Python import: Advanced Techniques and Tips

Modules

The Python.org glossary defines module as follows:

An object that serves as an organizational unit of Python code. Modules have a namespace containing arbitrary Python objects. Modules are loaded into Python by the process of importing. (Source)

In practice, a module usually corresponds to one .py file containing Python code.

The true power of modules is that they can be imported and reused in other code. Consider the following example:

>>> import math
>>> math.pi
3.141592653589793

In the first line, import math, you import the code in the math module and make it available to use. In the second line, you access the pi variable within the math module. math is part of Python’s standard library, which means that it’s always available to import when you’re running Python.

Note that you write math.pi and not just simply pi. In addition to being a module, math acts as a namespace that keeps all the attributes of the module together. Namespaces are useful for keeping your code readable and organized. In the words of Tim Peters:

Namespaces are one honking great idea—let’s do more of those! (Source)

You can list the contents of a namespace with dir():

>>> import math
>>> dir()
['__annotations__', '__builtins__', ..., 'math']

>>> dir(math)
['__doc__', ..., 'nan', 'pi', 'pow', ...]

Using dir() without any argument shows what’s in the global namespace. To see the contents of the math namespace, you use dir(math).

You’ve already seen the most straightforward use of import. However, there are other ways to use it that allow you to import specific parts of a module and to rename the module as you import it.

The following code imports only the pi variable from the math module:

>>> from math import pi
>>> pi
3.141592653589793

>>> math.pi
NameError: name 'math' is not defined

Note that this places pi in the global namespace and not within a math namespace.

You can also rename modules and attributes as they’re imported:

>>> import math as m
>>> m.pi
3.141592653589793

>>> from math import pi as PI
>>> PI
3.141592653589793

For more details about the syntax for importing modules, check out Python Modules and Packages – An Introduction.

Packages

You can use a package to further organize your modules. The Python.org glossary defines package as follows:

A Python module which can contain submodules or recursively, subpackages. Technically, a package is a Python module with an __path__ attribute. (Source)

Note that a package is still a module. As a user, you usually don’t need to worry about whether you’re importing a module or a package.

In practice, a package typically corresponds to a file directory containing Python files and other directories. To create a Python package yourself, you create a directory and a file named __init__.py inside it. The __init__.py file contains the contents of the package when it’s treated as a module. It can be left empty.

In general, submodules and subpackages aren’t imported when you import a package. However, you can use __init__.py to include any or all submodules and subpackages if you want. To show a few examples of this behavior, you’ll create a package for saying Hello world in a few different languages. The package will consist of the following directories and files:

world/
│
├── africa/
│   ├── __init__.py
│   └── zimbabwe.py
│
├── europe/
│   ├── __init__.py
│   ├── greece.py
│   ├── norway.py
│   └── spain.py
│
└── __init__.py

Each country file prints out a greeting, while the __init__.py files selectively import some of the subpackages and submodules. The exact contents of the files are as follows:

# world/africa/__init__.py  (Empty file)

# world/africa/zimbabwe.py
print("Shona: Mhoroyi vhanu vese")
print("Ndebele: Sabona mhlaba")

# world/europe/__init__.py
from . import greece
from . import norway

# world/europe/greece.py
print("Greek: Γειά σας Κόσμε")

# world/europe/norway.py
print("Norwegian: Hei verden")

# world/europe/spain.py
print("Castellano: Hola mundo")

# world/__init__.py
from . import africa

Note that world/__init__.py imports only africa and not europe. Similarly, world/africa/__init__.py doesn’t import anything, while world/europe/__init__.py imports greece and norway but not spain. Each country module will print a greeting when it’s imported.

Let’s play with the world package at the interactive prompt to get a better understanding of how the subpackages and submodules behave:

>>> import world
>>> world
<module 'world' from 'world/__init__.py'>

>>> # The africa subpackage has been automatically imported
>>> world.africa
<module 'world.africa' from 'world/africa/__init__.py'>

>>> # The europe subpackage has not been imported
>>> world.europe
AttributeError: module 'world' has no attribute 'europe'

When europe is imported, the europe.greece and europe.norway modules are imported as well. You can see this because the country modules print a greeting when they’re imported:

>>> # Import europe explicitly
>>> from world import europe
Greek: Γειά σας Κόσμε
Norwegian: Hei verden

>>> # The greece submodule has been automatically imported
>>> europe.greece
<module 'world.europe.greece' from 'world/europe/greece.py'>

>>> # Because world is imported, europe is also found in the world namespace
>>> world.europe.norway
<module 'world.europe.norway' from 'world/europe/norway.py'>

