BINARY",
"VARBINARY",
"BIT",
"REAL",
"IMAGE",
"TIMESTAMP",
"ROWVERSION",
"MONEY",
"SMALLMONEY",
"UNIQUEIDENTIFIER",
"SQL_VARIANT",
"XML",
"dialect",
"try_cast",
)

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lib/sqlalchemy/dialects/mssql/base.py Normal file
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lib/sqlalchemy/dialects/mssql/information_schema.py Normal file
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# mssql/information_schema.py
# Copyright (C) 2005-2022 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
from ... import cast
from ... import Column
from ... import MetaData
from ... import Table
from ... import util
from ...ext.compiler import compiles
from ...sql import expression
from ...types import Boolean
from ...types import Integer
from ...types import Numeric
from ...types import String
from ...types import TypeDecorator
from ...types import Unicode
ischema = MetaData()
class CoerceUnicode(TypeDecorator):
impl = Unicode
cache_ok = True
def process_bind_param(self, value, dialect):
if util.py2k and isinstance(value, util.binary_type):
value = value.decode(dialect.encoding)
return value
def bind_expression(self, bindvalue):
return _cast_on_2005(bindvalue)
class _cast_on_2005(expression.ColumnElement):
def __init__(self, bindvalue):
self.bindvalue = bindvalue
@compiles(_cast_on_2005)
def _compile(element, compiler, **kw):
from . import base
if (
compiler.dialect.server_version_info is None
or compiler.dialect.server_version_info < base.MS_2005_VERSION
):
return compiler.process(element.bindvalue, **kw)
else:
return compiler.process(cast(element.bindvalue, Unicode), **kw)
schemata = Table(
"SCHEMATA",
ischema,
Column("CATALOG_NAME", CoerceUnicode, key="catalog_name"),
Column("SCHEMA_NAME", CoerceUnicode, key="schema_name"),
Column("SCHEMA_OWNER", CoerceUnicode, key="schema_owner"),
schema="INFORMATION_SCHEMA",
)
tables = Table(
"TABLES",
ischema,
Column("TABLE_CATALOG", CoerceUnicode, key="table_catalog"),
Column("TABLE_SCHEMA", CoerceUnicode, key="table_schema"),
Column("TABLE_NAME", CoerceUnicode, key="table_name"),
Column("TABLE_TYPE", CoerceUnicode, key="table_type"),
schema="INFORMATION_SCHEMA",
)
columns = Table(
"COLUMNS",
ischema,
Column("TABLE_SCHEMA", CoerceUnicode, key="table_schema"),
Column("TABLE_NAME", CoerceUnicode, key="table_name"),
Column("COLUMN_NAME", CoerceUnicode, key="column_name"),
Column("IS_NULLABLE", Integer, key="is_nullable"),
Column("DATA_TYPE", String, key="data_type"),
Column("ORDINAL_POSITION", Integer, key="ordinal_position"),
Column(
"CHARACTER_MAXIMUM_LENGTH", Integer, key="character_maximum_length"
),
Column("NUMERIC_PRECISION", Integer, key="numeric_precision"),
Column("NUMERIC_SCALE", Integer, key="numeric_scale"),
Column("COLUMN_DEFAULT", Integer, key="column_default"),
Column("COLLATION_NAME", String, key="collation_name"),
schema="INFORMATION_SCHEMA",
)
mssql_temp_table_columns = Table(
"COLUMNS",
ischema,
Column("TABLE_SCHEMA", CoerceUnicode, key="table_schema"),
Column("TABLE_NAME", CoerceUnicode, key="table_name"),
Column("COLUMN_NAME", CoerceUnicode, key="column_name"),
Column("IS_NULLABLE", Integer, key="is_nullable"),
Column("DATA_TYPE", String, key="data_type"),
Column("ORDINAL_POSITION", Integer, key="ordinal_position"),
Column(
"CHARACTER_MAXIMUM_LENGTH", Integer, key="character_maximum_length"
),
Column("NUMERIC_PRECISION", Integer, key="numeric_precision"),
Column("NUMERIC_SCALE", Integer, key="numeric_scale"),
Column("COLUMN_DEFAULT", Integer, key="column_default"),
Column("COLLATION_NAME", String, key="collation_name"),
schema="tempdb.INFORMATION_SCHEMA",
)
constraints = Table(
"TABLE_CONSTRAINTS",
ischema,
Column("TABLE_SCHEMA", CoerceUnicode, key="table_schema"),
Column("TABLE_NAME", CoerceUnicode, key="table_name"),
Column("CONSTRAINT_NAME", CoerceUnicode, key="constraint_name"),
Column("CONSTRAINT_TYPE", CoerceUnicode, key="constraint_type"),
schema="INFORMATION_SCHEMA",
)
column_constraints = Table(
"CONSTRAINT_COLUMN_USAGE",
ischema,
Column("TABLE_SCHEMA", CoerceUnicode, key="table_schema"),
Column("TABLE_NAME", CoerceUnicode, key="table_name"),
Column("COLUMN_NAME", CoerceUnicode, key="column_name"),
Column("CONSTRAINT_NAME", CoerceUnicode, key="constraint_name"),
schema="INFORMATION_SCHEMA",
)
key_constraints = Table(
"KEY_COLUMN_USAGE",
ischema,
Column("TABLE_SCHEMA", CoerceUnicode, key="table_schema"),
Column("TABLE_NAME", CoerceUnicode, key="table_name"),
Column("COLUMN_NAME", CoerceUnicode, key="column_name"),
Column("CONSTRAINT_NAME", CoerceUnicode, key="constraint_name"),
Column("CONSTRAINT_SCHEMA", CoerceUnicode, key="constraint_schema"),
Column("ORDINAL_POSITION", Integer, key="ordinal_position"),
schema="INFORMATION_SCHEMA",
)
