pandalchemy: an intuitive combination of Pandas and sqlalchemy to manipulate sql databases with pandas

What is it?

pandalchemy is a Python package that lets Data Scientists create and manipulte sql databases with the Pandas package that they know and love without needing to learn the ins and outs of sqlalchemy.

Main Features

Here are just a few of the things that pandalchemy does:

• Pulls down any sql table as a Pandas DataFrame with sqlalchemy and maintains all data types, keys, and indexes after you push your changes.
• Make changes to Pandas DataFrame as you normally would then push any changes (new columns, delete columns, new rows, updated rows) to sql database.
• Adds a primary key to a new sql table, something pandas to_sql method does not do.
• Add or delete columns in a database table thanks to sqlalchemy-migrate.

Where to get it

The source code is currently hosted on GitHub at: https://github.com/eddiethedean/pandalchemy

# PyPI
pip install pandalchemy

Dependencies

• pandas
• sqlalchemy==1.3.18
• sqlalchemy-migrate
• numpy
• [tabulate]

Example code

from sqlalchemy import create_engine 
import pandalchemy as ba 
        
# Use sqlalchemy to create an engine to connect to existing database 
engine = create_engine('postgresql://scott:tiger@localhost:5432/mydatabase') 
        
# Initialize a pandalchemy DataBase object 
db = ba.DataBase(engine) 
        
# Accessing a table by name gives you a DataFrame like Table object 
tbl = db['test_table'] 
        
# Make changes to the Table just like you would a pandas DataFrame 
tbl['age'] = [11, 12, 13, 14, 15] 
        
# Use the push method to push all your changes to your database 
db.push()