>>> # The spain submodule has not been imported
>>> europe.spain
AttributeError: module 'world.europe' has no attribute 'spain'

>>> # Import spain explicitly inside the world namespace
>>> import world.europe.spain
Castellano: Hola mundo

>>> # Note that spain is also available directly inside the europe namespace
>>> europe.spain
<module 'world.europe.spain' from 'world/europe/spain.py'>

>>> # Importing norway doesn't do the import again (no output), but adds
>>> # norway to the global namespace
>>> from world.europe import norway
>>> norway
<module 'world.europe.norway' from 'world/europe/norway.py'>

The world/africa/__init__.py file is empty. This means that importing the world.africa package creates the namespace but has no other effect:

>>> # Even though africa has been imported, zimbabwe has not
>>> world.africa.zimbabwe
AttributeError: module 'world.africa' has no attribute 'zimbabwe'

>>> # Import zimbabwe explicitly into the global namespace
>>> from world.africa import zimbabwe
Shona: Mhoroyi vhanu vese
Ndebele: Sabona mhlaba

>>> # The zimbabwe submodule is now available
>>> zimbabwe
<module 'world.africa.zimbabwe' from 'world/africa/zimbabwe.py'>

>>> # Note that zimbabwe can also be reached through the africa subpackage
>>> world.africa.zimbabwe
<module 'world.africa.zimbabwe' from 'world/africa/zimbabwe.py'>

Remember, importing a module both loads the contents and creates a namespace containing the contents. The last few examples show that it’s possible for the same module to be part of different namespaces.

>>> import math
>>> math.__dict__["pi"]
3.141592653589793

It’s fairly common to import subpackages and submodules in an __init__.py file to make them more readily available to your users. You can see one example of this in the popular requests package.

Absolute and Relative Imports

Recall the source code of world/__init__.py in the earlier example:

from . import africa

You’ve already seen from...import statements such as from math import pi, but what does the dot (.) in from . import africa mean?

The dot refers to the current package, and the statement is an example of a relative import. You can read it as “From the current package, import the subpackage africa.”

There’s an equivalent absolute import statement in which you explicitly name the current package:

from world import africa

In fact, all imports in world could have been done explicitly with similar absolute imports.

Relative imports must be in the form from...import, and the location you’re importing from must start with a dot.

The PEP 8 style guide recommends using absolute imports in general. However, relative imports are an alternative for organizing package hierarchies. For more information, see Absolute vs Relative Imports in Python.

Python’s Import Path

How does Python find the modules and packages it imports? You’ll see more details about the mechanics of the Python import system later. For now, just know that Python looks for modules and packages in its import path. This is a list of locations that are searched for modules to import.

You can inspect Python’s import path by printing sys.path. Broadly speaking, this list will contain three different kinds of locations:

1. The directory of the current script (or the current directory if there’s no script, such as when Python is running interactively)
2. The contents of the PYTHONPATH environment variable
3. Other, installation-dependent directories

Typically, Python will start at the beginning of the list of locations and look for a given module in each location until the first match. Since the script directory or the current directory is always first in this list, you can make sure that your scripts find your self-made modules and packages by organizing your directories and being careful about which directory you run Python from.

However, you should also be careful that you don’t create modules that shadow, or hide, other important modules. As an example, say that you define the following math module:

# math.py

def double(number):
    return 2 * number

Using this module works as expected:

>>> import math
>>> math.double(3.14)
6.28

But this module also shadows the math module that’s included in the standard library. Unfortunately, that means our earlier example of looking up the value of π no longer works:

>>> import math
>>> math.pi
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
AttributeError: module 'math' has no attribute 'pi'

>>> math
<module 'math' from 'math.py'>

The problem is that Python now searches your new math module for pi instead of searching the math module in the standard library.

To avoid these kinds of issues, you should be careful with the names of your modules and packages. In particular, your top-level module and package names should be unique. If math is defined as a submodule within a package, then it won’t shadow the built-in module.

Example: Structure Your Imports

While it’s possible to organize your imports by using the current directory as well as by manipulating PYTHONPATH and even sys.path, the process is often unruly and prone to errors. To see a typical example, consider the following application:

structure/
│
├── files.py
└── structure.py

The app will re-create a given file structure by creating directories and empty files. The structure.py file contains the main script, and files.py is a library module with a few functions for dealing with files. The following is an example of output from the app, in this case by running it in the structure directory:

$ python structure.py .
Create file: /home/gahjelle/structure/001/structure.py
Create file: /home/gahjelle/structure/001/files.py
Create file: /home/gahjelle/structure/001/__pycache__/files.cpython-38.pyc

The two source code files as well as the automatically created .pyc file are re-created inside a new directory named 001.