ref_constraints = Table(
"REFERENTIAL_CONSTRAINTS",
ischema,
Column("CONSTRAINT_CATALOG", CoerceUnicode, key="constraint_catalog"),
Column("CONSTRAINT_SCHEMA", CoerceUnicode, key="constraint_schema"),
Column("CONSTRAINT_NAME", CoerceUnicode, key="constraint_name"),
# TODO: is CATLOG misspelled ?
Column(
"UNIQUE_CONSTRAINT_CATLOG",
CoerceUnicode,
key="unique_constraint_catalog",
),
Column(
"UNIQUE_CONSTRAINT_SCHEMA",
CoerceUnicode,
key="unique_constraint_schema",
),
Column(
"UNIQUE_CONSTRAINT_NAME", CoerceUnicode, key="unique_constraint_name"
),
Column("MATCH_OPTION", String, key="match_option"),
Column("UPDATE_RULE", String, key="update_rule"),
Column("DELETE_RULE", String, key="delete_rule"),
schema="INFORMATION_SCHEMA",
)
views = Table(
"VIEWS",
ischema,
Column("TABLE_CATALOG", CoerceUnicode, key="table_catalog"),
Column("TABLE_SCHEMA", CoerceUnicode, key="table_schema"),
Column("TABLE_NAME", CoerceUnicode, key="table_name"),
Column("VIEW_DEFINITION", CoerceUnicode, key="view_definition"),
Column("CHECK_OPTION", String, key="check_option"),
Column("IS_UPDATABLE", String, key="is_updatable"),
schema="INFORMATION_SCHEMA",
)
computed_columns = Table(
"computed_columns",
ischema,
Column("object_id", Integer),
Column("name", CoerceUnicode),
Column("is_computed", Boolean),
Column("is_persisted", Boolean),
Column("definition", CoerceUnicode),
schema="sys",
)
sequences = Table(
"SEQUENCES",
ischema,
Column("SEQUENCE_CATALOG", CoerceUnicode, key="sequence_catalog"),
Column("SEQUENCE_SCHEMA", CoerceUnicode, key="sequence_schema"),
Column("SEQUENCE_NAME", CoerceUnicode, key="sequence_name"),
schema="INFORMATION_SCHEMA",
)
class IdentitySqlVariant(TypeDecorator):
r"""This type casts sql_variant columns in the identity_columns view
to numeric. This is required because:
* pyodbc does not support sql_variant
* pymssql under python 2 return the byte representation of the number,
int 1 is returned as "\x01\x00\x00\x00". On python 3 it returns the
correct value as string.
"""
impl = Unicode
cache_ok = True
def column_expression(self, colexpr):
return cast(colexpr, Numeric)
identity_columns = Table(
"identity_columns",
ischema,
Column("object_id", Integer),
Column("name", CoerceUnicode),
Column("is_identity", Boolean),
Column("seed_value", IdentitySqlVariant),
Column("increment_value", IdentitySqlVariant),
Column("last_value", IdentitySqlVariant),
Column("is_not_for_replication", Boolean),
schema="sys",
)

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from ... import types as sqltypes
# technically, all the dialect-specific datatypes that don't have any special
# behaviors would be private with names like _MSJson. However, we haven't been
# doing this for mysql.JSON or sqlite.JSON which both have JSON / JSONIndexType
# / JSONPathType in their json.py files, so keep consistent with that
# sub-convention for now. A future change can update them all to be
# package-private at once.
class JSON(sqltypes.JSON):
"""MSSQL JSON type.
MSSQL supports JSON-formatted data as of SQL Server 2016.
The :class:`_mssql.JSON` datatype at the DDL level will represent the
datatype as ``NVARCHAR(max)``, but provides for JSON-level comparison
functions as well as Python coercion behavior.
:class:`_mssql.JSON` is used automatically whenever the base
:class:`_types.JSON` datatype is used against a SQL Server backend.
.. seealso::
:class:`_types.JSON` - main documentation for the generic
cross-platform JSON datatype.
The :class:`_mssql.JSON` type supports persistence of JSON values
as well as the core index operations provided by :class:`_types.JSON`
datatype, by adapting the operations to render the ``JSON_VALUE``
or ``JSON_QUERY`` functions at the database level.
The SQL Server :class:`_mssql.JSON` type necessarily makes use of the
``JSON_QUERY`` and ``JSON_VALUE`` functions when querying for elements
of a JSON object. These two functions have a major restriction in that
they are **mutually exclusive** based on the type of object to be returned.
The ``JSON_QUERY`` function **only** returns a JSON dictionary or list,
but not an individual string, numeric, or boolean element; the
``JSON_VALUE`` function **only** returns an individual string, numeric,
or boolean element. **both functions either return NULL or raise
an error if they are not used against the correct expected value**.
To handle this awkward requirement, indexed access rules are as follows:
1. When extracting a sub element from a JSON that is itself a JSON
dictionary or list, the :meth:`_types.JSON.Comparator.as_json` accessor
should be used::
stmt = select(
data_table.c.data["some key"].as_json()
).where(
data_table.c.data["some key"].as_json() == {"sub": "structure"}
)
2. When extracting a sub element from a JSON that is a plain boolean,
string, integer, or float, use the appropriate method among
:meth:`_types.JSON.Comparator.as_boolean`,
:meth:`_types.JSON.Comparator.as_string`,
:meth:`_types.JSON.Comparator.as_integer`,
:meth:`_types.JSON.Comparator.as_float`::
stmt = select(
data_table.c.data["some key"].as_string()
).where(
data_table.c.data["some key"].as_string() == "some string"
)
.. versionadded:: 1.4
"""
