5 Best Ways to Check Python Module Version from the Command Line

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💡 Problem Formulation: When working with Python, it’s essential to know the version of the modules you are utilizing to ensure compatibility and troubleshoot potential issues. For example, if you’re using the requests module, you might want to confirm that you have the correct version installed to work with your code: “Input: ‘requests’ module, Desired output: version ‘2.25.1’ or similar.”

Method 1: Utilizing pip show Command

This method involves the usage of Python’s package manager pip. The pip show command provides information about installed packages, including the version. It’s an easy-to-use and straightforward method to check the installed version of any Python module.

Here’s an example:

$ pip show requests

Output:

Name: requests
Version: 2.25.1
Summary: Python HTTP for Humans.
...

This command lists detailed information about the requests module, including the currently installed version, which in this case is 2.25.1. It’s simple, concise, and provides more than just the version number, which could be useful for debugging purposes.

Method 2: Using Python’s Interpreter with __version__ Attribute

Python modules often have a __version__ attribute defined. By starting a Python interpreter session, you can import a module and check its version using this attribute. This method is quick and doesn’t require any external tools.

Here’s an example:

import requests
print(requests.__version__)

Output:

2.25.1

The example demonstrates fetching the version of the requests module directly from within a Python script or interactive session. This is a very straightforward method, but not all modules follow the convention of using a __version__ attribute, so it may not work universally.

Method 3: Inspecting Module Properties with the pkg_resources Library

The pkg_resources module, which is part of the setuptools package, can be used to check the version of installed packages. It’s a more programmatic way to obtain module versions and can be useful in scripts and applications to check dependencies.

Here’s an example:

import pkg_resources
print(pkg_resources.get_distribution('requests').version)

Output:

2.25.1

This code utilizes the pkg_resources library to retrieve the version of the requests module. While this is a powerful method, it assumes that the setuptools package is installed and available. This method is particularly effective for detecting a module’s version programmatically within a Python script.

Method 4: Using the conda list Command

If you’re using the Anaconda distribution or manage your environments with Conda, the conda list command is a convenient way to see the version of all installed packages in the current environment, including Python modules.

Here’s an example:

$ conda list requests

Output:

# packages in environment at /Users/username/miniconda3:
#
# Name                    Version                   Build  Channel
requests                  2.25.1                   py_0    conda-forge

This command filters the list of all packages to show only the requests module and its details. It’s highly useful for Conda users, but it’s only applicable in a Conda-managed environment, thus limiting its use to a subset of Python users.

Bonus One-Liner Method 5: Using a One-Liner in the Python Interpreter

For those who appreciate brevity, Python offers a way to combine the interpreter startup with a one-liner script that can be used to check a module’s version.

Here’s an example:

$ python -c "import requests; print(requests.__version__)"

Output:

2.25.1

This one-liner command quickly checks the version of the requests module by running a short Python script from the command line. This method is extremely succinct but shares the same limitations as Method 2 regarding the use of the __version__ attribute.

Summary/Discussion

  • Method 1: pip show Command. Universally applicable to all Python environments. Provides detailed package information. Requires pip.
  • Method 2: __version__ Attribute. Simple and quick. Doesn’t work if the attribute is not defined.
  • Method 3: pkg_resources Library. Can be integrated into scripts. Requires setuptools.
  • Method 4: conda list Command. Native to Conda users. Not applicable outside of Conda environments.
  • Bonus Method 5: Python One-Liner. Fast and direct. Dependent on __version__ attribute existence.