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How to Solve Python ModuleNotFoundError: no module named ‘imblearn’

by | Programming, Python, Tips

A common error you may encounter when using Python is modulenotfounderror: no module named ‘imblearn’.

This error occurs when the Python interpreter cannot detect the Imbalanced-learn library in your current environment.

We import Imbalanced-learn as imblearn in Python, similar to how we import scikit-learn as sklearn.

You can install imbalanced-learn in Python 3 with python -m pip install imbalanced-learn.

This tutorial goes through the exact steps to troubleshoot this error for the Windows, Mac and Linux operating systems.

Table of contents

ModuleNotFoundError: no module named ‘imblearn’

What is ModuleNotFoundError?

The ModuleNotFoundError occurs when the module you want to use is not present in your Python environment. There are several causes of the modulenotfounderror:

The module’s name is incorrect, in which case you have to check the name of the module you tried to import. Let’s try to import the re module with a double e to see what happens:

import ree
---------------------------------------------------------------------------
ModuleNotFoundError                       Traceback (most recent call last)
1 import ree

ModuleNotFoundError: No module named 'ree'

To solve this error, ensure the module name is correct. Let’s look at the revised code:

import re

print(re.__version__)
2.2.1

You may want to import a local module file, but the module is not in the same directory. Let’s look at an example package with a script and a local module to import. Let’s look at the following steps to perform from your terminal:

mkdir example_package

cd example_package

mkdir folder_1

cd folder_1

vi module.py

Note that we use Vim to create the module.py file in this example. You can use your preferred file editor, such as Emacs or Atom. In module.py, we will import the re module and define a simple function that prints the re version:

import re

def print_re_version():

    print(re.__version__)

Close the module.py, then complete the following commands from your terminal:

cd ../

vi script.py

Inside script.py, we will try to import the module we created.

import module

if __name__ == '__main__':

    mod.print_re_version()

Let’s run python script.py from the terminal to see what happens: 

Traceback (most recent call last):
  File "script.py", line 1, in ≺module≻
    import module
ModuleNotFoundError: No module named 'module'

To solve this error, we need to point to the correct path to module.py, which is inside folder_1. Let’s look at the revised code:

import folder_1.module as mod

if __name__ == '__main__':

    mod.print_re_version()

When we run python script.py, we will get the following result:

2.2.1

Lastly, you can encounter the modulenotfounderror when you import a module that is not installed in your Python environment.

What is imblearn?

Imbalanced-learn is a scientific library for resampling datasets with strong between-class imbalance. The library is compatible with scikit-learn and is a part of the scikit-learn-contrib project. We import imbalanced-learn as imblearn.

The simplest way to install imblearn is to use the package manager for Python called pip. The following installation instructions are for the major Python version 3.

Always Use a Virtual Environment to Install Packages

It is always best to install new libraries within a virtual environment. You should not install anything into your global Python interpreter when you develop locally. You may introduce incompatibilities between packages, or you may break your system if you install an incompatible version of a library that your operating system needs. Using a virtual environment helps compartmentalize your projects and their dependencies. Each project will have its environment with everything the code needs to run. Most ImportErrors and ModuleNotFoundErrors occur due to installing a library for one interpreter and using the library with another interpreter. Using a virtual environment avoids this. In Python, you can use virtual environments and conda environments. We will go through how to install imblearn with both.

How to Install imblearn on Windows Operating System

First, you need to download and install Python on your PC. Ensure you select the install launcher for all users and Add Python to PATH checkboxes. The latter ensures the interpreter is in the execution path. Pip is automatically on Windows for Python versions 2.7.9+ and 3.4+.

You can check your Python version with the following command:

python3 --version

You can install pip on Windows by downloading the installation package, opening the command line and launching the installer. You can install pip via the CMD prompt by running the following command.

python get-pip.py

You may need to run the command prompt as administrator. Check whether the installation has been successful by typing.

pip --version

imblearn installation on Windows Using pip

To install imblearn, first, create the virtual environment. The environment can be any name, in this we choose “env”:

virtualenv env

You can activate the environment by typing the command:

env\Scripts\activate

You will see “env” in parenthesis next to the command line prompt. You can install imblearn within the environment by running the following command from the command prompt.

python3 -m pip install imbalanced-learn

We use python -m pip to execute pip using the Python interpreter we specify as Python. Doing this helps avoid ImportError when we try to use a package installed with one version of Python interpreter with a different version. You can use the command which python to determine which Python interpreter you are using.