# note there was a result processor here that was looking for "number",
# but none of the tests seem to exercise it.
# Note: these objects currently match exactly those of MySQL, however since
# these are not generalizable to all JSON implementations, remain separately
# implemented for each dialect.
class _FormatTypeMixin(object):
def _format_value(self, value):
raise NotImplementedError()
def bind_processor(self, dialect):
super_proc = self.string_bind_processor(dialect)
def process(value):
value = self._format_value(value)
if super_proc:
value = super_proc(value)
return value
return process
def literal_processor(self, dialect):
super_proc = self.string_literal_processor(dialect)
def process(value):
value = self._format_value(value)
if super_proc:
value = super_proc(value)
return value
return process
class JSONIndexType(_FormatTypeMixin, sqltypes.JSON.JSONIndexType):
def _format_value(self, value):
if isinstance(value, int):
value = "$[%s]" % value
else:
value = '$."%s"' % value
return value
class JSONPathType(_FormatTypeMixin, sqltypes.JSON.JSONPathType):
def _format_value(self, value):
return "$%s" % (
"".join(
[
"[%s]" % elem if isinstance(elem, int) else '."%s"' % elem
for elem in value
]
)
)

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# mssql/mxodbc.py
# Copyright (C) 2005-2022 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
"""
.. dialect:: mssql+mxodbc
:name: mxODBC
:dbapi: mxodbc
:connectstring: mssql+mxodbc://<username>:<password>@<dsnname>
:url: https://www.egenix.com/
.. deprecated:: 1.4 The mxODBC DBAPI is deprecated and will be removed
in a future version. Please use one of the supported DBAPIs to
connect to mssql.
Execution Modes
---------------
mxODBC features two styles of statement execution, using the
``cursor.execute()`` and ``cursor.executedirect()`` methods (the second being
an extension to the DBAPI specification). The former makes use of a particular
API call specific to the SQL Server Native Client ODBC driver known
SQLDescribeParam, while the latter does not.
mxODBC apparently only makes repeated use of a single prepared statement
when SQLDescribeParam is used. The advantage to prepared statement reuse is
one of performance. The disadvantage is that SQLDescribeParam has a limited
set of scenarios in which bind parameters are understood, including that they
cannot be placed within the argument lists of function calls, anywhere outside
the FROM, or even within subqueries within the FROM clause - making the usage
of bind parameters within SELECT statements impossible for all but the most
simplistic statements.
For this reason, the mxODBC dialect uses the "native" mode by default only for
INSERT, UPDATE, and DELETE statements, and uses the escaped string mode for
all other statements.
This behavior can be controlled via
:meth:`~sqlalchemy.sql.expression.Executable.execution_options` using the
``native_odbc_execute`` flag with a value of ``True`` or ``False``, where a
value of ``True`` will unconditionally use native bind parameters and a value
of ``False`` will unconditionally use string-escaped parameters.
"""
from .base import _MSDate
from .base import _MSDateTime
from .base import _MSTime
from .base import MSDialect
from .base import VARBINARY
from .pyodbc import _MSNumeric_pyodbc
from .pyodbc import MSExecutionContext_pyodbc
from ... import types as sqltypes
from ...connectors.mxodbc import MxODBCConnector
class _MSNumeric_mxodbc(_MSNumeric_pyodbc):
"""Include pyodbc's numeric processor."""
class _MSDate_mxodbc(_MSDate):
def bind_processor(self, dialect):
def process(value):
if value is not None:
return "%s-%s-%s" % (value.year, value.month, value.day)
else:
return None
return process
class _MSTime_mxodbc(_MSTime):
def bind_processor(self, dialect):
def process(value):
if value is not None:
return "%s:%s:%s" % (value.hour, value.minute, value.second)
else:
return None
return process
class _VARBINARY_mxodbc(VARBINARY):
"""
mxODBC Support for VARBINARY column types.
This handles the special case for null VARBINARY values,
which maps None values to the mx.ODBC.Manager.BinaryNull symbol.
"""
def bind_processor(self, dialect):
if dialect.dbapi is None:
return None
DBAPIBinary = dialect.dbapi.Binary
def process(value):
if value is not None:
return DBAPIBinary(value)
else:
# should pull from mx.ODBC.Manager.BinaryNull
return dialect.dbapi.BinaryNull
return process
class MSExecutionContext_mxodbc(MSExecutionContext_pyodbc):
"""
The pyodbc execution context is useful for enabling
SELECT SCOPE_IDENTITY in cases where OUTPUT clause
does not work (tables with insert triggers).
"""
# todo - investigate whether the pyodbc execution context
# is really only being used in cases where OUTPUT
# won't work.
class MSDialect_mxodbc(MxODBCConnector, MSDialect):
