clipscreen is a simple application that creates a virtual monitor that mirrors a portion of your screen. A green rectangle highlights the specified area.

Why's this useful? You can use any screen sharing tool (Google Meet, Microsoft Teams, Jitsi Meet, etc.) to share the virtual monitor instead of your entire screen. No need to share individual windows and having to switch between them, just move any window you wannt to share into the green border.

Pytype checks and infers types for your Python code - without requiring type annotations. Pytype can:

• Lint plain Python code, flagging common mistakes such as misspelled attribute names, incorrect function calls, and much more, even across file boundaries.
• Enforce user-provided type annotations. While annotations are optional for pytype, it will check and apply them where present.
• Generate type annotations in standalone files ("pyi files"), which can be merged back into the Python source with a provided merge-pyi tool.

Pytype is a static analyzer; it does not execute the code it runs on.

Thousands of projects at Google rely on pytype to keep their Python code well-typed and error-free.

For more information, check out the user guide, FAQ, or supported features.

UnifiedPush is a specification and set of tools to let the user choose how push notifications are delivered. All in a free and open source way.

End users should look at setting up a distributor. Developers wanting to integrate UnifiedPush in their apps should look at the definitions and the documentation for your platform.

This is where you have to bring in the unpopular opinion, and let people comment on it. One unpopular opinion that people disagree with me a bit is – there’s two. Don’t run stateful things on Kubernetes. That’s a very unpopular thing, because people wanna Kubernetes all the things, and I’m just saying “But why?”

And then the second one is “Monoliths are the future.” Because the problem people are trying to solve with microservices doesn’t really line up with reality.

kaniko is a tool to build container images from a Dockerfile, inside a container or Kubernetes cluster.

kaniko doesn't depend on a Docker daemon and executes each command within a Dockerfile completely in userspace. This enables building container images in environments that can't easily or securely run a Docker daemon, such as a standard Kubernetes cluster.

Over the last few years I’ve written over forty blog posts that discuss ETW/xperf profiling. I’ve done this because it’s one of the best profilers I’ve ever used, and it’s been woefully undersold and under documented by Microsoft. My goal has been to let people know about this tool, make it easier for developers and users to record ETW traces, and to make it as easy as possible for developers to analyze ETW traces.

gVisor is a user-space kernel, written in Go, that implements a substantial portion of the Linux system surface. It includes an Open Container Initiative (OCI) runtime called runsc that provides an isolation boundary between the application and the host kernel. The runsc runtime integrates with Docker and Kubernetes, making it simple to run sandboxed containers.

gVisor takes a distinct approach to container sandboxing and makes a different set of technical trade-offs compared to existing sandbox technologies, thus providing new tools and ideas for the container security landscape.

Python Fire is a library for automatically generating command line interfaces (CLIs) from absolutely any Python object.

• Python Fire is a simple way to create a CLI in Python. [1]
• Python Fire is a helpful tool for developing and debugging Python code. [2]
• Python Fire helps with exploring existing code or turning other people's code into a CLI. [3]
• Python Fire makes transitioning between Bash and Python easier. [4]
• Python Fire makes using a Python REPL easier by setting up the REPL with the modules and variables you'll need already imported and created. [5]

Three weeks ago I blogged about how to get rid of non-free Google services and moving to free software on my Android phone. I’ve got a lot of feedback via email, lwn, and Google+, many thanks to all of you for helpful hints! As this is obviously important to many people, I want to tie up some lose ends and publish the results of these discussions.

This guide describes how to use the protocol buffer language to structure your protocol buffer data, including .proto file syntax and how to generate data access classes from your .proto files. It covers the proto2 version of the protocol buffers language: for information on the newer proto3 syntax, see the Proto3 Language Guide.

This is a reference guide – for a step by step example that uses many of the features described in this document, see the tutorial for your chosen language.

This tutorial provides a basic Python programmer’s introduction to working with gRPC.

By walking through this example you’ll learn how to:

Define a service in a .proto file.
Generate server and client code using the protocol buffer compiler.
Use the Python gRPC API to write a simple client and server for your service.

It assumes that you have read the Overview and are familiar with protocol buffers. Note that the example in this tutorial uses the proto3 version of the protocol buffers language, which is currently in beta release: you can find out more in the proto3 language guide and Python generated code guide, and see the release notes for the new version in the protocol buffers Github repository.

A cross-platform C library to retrieve CPU features (such as available instructions) at runtime

A single distribution of libraries that automatically collects traces and metrics from your app, displays them locally, and sends them to any analysis tool.

The key features of OpenCensus include:

• Standard wire protocols and consistent APIs for handling trace and metric data.
• A single set of libraries for many languages, including Java, C++, Go, .Net, Python, PHP, Node.js, Erlang, and Ruby.
• Included integrations with web and RPC frameworks, making traces and metrics available out of the box.
• Included exporters for storage and analysis tools. Right now the list includes Zipkin, Prometheus, Datadog, Stackdriver, and Azure App Insights.
• Full open source availability for additional integrations and export options.
• No additional server or daemon is required to support OpenCensus.
• In process debugging: an optional agent for displaying request and metrics data on instrumented hosts.

This guide describes how to use the protocol buffer language to structure your protocol buffer data, including .proto file syntax and how to generate data access classes from your .proto files. It covers the proto3 version of the protocol buffers language: for information on the older proto2 syntax, see the Proto2 Language Guide.

This is a reference guide – for a step by step example that uses many of the features described in this document, see the tutorial for your chosen language (currently proto2 only; more proto3 documentation is coming soon).

Most of the current formatters for Python --- e.g., autopep8, and pep8ify --- are made to remove lint errors from code. This has some obvious limitations. For instance, code that conforms to the PEP 8 guidelines may not be reformatted. But it doesn't mean that the code looks good.

YAPF takes a different approach. It's based off of 'clang-format', developed by Daniel Jasper. In essence, the algorithm takes the code and reformats it to the best formatting that conforms to the style guide, even if the original code didn't violate the style guide. The idea is also similar to the 'gofmt' tool for the Go programming language: end all holy wars about formatting - if the whole codebase of a project is simply piped through YAPF whenever modifications are made, the style remains consistent throughout the project and there's no point arguing about style in every code review.

The ultimate goal is that the code YAPF produces is as good as the code that a programmer would write if they were following the style guide. It takes away some of the drudgery of maintaining your code.

Python is the main scripting language used at Google. This style guide is a list of dos and don'ts for Python programs.

To help you format code correctly, we've created a settings file for Vim[1]. For Emacs, the default settings should be fine.

[1] https://google.github.io/styleguide/google_python_style.vim

The Open GApps Project is an open-source effort to script the automatic generation of up-to-date Google Apps packages.
On OpenGApps.org you can find more information about the project effort and also pre-built Google Apps packages generated by the OpenGApps.org buildbot.