python

Cloudflare workers for wikibase.cloud uptime & status

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Recently I wanted to create a live status page for wikibase.cloud, that also tracking the status of the various services and response times, so that people in the Telegram group might be able to try and correlate their experiences (possibly slow behaviour) with what was seen by others in other locations on other sites, without needing to message in the Telegram group.

In a way, this could be seen as an iteration on the current status page for the service, which is maintained as a static site on Github, making use of cState, a static status page.

Screenshot of the current status page

I initially chose to experiment with Cloudflare Workers to do the minutely checks, after looking around at the current offerings for free online code running (thinking Heroku style etc).

Why Workers?

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COVID-19 Wikipedia pageview spikes, 2019-2022

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Back in 2019 at the start of the COVID-19 outbreak, Wikipedia saw large spikes in page views on COVID-19 related topics while people here hunting for information.

I briefly looked at some of the spikes in March 2020 using the easy-to-use pageview tool for Wikimedia sites. But the problem with viewing the spikes through this tool is that you can only look at 10 pages at a time on a single site, when in reality you’d want to look at many pages relating to a topic, across multiple sites at once.

I wrote a notebook to do just this, submitted it for privacy review, and I am finally getting around to putting some of those moving parts and visualizations in public view.

Methodology

It certainly isn’t perfect, but the representation of spikes is much more accurate than looking at a single Wikipedia or set of hand selected pages.

  1. Find statements on Wikidata that relate to COVID-19 items
  2. Find Wikipedia site links for these items
  3. Find previous names of these pages if they have been moved
  4. Lookup pageviews for all titles in the pageview_hourly dataset
  5. Compile into a gigantic table and make some graphs using plotly

I’ll come onto the details later, but first for the…

Graphics

All graphics generally show an initial peak in the run-up to the WHO declaring an international public health emergency (12 Feb 2020), and another peak starting prior to the WHO declaring a pandemic.

Be sure to have a look at the interactive views of each diagram to really see the details.

COVID-19 related Wikimedia pageviews (interactive view)

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Creating properties with statements using Wikidata Integrator

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Wikidata Integrator is a Python library that simplifies data integration from Wikidata (and other Wikibases). It is written in Python, is focused on Wikibase concepts (as opposed to some libraries which are MediaWiki focused) and has a user-friendly interface.

I’m currently working on a demo Wikibase and decided to bring all of the data into the Wikibase making use of a Jupyter notebook, and Wikidata integrator was my choice library to use for this task. (Jupyter notebooks are interactive coding environments that allow users to create and share documents containing live code, visualizations, and explanations.)

Along that journey I found the Wikidata Integrator documentation lacking slightly, but I managed to get initial property and item creation working with little effort. However, I couldn’t get properties to create with statements already on them (needed a subsequent edit instead).

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Python3, Using some shared state in 2 async methods

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Python logoThe asyncio module was added to Python in version 3.4 to “provides infrastructure for writing single-threaded concurrent code using coroutines, multiplexing I/O access over sockets and other resources, running network clients and servers, and other related primitives”. If you want an introduction to asyncio take a look at this blog post.

This post will look at how to share state between multiple async methods that may be running at the same time without using anything silly like globals. The examples should be easy to follow and easy to extrapolate from. Also I’ll be embedding trinket.io  code snippets which you should be able to run in the browser.

Disclaimer: I don’t really write much python so there might be better solutions. This post is only meant to serve as a consolidation of knowledge to be passed to another.

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