Last Updated: November 22nd 2019
The United States Prosecutor Database is a website housing the data of current & previous elected/appointed government attorneys at the local, state, & federal level. This includes (but is not limited to):
- Attorney Generals
- U.S. Attorneys
- District/State Attorneys
- Municipal/County/City Attorneys
Our goal is to showcase prosecutorial news articles, demographics, trends, office culture, & history. This goal is in service to the Post-Carceral mission, which is to:
- Cultivate a community of holding prosecutors accountable as a voting public
- Change the political and cultural landscape of this nation's real lawmakers
- Assist prosecutors who are aiming to end mass incarceration with a commitment to decarceration
Unfortunately, a complete & comprehensive dataset of prosecutors does not already exist.
You can help by: manually collecting data into a spreadsheet ("beginner"), manually collecting data & pushing it to the csv-json-data folder ("intermediate"), and/or updating the app ("advanced").
How to search, Google, and collect information into a simple document.
Instructions on how to pull down the repo, begin the manual data mining/entry process, then submit a pull request: Data Collection. It includes both manual .json/.csv collection as well as Python scraping.
Additionally, we now have a headshots folder for hosting prosecutor pictures. Feel free to submit a pull request if you've gathered this data in your own fork. After merging, I'll upload your images to mLab so the Heroku app can sync up.
To help build the app:
- cd to repo/app
npm installmeteor runmeteor mongo
Production: https://us-prosecutor-database.herokuapp.com/
If you think of a new method for collecting and retrieving prosecutor data, please create a new issue. Good luck!
git clone git@github.com:billimarie/prosecutor-database.git
cd [repo]/csv-json-data
git checkout -b [state]-[role]
npm install
npm install -g csvtojson
As previously noted, a dataset of all U.S. Prosecutors does not exist. Therefore, in order to create it, we work in a narrow scope: LOCATION (State) and ROLE (ex: District Attorney). You will see this emphasized repeatedly as State-Role. Your branch should only consist of data from one state, one role. It is okay to submit multiple pull requests, as long as you keep your work isolated in this manner.
There are one of two options you can choose for cultivating your dataset:
- Manually collecting prosecutor names by hand
- Creating a Python script to scrape the data
To manually collect prosecutor names by hand, complete the steps, below.
It is not recommended to go the data scraping route, as there is no uniform data to scrape from. This method is often not ideal as it will require more energy than simply collecting the data by hand. However, this is a good avenue to try if you come across some semblance of uniformity and/or want to see how scraping works. To scrape data, complete the steps below after running the Python script.
* Name
* Location (State, County)
* Role
* Website
* Office Info (Address)
* Contact Info (Phone, Fax, Email)
* Optional: headshot / profile image (url)
csvtojson [state-role].csv > [state-role].json
git add .
git commit -m "Added [state] [role] as .csv and .json"
git push origin [branch]
Again, it is highly recommended you collect the data by hand. If you are adamant on data scraping, here's the Python script I created a few years ago. You can use it as a base and adjust the logic according to each state's system. Please feel free to submit a pull request if you can enhance this script (or provide a newer, better, faster version).
#!/usr/bin/python3
from pyquery import PyQuery as pq
import requests as req
urls = [
'https://www.nypti.org/DA Htmls/stlawrence.html',
'https://www.nypti.org/DA Htmls/franklin.html',
'https://www.nypti.org/DA Htmls/clinton.html',
...
'https://www.nypti.org/DA Htmls/orleans.html',
'https://www.nypti.org/DA Htmls/niagara.html',
'https://www.nypti.org/DA Htmls/chautauqua.html'
]
for url in urls:
page = req.get(url)
doc = pq(page.text)
link = doc('a')
website = pq(link).attr('href')
da = doc('div').text()
print(da)
print(website)
Post-Carceral is a digital community group of volunteers working on civic tech projects (like the US Prosecutor Database) in service of working toward a post-carceral ("beyond prison") world.
- Sign up for our mailing list.
- You can also find USPD updates on our Twitter: @USProsecutorDB.
- To get involved in a remote Sunday session, follow @postcarceral. This is our general prisoners' rights group responsible for housing the USPD project.
You don't have to be a developer or a prisoners' rights activist to join. We're looking for all types of people with all types of interestes & expertise to collaborate with.
Datathons: On Sundays, we hang out remotely and discuss recent prosecutor news, primary results, & campaigns. We also brainstorm new ways to collect data (considering the strange logic of the prosecutorial system, especially as it differes between localities & regions). If you'd like to join, send me an email.
The USPD is an open-source community project built to house data about current and previous US Prosecutors (copyright (c) 2017 - 2019 Billimarie Lubiano Robinson). It is licensed under GNU GPLv3. This means you are able to use, modify, & distribute USPD as long as the following conditions are met:
- Acknowledge the original source (this repository & its contributors)
- Apply the same license & copyright usage
- Make public any changes, updates, or improvements upon USPD
For more information, please view the LICENSE.md file.