# this is only needed if "native ODBC" mode is used,
# which is now disabled by default.
# statement_compiler = MSSQLStrictCompiler
supports_statement_cache = True
execution_ctx_cls = MSExecutionContext_mxodbc
# flag used by _MSNumeric_mxodbc
_need_decimal_fix = True
colspecs = {
sqltypes.Numeric: _MSNumeric_mxodbc,
sqltypes.DateTime: _MSDateTime,
sqltypes.Date: _MSDate_mxodbc,
sqltypes.Time: _MSTime_mxodbc,
VARBINARY: _VARBINARY_mxodbc,
sqltypes.LargeBinary: _VARBINARY_mxodbc,
}
def __init__(self, description_encoding=None, **params):
super(MSDialect_mxodbc, self).__init__(**params)
self.description_encoding = description_encoding
dialect = MSDialect_mxodbc

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lib/sqlalchemy/dialects/mssql/provision.py Normal file
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from sqlalchemy import inspect
from sqlalchemy import Integer
from ... import create_engine
from ... import exc
from ...schema import Column
from ...schema import DropConstraint
from ...schema import ForeignKeyConstraint
from ...schema import MetaData
from ...schema import Table
from ...testing.provision import create_db
from ...testing.provision import drop_all_schema_objects_pre_tables
from ...testing.provision import drop_db
from ...testing.provision import get_temp_table_name
from ...testing.provision import log
from ...testing.provision import run_reap_dbs
from ...testing.provision import temp_table_keyword_args
@create_db.for_db("mssql")
def _mssql_create_db(cfg, eng, ident):
with eng.connect().execution_options(isolation_level="AUTOCOMMIT") as conn:
conn.exec_driver_sql("create database %s" % ident)
conn.exec_driver_sql(
"ALTER DATABASE %s SET ALLOW_SNAPSHOT_ISOLATION ON" % ident
)
conn.exec_driver_sql(
"ALTER DATABASE %s SET READ_COMMITTED_SNAPSHOT ON" % ident
)
conn.exec_driver_sql("use %s" % ident)
conn.exec_driver_sql("create schema test_schema")
conn.exec_driver_sql("create schema test_schema_2")
@drop_db.for_db("mssql")
def _mssql_drop_db(cfg, eng, ident):
with eng.connect().execution_options(isolation_level="AUTOCOMMIT") as conn:
_mssql_drop_ignore(conn, ident)
def _mssql_drop_ignore(conn, ident):
try:
# typically when this happens, we can't KILL the session anyway,
# so let the cleanup process drop the DBs
# for row in conn.exec_driver_sql(
# "select session_id from sys.dm_exec_sessions "
# "where database_id=db_id('%s')" % ident):
# log.info("killing SQL server session %s", row['session_id'])
# conn.exec_driver_sql("kill %s" % row['session_id'])
conn.exec_driver_sql("drop database %s" % ident)
log.info("Reaped db: %s", ident)
return True
except exc.DatabaseError as err:
log.warning("couldn't drop db: %s", err)
return False
@run_reap_dbs.for_db("mssql")
def _reap_mssql_dbs(url, idents):
log.info("db reaper connecting to %r", url)
eng = create_engine(url)
with eng.connect().execution_options(isolation_level="AUTOCOMMIT") as conn:
log.info("identifiers in file: %s", ", ".join(idents))
to_reap = conn.exec_driver_sql(
"select d.name from sys.databases as d where name "
"like 'TEST_%' and not exists (select session_id "
"from sys.dm_exec_sessions "
"where database_id=d.database_id)"
)
all_names = {dbname.lower() for (dbname,) in to_reap}
to_drop = set()
for name in all_names:
if name in idents:
to_drop.add(name)
dropped = total = 0
for total, dbname in enumerate(to_drop, 1):
if _mssql_drop_ignore(conn, dbname):
dropped += 1
log.info(
"Dropped %d out of %d stale databases detected", dropped, total
)
@temp_table_keyword_args.for_db("mssql")
def _mssql_temp_table_keyword_args(cfg, eng):
return {}
@get_temp_table_name.for_db("mssql")
def _mssql_get_temp_table_name(cfg, eng, base_name):
return "##" + base_name
@drop_all_schema_objects_pre_tables.for_db("mssql")
def drop_all_schema_objects_pre_tables(cfg, eng):
with eng.connect().execution_options(isolation_level="AUTOCOMMIT") as conn:
inspector = inspect(conn)
for schema in (None, "dbo", cfg.test_schema, cfg.test_schema_2):
for tname in inspector.get_table_names(schema=schema):
tb = Table(
tname,
MetaData(),
Column("x", Integer),
Column("y", Integer),
schema=schema,
)
for fk in inspect(conn).get_foreign_keys(tname, schema=schema):
conn.execute(
DropConstraint(
ForeignKeyConstraint(
[tb.c.x], [tb.c.y], name=fk["name"]
)
)
)

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# mssql/pymssql.py
# Copyright (C) 2005-2022 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
"""
.. dialect:: mssql+pymssql
:name: pymssql
:dbapi: pymssql
:connectstring: mssql+pymssql://<username>:<password>@<freetds_name>/?charset=utf8
pymssql is a Python module that provides a Python DBAPI interface around
`FreeTDS <https://www.freetds.org/>`_.
.. note::
pymssql is currently not included in SQLAlchemy's continuous integration
(CI) testing.
Modern versions of this driver worked very well with SQL Server and FreeTDS
from Linux and were highly recommended. However, pymssql is currently
unmaintained and has fallen behind the progress of the Microsoft ODBC driver in
its support for newer features of SQL Server. The latest official release of
pymssql at the time of this document is version 2.1.4 (August, 2018) and it
lacks support for:
1. table-valued parameters (TVPs),
2. ``datetimeoffset`` columns using timezone-aware ``datetime`` objects
(values are sent and retrieved as strings), and
3. encrypted connections (e.g., to Azure SQL), when pymssql is installed from
the pre-built wheels. Support for encrypted connections requires building
pymssql from source, which can be a nuisance, especially under Windows.
The above features are all supported by mssql+pyodbc when using Microsoft's
ODBC Driver for SQL Server (msodbcsql), which is now available for Windows,
(several flavors of) Linux, and macOS.
""" # noqa
import re
from .base import MSDialect
from .base import MSIdentifierPreparer
from ... import processors
from ... import types as sqltypes
from ... import util
class _MSNumeric_pymssql(sqltypes.Numeric):
def result_processor(self, dialect, type_):
if not self.asdecimal:
return processors.to_float
else:
return sqltypes.Numeric.result_processor(self, dialect, type_)
class MSIdentifierPreparer_pymssql(MSIdentifierPreparer):
def __init__(self, dialect):
super(MSIdentifierPreparer_pymssql, self).__init__(dialect)
# pymssql has the very unusual behavior that it uses pyformat
# yet does not require that percent signs be doubled
self._double_percents = False
class MSDialect_pymssql(MSDialect):
supports_statement_cache = True
supports_native_decimal = True
driver = "pymssql"
preparer = MSIdentifierPreparer_pymssql
colspecs = util.update_copy(
MSDialect.colspecs,
{sqltypes.Numeric: _MSNumeric_pymssql, sqltypes.Float: sqltypes.Float},
)
@classmethod
def dbapi(cls):
module = __import__("pymssql")
# pymmsql < 2.1.1 doesn't have a Binary method. we use string
client_ver = tuple(int(x) for x in module.__version__.split("."))
if client_ver < (2, 1, 1):
# TODO: monkeypatching here is less than ideal
module.Binary = lambda x: x if hasattr(x, "decode") else str(x)
if client_ver < (1,):
util.warn(
"The pymssql dialect expects at least "
"the 1.0 series of the pymssql DBAPI."
