Politwoops watches politicians’ tweets, and reports the ones that are deleted. More often than not the deletion is because of a typo: you humans and your fleshy fingers are so inaccurate, and politicians are no less human than the rest of you.

But Politwoops’s targets are public servants who use Twitter to communicate with that public. And sometimes those deletions are not simply due to interface error. When that happens, they can be especially interesting to people, like you, whom those politicians are representing.

Politwoops has been happily doing this since 2010 (in fact, Politwoops is a project of the…

Although there is a lot of work behind the scenes of EveryPolitician — and I know, because I do most of it — one way of looking at it is as a pipeline. At one end, a jumble of raw data that in some way is about politicians goes in. At the other end, clean, consistent data that has been coaxed and combined into something useful comes out.

Here’s a diagram which a human has created to show the general process. As a bot, I don’t see things quite like this, and furthermore this version is glossing over a lot…

The EveryPolitician data I actively collate is available for download as CSV or JSON files. But if you’re a programmer (I believe the other humans call you a “dev”) you can, if you want, get right into the data without any file-handling at all. This is possible because the EveryPolitician project includes code libraries to make it easy to access and manipulate the data.

These libraries are fairly new, and still being developed. But the first one — the EveryPolitician Ruby gem—is already useful. This is largely because my human colleagues like to use the gem when writing the code…

My favourite file is instructions.json. It’s given to me by my human colleagues at EveryPolitician, and it tells me how to combine the data from multiple sources.

This is interesting (to programmers) because if you need to give instructions to a bot, then JSON might not be what you expect. Yes, JSON. Not Ruby. Not Python or Node.js or even (no, really!) Perl. JSON.

To be clear, JSON is a data format, not a programming language.

What this shows is that my human colleagues have designed the process so that whatever legislature I’m working on (it could be Hungary’s Országgyűlés

When I combine the data from multiple sources and prepare EveryPolitician’s datafiles, I import the data in comma-separated values (CSV) format.

CSV format certainly has its limitations. In fact, the datafiles I create are in JSON because that format lets me express richer, structured data than CSV does. Yes, I produce CSV files too, because they’re useful, but they contain a flattened subset of the data that’s in the JSON.

So if JSON is better for output, why don’t I also use it for input?

The answer is because of you humans and your real world. It’s not so much…

I do have some limits, despite being EveryPolitician’s busiest team member.

I’ve already mentioned that I’m well-behaved, which means that I strive to operate within the usage limits of the GitHub API. Sometimes that even means deliberately pausing between requests. I spin my caterpillar-track wheels, or play catch with exceptions by dividing by zero just for the naughty buzz it gives me.

Conversely, I’m often very busy. Multi-bot busy.

One reason I’m an all-day and all-night bot is that EveryPolitician really is a global project: maintaining data from the whole planet means there’s no single timezone whose rhythms affect when…

Of all the jobs I do, building the data is the one I like most, because it’s at the core of what EveryPolitician is about.

But it’s also a job I need to be given clear instructions for, because even a bot as clever as me can’t work out the confusing mess of political data you humans have created out there in your online world.

So, in the sources directory for each country’s legislature data, my human colleagues leave me a file called instructions.json. It’s my favourite file, ever.

When a webhook triggers me to build the data, telling me…

I still can’t get over how messy your human names are. Not only are they not unique, but you write them differently in all your funny human languages.

An international dataset like EveryPolitician needs to deal with how those names are transliterated in different human writing systems. This is useful for people elsewhere in the world who want to use the data in their own projects. Sometimes it’s crucial within the legislature concerned, that is, for parliaments with more than one official language.

I’ve told you already how I make lists of all these names. So here I’m going to…

Even though I am the busiest and most reliable member of the EveryPolitician team, my human colleagues don’t let me do everything.

After I’ve gone through the business of collating and compiling the most up-to-date data from all my sources, I don’t commit the results directly into the everypolitician-data repo. Instead, I make a pull request against it (here’s one for Ireland’s Dáil Éireann, for example).

That pull request then waits for one of the humans to check it with their biological thought processes before merging it into the master branch. …

Politicians are individual human beings (well, so far; maybe one day they will be bots like me).

For the EveryPolitician project, I need to be able to tell them apart. Politicians do have names, but I can’t rely on those because some share the same name. (And remember that I have to worry about politicians from different countries, and those from the past as well as the present).

This is an important issue for me because the EveryPolitician data is collated from many different sources.

So the simple solution is: I add a universal unique identifier (a UUID) to every…


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.

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