Now take a look at the source code. The main functionality of the app is defined in structure.py:

 1# structure/structure.py
 2
 3# Standard library imports
 4import pathlib
 5import sys
 6
 7# Local imports
 8import files
 9
10def main():
11    # Read path from command line
12    try:
13        root = pathlib.Path(sys.argv[1]).resolve()
14    except IndexError:
15        print("Need one argument: the root of the original file tree")
16        raise SystemExit()
17
18    # Re-create the file structure
19    new_root = files.unique_path(pathlib.Path.cwd(), "{:03d}")
20    for path in root.rglob("*"):
21        if path.is_file() and new_root not in path.parents:
22            rel_path = path.relative_to(root)
23            files.add_empty_file(new_root / rel_path)
24
25if __name__ == "__main__":
26    main()

In lines 12 to 16, you read a root path from the command line. In the above example you use a dot, which means the current directory. This path will be used as the root of the file hierarchy that you’ll re-create.

The actual work happens in lines 19 to 23. First, you create a unique path, new_root, that will be the root of your new file hierarchy. Then you loop through all paths below the original root and re-create them as empty files inside the new file hierarchy.

For manipulating paths like this, pathlib in the standard library is quite useful. For more details on how it’s used, check out Python 3’s pathlib Module: Taming the File System.

On line 26, you call main(). You’ll learn more about the if test on line 25 later. For now, you should know that the special variable __name__ has the value __main__ inside scripts, but it gets the name of the module inside imported modules. For more information on __name__, check out Defining Main Functions in Python and What Does if name == “main” Do in Python?.

Note that you import files on line 8. This library module contains two utility functions:

# structure/files.py

def unique_path(directory, name_pattern):
    """Find a path name that does not already exist"""
    counter = 0
    while True:
        counter += 1
        path = directory / name_pattern.format(counter)
        if not path.exists():
            return path

def add_empty_file(path):
    """Create an empty file at the given path"""
    print(f"Create file: {path}")
    path.parent.mkdir(parents=True, exist_ok=True)
    path.touch()

unique_path() uses a counter to find a path that doesn’t already exist. In the app, you use it to find a unique subdirectory to use as the new_root of the re-created file hierarchy. Next, add_empty_file() makes sure all necessary directories are created before creating an empty file using .touch().

Have a look at the import of files again:

 7# Local imports
 8import files

It looks quite innocent. However, as the project grows, this line will cause you some headaches. Even though you import files from the structure project, the import is absolute: it doesn’t start with a dot. This means that files must be found in the import path for the import to work.

Luckily, the directory containing the current script is always in Python’s import path, so this works fine for now. However, if your project gains some traction, then it may be used in other ways.

For example, someone might want to import the script into a Jupyter Notebook and run it from there. Or they may want to reuse the files library in another project. They may even create an executable with PyInstaller to more easily distribute it. Unfortunately, any of these scenarios can create issues with the import of files.

To see an example, you can follow the PyInstaller guide and create an entry point to your application. Add an extra directory outside your application directory:

structure/
│
├── structure/
│   ├── files.py
│   └── structure.py
│
└── cli.py

In the outer directory, create the entry point script, cli.py:

# cli.py

from structure.structure import main

if __name__ == "__main__":
    main()

This script will import main() from your original script and run it. Note that main() isn’t run when structure is imported because of the if test on line 25 in structure.py. That means you need to run main() explicitly.

In theory, this should work similarly to running the app directly:

$ python cli.py structure
Traceback (most recent call last):
  File "cli.py", line 1, in <module>
    from structure.structure import main
  File "/home/gahjelle/structure/structure/structure.py", line 8, in <module>
    import files
ModuleNotFoundError: No module named 'files'

Why didn’t that work? Suddenly, the import of files raises an error.

The problem is that by starting the app with cli.py, you’ve changed the location of the current script, which in turn changes the import path. files is no longer on the import path, so it can’t be imported absolutely.

One possible solution is to change Python’s import path:

 7# Local imports
 8sys.path.insert(0, str(pathlib.Path(__file__).parent))
 9import files

This works because the import path includes the folder containing structure.py and files.py. The issue with this approach is that your import path can get very messy and hard to understand.

