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elitebot/lib/python3.11/site-packages/sqlalchemy/dialects/mssql/__init__.py Normal file
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# dialects/mssql/__init__.py
# Copyright (C) 2005-2024 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
# mypy: ignore-errors
from . import aioodbc # noqa
from . import base # 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 DOUBLE_PRECISION
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 UNIQUEIDENTIFIER
from .base import VARBINARY
from .base import VARCHAR
from .base import XML
from ...sql import try_cast
base.dialect = dialect = pyodbc.dialect
__all__ = (
"JSON",
"INTEGER",
"BIGINT",
"SMALLINT",
"TINYINT",
"VARCHAR",
"NVARCHAR",
"CHAR",
"NCHAR",
"TEXT",
"NTEXT",
"DECIMAL",
"NUMERIC",
"FLOAT",
"DATETIME",
"DATETIME2",
"DATETIMEOFFSET",
"DATE",
"DOUBLE_PRECISION",
"TIME",
"SMALLDATETIME",
"BINARY",
"VARBINARY",
"BIT",
"REAL",
"IMAGE",
"TIMESTAMP",
"ROWVERSION",
"MONEY",
"SMALLMONEY",
"UNIQUEIDENTIFIER",
"SQL_VARIANT",
"XML",
"dialect",
"try_cast",
)

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elitebot/lib/python3.11/site-packages/sqlalchemy/dialects/mssql/aioodbc.py Normal file
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# dialects/mssql/aioodbc.py
# Copyright (C) 2005-2024 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
# mypy: ignore-errors
r"""
.. dialect:: mssql+aioodbc
:name: aioodbc
:dbapi: aioodbc
:connectstring: mssql+aioodbc://<username>:<password>@<dsnname>
:url: https://pypi.org/project/aioodbc/
Support for the SQL Server database in asyncio style, using the aioodbc
driver which itself is a thread-wrapper around pyodbc.
.. versionadded:: 2.0.23 Added the mssql+aioodbc dialect which builds
on top of the pyodbc and general aio* dialect architecture.
Using a special asyncio mediation layer, the aioodbc dialect is usable
as the backend for the :ref:`SQLAlchemy asyncio <asyncio_toplevel>`
extension package.
Most behaviors and caveats for this driver are the same as that of the
pyodbc dialect used on SQL Server; see :ref:`mssql_pyodbc` for general
background.
This dialect should normally be used only with the
:func:`_asyncio.create_async_engine` engine creation function; connection
styles are otherwise equivalent to those documented in the pyodbc section::
from sqlalchemy.ext.asyncio import create_async_engine
engine = create_async_engine(
"mssql+aioodbc://scott:tiger@mssql2017:1433/test?"
"driver=ODBC+Driver+18+for+SQL+Server&TrustServerCertificate=yes"
)
"""
from __future__ import annotations
from .pyodbc import MSDialect_pyodbc
from .pyodbc import MSExecutionContext_pyodbc
from ...connectors.aioodbc import aiodbcConnector
class MSExecutionContext_aioodbc(MSExecutionContext_pyodbc):
def create_server_side_cursor(self):
return self._dbapi_connection.cursor(server_side=True)
class MSDialectAsync_aioodbc(aiodbcConnector, MSDialect_pyodbc):
driver = "aioodbc"
supports_statement_cache = True
execution_ctx_cls = MSExecutionContext_aioodbc
dialect = MSDialectAsync_aioodbc

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elitebot/lib/python3.11/site-packages/sqlalchemy/dialects/mssql/base.py Normal file
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elitebot/lib/python3.11/site-packages/sqlalchemy/dialects/mssql/information_schema.py Normal file
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# dialects/mssql/information_schema.py
# Copyright (C) 2005-2024 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
# mypy: ignore-errors
from ... import cast
from ... import Column
from ... import MetaData
from ... import Table
from ...ext.compiler import compiles
from ...sql import expression
from ...types import Boolean
from ...types import Integer
from ...types import Numeric
from ...types import NVARCHAR
from ...types import String
from ...types import TypeDecorator
from ...types import Unicode
ischema = MetaData()
class CoerceUnicode(TypeDecorator):
impl = Unicode
cache_ok = True
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 NumericSqlVariant(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(38, 0))
identity_columns = Table(
"identity_columns",
ischema,
Column("object_id", Integer),
Column("name", CoerceUnicode),
Column("is_identity", Boolean),
Column("seed_value", NumericSqlVariant),
Column("increment_value", NumericSqlVariant),
Column("last_value", NumericSqlVariant),
Column("is_not_for_replication", Boolean),
schema="sys",
)
class NVarcharSqlVariant(TypeDecorator):
"""This type casts sql_variant columns in the extended_properties view
to nvarchar. This is required because pyodbc does not support sql_variant
"""
impl = Unicode
cache_ok = True
def column_expression(self, colexpr):
return cast(colexpr, NVARCHAR)
extended_properties = Table(
"extended_properties",
ischema,
Column("class", Integer), # TINYINT
Column("class_desc", CoerceUnicode),
Column("major_id", Integer),
Column("minor_id", Integer),
Column("name", CoerceUnicode),
Column("value", NVarcharSqlVariant),
schema="sys",
)

