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I'd love property-based testing in big data cluster computing applications done in Databricks/Spark. However, (Py)Spark is very high-latency, even in local mode

• chriswarbo 4y ago
  There are lots of dials that can be tweaked; e.g. timeouts, number of tests, etc. For example, I've used Hypothesis to test some browser-automation, which uses the ChromeController package to launch a Chrom(ium) browser to take screenshots and print-to-PDF. The tests do things like: - Generate random HTML - Write it to a temp file - Launch Chromium, set its window width+height, and navigate to that file:// address - Take a PNG screenshot - Use a PNG library to assert we've got a valid PNG, of the given width + height There are similar tests for print-to-PDF (checking that it's a valid PDF with at least one page), etc. The only fiddling I had to do was put `deadline=1000` in the `@settings` decorators. This prevents Hypothesis giving up on a test run too early; it automatically runs the tests fewer times, so it stays within a reasonable time frame. These sorts of tests are good for sanity-checking that we're plugging things together in the right way; but I wouldn't rely on them checking enough times to e.g. catch arithmetic edge-cases, etc.