CODEWITHSUNDEEP
pythonpandassqlalchemy
Nasia Ntalla
Nasia Ntalla

Reputation: 1789

Pandas to_sql doesn't insert any data in my table

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

dataframe

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?

Upvotes: 39

Views: 54892

Answers (12)

debo
debo

Reputation: 380

This is what worked for me,

engine = create_engine('postgresql://username:password@localhost:5432/database_name')
with engine.begin() as connection:
     dataset.to_sql(name='table_name', con=connection, schema='schema_name', if_exists='append', index=False)

Use engine.begin()

Upvotes: 0

Atehe
Atehe

Reputation: 117

Check that you are passing in the database to create_engine

for postgres, it will be something like this

engine = create_engine(f'postgresql://{DB_USER}:{DB_PASS}@{DB_HOST}:{DB_PORT}/{DB_NAME}')

Upvotes: 0

Arnab Roy
Arnab Roy

Reputation: 317

5 Years later faced the same issue with PostgreSQL.

I solved it by passing the actual connection object instead of the engine itself (which I did previously).

engine = create_engine('postgresql://username:password@localhost:5432/database_name')
with engine.connect() as connection:
     dataset.to_sql(name='table_name', con=connection, schema='schema_name', if_exists='append', chunksize=1000, index=False)

Previously I was doing

engine = create_engine('postgresql://username:password@localhost:5432/database_name')
dataset.to_sql(name='table_name', con=engine, schema='schema_name', if_exists='append', chunksize=1000, index=False)

As you may have noticed above that I have passed the schema_name too. I did that after I saw the responses above. But that did not solve the issue.

While the table was created in the DB, no records were written into it. I found it pretty strange due to this last bit. I could have fully understood if the table itself wasn't getting created and I would have concluded that Python is failing to establish a database connection altogether.

Upvotes: 0

Maruf Ibragimov
Maruf Ibragimov

Reputation: 43

Try adding commit after you code, like this:

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

Works for me.

Upvotes: 1

Julio Marins
Julio Marins

Reputation: 10649

use method=None

None : Uses standard SQL INSERT clause (one per row).

https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.to_sql.html

Mine worked like this:

df.to_sql(name=table_name, method=None, schema=schema, index=False, if_exists='append', chunksize=50, con=conn.get_bind())

*table_name without prepending the schema name

Upvotes: 0

Alex Zidcov
Alex Zidcov

Reputation: 41

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.

Upvotes: 4

lewk
lewk

Reputation: 201

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(),

Upvotes: 20

Flavio
Flavio

Reputation: 839

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.

Upvotes: 1

Tony
Tony

Reputation: 31

Check the autocommit setting: https://docs.sqlalchemy.org/en/latest/core/connections.html#understanding-autocommit

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

Upvotes: 2

PierPuce
PierPuce

Reputation: 181

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.

Upvotes: 17

being_felicity
being_felicity

Reputation: 91

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

Upvotes: 1

MaxU - stand with Ukraine
MaxU - stand with Ukraine

Reputation: 210852

Try to specify a schema name:

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

Upvotes: 62

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