GitHub recently upgraded to Ruby 2.7. Learn how the team approached the deprecation warnings, why upgrading is important, and the notable performance improvements. After many months of work, we deployed GitHub to production using Ruby 2.7 in July. For those who aren’t familiar with GitHub’s stack, we’ve been running on Ruby since the beginning. Many years ago, we ran GitHub on a fork of Ruby (and Rails!) and while that hasn’t been the case for some time, that experience taught us how important it is to keep up with new releases.
After many months of work, we deployed GitHub to production using Ruby 2.7 in July. For those who aren’t familiar with GitHub’s stack, we’ve been running on Ruby since the beginning. Many years ago, we ran GitHub on a fork of Ruby (and Rails!) and while that hasn’t been the case for some time, that experience taught us how important it is to keep up with new releases.
Ruby 2.7 is a unique upgrade because the Ruby Core team has deprecated how keyword arguments behave. With this release, future versions of Ruby will no longer accept passing an options hash when a method expects keyword arguments. At GitHub, we’re committed to running deprecation-free on both Ruby and Rails to prevent falling behind on future upgrades. It’s important to identify major changes early so we can evolve the application when necessary.
In order to run Ruby 2.7 deprecation-free, we had to fix over 11k warnings. Fixing that many warnings, some of which were coming from external libraries, takes a lot of coordination and teamwork. In order to be successful we needed a solid strategy for sharing the work.
Just like we did with our Rails upgrade, we set up our application to be dual-bootable in both Ruby 2.6 and Ruby 2.7 by using an environment variable. This made it easy for us to make backwards compatible changes, merge those to the main branch, and avoid maintaining a long running branch for our upgrade. It also made it easier for other engineering teams who needed to make changes to get their system running with the new Ruby version. Due to how large our application is (over 400k lines!) and how many changes go in daily (100’s of PRs!), this drastically simplifies our upgrade process.
Once we had the build running, we weren’t quite yet ready to ask other teams to help fix warnings. Since Ruby warnings are simply strings in the test output we needed to capture the deprecations and turn them into lists for each team to fix.
To accomplish this we monkey patched the
Warning module in Ruby. Here’s a simplified version of our monkey patch:
module Warning def self.warn(warning) root = ENV["RAILS_ROOT"].to_s + "/" warning = warning.gsub(root, "") line = caller_locations.find do |location| location.path.end_with?("_test.rb") end origin = line&.path&.gsub(root, "") WarningsCollector.instance << [warning.chomp, origin] STDERR.print(message) end end
In this tutorial, you’re going to learn a variety of Python tricks that you can use to write your Python code in a more readable and efficient way like a pro.
Today you're going to learn how to use Python programming in a way that can ultimately save a lot of space on your drive by removing all the duplicates. We gonna use Python OS remove( ) method to remove the duplicates on our drive. Well, that's simple you just call remove ( ) with a parameter of the name of the file you wanna remove done.
In the programming world, Data types play an important role. Each Variable is stored in different data types and responsible for various functions. Python had two different objects, and They are mutable and immutable objects.
Magic Methods are the special methods which gives us the ability to access built in syntactical features such as ‘<’, ‘>’, ‘==’, ‘+’ etc.. You must have worked with such methods without knowing them to be as magic methods. Magic methods can be identified with their names which start with __ and ends with __ like __init__, __call__, __str__ etc. These methods are also called Dunder Methods, because of their name starting and ending with Double Underscore (Dunder).
The OS module is a python module that provides the interface for interacting with the underlying operating system that Python is running.