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elitebot/lib/python3.11/site-packages/sqlalchemy/dialects/mssql/json.py Normal file
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# dialects/mssql/json.py
# Copyright (C) 2005-2024 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
# mypy: ignore-errors
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:
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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elitebot/lib/python3.11/site-packages/sqlalchemy/dialects/mssql/provision.py Normal file
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# dialects/mssql/provision.py
# Copyright (C) 2005-2024 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
# mypy: ignore-errors
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 generate_driver_url
from ...testing.provision import get_temp_table_name
from ...testing.provision import log
from ...testing.provision import normalize_sequence
from ...testing.provision import run_reap_dbs
from ...testing.provision import temp_table_keyword_args
@generate_driver_url.for_db("mssql")
def generate_driver_url(url, driver, query_str):
backend = url.get_backend_name()
new_url = url.set(drivername="%s+%s" % (backend, driver))
if driver not in ("pyodbc", "aioodbc"):
new_url = new_url.set(query="")
if driver == "aioodbc":
new_url = new_url.update_query_dict({"MARS_Connection": "Yes"})
if query_str:
new_url = new_url.update_query_string(query_str)
try:
new_url.get_dialect()
except exc.NoSuchModuleError:
return None
else:
return new_url
@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"]
)
)
)
@normalize_sequence.for_db("mssql")
def normalize_sequence(cfg, sequence):
if sequence.start is None:
sequence.start = 1
return sequence

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elitebot/lib/python3.11/site-packages/sqlalchemy/dialects/mssql/pymssql.py Normal file
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# dialects/mssql/pymssql.py
# Copyright (C) 2005-2024 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
# mypy: ignore-errors
"""
.. 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/>`_.
.. versionchanged:: 2.0.5
pymssql was restored to SQLAlchemy's continuous integration testing
""" # noqa
import re
from .base import MSDialect
from .base import MSIdentifierPreparer
from ... import types as sqltypes
from ... import util
from ...engine import processors
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().__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
supports_native_uuid = True
driver = "pymssql"
preparer = MSIdentifierPreparer_pymssql
colspecs = util.update_copy(
MSDialect.colspecs,
{sqltypes.Numeric: _MSNumeric_pymssql, sqltypes.Float: sqltypes.Float},
)
@classmethod
def import_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 get_isolation_level_values(self, dbapi_connection):
return super().get_isolation_level_values(dbapi_connection) + [
"AUTOCOMMIT"
]
def set_isolation_level(self, dbapi_connection, level):
if level == "AUTOCOMMIT":
dbapi_connection.autocommit(True)
else:
dbapi_connection.autocommit(False)
super().set_isolation_level(dbapi_connection, level)
dialect = MSDialect_pymssql

