Bump sqlalchemy from 1.4.42 to 2.0.9

[dependabot]

Bumps sqlalchemy from 1.4.42 to 2.0.9.

Release notes

Sourced from sqlalchemy's releases.

2.0.9

Released: April 5, 2023

orm

• [orm] [bug] Fixed endless loop which could occur when using "relationship to aliased class" feature and also indicating a recursive eager loader such as lazy="selectinload" in the loader, in combination with another eager loader on the opposite side. The check for cycles has been fixed to include aliased class relationships.

  This change is also backported to: 1.4.48

  References: #9590

mariadb

• [mariadb] [bug] Added row_number as reserved word in MariaDb.

  References: #9588

mssql

• [mssql] [bug] Due to a critical bug identified in SQL Server, the SQLAlchemy "insertmanyvalues" feature which allows fast INSERT of many rows while also supporting RETURNING unfortunately needs to be disabled for SQL Server. SQL Server is apparently unable to guarantee that the order of rows inserted matches the order in which they are sent back by OUTPUT inserted when table-valued rows are used with INSERT in conjunction with OUTPUT inserted. We are trying to see if Microsoft is able to confirm this undocumented behavior however there is no known workaround, other than it's not safe to use table-valued expressions with OUTPUT inserted for now.

  References: #9603

• [mssql] [bug] Changed the bulk INSERT strategy used for SQL Server "executemany" with pyodbc when fast_executemany is set to True by using fast_executemany / cursor.executemany() for bulk INSERT that does not include RETURNING, restoring the same behavior as was used in SQLAlchemy 1.4 when this parameter is set.

  New performance details from end users have shown that fast_executemany is still much faster for very large datasets as it uses ODBC commands that can receive all rows in a single round trip, allowing for much larger datasizes than the batches that can be sent by "insertmanyvalues" as was implemented for SQL Server.

... (truncated)

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