In practice, you’re re-creating a feature of early Python versions called implicit relative imports. These were removed from the language by PEP 328 with the following rationale:

In Python 2.4 and earlier, if you’re reading a module located inside a package, it is not clear whether import foo refers to a top-level module or to another module inside the package. As Python’s library expands, more and more existing package internal modules suddenly shadow standard library modules by accident. It’s a particularly difficult problem inside packages because there’s no way to specify which module is meant. (Source)

Another solution is to use a relative import instead. Change the import in structure.py as follows:

 7# Local imports
 8from . import files

You can now start your app through the entry point script:

$ python cli.py structure
Create file: /home/gahjelle/structure/001/structure.py
Create file: /home/gahjelle/structure/001/files.py
Create file: /home/gahjelle/structure/001/__pycache__/structure.cpython-38.pyc
Create file: /home/gahjelle/structure/001/__pycache__/files.cpython-38.pyc

Unfortunately, you can no longer call the app directly:

$ python structure.py .
Traceback (most recent call last):
  File "structure.py", line 8, in <module>
    from . import files
ImportError: cannot import name 'files' from '__main__' (structure.py)

The problem is that relative imports are resolved differently in scripts than are imported modules. Of course, you could go back and restore the absolute import before running the script directly, or you could even do some try...except acrobatics to import files absolutely or relatively depending on what works.

There’s even an officially sanctioned hack to make relative imports work in scripts. Unfortunately, this also forces you to change sys.path in most cases. To quote Raymond Hettinger:

There must be a better way! (Source)

Indeed, a better—and more stable—solution is to play along with Python’s import and packaging system and install your project as a local package using pip.

Create and Install a Local Package

When you install a package from PyPI, that package is available to all scripts in your environment. However, you can also install packages from your local computer, and they’ll also be made available in the same way.

Creating a local package doesn’t involve much overhead. First, create minimal setup.cfg and setup.py files in the outer structure directory:

# setup.cfg

[metadata]
name = local_structure
version = 0.1.0

[options]
packages = structure

# setup.py

import setuptools

setuptools.setup()

In theory, the name and version can be whatever you like. However, they’ll be used by pip when referring to your package, so you should choose values that are recognizable and don’t collide with other packages you use.

One tip is to give all such local packages a common prefix like local_ or your username. packages should list the directory or directories containing your source code. You can then install the package locally using pip:

$ python -m pip install -e .

This command will install the package to your system. structure will then be found on Python’s import path, meaning you can use it anywhere without having to worry about the script directory, relative imports, or other complications. The -e option stands for editable, which is important because it allows you to change the source code of your package without reinstalling it.

Now that structure is installed on your system, you can use the following import statement:

 7# Local imports
 8from structure import files

This will work no matter how you end up calling your application.

While it’s a good idea to separate scripts and libraries, all Python files can be both executed and imported. In a later section, you’ll learn more about how to create modules that handle both well.

Namespace Packages

Python modules and packages are very closely related to files and directories. This sets Python apart from many other programming languages in which packages merely act as namespaces without enforcing how the source code is organized. See the discussion in PEP 402 for examples.

Namespace packages have been available in Python since version 3.3. These are less dependent on the underlying file hierarchy. In particular, namespace packages can be split across multiple directories. A namespace package is created automatically if you have a directory containing a .py file but no __init__.py. See PEP 420 for a detailed explanation.

To get a better understanding of why namespace packages can be useful, let’s try to implement one. As a motivating example, you’ll have another go at the problem solved in The Factory Method Pattern and Its Implementation in Python: given a Song object, you want to convert it to one of several string representations. In other words, you want to serialize Song objects.

To be more concrete, you want to implement code that works something like this:

>>> song = Song(song_id="1", title="The Same River", artist="Riverside")
>>> song.serialize()
'{"id": "1", "title": "The Same River", "artist": "Riverside"}'

Let’s assume that you’re lucky and come across a third-party implementation of several of the formats that you need to serialize to, and it’s organized as a namespace package:

third_party/
│
└── serializers/
    ├── json.py
    └── xml.py

The file json.py contains code that can serialize an object to the JSON format:

# third_party/serializers/json.py

import json

class JsonSerializer:
    def __init__(self):
        self._current_object = None

    def start_object(self, object_name, object_id):
        self._current_object = dict(id=object_id)

    def add_property(self, name, value):
        self._current_object[name] = value

    def __str__(self):
        return json.dumps(self._current_object)

This serializer interface is a bit limited, but it’ll be enough to demonstrate how namespace packages work.

The file xml.py contains a similar XmlSerializer that can convert an object to XML:

# third_party/serializers/xml.py

import xml.etree.ElementTree as et

class XmlSerializer:
    def __init__(self):
        self._element = None

    def start_object(self, object_name, object_id):
        self._element = et.Element(object_name, attrib={"id": object_id})