How to Import Functions From Another Python File

In Python, code reusability is king: Why write the same function over and over when you can simply import it from another file? Learning how to import functions from another Python file is a fundamental skill for any data scientist. It allows you to tap into code defined elsewhere, saving time and effort while promoting cleaner, more maintainable projects.

What Does It Mean to Import Functions from Another Python File?

At its core, importing a function means making that function’s code available within your current Python script or environment. This streamlines your workflow, allowing you to focus on higher-level tasks without reinventing the wheel. 

The Benefits of Importing Functions

Importing a function from another Python file offers a multitude of benefits:

  • Reusability: Avoid writing the same code repeatedly, saving time while reducing the risk of errors.
  • Organization: Break down your project into logical modules, each with its own set of functions. This makes your codebase more manageable and easier to understand.
  • Collaboration: Share code seamlessly across different files or even projects. This is especially valuable when working in teams.
  • Maintainability: Updating a function in one place automatically updates it everywhere it’s imported, ensuring consistency throughout your project. When you know how to import a function from another Python file, maintaining and updating your code becomes a breeze.

The Basics of Importing a Function From Another File in Python

The most fundamental way to import a function is by using the following syntax:

from filename import function_name

Let’s break down this essential syntax of how to import functions from another Python file:

  • from filename: Specifies the file (without the .py extension) where your desired function resides
  • import function_name: Tells Python exactly which function you want to bring into your current script

Illustrative Example

Imagine you have a file named data_utils.py containing a function called clean_data. To utilize this function in your current script, you would write:

from data_utils import clean_data
df = clean_data(raw_df)

In this example, raw_df is your DataFrame, and after this line of code executes, df will hold the cleaned version of your data.

Important Considerations

Python needs to know the location of the file you’re importing from. By default, it searches:

  1. The same directory as your current script.
  2. Directories listed in your Python path.

If data_utils.py isn’t in one of these locations, you’ll need to adjust the path accordingly. For instance, if it’s in a subdirectory called utils, you would write:

from utils.data_utils import clean_data 

How to Import Multiple Functions from Another Python File

Frequently, you’ll find yourself needing multiple functions from the same Python file. Instead of importing them individually, you can import them all in one concise line:

from filename import function1, function2, function3

Suppose data_utils.py also has functions named impute_missing_values and encode_categorical_features. You can import and then use all three like this:

from data_utils import clean_data, impute_missing_values, encode_categorical_features
df = clean_data(raw_df)
df = impute_missing_values(df)
df = encode_categorical_features(df)

How to Import All Functions from Another Python File

Python provides a way to import all functions from a module at once using the asterisk (*) wildcard:

from filename import *

While this might seem like a convenient shortcut, it’s generally discouraged due to a problem called namespace pollution. Importing everything can lead to:

  • Name Collisions: If your script or another imported module has functions with the same names, Python won’t know which one to use. This can lead to unexpected behavior and bugs.
  • Reduced Readability: It becomes unclear where functions are coming from, making your code harder to understand and maintain.

Importing all functions from another Python file can make sen se in certain situations:

  • Small, Trusted Modules: If you’re working with a module that you know is well-organized and won’t cause conflicts, using * can save some typing.
  • Interactive Sessions: Importing everything can be helpful for quick experimentation and exploration.

Beyond the Basics: Modules and Packages

Python projects often organize code into packages: collections of modules (files) that work together. To import functions from a package, you specify the package name and the module within it:

from package_name.module_name import function_name

Python uses a special file named __init__.py within a directory to mark it as a package. This file can contain initialization code or simply be empty.

Python looks for imported modules and files in a specific order, defined by its search path (sys.path). This path includes:

  • The directory of your current script
  • Other directories you’ve added to the path
  • Standard library locations

Understanding absolute and relative paths is crucial for importing functions from different locations within your project. 

Exaloop: Your Python Productivity Partner

As a data scientist, your time is valuable. Exaloop is a powerful platform designed to streamline your Python workflow, including importing functions from other Python files.

Here are some of Exaloop’s key features for importing:

  • Intelligent Auto-Completion: Quickly find and import functions without needing to remember their exact names or locations.
  • Dependency Tracking: Visualize the relationships among your modules to prevent circular imports and other issues.

Environment Management: Seamlessly switch between project environments with different dependencies, ensuring smooth collaboration and reproducibility.

Ready to supercharge your Python coding? Try Exaloop and experience a more efficient and enjoyable development process.