How to Create Tables with Primary Keys using Pandas to_sql?

Pandas to_sql: Creating Tables with Primary Keys

The Pandas library provides a convenient method (to_sql) for exporting dataframes to SQL databases. However, users may encounter situations where they need to create tables with primary keys using to_sql.

The default behavior of to_sql does not enable automatic creation of primary keys. While the documentation mentions the option to use index and index_label to create indexes, there is no explicit parameter for primary keys.

To address this issue, we can utilize a combination of to_sql and direct SQL manipulation:

# Create the table without a primary key
group_export.to_sql(con = db, name = config.table_group_export, 
                    if_exists = 'replace', flavor = 'mysql', index = False)

# Execute a separate SQL statement to add the primary key
with db.connect() as con:
    con.execute('ALTER TABLE `' + config.table_group_export + '` ADD PRIMARY KEY (`field_name`)')

In this approach, we first use to_sql to create the table without a primary key. Then, we establish a connection to the database and execute an ALTER TABLE statement to add the desired primary key constraint to the table. By specifying the field name within the parentheses of ADD PRIMARY KEY, we define which column should serve as the primary key.

Using this method, it is possible to create MySQL tables with primary keys using Pandas' to_sql function and subsequent SQL manipulation.

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