Pandas to_sql doesn't insert any data in my table

Question

I am trying to insert some data in a table I have created. I have a data frame that looks like this:

I created a table:

create table online.ds_attribution_probabilities
(
attribution_type text,
channel text,
date date ,
value float
)

And I am running this python script:

engine = create_engine("postgresql://@e.eu-central-1.redshift.amazonaws.com:5439/mdhclient_encoding=utf8")
connection = engine.raw_connection()
result.to_sql('online.ds_attribution_probabilities', con=engine, index = False, if_exists = 'append')

I get no error, but when I check there are no data in my table. What can be wrong? Do I have to commit or do an extra step?

Answer 1

Try to specify a schema name:

result.to_sql('ds_attribution_probabilities', con=engine, 
              schema='online', index=False, if_exists='append')

Answer 2

Hopefully this helps someone else. to_sql will fail silently in the form of what looks like a successful insert if you pass a connection object. This is definitely true for Postgres, but i assume the same for others as well, based on the method docs:

con : sqlalchemy.engine.Engine or sqlite3.Connection
    Using SQLAlchemy makes it possible to use any DB supported by that
    library. Legacy support is provided for sqlite3.Connection objects.

This got me because the typing hints stated Union[Engine, Connection] , which is "technically" true.

If you have a session with SQLAlchemy try passing con=session.get_bind(),

Answer 3

I had a similar issue caused by the fact that I was passing sqlalchemy connection object instead of engine object to the con parameter. In my case tables were created but left empty.

Answer 4

In my case, writing data to the database was hampered by the fast option.

Why is this not fast loading interfering, I have not yet figured out.

This code doesn't work:

engine = sqlalchemy.create_engine("mssql+pyodbc:///?odbc_connect={}".format(db_params), fast_executemany=True)
df.to_sql('tablename', engine, index=False, schema = 'dbo', if_exists='replace' )

Without fast_executemany=True the code works well.

Answer 5

检查autocommit设置： https : //docs.sqlalchemy.org/en/latest/core/connections.html#understanding-autocommit

engine.execute(text("SELECT my_mutating_procedure()").execution_options(autocommit=True))

Answer 6

I have a similar situation. Not able to insert pandas dataframe into oracle table. I am using cx_oracle and SQLalchemy for oracle connection. There is no error. I am using following command:

pd_df.to_sql('abc.xyz', conn, schema = 'abc', if_exists='replace', index='false')

Answer 7

I faced the same problem when I used .connect() and .begin()

with engine.connect() as conn, conn.begin():
         dataframe.to_sql(name='table_name', schema='schema',
         con=conn, if_exists='append', index=False)
         conn.close()

Just remove the .connect() and .begin() and it will work.

Answer 8

This could happen because it defaults to the public database, and there's probably a table with that name under the public database/schema, with your data in it.

@MaxU's answer does help some, but not the others. For others, here is something else you can try:

When you create the engine, specify the schemaname like this:

engine = create_engine(*<connection_string>*,
    connect_args={'options': '-csearch_path={}'.format(*<dbschema_name>*)})

Link: https://stackoverflow.com/a/49930672/8656608