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The Python Packaging Hell: The Expression of Needs (6 / 7)

Python packaging can sometimes be a nightmare. It’s all the more hellish because when we talk about package creation and installation, we should first start to define precisely what we mean.


This article is part of a series of tearful articles about Python packaging:

  1. The Can of Worms
  2. The Roots of Evil
  3. Delusions of Formats
  4. Files Everywhere
  5. The Toolbox
  6. The Expression of Needs
  7. The Minimal Solution

Before starting, we would like to send a lot of love to the members of the PyPA team. We complain a lot in this series, but we have a lot of respect for the sisyphean work already done.

That being said, let’s start (again) the whining 😭.


Daddy, Mommy: How Do We Make Packages?

It’s all well and good to talk about a package in up, but we often talk about it in down. Actually, we talk a lot about what’s in it, about what we can do with it, but not in detail about the different steps of its birth and its life.

The goal isn’t to present setuptools technically (you can thank us). The goal is rather to become aware that the notion of package groups together miscellaneous realities, and that we shouldn’t use the same tools and the same protocols depending on the reality we face.

You’ve always thought that creating a package was just putting files from a folder into an archive? Sorry to spoil the fun, but it’s definitely not. Not at all. Otherwise, we wouldn’t be there to write about this topic, and you wouldn’t be there to read this article.

Mandatory Related XKCD™
The mandatory XKCD. People making Python packages are all incompetent, give me 5 minutes and I can solve this issue once and for all.

The Scene of Operations

Here we are. You’ve finished your code, you want to share it, and for that you want to create a package. You’ve read countless tutorials that boasted countless foolproof techniques, countless wonderful tools, countless magical files.

We’re going to give you our opinion (you’re here for that, no?). The good question to ask yourself is: "which operations will have to be done to create and install my packages?". From that, you’ll be able to pick in your library the most suitable tutorial for your situation.

Jumping headlong into the creation of your package is taking a double risk: the risk of doing too much, and the risk of not being able to do enough. You can take our word for it: you want neither of that. Life is too short.

So, what happens in our packages?


Obviously, if you want to share a Python package, there is good chance that you have Python code to include in your package. And when we talk about code, we often talk about a module.

A Python module, in its simple expression, is a simple file, or a folder containing several files, and, eventually sub-folders composing as many sub-modules as you’ll need.

If we put aside the installation of executable scripts (we’ll talk about them later), this step is without surprise especially well managed by the different tools available. If you want to specify a folder to include (and automatically include the code inside), if you want specify manually the list of files and folders to include, even if you have several modules to include in your package, this step shouldn’t cause any particular issue.

If you really look for complication (that crossed your mind, there’s no need to lie), you’ll be tempted to include some files only for some platforms: a file for Windows, a file for normal operating systems. You’ll want to apply some code updates for a specific version of Python, or depending on the presence of some dependencies. Don’t be afraid, your sickly vice won’t be swept under the carpet: we’ll see that later, during creation and installation steps.


With you packages, maybe even without noticing, you want to lug a swarm of metadata. Hardly nothing, indeed. A package name, a version number, a contact email address. And supported versions of Python. And dependencies, required and optional. And a description, keywords, some classifiers, some standard links to the documentation and the source repository to put on PyPI. And some specific options to launch tests or build documentation. And…

OK. That’s not "nothing".

For our mental health, most of this metadata is standardized and can easily be integrated. As long as we want to integrate what is expected to integrate. Be reasonable. Be quiet.

Can you feel it coming?

You may be tempted to integrate metadata in files. Not configuration files, not code files. Files aside. A README, a CHANGELOG, things like that. A code of conduct, a list of contributors, a roadmap…

And that’s only for the source package. For the wheel, we don’t want these annex files. Obviously. It goes without saying.

Don’t worry, you can. However, here’s a small detail: by default, the configuration file that allows to do that is based on a pseudo-code including 8 different commands and a specific syntax of regular expressions. This file’s only goal is to define the list of files to include in the source package, and it’s got a name IN CAPITAL LETTERS, a dot, and an extension of two lowercase letters (we won’t say its name). It follows implicit rules that depend on the setuptools version, it’s automatically adapted to CVS and Subversion repositories (!), it necessarily creates files we can’t change.

Apart from this microscopic detail, that is very similar to a purulent wart from the Jurassic period, nothing to report.

Annex Files

You develop a spell checker and you want to integrate dictionaries. You develop a game and you want to integrate images. You develop a simulator of giant chicken fights and you want to generate cards from geospatial data of Mars. Of course, why not.

Image du rover Curiosity sur Mars
It’s not because Curiosity didn’t find giant chickens that they don’t exist.

The common point? You want to integrate files that aren’t Python code.

These files aren’t metadata. They are data to install with the code, directly used by code, and without them your module wouldn’t work. By the way, if you suffer from a serious lack of empathy towards the rest of the human race, you put these data inside the folder of your module, if possible in a dedicated sub-folder.

We have good news. Everything that’s quite classic is easily manageable. Everything that has to be managed manually can be handled with the needed tact (and patience).

