awswrangler.data_api.rds.to_sql

awswrangler.data_api.rds.to_sql(df: DataFrame, con: RdsDataApi, table: str, database: str, mode: Literal['append', 'overwrite'] = 'append', index: bool = False, dtype: dict[str, str] | None = None, varchar_lengths: dict[str, int] | None = None, use_column_names: bool = False, chunksize: int = 200, sql_mode: str = 'mysql') → None

Insert data using an SQL query on a Data API connection.

Parameters:

  • df (DataFrame) – Pandas DataFrame

  • con (RdsDataApi) – A RdsDataApi connection instance

  • database (str) – Database to run query on - defaults to the database specified by con.

  • table (str) – Table name

  • mode (Literal['append', 'overwrite']) – append (inserts new records into table), overwrite (drops table and recreates)

  • index (bool) – True to store the DataFrame index as a column in the table, otherwise False to ignore it.

  • dtype (dict[str, str] | None) – Dictionary of columns names and MySQL types to be casted. Useful when you have columns with undetermined or mixed data types. (e.g. `{'col name': 'TEXT', 'col2 name': 'FLOAT'}`)

  • varchar_lengths (dict[str, int] | None) – Dict of VARCHAR length by columns. (e.g. `{"col1": 10, "col5": 200}`).

  • use_column_names (bool) – If set to True, will use the column names of the DataFrame for generating the INSERT SQL Query. E.g. If the DataFrame has two columns col1 and col3 and use_column_names is True, data will only be inserted into the database columns col1 and col3.

  • chunksize (int) – Number of rows which are inserted with each SQL query. Defaults to inserting 200 rows per query.

  • sql_mode (str) – “mysql” for default MySQL identifiers (backticks) or “ansi” for ANSI-compatible identifiers (double quotes).

Return type:

None