Reputation: 123399
I would like to upsert my pandas DataFrame into a SQL Server table. This question has a workable solution for PostgreSQL, but T-SQL does not have an ON CONFLICT
variant of INSERT
. How can I accomplish the same thing for SQL Server?
Upvotes: 1
Views: 9321
Reputation: 123399
Update, July 2022: You can save some typing by using this function to build the MERGE statement and perform the upsert for you.
SQL Server offers the MERGE statement:
import pandas as pd
import sqlalchemy as sa
connection_string = (
"Driver=ODBC Driver 17 for SQL Server;"
"Server=192.168.0.199;"
"UID=scott;PWD=tiger^5HHH;"
"Database=test;"
"UseFMTONLY=Yes;"
)
connection_url = sa.engine.URL.create(
"mssql+pyodbc",
query={"odbc_connect": connection_string}
)
engine = sa.create_engine(connection_url, fast_executemany=True)
with engine.begin() as conn:
# step 0.0 - create test environment
conn.exec_driver_sql("DROP TABLE IF EXISTS main_table")
conn.exec_driver_sql(
"CREATE TABLE main_table (id int primary key, txt varchar(50))"
)
conn.exec_driver_sql(
"INSERT INTO main_table (id, txt) VALUES (1, 'row 1 old text')"
)
# step 0.1 - create DataFrame to UPSERT
df = pd.DataFrame(
[(2, "new row 2 text"), (1, "row 1 new text")], columns=["id", "txt"]
)
# step 1 - upload DataFrame to temporary table
df.to_sql("#temp_table", conn, index=False, if_exists="replace")
# step 2 - merge temp_table into main_table
conn.exec_driver_sql(
"""\
MERGE main_table WITH (HOLDLOCK) AS main
USING (SELECT id, txt FROM #temp_table) AS temp
ON (main.id = temp.id)
WHEN MATCHED THEN
UPDATE SET txt = temp.txt
WHEN NOT MATCHED THEN
INSERT (id, txt) VALUES (temp.id, temp.txt);
"""
)
# step 3 - confirm results
result = conn.exec_driver_sql(
"SELECT * FROM main_table ORDER BY id"
).fetchall()
print(result)
# [(1, 'row 1 new text'), (2, 'new row 2 text')]
Upvotes: 5