awswrangler.postgresql.to_sql¶
-
awswrangler.postgresql.
to_sql
(df: pandas.core.frame.DataFrame, con: pg8000.core.Connection, table: str, schema: str, mode: str = 'append', index: bool = False, dtype: Optional[Dict[str, str]] = None, varchar_lengths: Optional[Dict[str, int]] = None) → None¶ Write records stored in a DataFrame into PostgreSQL.
- Parameters
df (pandas.DataFrame) – Pandas DataFrame https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.html
con (pg8000.Connection) – Use pg8000.connect() to use credentials directly or wr.postgresql.connect() to fetch it from the Glue Catalog.
table (str) – Table name
schema (str) – Schema name
mode (str) – Append or overwrite.
index (bool) – True to store the DataFrame index as a column in the table, otherwise False to ignore it.
dtype (Dict[str, str], optional) – Dictionary of columns names and PostgreSQL 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], optional) – Dict of VARCHAR length by columns. (e.g. {“col1”: 10, “col5”: 200}).
- Returns
None.
- Return type
None
Examples
Writing to PostgreSQL using a Glue Catalog Connections
>>> import awswrangler as wr >>> con = wr.postgresql.connect("MY_GLUE_CONNECTION") >>> wr.postgresql.to_sql( ... df=df, ... table="my_table", ... schema="public", ... con=con ... ) >>> con.close()