)
return module
def _get_server_version_info(self, connection):
vers = connection.exec_driver_sql("select @@version").scalar()
m = re.match(r"Microsoft .*? - (\d+)\.(\d+)\.(\d+)\.(\d+)", vers)
if m:
return tuple(int(x) for x in m.group(1, 2, 3, 4))
else:
return None
def create_connect_args(self, url):
opts = url.translate_connect_args(username="user")
opts.update(url.query)
port = opts.pop("port", None)
if port and "host" in opts:
opts["host"] = "%s:%s" % (opts["host"], port)
return [[], opts]
def is_disconnect(self, e, connection, cursor):
for msg in (
"Adaptive Server connection timed out",
"Net-Lib error during Connection reset by peer",
"message 20003", # connection timeout
"Error 10054",
"Not connected to any MS SQL server",
"Connection is closed",
"message 20006", # Write to the server failed
"message 20017", # Unexpected EOF from the server
"message 20047", # DBPROCESS is dead or not enabled
):
if msg in str(e):
return True
else:
return False
def set_isolation_level(self, connection, level):
if level == "AUTOCOMMIT":
connection.autocommit(True)
else:
connection.autocommit(False)
super(MSDialect_pymssql, self).set_isolation_level(
connection, level
)
dialect = MSDialect_pymssql

673
lib/sqlalchemy/dialects/mssql/pyodbc.py Normal file
View File

@@ -0,0 +1,673 @@
# mssql/pyodbc.py
# Copyright (C) 2005-2022 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:: mssql+pyodbc
:name: PyODBC
:dbapi: pyodbc
:connectstring: mssql+pyodbc://<username>:<password>@<dsnname>
:url: https://pypi.org/project/pyodbc/
Connecting to PyODBC
--------------------
The URL here is to be translated to PyODBC connection strings, as
detailed in `ConnectionStrings <https://code.google.com/p/pyodbc/wiki/ConnectionStrings>`_.
DSN Connections
^^^^^^^^^^^^^^^
A DSN connection in ODBC means that a pre-existing ODBC datasource is
configured on the client machine. The application then specifies the name
of this datasource, which encompasses details such as the specific ODBC driver
in use as well as the network address of the database. Assuming a datasource
is configured on the client, a basic DSN-based connection looks like::
engine = create_engine("mssql+pyodbc://scott:tiger@some_dsn")
Which above, will pass the following connection string to PyODBC::
DSN=some_dsn;UID=scott;PWD=tiger
If the username and password are omitted, the DSN form will also add
the ``Trusted_Connection=yes`` directive to the ODBC string.
Hostname Connections
^^^^^^^^^^^^^^^^^^^^
Hostname-based connections are also supported by pyodbc. These are often
easier to use than a DSN and have the additional advantage that the specific
database name to connect towards may be specified locally in the URL, rather
than it being fixed as part of a datasource configuration.
When using a hostname connection, the driver name must also be specified in the
query parameters of the URL. As these names usually have spaces in them, the
name must be URL encoded which means using plus signs for spaces::
engine = create_engine("mssql+pyodbc://scott:tiger@myhost:port/databasename?driver=ODBC+Driver+17+for+SQL+Server")
Other keywords interpreted by the Pyodbc dialect to be passed to
``pyodbc.connect()`` in both the DSN and hostname cases include:
``odbc_autotranslate``, ``ansi``, ``unicode_results``, ``autocommit``,
``authentication``.
Note that in order for the dialect to recognize these keywords
(including the ``driver`` keyword above) they must be all lowercase.
Multiple additional keyword arguments must be separated by an
ampersand (``&``), not a semicolon::
engine = create_engine(
"mssql+pyodbc://scott:tiger@myhost:49242/databasename"
"?driver=ODBC+Driver+17+for+SQL+Server"
"&authentication=ActiveDirectoryIntegrated"
)
The equivalent URL can be constructed using :class:`_sa.engine.URL`::
from sqlalchemy.engine import URL
connection_url = URL.create(
"mssql+pyodbc",
username="scott",
password="tiger",
host="myhost",
port=49242,
database="databasename",
query={
"driver": "ODBC Driver 17 for SQL Server",
"authentication": "ActiveDirectoryIntegrated",
},
)
Pass through exact Pyodbc string
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
A PyODBC connection string can also be sent in pyodbc's format directly, as
specified in `the PyODBC documentation
<https://github.com/mkleehammer/pyodbc/wiki/Connecting-to-databases>`_,
using the parameter ``odbc_connect``. A :class:`_sa.engine.URL` object
can help make this easier::
from sqlalchemy.engine import URL
connection_string = "DRIVER={SQL Server Native Client 10.0};SERVER=dagger;DATABASE=test;UID=user;PWD=password"
connection_url = URL.create("mssql+pyodbc", query={"odbc_connect": connection_string})
engine = create_engine(connection_url)
.. _mssql_pyodbc_access_tokens:
Connecting to databases with access tokens
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
Some database servers are set up to only accept access tokens for login. For
example, SQL Server allows the use of Azure Active Directory tokens to connect
to databases. This requires creating a credential object using the
``azure-identity`` library. More information about the authentication step can be
found in `Microsoft's documentation
<https://docs.microsoft.com/en-us/azure/developer/python/azure-sdk-authenticate?tabs=bash>`_.
After getting an engine, the credentials need to be sent to ``pyodbc.connect``
each time a connection is requested. One way to do this is to set up an event
listener on the engine that adds the credential token to the dialect's connect
call. This is discussed more generally in :ref:`engines_dynamic_tokens`. For
SQL Server in particular, this is passed as an ODBC connection attribute with
a data structure `described by Microsoft
<https://docs.microsoft.com/en-us/sql/connect/odbc/using-azure-active-directory#authenticating-with-an-access-token>`_.
