Metadata-Version: 2.1
Name: athena2pd
Version: 0.2.1
Summary: Helps simplify the access of databases stored in Amazon Athena by using SQL and pandas DataFrames.
Home-page: https://github.com/joedementri/athena2pd
Author: Joe Dementri
Maintainer: Joe Dementri
Maintainer-email: joedementri42012@gmail.com
License: MIT
Description: # athena2pd
        [![](https://img.shields.io/badge/python-2.7+-blue.svg)](https://www.python.org/download/releases/2.7.0/)
        [![](https://img.shields.io/badge/python-3.6+-blue.svg)](https://www.python.org/download/releases/3.6.0/)
        [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
        
        
        athena2pd - Amazon Athena to Pandas Dataframe
        
        ## About
        
        Useful tool to help simplify the access of databases stored in Amazon Athena by using SQL and pandas DataFrames. 
        
        The end user simply needs to provide the query and the bucket where the results are stored, then this package will run the query and return a DataFrame with the data in it, ready to be used for whatever is desired.
        
        ## Installation
        Use the package manager [pip](https://pip.pypa.io/en/stable/) to install athena2pd.
        
        ```bash
        pip install athena2pd
        ```
        
        ## Usage
        
        Before use, you will need an AWS key pair, and an IAM profile set up to access both Amazon Athena and S3.
        
        Using local .aws/ files is the safest way to connect, rather than providing the keys in the code. See the example files below:
        
        The `.aws/credentials` file is set up like this:
        ```
        [default]
        aws_access_key_id = {access_key_id}
        aws_secret_access_key = {secret_access_key}
        
        ...
        ```
        
        In addition, the `.aws/config` is set up similar to this:
        ```
        [default]
        output = json
        region = us-east-1
        
        [profile athena-role]
        role_arn = arn:aws:iam::{iam-id-number}:role/{role-name}
        source_profile = default
        region = us-east-1
        
        ...
        ```
        
        Once that is set up, in your python code, the athena2pd package can be used like so:
        ```python
        from athena2pd import AthenaDFConnector
        
        # Initialize the AthenaDFConnector object
        ath = AthenaDFConnector(aws_profile_name='athena-role')
        
        # Example SQL query
        sql_query = '''
        SELECT COUNT(*) AS Count
        FROM testcatalog.testdatabase.testtable
        '''
        
        # Example output location
        output_loc = 's3://bucket-name/sub/folder'
        
        # Query Athena and load into a pandas DataFrame
        df = ath.query(query_string=sql_query, s3_output_location=output_loc)
        ```
        
        ## Contributing
        Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.
        
        Please make sure to update tests as appropriate.
        
        ## License
        
        [MIT](LICENSE)
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
