One error you might encounter when setting up Python environment is:
ModuleNotFoundError: No module named 'skbuild'
This error occurs when Python can’t find the
skbuild library in the current environment.
In this tutorial, I will show you an example that causes this error and how to fix it in practice.
How to reproduce the error
Suppose you want to use the
skbuild module to compile a Python package as follows:
But you get the following error when running the code:
Traceback (most recent call last): File "main.py", line 1, in <module> import skbuild ModuleNotFoundError: No module named 'skbuild'
To my knowledge, the
ModuleNotFoundError happens when Python can’t find the module you’re trying to import.
skbuild module is not bundled with Python, so you need to install it first.
How to fix this error
To resolve this error, you need to install the
skbuild library using the
pip install command:
pip install scikit-build # For pip3: pip3 install scikit-build
Note that the package name is different than the module name. Once the module is installed, you should be able to run the code that imports
skbuild without receiving the error.
Install commands for other environments
The install command might differ depending on what environment you used to run the Python code.
Here’s a list of common install commands in popular Python environments to install the
# if you don't have pip in your PATH: python -m pip install scikit-build python3 -m pip install scikit-build # Windows py -m pip install scikit-build # Anaconda conda install scikit-build # Jupyter Notebook !pip install scikit-build
Once the module is installed, you should be able to run the code without receiving this error.
Other common causes for this error
If you still see the error even after installing the module, it means that the
skbuild module can’t be found in your Python environment.
There are several reasons why this error can happen:
- You may have multiple versions of Python installed on your system, and you are using a different version of Python than the one where skbuild is installed.
- You might have skbuild installed in a virtual environment, and you are not activating the virtual environment before running your code.
- Your IDE uses a different version of Python from the one that has skbuild
- The package is not installed in PyCharm
Let’s see how to fix these errors in practice.
1. You have multiple versions of Python
If you have multiple versions of Python installed on your system, you need to make sure that you are using the specific version where the skbuild module is available.
You can test this by running the
which -a python or
which -a python3 command from the terminal:
$ which -a python3 /opt/homebrew/bin/python3 /usr/bin/python3
In the example above, there are two versions of Python installed on
Suppose you run the following steps in your project:
- Install skbuild with
- Install Python using Homebrew, you have Python in
- Then you run
import skbuildin your code
The steps above will cause the error because skbuild is installed in
/usr/bin/, and your code is probably executed using Python from
To solve this error, you need to run the
pip install scikit-build command again so that skbuild is installed and accessible by the active Python version.
2. Python virtual environment is active
Another scenario that could cause this error is you may have skbuild installed in a virtual environment.
venv package allows you to create a virtual environment where you can install different versions of packages required by your project.
If you are installing
skbuild inside a virtual environment, then the module won’t be accessible outside of that environment.
You can see if a virtual environment is active or not by looking at your prompt in the terminal.
When a virtual environment is active, the name of that environment will be shown inside parentheses as shown below:
In the picture above, the name of the virtual environment
(demoenv) appears, indicating that the virtual environment is currently active.
If you run
pip install while the virtual environment is active, then the package is installed only for that environment
Likewise, any package installed outside of that virtual environment won’t be accessible from the virtual environment. The solution is to run the
pip install command on the environment you want to use.
If you want to install skbuild globally, then turn off the virtual environment by running the
deactivate command before running the
pip install command.
3. IDE using a different Python version
Finally, the IDE from where you run your Python code may use a different Python version when you have multiple versions installed.
For example, you can check the Python interpreter used in VSCode by opening the command palette (
CTRL + Shift + P for Windows and
⌘ + Shift + P for Mac) then run the
Python: Select Interpreter command.
You should see all available Python versions listed as follows:
You need to use the same version where you installed skbuild so that the module can be found when you run the code from VSCode.
Once done, you should be able to import skbuild without receiving any errors.
4. You see this error in PyCharm
If you’re using PyCharm as your IDE, then this error might occur because the package is not installed in the Python interpreter used by PyCharm.
This is because PyCharm creates a new virtual environment for each project you create using the IDE.
To resolve this error, you can install the package using PyCharm’s terminal.
For more information, you can see the guide to install and uninstall packages in PyCharm.
In summary, the
ModuleNotFoundError: No module named 'skbuild' occurs when the
skbuild library is not installed in your Python environment. To resolve this error, you need to run the
pip install scikit-build command.
If you already have the module installed, make sure you are using the correct version of Python, check if the virtual environment is active if you have one, and check for the Python version used by your IDE.
By following these steps, you should be able to import the
skbuild module in your code successfully.
I hope you find this tutorial helpful. Until next time! 👋