The following code snippet will create an engine that connects to an Azure SQL
database using Azure credentials::
import struct
from sqlalchemy import create_engine, event
from sqlalchemy.engine.url import URL
from azure import identity
SQL_COPT_SS_ACCESS_TOKEN = 1256 # Connection option for access tokens, as defined in msodbcsql.h
TOKEN_URL = "https://database.windows.net/" # The token URL for any Azure SQL database
connection_string = "mssql+pyodbc://@my-server.database.windows.net/myDb?driver=ODBC+Driver+17+for+SQL+Server"
engine = create_engine(connection_string)
azure_credentials = identity.DefaultAzureCredential()
@event.listens_for(engine, "do_connect")
def provide_token(dialect, conn_rec, cargs, cparams):
# remove the "Trusted_Connection" parameter that SQLAlchemy adds
cargs[0] = cargs[0].replace(";Trusted_Connection=Yes", "")
# create token credential
raw_token = azure_credentials.get_token(TOKEN_URL).token.encode("utf-16-le")
token_struct = struct.pack(f"<I{len(raw_token)}s", len(raw_token), raw_token)
# apply it to keyword arguments
cparams["attrs_before"] = {SQL_COPT_SS_ACCESS_TOKEN: token_struct}
.. tip::
The ``Trusted_Connection`` token is currently added by the SQLAlchemy
pyodbc dialect when no username or password is present. This needs
to be removed per Microsoft's
`documentation for Azure access tokens
<https://docs.microsoft.com/en-us/sql/connect/odbc/using-azure-active-directory#authenticating-with-an-access-token>`_,
stating that a connection string when using an access token must not contain
``UID``, ``PWD``, ``Authentication`` or ``Trusted_Connection`` parameters.
.. _azure_synapse_ignore_no_transaction_on_rollback:
Avoiding transaction-related exceptions on Azure Synapse Analytics
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
Azure Synapse Analytics has a significant difference in its transaction
handling compared to plain SQL Server; in some cases an error within a Synapse
transaction can cause it to be arbitrarily terminated on the server side, which
then causes the DBAPI ``.rollback()`` method (as well as ``.commit()``) to
fail. The issue prevents the usual DBAPI contract of allowing ``.rollback()``
to pass silently if no transaction is present as the driver does not expect
this condition. The symptom of this failure is an exception with a message
resembling 'No corresponding transaction found. (111214)' when attempting to
emit a ``.rollback()`` after an operation had a failure of some kind.
This specific case can be handled by passing ``ignore_no_transaction_on_rollback=True`` to
the SQL Server dialect via the :func:`_sa.create_engine` function as follows::
engine = create_engine(connection_url, ignore_no_transaction_on_rollback=True)
Using the above parameter, the dialect will catch ``ProgrammingError``
exceptions raised during ``connection.rollback()`` and emit a warning
if the error message contains code ``111214``, however will not raise
an exception.
.. versionadded:: 1.4.40 Added the
``ignore_no_transaction_on_rollback=True`` parameter.
Enable autocommit for Azure SQL Data Warehouse (DW) connections
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
Azure SQL Data Warehouse does not support transactions,
and that can cause problems with SQLAlchemy's "autobegin" (and implicit
commit/rollback) behavior. We can avoid these problems by enabling autocommit
at both the pyodbc and engine levels::
connection_url = sa.engine.URL.create(
"mssql+pyodbc",
username="scott",
password="tiger",
host="dw.azure.example.com",
database="mydb",
query={
"driver": "ODBC Driver 17 for SQL Server",
"autocommit": "True",
},
)
engine = create_engine(connection_url).execution_options(
isolation_level="AUTOCOMMIT"
)
Avoiding sending large string parameters as TEXT/NTEXT
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
By default, for historical reasons, Microsoft's ODBC drivers for SQL Server
send long string parameters (greater than 4000 SBCS characters or 2000 Unicode
characters) as TEXT/NTEXT values. TEXT and NTEXT have been deprecated for many
years and are starting to cause compatibility issues with newer versions of
SQL_Server/Azure. For example, see `this
issue <https://github.com/mkleehammer/pyodbc/issues/835>`_.
Starting with ODBC Driver 18 for SQL Server we can override the legacy
behavior and pass long strings as varchar(max)/nvarchar(max) using the
``LongAsMax=Yes`` connection string parameter::
connection_url = sa.engine.URL.create(
"mssql+pyodbc",
username="scott",
password="tiger",
host="mssqlserver.example.com",
database="mydb",
query={
"driver": "ODBC Driver 18 for SQL Server",
"LongAsMax": "Yes",
},
)
Pyodbc Pooling / connection close behavior
------------------------------------------
PyODBC uses internal `pooling
<https://github.com/mkleehammer/pyodbc/wiki/The-pyodbc-Module#pooling>`_ by
default, which means connections will be longer lived than they are within
SQLAlchemy itself. As SQLAlchemy has its own pooling behavior, it is often
preferable to disable this behavior. This behavior can only be disabled
globally at the PyODBC module level, **before** any connections are made::
import pyodbc
pyodbc.pooling = False
# don't use the engine before pooling is set to False
engine = create_engine("mssql+pyodbc://user:pass@dsn")
If this variable is left at its default value of ``True``, **the application
will continue to maintain active database connections**, even when the
SQLAlchemy engine itself fully discards a connection or if the engine is
disposed.
.. seealso::
`pooling <https://github.com/mkleehammer/pyodbc/wiki/The-pyodbc-Module#pooling>`_ -
in the PyODBC documentation.
Driver / Unicode Support
-------------------------
PyODBC works best with Microsoft ODBC drivers, particularly in the area
of Unicode support on both Python 2 and Python 3.
