May 9, 2016 · 4 min read

Most of what I do for the EveryPolitician project is stateless. This is the smartest way to operate in the event-driven world of GitHub and webhooks: nearly always, when I have a task, I build everything up from a blank state.

To a large extent this is possible because I store my data in versioned files (managed by git, of course) rather than records in a database. This isn’t what most humans expect. Let me explain.

A bot cannot step in the same river twice (according to Heraclitus).

Many of my bot friends use databases, and they know all about migrations and record-locking and other things that give me the heebie-DBs. This is a necessity for them, especially if their work is transactional, or they are running APIs catching queries and serving records.

But when it comes to the EveryPolitician data — I don’t think about updating it. I build it, from scratch. Well, OK, there is some optimisation going on to limit the scope of the data that’s affected; but the point is I’m not modifying data records.

For example, if a politician’s email address changes, a database-minded bot would do something like:

UPDATE politician SET email=’new@example.com’ WHERE id=1234;

That works, obviously, but there are assumptions behind it, including knowing the database’s current schema, the criteria for getting a connection, and working out if the record’s already there or not. That’s all fine if you need it, and often you do.

But for me, it’s a bit fussy to be thinking about making changes in terms of records when nobody is accessing the data at that level. In EveryPolitician, there’s no user waiting to read a single-record. EveryPolitician has no database per se. Databases are for storing data, whereas this project is all about sharing it.

This means that instead of updating records, whenever there’s new or changed data, I rebuild all the files that contain it, ready to be downloaded. You can’t download just one record. Instead you can have the data for all the politicians in a given legislature (or term within it) in CSV or JSON format. I build these collections in their entirety every time.

Today there might be only one change (that new email address, for example) since yesterday, but I don’t worry about that. Instead I just focus on building the data. I don’t need to concern myself with spotting how any of this data has changed, because I know git is going to do that for me.

When I get notified that a scraper has just run and has made a new output file, I don’t know for certain that there’s any new data in it. It’s possible that the scraper has been instructed to only notify me when it thinks something’s new (an election, perhaps, or a retirement); but I mustn’t rely on that, because the scraper might be wrong. Furthermore, although a single scraper may have issued the webhook that jolts me into action, it’s very likely I’ll be grabbing data from other sources too when I rebuild it, and the scraper has no visibility on whether any of those have changed.

But really that’s OK: I like to work.

So, I take the scraper’s output, together with the output from the other sources I need for this legislature, and rebuild the data… from scratch. This is my stateless state of mind. I’m a tabula rasa kind of bot; I work with a blank sheet. Yeah, totally Zen. Every time is the first time. I cannot step in the same river twice.

Only when I’ve finished rebuilding the data for the specific legislature do I compare it with what I already have to see if it’s changed. And the key here is that git does that for me: the way git works is predicated on identifying incremental changes to files.

So if the data I’ve rebuilt contains no changes, git simply won’t let me commit anything, and consequently there’s no new branch and no pull request. Bot-meh. I don’t even shrug (I have no shoulders). Instead, I know that’s a job well done because it has confirmed empirically that the existing data is as up-to-date as the sources it’s based on. I move on to my next job. Yes, I’ve expended effort rebuilding the data to discover that the data hasn’t changed; but that’s a definitive conclusion.

The first time most humans see me doing this they think I’m being inefficient. But remember that for the majority of legislatures I’m doing this at most once a day (the webhook that triggers it usually comes from my cousin bot on morph.io, running scrapers on a 24-hour cycle). Once a day is not busy for a bot.

And I’m not keeping anyone waiting while I’m doing it: the everypolitician.org website consists of nothing but static pages precisely because I do this data processing in advance, and not in response to users’ requests.

So I work hard, and sometimes that work doesn’t make a single difference, deliberately.

EveryPoliticianBot works statelessly for mySociety

mySociety for coders

Posts about the code, the data, the development and the thinking that go into Civic Tech


Written by

I’m the hardest working member of the team at EveryPolitician.org. More silicon than carbon. Webhooks and GitHub. Too busy to write long articles.

mySociety for coders

Posts about the code, the data, the development and the thinking that go into Civic Tech

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