About¶

Parsons, named after Lucy Parsons, is a Python package that contains a growing list of connectors and integrations to move data between various tools. Parsons is focused on integrations and connectors for tools utilized by the progressive community.

Parsons was built out of a belief that progressive organizations spend far too much time building the same integrations, over and over and over again, while they should be engaged in more important and impactful work. It was built and is maintained by The Movement Cooperative.

The Movement Cooperative¶

The Movement Cooperative is a member led organization focused on providing data, tools and strategic support for the progressive community. Our mission is to break down technological barriers for organizations that fight for social justice.

License and Usage¶

Usage of Parsons is governed by a modified Apache License with author attribution statement.

Resources¶

Documentation: https://move-coop.github.io/parsons/html/index.html
Source Code: https://github.com/move-coop/parsons
Project Website: https://www.parsonsproject.org/
Docker Image: https://hub.docker.com/r/movementcooperative/parsons

Installation¶

You can install Parsons using pip install parsons. We recommend using a virtual environment.

Need more detail? We have a detailed, beginner-friendly guide to installing Parsons on our website.

We also have a Parsons Docker container hosted on DockerHub for each release of Parsons.

QuickStart¶

VAN - Download activist codes to a CSV¶

from parsons import VAN
van = VAN(db='MyVoters')
ac = van.get_activist_codes()
ac.to_csv('my_activist_codes.csv')

Redshift - Create a table from a CSV¶

from parsons import Table
tbl = Table.from_csv('my_table.csv')
tbl.to_redshift('my_schema.my_table')

Redshift - Export from a query to CSV¶

from parsons import Redshift
sql = 'select * from my_schema.my_table'
rs = Redshift()
tbl = rs.query(sql)
tbl.to_csv('my_table.csv')

S3 - Upload a file¶

from parsons import S3
s3 = S3()
s3.put_file('my_bucket','my_table.csv')

TargetSmart - Append data to a record¶

from parsons import TargetSmart
ts = TargetSmart(api_key='MY_KEY')
record = ts.data_enhance(231231231, state='DC')

Design Goals¶

The goal of Parsons is to make the movement of data between systems as easy and straightforward as possible. Simply put, we seek to reduce the lines of code that are written by the progressive community. Not only is this a waste of time, but we rarely have the capacity and resources to fully unittest our scripts.

Parsons seeks to be flexible from a data ingestion and output perspective, while providing ETL tools that recognize that our data is always messy. Central to this concept is the Parsons Table the table-like object that most methods return.

Logging¶

Parsons uses the native python logging system. By default, log output will go to the console and look like:

parsons.modulename LOGLEVEL the specific log message

In your scripts that use Parsons, if you want to override the default Parsons logging behavior, just grab the “parsons” logger and tweak it:

import logging
parsons_logger = logging.getLogger('parsons')
# parsons_logger.setLevel('DEBUG')
# parsons_logger.addHandler(...)
# parsons_logger.setFormatter(...)

Indices and tables¶

Enhancements

US Census Geocoder

Framework

Contributor Documentation

Use Cases and Sample Scripts

Training Guides