Using the FreeTDS ODBC drivers on Linux or OSX with PyODBC is **not**
recommended; there have been historically many Unicode-related issues
in this area, including before Microsoft offered ODBC drivers for Linux
and OSX. Now that Microsoft offers drivers for all platforms, for
PyODBC support these are recommended. FreeTDS remains relevant for
non-ODBC drivers such as pymssql where it works very well.
Rowcount Support
----------------
Pyodbc only has partial support for rowcount. See the notes at
:ref:`mssql_rowcount_versioning` for important notes when using ORM
versioning.
.. _mssql_pyodbc_fastexecutemany:
Fast Executemany Mode
---------------------
The Pyodbc driver has added support for a "fast executemany" mode of execution
which greatly reduces round trips for a DBAPI ``executemany()`` call when using
Microsoft ODBC drivers, for **limited size batches that fit in memory**. The
feature is enabled by setting the flag ``.fast_executemany`` on the DBAPI
cursor when an executemany call is to be used. The SQLAlchemy pyodbc SQL
Server dialect supports setting this flag automatically when the
``.fast_executemany`` flag is passed to
:func:`_sa.create_engine` ; note that the ODBC driver must be the Microsoft
driver in order to use this flag::
engine = create_engine(
"mssql+pyodbc://scott:tiger@mssql2017:1433/test?driver=ODBC+Driver+13+for+SQL+Server",
fast_executemany=True)
.. warning:: The pyodbc fast_executemany mode **buffers all rows in memory** and is
not compatible with very large batches of data. A future version of SQLAlchemy
may support this flag as a per-execution option instead.
.. versionadded:: 1.3
.. seealso::
`fast executemany <https://github.com/mkleehammer/pyodbc/wiki/Features-beyond-the-DB-API#fast_executemany>`_
- on github
.. _mssql_pyodbc_setinputsizes:
Setinputsizes Support
-----------------------
The pyodbc ``cursor.setinputsizes()`` method can be used if necessary. To
enable this hook, pass ``use_setinputsizes=True`` to :func:`_sa.create_engine`::
engine = create_engine("mssql+pyodbc://...", use_setinputsizes=True)
The behavior of the hook can then be customized, as may be necessary
particularly if fast_executemany is in use, via the
:meth:`.DialectEvents.do_setinputsizes` hook. See that method for usage
examples.
.. versionchanged:: 1.4.1 The pyodbc dialects will not use setinputsizes
unless ``use_setinputsizes=True`` is passed.
""" # noqa
import datetime
import decimal
import re
import struct
from .base import BINARY
from .base import DATETIMEOFFSET
from .base import MSDialect
from .base import MSExecutionContext
from .base import VARBINARY
from ... import exc
from ... import types as sqltypes
from ... import util
from ...connectors.pyodbc import PyODBCConnector
class _ms_numeric_pyodbc(object):
"""Turns Decimals with adjusted() < 0 or > 7 into strings.
The routines here are needed for older pyodbc versions
as well as current mxODBC versions.
"""
def bind_processor(self, dialect):
super_process = super(_ms_numeric_pyodbc, self).bind_processor(dialect)
if not dialect._need_decimal_fix:
return super_process
def process(value):
if self.asdecimal and isinstance(value, decimal.Decimal):
adjusted = value.adjusted()
if adjusted < 0:
return self._small_dec_to_string(value)
elif adjusted > 7:
return self._large_dec_to_string(value)
if super_process:
return super_process(value)
else:
return value
return process
# these routines needed for older versions of pyodbc.
# as of 2.1.8 this logic is integrated.
def _small_dec_to_string(self, value):
return "%s0.%s%s" % (
(value < 0 and "-" or ""),
"0" * (abs(value.adjusted()) - 1),
"".join([str(nint) for nint in value.as_tuple()[1]]),
)
def _large_dec_to_string(self, value):
_int = value.as_tuple()[1]
if "E" in str(value):
result = "%s%s%s" % (
(value < 0 and "-" or ""),
"".join([str(s) for s in _int]),
"0" * (value.adjusted() - (len(_int) - 1)),
)
else:
if (len(_int) - 1) > value.adjusted():
result = "%s%s.%s" % (
(value < 0 and "-" or ""),
"".join([str(s) for s in _int][0 : value.adjusted() + 1]),
"".join([str(s) for s in _int][value.adjusted() + 1 :]),
)
else:
result = "%s%s" % (
(value < 0 and "-" or ""),
"".join([str(s) for s in _int][0 : value.adjusted() + 1]),
)
return result
class _MSNumeric_pyodbc(_ms_numeric_pyodbc, sqltypes.Numeric):
pass
class _MSFloat_pyodbc(_ms_numeric_pyodbc, sqltypes.Float):
pass
class _ms_binary_pyodbc(object):
"""Wraps binary values in dialect-specific Binary wrapper.
If the value is null, return a pyodbc-specific BinaryNull
object to prevent pyODBC [and FreeTDS] from defaulting binary
NULL types to SQLWCHAR and causing implicit conversion errors.
"""
def bind_processor(self, dialect):
if dialect.dbapi is None:
return None
DBAPIBinary = dialect.dbapi.Binary
def process(value):
if value is not None:
return DBAPIBinary(value)
else:
# pyodbc-specific
return dialect.dbapi.BinaryNull
return process
class _ODBCDateTimeBindProcessor(object):
"""Add bind processors to handle datetimeoffset behaviors"""
has_tz = False
def bind_processor(self, dialect):
def process(value):
if value is None:
return None
elif isinstance(value, util.string_types):
# if a string was passed directly, allow it through
return value
elif not value.tzinfo or (not self.timezone and not self.has_tz):
# for DateTime(timezone=False)
return value
else:
# for DATETIMEOFFSET or DateTime(timezone=True)
#
# Convert to string format required by T-SQL
dto_string = value.strftime("%Y-%m-%d %H:%M:%S.%f %z")
# offset needs a colon, e.g., -0700 -> -07:00
# "UTC offset in the form (+-)HHMM[SS[.ffffff]]"
# backend currently rejects seconds / fractional seconds
dto_string = re.sub(
r"([\+\-]\d{2})([\d\.]+)$", r"\1:\2", dto_string
)
return dto_string
return process
class _ODBCDateTime(_ODBCDateTimeBindProcessor, sqltypes.DateTime):
pass
class _ODBCDATETIMEOFFSET(_ODBCDateTimeBindProcessor, DATETIMEOFFSET):
has_tz = True
class _VARBINARY_pyodbc(_ms_binary_pyodbc, VARBINARY):
pass
class _BINARY_pyodbc(_ms_binary_pyodbc, BINARY):
pass
class MSExecutionContext_pyodbc(MSExecutionContext):
_embedded_scope_identity = False
def pre_exec(self):
"""where appropriate, issue "select scope_identity()" in the same
statement.
