pandas2redshift 0.0.4

A tool for exporting Pandas dataframes to Redshift tables

Pandas2Redshift

This is a utility library for uploading a Pandas DataFrame to Amazon Redshift table, utilizing AWS S3 for temporary storage.

Features

• Upload a Pandas DataFrame to a Redshift Table
• Uses the COPY command, using S3 as a middleware for fast inserts on Redshift
• Can create the table for you based on a Dict containing the datatypes or generates it automatically based on the pandas datatypes of the dataframe

Installation

Install the package using pip:

pip install pandas2redshift

Usage

Insert Data into Redshift

Insert data from a DataFrame into a Redshift table:

import pandas as pd
from sqlalchemy import create_engine
import pandas2redshift as p2r

data = pd.DataFrame({'col1': [1, 2], 'col2': ['a', 'b']})
engine = create_engine('redshift+psycopg2://user:password@host:port/dbname')

with engine.connect() as conn:
    p2r.insert(
        data=data,
        table_name='my_table',
        schema='public',
        conn=conn,
        aws_access_key='YOUR_AWS_ACCESS_KEY',
        aws_secret_key='YOUR_AWS_SECRET_KEY',
        aws_bucket_name='YOUR_S3_BUCKET_NAME',
    )

You can enhance the functionality of the insert function with several optional arguments:

• ensure_exists (bool, optional): Checks if the schema and table you are inserting data into exist in the database. If they do not exist, it creates them. Defaults to False.
• truncate_table (bool, optional): When set to True, truncates the target table before inserting the data. Defaults to False.
• table_data_types (Dict[str, str], optional): A dictionary specifying column names and their data types for table creation. If not provided, it infers the data types based on pandas dtypes and the mapping defined in the pandas_to_redshift_datatypes function. Defaults to None.