Bulk Saving and Updating while returning IDs

So I’m using sqlalchemy for a project I’m working on. I’ve got an issue where I will eventually have thousands of records that need to be saved every hour. These records may be inserted or updated. I’ve been using bulk_save_objects for this and it’s worked great. However now I have to introduce a history to these records being saved, which means I need the IDs returned so I can link these entries to an entry in a history table. I know about using return_defaults, and that works. However, it introduces a problem that my bulk_save_objects inserts and updates one entry at a time, instead of in bulk, which removes the purpose. Is there another option, where I can bulk insert and update at the same time, but retain the IDs?

Answer

The desired result can be achieved using a technique similar to the one described in the answer here by uploading the rows to a temporary table and then performing an UPDATE followed by an INSERT that returns the inserted ID values. For SQL Server, that would be an OUTPUT clause on the INSERT statement:

main_table = "team"

# <set up test environment>
with engine.begin() as conn:
    conn.execute(sa.text(f"DROP TABLE IF EXISTS [{main_table}]"))
    conn.execute(
        sa.text(
            f"""
            CREATE TABLE [dbo].[{main_table}](
                [id] [int] IDENTITY(1,1) NOT NULL,
                [prov] [varchar](2) NOT NULL,
                [city] [varchar](50) NOT NULL,
                [name] [varchar](50) NOT NULL,
                [comments] [varchar](max) NULL,
             CONSTRAINT [PK_team] PRIMARY KEY CLUSTERED 
            (
                [id] ASC
            )
            )
            """
        )
    )
    conn.execute(
        sa.text(
            f"""
            CREATE UNIQUE NONCLUSTERED INDEX [UX_team_prov_city] ON [dbo].[{main_table}]
            (
                [prov] ASC,
                [city] ASC
            )            
            """
        )
    )
    conn.execute(
        sa.text(
            f"""
            INSERT INTO [{main_table}] ([prov], [city], [name])
            VALUES ('AB', 'Calgary', 'Flames')            
            """
        )
    )

# <data for upsert>
df = pd.DataFrame(
    [
        ("AB", "Calgary", "Flames", "hard-working, handsome lads"),
        ("AB", "Edmonton", "Oilers", "ruffians and scalawags"),
    ],
    columns=["prov", "city", "name", "comments"],
)

# <perform upsert, returning IDs>
temp_table = "#so65525098"
with engine.begin() as conn:
    df.to_sql(temp_table, conn, index=False, if_exists="replace")
    conn.execute(
        sa.text(
            f"""
            UPDATE main SET main.name = temp.name, 
                main.comments = temp.comments
            FROM [{main_table}] main INNER JOIN [{temp_table}] temp
                ON main.prov = temp.prov AND main.city = temp.city
            """
        )
    )
    inserted = conn.execute(
        sa.text(
            f"""
            INSERT INTO [{main_table}] (prov, city, name, comments)
            OUTPUT INSERTED.prov, INSERTED.city, INSERTED.id
            SELECT prov, city, name, comments FROM [{temp_table}] temp
            WHERE NOT EXISTS (
                SELECT * FROM [{main_table}] main
                WHERE main.prov = temp.prov AND main.city = temp.city
            )
            """
        )
    ).fetchall()
    print(inserted)
    """console output:
    [('AB', 'Edmonton', 2)]
    """

# <check results>
with engine.begin() as conn:
    pprint(conn.execute(sa.text(f"SELECT * FROM {main_table}")).fetchall())
    """console output:
    [(1, 'AB', 'Calgary', 'Flames', 'hard-working, handsome lads'),
     (2, 'AB', 'Edmonton', 'Oilers', 'ruffians and scalawags')]
    """