Python Package Structure for Scientific Python Projects

There are two different layouts that you will commonly see within the Python packaging ecosystem: src and flat layouts. Both layouts have advantages for different groups of maintainers.

We strongly suggest, but do not require, that you use the src/ layout (discussed below) for creating your Python package. This layout is also recommended in the PyPA packaging guide.

pyOpenSci will never require a specific package structure for peer review

We understand that it would be tremendous effort for existing maintainers to move to a new layout.

The overview on this page presents recommendations that we think are best for someone getting started with Python packaging or someone who’s package has a simple build and might be open to moving to a more fail-proof approach.

An example of the src/package layout structure can be seen below.

myPackageRepoName
├── CHANGELOG.md               ┐
├── CODE_OF_CONDUCT.md         │
├── CONTRIBUTING.md            │
├── docs                       │ Package documentation
│   └── index.md
│   └── ...                    │
├── LICENSE                    │
├── README.md                  ┘
├── pyproject.toml             ] Package metadata and build configuration
├── src                        ┐
│   └── myPackage              │
│       ├── __init__.py        │ Package source code
│       ├── moduleA.py         │
│       └── moduleB.py         ┘
└── tests                      ┐
   └── ...                     ┘ Package tests

Note the location of the following directories in the example above:

• docs/: discussed in our docs chapter, this directory contains your user-facing documentation website. In a src/ layout docs/ are normally included at the same directory level of the src/ folder.

• tests/ this directory contains the tests for your project code. In a src/ layout tests are normally included at the same directory level of the src/ folder.

• src/package/: this is the directory that contains the code for your Python project. “Package” is normally your project’s name.

Also in the above example, notice that all of the core documentation files that pyOpenSci requires live in the root of your project directory. These files include:

• CHANGELOG.md

• CODE_OF_CONDUCT.md

• CONTRIBUTING.md

• LICENSE.txt

• README.md

Click here to read about our packaging documentation requirements.

While we recommend the src/ layout we also review the flat layout here. Both are used in the Python ecosystem.

Example scientific packages that use src/package layout

• Sourmash

• bokeh

• openscm

• awkward

• poliastro

The src/ layout and testing

The benefit of using the src/package layout, particularly if you are creating a new package, is that it ensures tests are run against the installed version of your package rather than the files in your package working directory. If you run your tests on your files rather than the installed version, you may be missing issues that users encounter when your package is installed.

If tests/ are outside of the src/package directory, they aren’t included in the package wheel. This makes your package size slightly smaller which then places places a smaller storage burden on PyPI which has over 400,000 packages to support.

• Read more about reasons to use the src/package layout

How Python discovers and prioritizes importing modules

By default, Python adds a module in your current working directory to the front of the Python module search path.

This means that if you run your tests in your package’s working directory, using a flat layout, /package/module.py, Python will discover package/module.py file before it discovers the installed package.

However, if your package lives in a src/ directory structure src/package then it won’t be, by default, added to the Python path. This means that when you import your package, Python will be forced to search the active environment (which has your package installed).

Note: Python versions 3.11 and above have a path setting that can be adjusted to ensure the priority is to use installed packages first (e.g. PYTHONSAFEPATH).

Sometimes tests are needed in a distribution

We do not recommend including tests as part of your package wheel by default. However, not including tests in your package distribution will make it harder for people other than yourself to test whether your package is functioning correctly on their system. If you have a small test suite (Python files + data), and think your users may want to run tests locally on their systems, you can include tests by moving the tests/ directory into the src/package directory (see example below).

src/
  package/
    tests/
docs/

Including the tests/ directory in your src/package directory ensures that tests will be included in your package’s wheel.

Be sure to read the pytest documentation for more about including tests in your package distribution.

Challenges with including tests and data in a package wheel

Tests, especially when accompanied by test data can create a few small challenges including:

• Take up space in your distribution which will build up over time as storage space on PyPI

• Large file sizes can also slow down package install.

However, in some cases, particularly in the scientific Python ecosystems you may need to include tests.

Don’t include test suite datasets in your package

If you do include your tests in your package distribution, we strongly discourage you from including data in your test suite directory. Rather, host your test data in a repository such as Figshare or Zenodo. Use a tool such as Pooch to access the data when you (or a user) runs tests.

Check out the testing section of our guide for more information about tests.

• The src/package layout is semantically more clear. Code is always found in the src/package directory, tests/ and docs/are in the root directory.

Important

If your package tests require data, we suggest that you do NOT include that data within your package structure. We will discuss this in more detail in a tutorial. Include data in your package structure increases the size of your distribution files. This places a maintenance toll on repositories like PyPI and Anaconda.org that have to deal with thousands of package uploads.

About the flat Python package layout

Currently most scientific packages use the flat-layout given:

• It’s the most commonly found layout with the scientific Python ecosystem and people tend to look to other packages / maintainers that they respect for examples of how to build Python packages.

• Many Python tools depend upon tools in other language and / or complex builds with compilation steps. Many developers thus appreciate / are used to features of the flat layout.

While we present this layout here in our guide, we suggest that those just getting started with python packaging start with the src/package layout discussed above. Numerous packages in the ecosystem have had to move to a src/ layout

Why most scientific Python packages do not use source

In most cases the advantages of using the src/package layout for larger scientific packages that already use flat approach are not worth it. Moving from a flat layout to a src/package layout would come at a significant cost to maintainers.

However, the advantages of using the src/package layout for a beginner are significant. As such, we recommend that if you are getting started with creating a package, that you consider using a src/package layout.

What does the flat layout structure look like?

The flat layout’s primary characteristics are:

• The source code for your package lives in a directory with your package’s name in the root of your directory

• Often the tests/ directory also lives within that same package directory.

Below you can see the recommended structure of a scientific Python package using the flat layout.

myPackage/
├── CHANGELOG.md             ┐
├── CODE_OF_CONDUCT.md       │
├── CONTRIBUTING.md          │
├── docs/                    │ Package documentation
│   └── ...                  │
├── LICENSE                  │
├── README.md                ┘
├── pyproject.toml           ] Package metadata and build configuration
|   myPackage/               ┐
│     ├── __init__.py        │ Package source code
│     ├── moduleA.py         │
│     └── moduleB.py         ┘
      tests/                 ┐
        └── test-file1.py    | Package tests
        └── ....             ┘

Benefits of using the flat layout in your Python package

There are some benefits to the scientific community in using the flat layout.

• This structure has historically been used across the ecosystem and packages using it are unlikely to change.

• You can import the package directly from the root directory. For some this is engrained in their respective workflows. However, for a beginner the danger of doing this is that you are not developing and testing against the installed version of your package. Rather, you are working directly with the flat files.

Core scientific Python packages that use the flat layout

• numpy

• scipy

• pandas

• xarray

• Jupyter-core

• Jupyter notebook

• scikit-learn

It would be a significant maintenance cost and burden to move all of these packages to a different layout. The potential benefits of the source layout for these tools is not worth the maintenance investment.