Friday, 10th January 2020
Serving 100µs reads with 100% availability (via) Fascinating use-case for SQLite from Segment: they needed a massively replicated configuration database across all of their instances that process streaming data. They chose to make the configuration available as a ~50GB SQLite database file mirrored to every instance, meaning lookups against that data could complete in microseconds. Changes to the central MySQL configuration store are pulled every 2-3 seconds, resulting in a trade-off of consistency for availability which fits their use-case just fine. # 5:15 am
A visual introduction to machine learning. Beautiful interactive essay explaining how a decision tree machine learning module is constructed, and using that to illustrate the concept of overfitting. This is one of the best explanations of machine learning fundamentals I’ve seen anywhere. # 5:12 am
Snowpack (via) Really interesting new twist on build systems for JavaScript. Modern browsers (everything since IE11) support JavaScript modules, but actually working with them is tricky since so much of the JavaScript ecosystem expects you to be using a bundler like Webpack. Snowpack is a tool for converting npm dependencies into JavaScript modules which can then be loaded directly by the browser, taking advantage of HTTP/2 to efficiently load the resulting larger number of files. # 5:06 am
Portable Cloud Functions with the Python Functions Framework (via) The new functions-framework library on PyPI lets you run Google Cloud Functions written in Python in other environments—on your local developer machine or bundled in a Docker container for example. I have real trouble trusting serverless platforms that lock you into a single provider (AWS Lambda makes me very uncomfortable) so this is a breath of fresh air. # 4:58 am
Async Support—HTTPX (via) HTTPX is the new async-friendly HTTP library for Python spearheaded by Tom Christie. It works in both async and non-async mode with an API very similar to requests. The async support is particularly interesting—it’s a really clean API, and now that Jupyter supports top-level await you can run ’(await httpx.AsyncClient().get(url)).text’ directly in a cell and get back the response. Most excitingly the library lets you pass an ASGI app directly to the client and then perform requests against it—ideal for unit tests. # 4:49 am