Blog, page 1 | Chris Warrick

In Python, virtual environments are used to isolate projects from each other (if they require different versions of the same library, for example). They let you install and manage packages without administrative privileges, and without conflicting with the system package manager. They also allow to quickly create an environment somewhere else with the same dependencies.

Virtual environments are a crucial tool for any Python developer. And at that, a very simple tool to work with.

Pipenv is a Python packaging tool that does one thing reasonably well — application dependency management. However, it is also plagued by issues, limitations and a break-neck development process. In the past, Pipenv’s promotional material was highly misleading as to its purpose and backers.

In this post, I will explore the problems with Pipenv. Was it really recommended by Python.org? Can everyone — or at least, the vast majority of people — benefit from it?

(This post has been updated in February 2020 and May 2020 to reflect the current state of Pipenv.)

I used up 0.99 GB out of my 1 GB allowance. So, I had to buy some more. My (former) operator, Orange, sells a 1GB package for an ultra-low price (not really) of 15 PLN. (You can get the same package for less money, even half of that price, with other carriers.)

How to turn that on? You can send a text message or call a robot. I’ll give them a call then.

As part of your code, you may be inclined to call a command to do something. But is it always a good idea? How to do it safely? What happens behind the scenes?

Gynvael Coldwind is a security researcher at Google, who hosts weekly livestreams about security and programming in Polish and English). As part of the streams, he gives out missions — basically, CTF-style reverse engineering tasks. Yesterday’s mission was about Elvish — I mean Paint — I mean Python programming and bytecode.

Setting up Python is usually simple, but there are some places where newcomers (and experienced users) need to be careful. What versions are there? What’s the difference between Python, CPython, Anaconda, PyPy? Those and many other questions may stump new developers, or people wanting to use Python.

A short time ago, the macOS display menu stopped working for me. It no longer had options to change mirroring settings, only supporting AirPlay. So I wrote my own, also solving some other issues.

You might get unusual errors about Unicode and inability to convert to ASCII. Programs might just crash at random. Those are often simple to fix — all you need is correct locale configuration.

On Monday, Apple announced some changes to its Mac lineup. All MacBooks (even the Air) got CPU upgrades, and the starting price of a MacBook Pro (13″, no Touch Bar) went down to US$1299. Which makes the 12-inch model effectively pointless.

A quick spec comparison reveals that the Pro comes with a much better CPU, GPU, screen, camera — the only drawback is the storage space.

To create a project that other people can use and contribute to, you need to follow a specific directory structure. Moreover, releasing a new version should be as simple and painless as possible. For my projects, I use a template that has the structure already in place, and comes with automation for almost every part of a release.

Python Virtual Environments in Five Minutes

Pipenv: promises a lot, delivers very little

Mobile phone woes, or how my carrier didn’t want my money

Spawning subprocesses smartly and securely

Gynvael’s Mission 11 (en): Python bytecode reverse-engineering

Setting up a Python development environment

Apple broke the display menu, so I wrote my own

Unix locales vs Unicode (‘ascii’ codec can’t encode character…)

Apple’s new pricing strategy: don't buy the 12″ MacBook

Structuring and automating a Python project with the Python Project Template