Python Pandas to_sql, how to create a table with a primary key?

with engine.connect() as con:
    con.execute('ALTER TABLE for_import_ml ADD PRIMARY KEY ("ID");')

for_import_ml is a table name in the database.

Adding a slight variation to tomp's answer (I would comment but don't have enough reputation points).

I am using PGAdmin with Postgres (on Heroku) to check and it works.

Disclaimer: this answer is more experimental then practical, but maybe worth mention.

I found that class pandas.io.sql.SQLTable has named argument key and if you assign it the name of the field then this field becomes the primary key:

Unfortunately you can't just transfer this argument from DataFrame.to_sql() function. To use it you should:

1. create pandas.io.SQLDatabase instance

   engine = sa.create_engine('postgresql:///somedb')
   pandas_sql = pd.io.sql.pandasSQL_builder(engine, schema=None, flavor=None)
   

2. define function analoguous to pandas.io.SQLDatabase.to_sql() but with additional *kwargs argument which is passed to pandas.io.SQLTable object created inside it (i've just copied original to_sql() method and added *kwargs):

   def to_sql_k(self, frame, name, if_exists='fail', index=True,
              index_label=None, schema=None, chunksize=None, dtype=None, **kwargs):
       if dtype is not None:
           from sqlalchemy.types import to_instance, TypeEngine
           for col, my_type in dtype.items():
               if not isinstance(to_instance(my_type), TypeEngine):
                   raise ValueError('The type of %s is not a SQLAlchemy '
                                    'type ' % col)
   
       table = pd.io.sql.SQLTable(name, self, frame=frame, index=index,
                        if_exists=if_exists, index_label=index_label,
                        schema=schema, dtype=dtype, **kwargs)
       table.create()
       table.insert(chunksize)
   

3. call this function with your SQLDatabase instance and the dataframe you want to save

   to_sql_k(pandas_sql, df2save, 'tmp',
           index=True, index_label='id', keys='id', if_exists='replace')
   

And we get something like

CREATE TABLE public.tmp
(
  id bigint NOT NULL DEFAULT nextval('tmp_id_seq'::regclass),
...
)

in the database.

PS You can of course monkey-patch DataFrame, io.SQLDatabase and io.to_sql() functions to use this workaround with convenience.

As of pandas 0.15, at least for some flavors, you can use argument dtype to define a primary key column. You can even activate AUTOINCREMENT this way. For sqlite3, this would look like so:

import sqlite3
import pandas as pd

df = pd.DataFrame({'MyID': [1, 2, 3], 'Data': [3, 2, 6]})
with sqlite3.connect('foo.db') as con:
    df.to_sql('df', con=con, dtype={'MyID': 'INTEGER PRIMARY KEY AUTOINCREMENT'})

Simply add the primary key after uploading the table with pandas.

group_export.to_sql(con=engine, name=example_table, if_exists='replace', 
                    flavor='mysql', index=False)

with engine.connect() as con:
    con.execute('ALTER TABLE `example_table` ADD PRIMARY KEY (`ID_column`);')