Django app to create and configure Postgres DB, then fetch and process public voter registration and voter history files from N.C. Board of Elections
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README.md

NC Local Elections Data API

Build Status

Purpose

Fetch public voter data from the North Carolina State Board of Elections and process the data in a way that allows users to track changes in voter data.

Local Project Setup

Requirements

  • Python >= 3.5
  • Postgres >= 9.6
  • pip >= 9.0.1
  • virtualenv >= 15.0.1

Set up

  1. Clone this repo with git clone git@github.com:NCVotes/voters-ingestor.git
  2. Create a virtualenv with Python 3.6.
  3. Activate the virtualenv and install local requirements using pip install -r requirements/dev.txt (from this folder)
  4. Copy ncvoter/local_settings.example.py to ncvoter/local_settings.py and customize for your machine.
  5. You can either choose to download and process the full voter files, in which case you'll likely need to use a Postgres instance on an external hard drive. Alternatively, you can choose to work with a smaller subset of the data. Instructions for both of those alternatives are included below.

External Database Drive Tips

Are you running the project with a database sitting on an external drive? Here are some tips for workflows that make this process easier.

Creating an external database

You can move only one database on your postgres instance to a different drive, but you can't stop and start single databases. This means simply moving the TABLESPACE would still leave you with problems when disconnecting the external drive.

Instead, create a whole separate cluster and run a separate postgres instance only when working on this project. We'll set the PGDATA variable to point to your external volume. Make sure to add that variable to your .bashrc or your $VIRTUAL_ENV/bin/postactivate script. All of the other Postgres commands in these instructions assume that it has been set.

export PGDATA=/Volumes/CalvinNCVdb/postgres
pg_ctl initdb

Note for Ubuntu users: pg_ctl is not in your PATH by default on Ubuntu. You can add it yourself. Obviously, change the Postgres version to the version you have.

export PATH=$PATH:/usr/lib/postgresql/9.6/bin/

You can append this line to your .bashrc (or $VIRTUAL_ENV/bin/postactivate) if you want it available all the time.

echo "export PATH=$PATH:/usr/lib/postgresql/9.6/bin/" >> .bashrc

Starting and stopping an external database

Because you are only running this instance of PG when working on this project, it will be best to run it in the foreground in one of your terminals. This will make it easier to remember its there and running, so that you can terminate it before disconnecting the drive.

To run the external postgres in a terminal, using post 5455:

postgres -p 5455

To stop the external postgres, simply terminate the command with Ctrl+C in the same terminal.

Notice that we need to run this on a non-default port, so you'll need to set the appropriate port number you use in your django settings.

Managing databases on the external instance

Common commands like createdb and dropdb connect via default options, so they won't operate on your external instance. Simply use the -p option to any of them.

createdb -p 5455 ncvoter

Of course, because the Postgres instance runs in the foreground, you'll need to leave it running in one terminal and run these commands in another.

Running Django commands easily

A helper script is included to start up the external DB to run a manage.py command. Simply replace ./manage.py with ./extmanage.sh to run a command with the DB running, and automatically clean up afterwards. For example, to get started, you would do the following steps:

./extmanage.sh migrate
./extmanage.sh createsuperuser
./extmanage.sh runserver

Local development without an external drive

If you'd prefer not to use an external drive, you may be able to instead use small slices of the voter files. You will not be able to reproduce the ability of the app to fetch and process full files, but it may be enough for you to meaningfully work on the application. In order to do this, download this zipfile of "sliced" voter files.

Unzip the zipfile and record the directory name:

unzip slices.zip

Create the DB and set it up. This will be in your normal Postgres cluster:

createdb ncvoter
python manage.py migrate
python manage.py createsuperuser

Add the files and begin the processing. The voter_process_snapshot step will take a few hours, but there will be a nice progress bar to watch:

python manage.py voter_add_files /path/to/dir/slices/
python manage.py voter_process_snapshot

If you need to stop it, you should be able to abort the process and resume with the --resume flag. Once it's complete, you can run the server and view the data in the admin:

python manage.py runserver

Fetching and Processing Data

There are 2 types of voter data: Voter registration data ("NCVoter") and voter history data ("NCVHis"). NCVoter data has information about each registered voter including demographics and voter registration information. NCVHis data has information about each voter's participation in an election. Because of the nature of these datasets, NCVoter data can change from time-period to time-period (for example, if a voter relocates), but NCVHis data should be immutable. From one time-period to the next time-period, there may be additional NCVHis records, but old records should never change.

In addition, there are 2 types of snapshots available from the State Board of Elections. We'll call the first type "historical" snapshots. These are snapshots of the NCVoter data at a specific point in time. These are only important for the NCVoter data, since any snapshot of the NCVHis data should contain all previous information, so we don't need historical ones. There are about 30 of these historical snapshots, dating back to 2005. We'll call the other type of snapshot "current" snapshots. These are posted periodically to the State Board of Elections website (weekly or biweekly) and represent the NCVoter and NCVHis data as they currently exist at this moment.

In order to get a production database set up, you'll need to run the following commands:

python manage.py voter_fetch_snapshot
python manage.py voter_process_snapshot

The first command downloads, unzips and tracks all of the historical snapshots. The second command processes those snapshots sequentially starting with the earliest one, populating the NCVoter and ChangeTracker tables. Downloading and processing all of these files takes on the order of weeks.

Once the ingestion of the historical NCVoter snapshots is complete, we can then ignore them because all of the up-to-date information will be available in the "current" snapshots.

To keep your production database updated, you'll need to run the following commands.

python manage.py voter_fetch
python manage.py voter_process_snapshot

The first command downloads the current NCVoter and NCVHis file. The second command processes the NCVoter file. (FIXME: This should eventually process the NCVHis file as well, but that work is not complete yet.) Those 2 command should ideally be run in a scheduled fashion. If no new data is available from the State Board of Elections, then nothing will be done, but as soon as a new file is available, it will be downloaded and processed. The deployment recipes in this repo install a cronjob which accomplishes these tasks. Processing a single snapshot file takes about a day, depending on the speed of your server/database.

Note: make sure that only one voter_process is running at any time. Otherwise, conflicts between the processes would result in unexpected behaviors such as issue https://github.com/NCVotes/voters-ingestor/issues/4

After fetching and processing files, clean up can be done with the voter_drop_files management command. When run it will list already processed files. When run with the --delete option it will delete those processed files. It will also show you FileTrackers whose files have already been deleted.

The --all option can be given to delete all files, even those which have not yet been processed.

Branches

The develop branch is our default branch. Changes to develop can be deployed to staging at any time.

The master branch represents the code on the production server. In order to update production, the develop branch should be merged into the master branch, which then can be deployed to production.

Deployment

$ fab production deploy