How To Import Modules in Python 2023 Guide

Modules and packages are the fundamental building blocks that enable Python programmers to write organized, reusable code. Mastering importing in Python is therefore a core skill for building robust and scalable applications.

This in-depth guide covers key import concepts, use cases, and best practices to level up your Python module usage.

Why Imports Matter for Python Developers

Importing modules and packages provides critical advantages:

  • Enables reusing code without copying and pasting.
  • Allows collaborating and sharing common code between files and projects.
  • Lets you leverage pre-built functionality beyond the standard library.
  • Promotes abstraction by separating components.
  • Allows managing namespaces to avoid naming collisions.
  • Enables large-scale code organization.

Robust import skills are indispensable for architecting Python projects and applications.

Key Concepts for Python Imports

  • The import statement brings module code into the current namespace.
  • from module import name imports specific names directly.
  • Packages contain collections of modules in nested directories.
  • files identify Python packages.
  • The PYTHONPATH environment variable specifies additional import directories.
  • Modules and packages help organize related code into coherent units.

Importing Modules

The basic import statement loads an entire module:

import math

Module contents must then be referenced using dot notation:


This separates the module namespace from local names.

Importing Specific Objects

Import just needed names with from:

from math import sin, cos 


This pulls in only sin and cos from the math module.

Importing All Module Names

Use from module import * to import everything:

from math import *

However, this pollutes the namespace and is discouraged.

Using Aliases

Alias overly long names with as:

import numpy as np

Now numpy can be referenced as np.

Organizing Code with Packages

Packages are directories containing multiple modules:


The project.utils.math module can then be imported.

Managing the Python Path

The PYTHONPATH environment variable specifies additional directories to search for imports:


This allows flexible organization across environments.

Best Practices for Productive Python Imports

Some key import best practices include:

  • Use explicit relative imports rather than implicit.
  • Avoid importing everything from a module using *.
  • Use aliases and packages to manage namespace conflicts.
  • Set PYTHONPATH appropriately for your project structure.
  • Prefer absolute imports over relative for readability.
  • Standardize import conventions in teams for consistency.
  • Document import dependencies and expected environment setup.


Mastering Python imports enables retrieving and reusing existing code in a clean, organized manner. Imports power code abstraction, sharing, and collaboration. Following import best practices will improve development efficiency, reliability, and collaboration in Python projects both large and small.

Let me know if you have any other questions!

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