Update: You can save yourself some typing by using this method.
If you are using PostgreSQL 9.5 or later you can perform the UPSERT using a temporary table and an INSERT ... ON CONFLICT statement:
import sqlalchemy as sa
# …
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 - create temporary table and upload DataFrame
conn.exec_driver_sql(
"CREATE TEMPORARY TABLE temp_table AS SELECT * FROM main_table WHERE false"
)
df.to_sql("temp_table", conn, index=False, if_exists="append")
# step 2 - merge temp_table into main_table
conn.exec_driver_sql(
"""\
INSERT INTO main_table (id, txt)
SELECT id, txt FROM temp_table
ON CONFLICT (id) DO
UPDATE SET txt = EXCLUDED.txt
"""
)
# step 3 - confirm results
result = conn.exec_driver_sql("SELECT * FROM main_table ORDER BY id").all()
print(result) # [(1, 'row 1 new text'), (2, 'new row 2 text')]
Answer from Gord Thompson on Stack OverflowUpdate: You can save yourself some typing by using this method.
If you are using PostgreSQL 9.5 or later you can perform the UPSERT using a temporary table and an INSERT ... ON CONFLICT statement:
import sqlalchemy as sa
# …
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 - create temporary table and upload DataFrame
conn.exec_driver_sql(
"CREATE TEMPORARY TABLE temp_table AS SELECT * FROM main_table WHERE false"
)
df.to_sql("temp_table", conn, index=False, if_exists="append")
# step 2 - merge temp_table into main_table
conn.exec_driver_sql(
"""\
INSERT INTO main_table (id, txt)
SELECT id, txt FROM temp_table
ON CONFLICT (id) DO
UPDATE SET txt = EXCLUDED.txt
"""
)
# step 3 - confirm results
result = conn.exec_driver_sql("SELECT * FROM main_table ORDER BY id").all()
print(result) # [(1, 'row 1 new text'), (2, 'new row 2 text')]
I have needed this so many times, I ended up creating a gist for it.
The function is below, it will create the table if it is the first time persisting the dataframe and will update the table if it already exists:
import pandas as pd
import sqlalchemy
import uuid
import os
def upsert_df(df: pd.DataFrame, table_name: str, engine: sqlalchemy.engine.Engine):
"""Implements the equivalent of pd.DataFrame.to_sql(..., if_exists='update')
(which does not exist). Creates or updates the db records based on the
dataframe records.
Conflicts to determine update are based on the dataframes index.
This will set unique keys constraint on the table equal to the index names
1. Create a temp table from the dataframe
2. Insert/update from temp table into table_name
Returns: True if successful
"""
# If the table does not exist, we should just use to_sql to create it
if not engine.execute(
f"""SELECT EXISTS (
SELECT FROM information_schema.tables
WHERE table_schema = 'public'
AND table_name = '{table_name}');
"""
).first()[0]:
df.to_sql(table_name, engine)
return True
# If it already exists...
temp_table_name = f"temp_{uuid.uuid4().hex[:6]}"
df.to_sql(temp_table_name, engine, index=True)
index = list(df.index.names)
index_sql_txt = ", ".join([f'"{i}"' for i in index])
columns = list(df.columns)
headers = index + columns
headers_sql_txt = ", ".join(
[f'"{i}"' for i in headers]
) # index1, index2, ..., column 1, col2, ...
# col1 = exluded.col1, col2=excluded.col2
update_column_stmt = ", ".join([f'"{col}" = EXCLUDED."{col}"' for col in columns])
# For the ON CONFLICT clause, postgres requires that the columns have unique constraint
query_pk = f"""
ALTER TABLE "{table_name}" DROP CONSTRAINT IF EXISTS unique_constraint_for_upsert;
ALTER TABLE "{table_name}" ADD CONSTRAINT unique_constraint_for_upsert UNIQUE ({index_sql_txt});
"""
engine.execute(query_pk)
# Compose and execute upsert query
query_upsert = f"""
INSERT INTO "{table_name}" ({headers_sql_txt})
SELECT {headers_sql_txt} FROM "{temp_table_name}"
ON CONFLICT ({index_sql_txt}) DO UPDATE
SET {update_column_stmt};
"""
engine.execute(query_upsert)
engine.execute(f"DROP TABLE {temp_table_name}")
return True
I made a Pandas.to_sql_upsert()
python - Insert into postgreSQL table from pandas with "on conflict" update - Stack Overflow
perform upsert operation on postgres like pandas to_sql function using python - Stack Overflow
Pandas to SQL DB
» pip install pangres
Hi guys. I made a Pandas.to_sql() upsert that uses the same syntax as Pandas.to_sql(), but allows you to upsert based on unique column(s): https://github.com/vile319/sql_upsert
This is incredibly useful to me for scraping multiple times daily with a live baseball database. The only thing is, I would prefer if pandas had this built in to the package, and I did open a pull request about it, but I think they are too busy to care.
Maybe it is just a stupid idea? I would like to know your opinions on whether or not pandas should have upsert. I think my code handles it pretty well as a workaround, but I feel like Pandas could just do this as part of their package. Maybe I am just thinking about this all wrong?
Not sure if this is the wrong subreddit to post this on. While this I guess is technically self promotion, I would much rather delete my package in exchange for pandas adopting any equivalent.
I know it's an old thread, but I ran into the same issue and this thread showed up in Google. None of the answers is really satisfying yet, so I here's what I came up with:
My solution is pretty similar to zdgriffith's answer, but much more performant as there's no need to iterate over data_iter:
Copydef postgres_upsert(table, conn, keys, data_iter):
from sqlalchemy.dialects.postgresql import insert
data = [dict(zip(keys, row)) for row in data_iter]
insert_statement = insert(table.table).values(data)
upsert_statement = insert_statement.on_conflict_do_update(
constraint=f"{table.table.name}_pkey",
set_={c.key: c for c in insert_statement.excluded},
)
conn.execute(upsert_statement)
Now you can use this custom upsert method in pandas' to_sql method like zdgriffith showed.
Please note that my upsert function uses the primary key constraint of the table. You can target another constraint by changing the constraint argument of .on_conflict_do_update.
This SO answer on a related thread explains the use of .excluded a bit more: https://stackoverflow.com/a/51935542/7066758
@ SaturnFromTitan, thanks for the reply to this old thread. That worked like magic. I would upvote, but I don't have the rep.
For those that are as new to all this as I am: You can cut and paste SaturnFromTitan answer and call it with something like:
Copy df.to_sql('my_table_name',
dbConnection,schema='my_schema',
if_exists='append',
index=False,
method=postgres_upsert)
And that's it. The upsert works.