Metadata-Version: 2.1
Name: pandalchemy
Version: 0.1.12
Summary: A package that integrates pandas and sqlalchemy.
Home-page: https://github.com/eddiethedean/pandalchemy
Author: Odos Matthews
Author-email: odosmatthews@gmail.com
License: MIT
Description: 
        # 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
        
        ```sh
        # PyPI
        pip install pandalchemy
        ```
        
        ## Dependencies
        - [pandas](https://pandas.pydata.org/)
        - [sqlalchemy==1.3.18](https://pypi.org/project/SQLAlchemy/1.3.18/)
        - [sqlalchemy-migrate](https://sqlalchemy-migrate.readthedocs.io/en/latest/)
        - [numpy](https://numpy.org/)
                
        # Example code
        ```sh
        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() 
        ```
        
        
        
        
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
