Database upsert all dataframe data
having a DataFrame df, how do I best approach upserting it's data into a postgres database?
I use the following code to upload the data - this seems to be super efficient (way more than pd.to_sql):
def to_sql(engine: sqlalchemy.engine, df: pd.DataFrame, table, if_exists='append', sep='t', encoding='utf8'):
# df[:0].to_sql(table, engine, if_exists=if_exists) # Not needed as the table has to exist
output = StringIO()
df.to_csv(output, sep=sep, header=False, encoding=encoding, index=False)
output.seek(0)
connection = engine.raw_connection()
cursor = connection.cursor()
cursor.copy_from(output, table, sep=sep, null='', columns=list(df.columns))
connection.commit()
cursor.close()
When I think about UPSERT the data though, an approach like that does obviously not work.
Thanks!
python pandas sqlalchemy
asked Nov 11 at 18:05
Bishonen_PL
1429
add a comment |
having a DataFrame df, how do I best approach upserting it's data into a postgres database?
I use the following code to upload the data - this seems to be super efficient (way more than pd.to_sql):
def to_sql(engine: sqlalchemy.engine, df: pd.DataFrame, table, if_exists='append', sep='t', encoding='utf8'):
# df[:0].to_sql(table, engine, if_exists=if_exists) # Not needed as the table has to exist
output = StringIO()
df.to_csv(output, sep=sep, header=False, encoding=encoding, index=False)
output.seek(0)
connection = engine.raw_connection()
cursor = connection.cursor()
cursor.copy_from(output, table, sep=sep, null='', columns=list(df.columns))
connection.commit()
cursor.close()
When I think about UPSERT the data though, an approach like that does obviously not work.
Thanks!
python pandas sqlalchemy
asked Nov 11 at 18:05
Bishonen_PL
1429
add a comment |
having a DataFrame df, how do I best approach upserting it's data into a postgres database?
I use the following code to upload the data - this seems to be super efficient (way more than pd.to_sql):
def to_sql(engine: sqlalchemy.engine, df: pd.DataFrame, table, if_exists='append', sep='t', encoding='utf8'):
# df[:0].to_sql(table, engine, if_exists=if_exists) # Not needed as the table has to exist
output = StringIO()
df.to_csv(output, sep=sep, header=False, encoding=encoding, index=False)
output.seek(0)
connection = engine.raw_connection()
cursor = connection.cursor()
cursor.copy_from(output, table, sep=sep, null='', columns=list(df.columns))
connection.commit()
cursor.close()
When I think about UPSERT the data though, an approach like that does obviously not work.
Thanks!
python pandas sqlalchemy
asked Nov 11 at 18:05
Bishonen_PL
1429
having a DataFrame df, how do I best approach upserting it's data into a postgres database?
I use the following code to upload the data - this seems to be super efficient (way more than pd.to_sql):
def to_sql(engine: sqlalchemy.engine, df: pd.DataFrame, table, if_exists='append', sep='t', encoding='utf8'):
# df[:0].to_sql(table, engine, if_exists=if_exists) # Not needed as the table has to exist
output = StringIO()
df.to_csv(output, sep=sep, header=False, encoding=encoding, index=False)
output.seek(0)
connection = engine.raw_connection()
cursor = connection.cursor()
cursor.copy_from(output, table, sep=sep, null='', columns=list(df.columns))
connection.commit()
cursor.close()
When I think about UPSERT the data though, an approach like that does obviously not work.
Thanks!
python pandas sqlalchemy
python pandas sqlalchemy
asked Nov 11 at 18:05
Bishonen_PL
1429
asked Nov 11 at 18:05
Bishonen_PL
1429
asked Nov 11 at 18:05
Bishonen_PL
1429
asked Nov 11 at 18:05
Bishonen_PL
1429
asked Nov 11 at 18:05
Bishonen_PL
1429
1429
add a comment |
add a comment |
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