How to Install imblearn on Mac Operating System using pip

Open a terminal by pressing command (⌘) + Space Bar to open the Spotlight search. Type in terminal and press enter. To get pip, first ensure you have installed Python3:

python3 --version
Python 3.8.8

Download pip by running the following curl command:

curl https://bootstrap.pypa.io/get-pip.py -o get-pip.py

The curl command allows you to specify a direct download link. Using the -o option sets the name of the downloaded file.

Install pip by running:

python3 get-pip.py

To install imblearn, first create the virtual environment:

python3 -m venv env

Then activate the environment using:

source env/bin/activate

You will see “env” in parenthesis next to the command line prompt. You can install imblearn within the environment by running the following command from the command prompt.

python3 -m pip install imbalanced-learn

How to Install imblearn on Linux Operating Systems

All major Linux distributions have Python installed by default. However, you will need to install pip. You can install pip from the terminal, but the installation instructions depend on the Linux distribution you are using. You will need root privileges to install pip. Open a terminal and use the commands relevant to your Linux distribution to install pip.

Installing pip for Ubuntu, Debian, and Linux Mint

sudo apt install python-pip3

Installing pip for CentOS 8 (and newer), Fedora, and Red Hat

sudo dnf install python-pip3

Installing pip for CentOS 6 and 7, and older versions of Red Hat

sudo yum install epel-release

sudo yum install python-pip3

Installing pip for Arch Linux and Manjaro

sudo pacman -S python-pip

Installing pip for OpenSUSE

sudo zypper python3-pip

imblearn installation on Linux with Pip

To install imblearn, first create the virtual environment:

python3 -m venv env

Then activate the environment using:

source env/bin/activate

You will see “env” in parenthesis next to the command line prompt. You can install imblearn within the environment by running the following command from the command prompt.

Once you have activated your virtual environment, you can install imblearn using:

python3 -m pip install imbalanced-learn

Installing imblearn Using Anaconda

Anaconda is a distribution of Python and R for scientific computing and data science. You can install Anaconda by going to the installation instructions. Once you have installed Anaconda, you can create a virtual environment and install imblearn.

To create a conda environment, you can use the following command:

conda create -n imblearn python=3.8

You can specify a different Python 3 version if you like. Ideally, choose the latest version of Python. Next, you will activate the project container. You will see “imblearn” in parentheses next to the command line prompt.

source activate imblearn

Now you’re ready to install imblearn using conda.

Once you have activated your conda environment, you can install imblearn using the following command:

conda install -c conda-forge imbalanced-learn

Check imblearn Version

Once you have successfully installed imblearn, you can check its version. If you used pip to install imblearn, you can use pip show from your terminal.

python3 -m pip show imbalanced-learn
Name: imbalanced-learn
Version: 0.8.1
Summary: Toolbox for imbalanced dataset in machine learning.

Second, within your python program, you can import the imblearn and then reference the __version__ attribute:

import imblearn
print(imblearn.__version__)
0.8.1

If you used conda to install imblearn, you could check the version using the following command:

conda list -f imbalanced-learn
## Name                    Version                   Build  Channel
imbalanced-learn          0.9.0              pyhd8ed1ab_0    conda-forge

Dependencies for Imblearn

You can find the complete list of the dependencies for imbalanced-learn under the imbalanced-learn getting started documentation.

Summary

Congratulations on reading to the end of this tutorial. The modulenotfounderror occurs if you misspell the module name, incorrectly point to the module path or do not have the module installed in your Python environment. If you do not have the module installed in your Python environment, you can use pip to install the package. However, you must ensure you have pip installed on your system. You can also install Anaconda on your system and use the conda install command to install imbalanced-learn.

Go to the online courses page on Python to learn more about Python for data science and machine learning.

For further reading on missing modules in Python, go to the article:

Have fun and happy researching!