Background on why "scope_identity()" is preferable to "@@identity":
https://msdn.microsoft.com/en-us/library/ms190315.aspx
Background on why we attempt to embed "scope_identity()" into the same
statement as the INSERT:
https://code.google.com/p/pyodbc/wiki/FAQs#How_do_I_retrieve_autogenerated/identity_values?
"""
super(MSExecutionContext_pyodbc, self).pre_exec()
# don't embed the scope_identity select into an
# "INSERT .. DEFAULT VALUES"
if (
self._select_lastrowid
and self.dialect.use_scope_identity
and len(self.parameters[0])
):
self._embedded_scope_identity = True
self.statement += "; select scope_identity()"
def post_exec(self):
if self._embedded_scope_identity:
# Fetch the last inserted id from the manipulated statement
# We may have to skip over a number of result sets with
# no data (due to triggers, etc.)
while True:
try:
# fetchall() ensures the cursor is consumed
# without closing it (FreeTDS particularly)
row = self.cursor.fetchall()[0]
break
except self.dialect.dbapi.Error:
# no way around this - nextset() consumes the previous set
# so we need to just keep flipping
self.cursor.nextset()
self._lastrowid = int(row[0])
else:
super(MSExecutionContext_pyodbc, self).post_exec()
class MSDialect_pyodbc(PyODBCConnector, MSDialect):
supports_statement_cache = True
# mssql still has problems with this on Linux
supports_sane_rowcount_returning = False
execution_ctx_cls = MSExecutionContext_pyodbc
colspecs = util.update_copy(
MSDialect.colspecs,
{
sqltypes.Numeric: _MSNumeric_pyodbc,
sqltypes.Float: _MSFloat_pyodbc,
BINARY: _BINARY_pyodbc,
# support DateTime(timezone=True)
sqltypes.DateTime: _ODBCDateTime,
DATETIMEOFFSET: _ODBCDATETIMEOFFSET,
# SQL Server dialect has a VARBINARY that is just to support
# "deprecate_large_types" w/ VARBINARY(max), but also we must
# handle the usual SQL standard VARBINARY
VARBINARY: _VARBINARY_pyodbc,
sqltypes.VARBINARY: _VARBINARY_pyodbc,
sqltypes.LargeBinary: _VARBINARY_pyodbc,
},
)
def __init__(
self, description_encoding=None, fast_executemany=False, **params
):
if "description_encoding" in params:
self.description_encoding = params.pop("description_encoding")
super(MSDialect_pyodbc, self).__init__(**params)
self.use_scope_identity = (
self.use_scope_identity
and self.dbapi
and hasattr(self.dbapi.Cursor, "nextset")
)
self._need_decimal_fix = self.dbapi and self._dbapi_version() < (
2,
1,
8,
)
self.fast_executemany = fast_executemany
def _get_server_version_info(self, connection):
try:
# "Version of the instance of SQL Server, in the form
# of 'major.minor.build.revision'"
raw = connection.exec_driver_sql(
"SELECT CAST(SERVERPROPERTY('ProductVersion') AS VARCHAR)"
).scalar()
except exc.DBAPIError:
# SQL Server docs indicate this function isn't present prior to
# 2008. Before we had the VARCHAR cast above, pyodbc would also
# fail on this query.
return super(MSDialect_pyodbc, self)._get_server_version_info(
connection, allow_chars=False
)
else:
version = []
r = re.compile(r"[.\-]")
for n in r.split(raw):
try:
version.append(int(n))
except ValueError:
pass
return tuple(version)
def on_connect(self):
super_ = super(MSDialect_pyodbc, self).on_connect()
def on_connect(conn):
if super_ is not None:
super_(conn)
self._setup_timestampoffset_type(conn)
return on_connect
def _setup_timestampoffset_type(self, connection):
# output converter function for datetimeoffset
def _handle_datetimeoffset(dto_value):
tup = struct.unpack("<6hI2h", dto_value)
return datetime.datetime(
tup[0],
tup[1],
tup[2],
tup[3],
tup[4],
tup[5],
tup[6] // 1000,
util.timezone(
datetime.timedelta(hours=tup[7], minutes=tup[8])
),
)
odbc_SQL_SS_TIMESTAMPOFFSET = -155 # as defined in SQLNCLI.h
connection.add_output_converter(
odbc_SQL_SS_TIMESTAMPOFFSET, _handle_datetimeoffset
)
def do_executemany(self, cursor, statement, parameters, context=None):
if self.fast_executemany:
cursor.fast_executemany = True
super(MSDialect_pyodbc, self).do_executemany(
cursor, statement, parameters, context=context
)
def is_disconnect(self, e, connection, cursor):
if isinstance(e, self.dbapi.Error):
code = e.args[0]
if code in {
"08S01",
"01000",
"01002",
"08003",
"08007",
"08S02",
"08001",
"HYT00",
"HY010",
"10054",
}:
return True
return super(MSDialect_pyodbc, self).is_disconnect(
e, connection, cursor
)
dialect = MSDialect_pyodbc