Oh. Before moving on, we have a small thing to tell you… To access these files from your code, you’ll undoubtedly have the naivety to search them with their filenames, from the relative path of your code. Did you forget what we said about eggs that can be used without being decompressed? Did you forget Windows .exe files that can include all the data in one single file? Did you forget people who will come to explain to you that, on Mars, giant chickens use a format of quantum archives used, at the same time, compressed and decompressed?

We’re hardly exaggerating. In doubt, use importlib.resources. What? It’s new in Python 3.7? Well… Show some resilience! After endless weeks spent to read all the forums on Earth you should easily find a solution that works for all the required cases.

Executable files

This part is simple: don’t integrate executable files.

Well, yes. You’re grumbling because you don’t understand how, without executable files, we’ll be able to launch your program that draws a Nyan Cat on your wallpaper. And you’re right.

Nyan Cat
This flying cat will look great on your wallpaper. Think about it. Seriously.

But we’re right too. To get an executable file installed by your package, you don’t need to write it. Python offers a clever system of entry points to save you some work.

These entry points are functions that will be automatically transformed into executable files during the installation of your package. This solution offers a lot of pros, like being able to use your backnyan app by launching backnyan in your terminal (or by clicking on the icon of the installed app), but also as a module with python -m backnyan. And voilà, without noticing, you’ve got the possibility to use an other module with your app. By chance, with python -m pdb -m backnyan you can now discover the joys of debugging.

We wish you a lot of fun with pdb. It’s a gift. A gift package.

Operations During Creation

Until this precise moment, we see in your eyes the innocent glimmers of hope, those which animate human beings with a still immaculate reason to live, intoxicated by the tempting fragrance of unreachable success.

We suggest you stop there.

Too bad for you, if you continue, don’t complain.

We saw many times that is a classic Python file allowing to execute all sorts of fantasies. And by "fantasies", we don’t talk about unicorns, we talk about Cerberus or Minotaur. Enemies who bite and hurt.

In the operations that can manage, we’ll determine two distinct groups: the ones done before creating the package, and the ones done after. We’ll start with the first group.

During the package creation, we may have deviant desire to tinker files. We would like to create files on the fly and to include them into the package, or to retrieve some files online. We may want to do some adjustments to create an optimized package for a specific version of Python, or for a specific OS.

Oh, wait, here are some other good ideas. We could compile C code to integrate different versions in specific wheels. We could directly create executable files or specific archives. We could obfuscate proprietary code.

Instead of writing a module, we could write a meta-module that generates the code of the module on the fly.

You get the idea.

If you think that these examples are strange, even eccentric, take some time to think about them seriously. They’re only examples from real life, listed with no bad faith. True story. And Python allows to do that without too much trouble, as is a simple Python file.

It also shows that with no file, it will be very hard to do that. We can’t create a simple configuration file taking care of all the different possibilities offered by code.

We’re now beginning to understand why, in Python, having a single tool to create packages is an illusion. Between simplicity and complexity, between static formats and dynamic code, the solution depends on the context. That why we’ll have for long time a lot of tutorials, focused on a particular solution, without no silver bullet.

Operations During Installation

There we are, the final step.

Even if we can do a lot of complex things during the creation of a package (sometimes for honest reasons), we’re limited by the responsibility of the person creating the package. In a pinch, all these operations could be done outside the tool used to create packages, by an external script executed before using the classic software stack to generate the archive.

Put it this way, it’s almost easy.

The real complexity is to execute code during the installation. For that, we (almost) have to depend of what pip offers, and thus to fall again in the hazards of setuptools.

Even worse: as the code is executed on the computer where the package is installed, it must be adapted to its specificities: its OS, its file system, its Python version, its installed tools… So, inventiveness and dexterity are often required to get code adapted to its target.

But, to do what?

During the installation of source packages, we may want to do almost everything we wanted during the creation of a wheel. But this time, we can do it using everything that is available on the host machine: optimized compilation depending on the architecture, interfaces with specific installed libraries, adjustments to the Python version, to the OS, to some dependencies…

setuptools, to name just one library, offers a lot of tools to simplify these tasks, in particular the compilation part. Writing C code in the middle of its Python library, to optimize some functions, is a fairly common practice. And in this case, we can either generate wheels for all platforms (pure utopia), or we can leave pip handle that during the installation step.

Unfortunately, depending on the host means depending on its installed tools. You have to hope that your target includes a functioning compiler, adapted to what setuptools does. Otherwise, the work required to install your code may well discourage everyone.

Where Do We Go Now?

Now that we have an overview of what can be done with a Python package, we’re well on our way. But, where do we go now?

We’ve made good progress. If you’ve been attentive (and you’ve probably been), you should now be able to find a way. After determining more precisely what you should and what you must do with your code, you’ll be able to use the table of The toolbox article to choose precisely the most adapted weapons.

Obviously, you’ll have to read a lot of documentation, articles and other forums to get a better idea. If you’re a bit patient, you can also read an umpteenth partial tutorial, as it’s the subject of our last article.

Until then, happy readings!