redshift-auto-schema 0.1.4

Auto-generate Redshift schemas from flat files

Redshift Auto Schema

Redshift Auto Schema is a Python library that takes a delimited flat file or parquet file as input, parses it, and provides a variety of functions that allow for the creation and validation of tables within Amazon Redshift. For each field, the appropriate Redshift data type is inferred from the contents of the file.

Installation

Use the package manager pip to install Redshift Auto Schema.

pip install redshift-auto-schema

Usage

from redshift_auto_schema import RedshiftAutoSchema
import psycopg2 as pg

redshift_conn = pg.connect()

new_table = RedshiftAutoSchema(file='sample_file.parquet',
                               schema='test_schema',
                               table='test_table',
                               conn=redshift_conn)

if not new_table.check_table_existence():
    ddl = new_table.generate_table_ddl()

    with redshift_conn.cursor() as redshift_cursor:
        redshift_cursor.execute(ddl)

Methods

NAME	DESCRIPTION
get_column_list	Returns column list based on header of file.
check_schema_existence	Checks Redshift for the existence of a schema.
check_table_existence	Checks Redshift for the existence of a table.
generate_schema_ddl	Returns a SQL statement that creates a Redshift schema.
generate_schema_permissions	Returns a SQL statement that grants schema usage to the default group.
generate_table_ddl	Returns a SQL statement that creates a Redshift table.
generate_column_ddl	Returns SQL statement(s) that adds missing column(s) a Redshift table.
generate_table_permissions	Returns a SQL statement that grants table read access to the default group.
evaluate_table_ddl_diffs	Returns a dataframe containing differences between generated and existing table DDL.

Contributing

Pull requests are welcome.

License

Apache License 2.0