745
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@ -0,0 +1,745 @@
# dialects/mssql/pyodbc.py
# Copyright (C) 2005-2024 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
# mypy: ignore-errors
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")
The ``driver`` keyword is significant to the pyodbc dialect and must be
specified in lowercase.
Any other names passed in the query string are passed through in the pyodbc
connect string, such as ``authentication``, ``TrustServerCertificate``, etc.
Multiple keyword arguments must be separated by an ampersand (``&``); these
will be translated to semicolons when the pyodbc connect string is generated
internally::
e = create_engine(
"mssql+pyodbc://scott:tiger@mssql2017:1433/test?"
"driver=ODBC+Driver+18+for+SQL+Server&TrustServerCertificate=yes"
"&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="mssql2017",
port=1433,
database="test",
query={
"driver": "ODBC Driver 18 for SQL Server",
"TrustServerCertificate": "yes",
"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
----------------
Previous limitations with the SQLAlchemy ORM's "versioned rows" feature with
Pyodbc have been resolved as of SQLAlchemy 2.0.5. See the notes at
:ref:`mssql_rowcount_versioning`.
.. _mssql_pyodbc_fastexecutemany:
Fast Executemany Mode
---------------------
The PyODBC driver includes 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 attribute ``.fast_executemany`` on the DBAPI
cursor when an executemany call is to be used. The SQLAlchemy PyODBC SQL
Server dialect supports this parameter by passing the
``fast_executemany`` parameter to
:func:`_sa.create_engine` , when using the **Microsoft ODBC driver only**::
engine = create_engine(
"mssql+pyodbc://scott:tiger@mssql2017:1433/test?driver=ODBC+Driver+17+for+SQL+Server",
fast_executemany=True)
.. versionchanged:: 2.0.9 - the ``fast_executemany`` parameter now has its
intended effect of this PyODBC feature taking effect for all INSERT
statements that are executed with multiple parameter sets, which don't
include RETURNING. Previously, SQLAlchemy 2.0's :term:`insertmanyvalues`
feature would cause ``fast_executemany`` to not be used in most cases
even if specified.
.. 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
-----------------------
As of version 2.0, the pyodbc ``cursor.setinputsizes()`` method is used for
all statement executions, except for ``cursor.executemany()`` calls when
fast_executemany=True where it is not supported (assuming
:ref:`insertmanyvalues <engine_insertmanyvalues>` is kept enabled,
"fastexecutemany" will not take place for INSERT statements in any case).
The use of ``cursor.setinputsizes()`` can be disabled by passing
``use_setinputsizes=False`` to :func:`_sa.create_engine`.
When ``use_setinputsizes`` is left at its default of ``True``, the
specific per-type symbols passed to ``cursor.setinputsizes()`` can be
programmatically customized using the :meth:`.DialectEvents.do_setinputsizes`
hook. See that method for usage examples.
.. versionchanged:: 2.0 The mssql+pyodbc dialect now defaults to using
``use_setinputsizes=True`` for all statement executions with the exception of
cursor.executemany() calls when fast_executemany=True. The behavior can
be turned off by passing ``use_setinputsizes=False`` to
:func:`_sa.create_engine`.
""" # noqa
import datetime
import decimal
import re
import struct
from .base import _MSDateTime
from .base import _MSUnicode
from .base import _MSUnicodeText
from .base import BINARY
from .base import DATETIMEOFFSET
from .base import MSDialect
from .base import MSExecutionContext
from .base import VARBINARY
from .json import JSON as _MSJson
from .json import JSONIndexType as _MSJsonIndexType
from .json import JSONPathType as _MSJsonPathType
from ... import exc
from ... import types as sqltypes
from ... import util
from ...connectors.pyodbc import PyODBCConnector
from ...engine import cursor as _cursor
class _ms_numeric_pyodbc:
"""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().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:
"""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:
"""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, str):
# 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, _MSDateTime):
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 _String_pyodbc(sqltypes.String):
def get_dbapi_type(self, dbapi):
if self.length in (None, "max") or self.length >= 2000:
return (dbapi.SQL_VARCHAR, 0, 0)
else:
return dbapi.SQL_VARCHAR
class _Unicode_pyodbc(_MSUnicode):
def get_dbapi_type(self, dbapi):
if self.length in (None, "max") or self.length >= 2000:
return (dbapi.SQL_WVARCHAR, 0, 0)
else:
return dbapi.SQL_WVARCHAR
class _UnicodeText_pyodbc(_MSUnicodeText):
def get_dbapi_type(self, dbapi):
if self.length in (None, "max") or self.length >= 2000:
return (dbapi.SQL_WVARCHAR, 0, 0)
else:
return dbapi.SQL_WVARCHAR
class _JSON_pyodbc(_MSJson):
def get_dbapi_type(self, dbapi):
return (dbapi.SQL_WVARCHAR, 0, 0)
class _JSONIndexType_pyodbc(_MSJsonIndexType):
def get_dbapi_type(self, dbapi):
return dbapi.SQL_WVARCHAR
class _JSONPathType_pyodbc(_MSJsonPathType):
def get_dbapi_type(self, dbapi):
return dbapi.SQL_WVARCHAR
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().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)
rows = self.cursor.fetchall()
except self.dialect.dbapi.Error:
# no way around this - nextset() consumes the previous set
# so we need to just keep flipping
self.cursor.nextset()
else:
if not rows:
# async adapter drivers just return None here
self.cursor.nextset()
continue
row = rows[0]
break
self._lastrowid = int(row[0])
self.cursor_fetch_strategy = _cursor._NO_CURSOR_DML
else:
super().post_exec()
class MSDialect_pyodbc(PyODBCConnector, MSDialect):
supports_statement_cache = True
# note this parameter is no longer used by the ORM or default dialect
# see #9414
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,
sqltypes.String: _String_pyodbc,
sqltypes.Unicode: _Unicode_pyodbc,
sqltypes.UnicodeText: _UnicodeText_pyodbc,
sqltypes.JSON: _JSON_pyodbc,
sqltypes.JSON.JSONIndexType: _JSONIndexType_pyodbc,
sqltypes.JSON.JSONPathType: _JSONPathType_pyodbc,
# this excludes Enum from the string/VARCHAR thing for now
# it looks like Enum's adaptation doesn't really support the
# String type itself having a dialect-level impl
sqltypes.Enum: sqltypes.Enum,
},
)
def __init__(
self,
fast_executemany=False,
use_setinputsizes=True,
**params,
):
super().__init__(use_setinputsizes=use_setinputsizes, **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
if fast_executemany:
self.use_insertmanyvalues_wo_returning = False
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()._get_server_version_info(connection)
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().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,
datetime.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().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().is_disconnect(e, connection, cursor)
dialect = MSDialect_pyodbc