All articles on Programming

Python is booming and Flask is a pretty popular web-framework nowadays. Probably, quite some new projects are being started in Flask. But people should be aware, it's synchronous by design and ASGI is not a thing yet. So, if someday you realize that your project really needs asynchronous I/O but you already have a considerable codebase on top of Flask, this tutorial is for you. The charming gevent library will enable you to keep using Flask while start benefiting from all the I/O being asynchronous. In the tutorial we will see:

• How to monkey patch a Flask app to make it asynchronous w/o changing its code.
• How to run the patched application using gevent.pywsgi application server.
• How to run the patched application using Gunicorn application server.
• How to run the patched application using uWSGI application server.
• How to configure Nginx proxy in front of the application server.
• [Bonus] How to use psycopg2 with psycogreen to make PostgreSQL access non-blocking.

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Regardless of whether it's the end of the calendar decade or not it's the end of a programming decade for me. I started early in 2010 and since then I've been programming almost every day, including weekends and vacations. This was a really exciting period in my life and I realized that it's been a while since 2010 only recently. So, I decided to put into words some of my learnings from that time. Warning: the content of this article is highly opinionated and extremely subjective.

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When I'm diving into a new codebase, I always start from the project structure analysis. And my favorite tool is tree. However, not every project is perfectly balanced. Some files and folders tend to be more popular and contain much more code than others. Seems like yet another incarnation of the Pareto principle.

So, when the tree's capabilities aren't enough, I jump to cloc. This tool is much more powerful and can show nice textual statistics for the number of code lines and programming languages used per the whole project or per each file individually.

However, some projects are really huge and some lovely visualization would be truly helpful! And here the FlameGraph goes! What if we feed the cloc's output for the Kubernetes codebase to FlameGraph? Thanks to the author of this article for the original cloc-to-flamegraph one-liner:

git clone https://github.com/brendangregg/FlameGraph
go get -d github.com/kubernetes/kubernetes

cd $(go env GOPATH)/src/github.com/kubernetes/kubernetes

cloc --csv-delimiter="$(printf '\t')" --by-file --quiet --csv . | \
    sed '1,2d' | \
    cut -f 2,5 | \
    sed 's/\//;/g' | \
    ~/FlameGraph/flamegraph.pl \
        --width=3600 \
        --height=32 \
        --fontsize=8 \
        --countname=lines \
        --nametype=package \
    > kubernetes.html

open kubernetes.html

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A looooong one this time, so straight to the point! First, we'll discuss the Linux processes trivia and then review the following scenarios, as usually, with some code examples:

• awaiting a child process termination;
• awaiting a grandchild process termination;
• catching the parent process termination.

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Have you ever been wondering how docker (or kubectl) attach command is implemented under the hood? If so, you're in the right place! This article covers the basics of Linux pseudoterminal capabilities and continuously shows how attach-like feature can be implemented in a ridiculously small amount of code.

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