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Atlas: Our journey from a Python monolith to a managed platform // By Naphat Sanguansin and Utsav Shah • Mar 04, 2021 Dropbox, to our customers, needs to be a reliable and responsive service. As a company, we’ve had to scale constantly since our start, today serving more than 700M registered users in every time zone on the planet who generate at least 300,000 requests per second. Systems that worked great for a startup hadn’t scaled well, so we needed to devise a new model for our internal systems, and a way to get there without disrupting the use of our product. In this post, we’ll explain why and how we developed and deployed Atlas, a platform which provides the majority of benefits of a Service Oriented Architecture, while minimizing the operational cost that typically comes with owning a service.
Pattern Matching This repo contains an issue tracker, examples, and early work related to PEP 622: Structural Pattern Matching. The current version of the proposal is PEP 634, which was accepted by the Steering Council on February 8, 2021. The motivation and rationale are written up in PEP 635, and a tutorial is in PEP 636. The tutorial below is also included in PEP 636 as Appendix A. Updates to the PEPs should be made in the PEPs repo. Origins Many statically compiled languages (especially functional ones) have a match expression, for example Scala, Rust, F#; Several extensive discussions on python-ideas, culminating in a summarizing blog post