Working on a Python project may require listing installed Python packages in order to manage dependencies, check for updates, or share project requirements with others. In this article, we will look at various techniques for listing the Python packages installed on a system.
List installed Python packages
Here are some ways we can list installed Python packages:
- Using pip list
- Freeze using pip
- Using Python’s pkg_resources
- Use pipdeptree
- Use pipenv
- Using Jupyter Notebooks
Use pip list to list installed Python packages
The most common way to list installed Python packages is to use the pip command line tool. pip is Python’s standard package manager, and it comes pre-installed with Python 3.4 and above.
We can use the list command to list the packages that have been installed using pip. Just open a terminal or command prompt and run the following command and you will see a list of all installed packages.
python Copy code pip list
This command will display a list of all Python packages installed in the Python environment and their versions. You can also redirect the output to a text file (optional) If you want to save the list of installed packages to a text file, you can use the following command:
python Copy code pip list > installed_packages.txt
This command creates a file named installed_packages.txt and saves the package list in it.
Use pip freeze to list Python packages
Another commonly used command to list installed packages, especially in a Python project management context, is pip freeze. This command generates a list of installed packages and their versions in a format typically used to specify project dependencies in a requirements.txt file.
We can use pip freeze to list installed Python packages. Just open a terminal or command prompt and run the following commands.
python Copy code pip freeze
This command will display a list of installed packages and their versions, similar to what you might find in the requirements.txt file.
List Python packages using Python’s pkg_resources module
If you prefer to programmatically list installed packages from a Python script, you can use the pkg_resources module from the setuptools package. Here’s an example of how to use it:
python
Copy code
import pkg_resources
installed_packages = pkg_resources.working_set
for package in installed_packages:
print(f"{package.key}=={package.version}")
This script will print the names and versions of all installed packages in your Python environment.
Use pipdeptree to list Python packages
pipdeptree is a Python package that helps you visualize and list the dependencies of installed packages in a tree structure. To use it, you need to install it first:
python Copy code pip install pipdeptree
After installing pipdeptree, you can list installed packages and their dependencies as follows:
python Copy code pipdeeptree
This command will display a tree structure of installed packages and their dependencies.
Use pipelinev to list installed packages
Pipenv is a popular tool for managing Python project environments and dependencies. It combines pip and virtualenv to create isolated Python environments for your projects. To list installed packages in a Pipenv environment, follow these steps:
- Open a terminal or command prompt and navigate to the directory where Pipfile is located.
- Activate the virtual environment:
python Copy code pipenv shell
List installed packages:
python Copy code pipenv lock --requirements
This command will display a list of installed packages and their versions.
Using Jupyter Notebook
If we are using Jupyter Notebook for Python development and want to list the installed packages in the notebook, we can use the ! (shell command) prefix. That’s it:
- Open Jupyter Notebook: Start Jupyter Notebook by running jupyter Notebook in the terminal.
- Create a new notebook or open an existing notebook: You can create a new notebook or open an existing notebook to list installed packages.
- List installed packages in a notebook unit:
python Copy code !pip list
Running this command in a notebook cell will display a list of installed packages and their versions in the notebook output.
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