error: failed building wheel for numpy ( Solved )

error_ failed building wheel for numpy ( Solved )

Numpy is the best Python package for array creation and computing complex mathematic calculations. Generally, you are able to install NumPy easily using the pip command. But sometimes you are unable to install it and get the error message failed building wheel for numpy. In this entire tutorial, you will know why this error comes and how to solve the error: failed building wheel for NumPy error.

What is a Wheel?

The wheel is a distribution or packaging format. Today most coders use it for building and packaging Python code. There is a file of the format WHL that saves the packaging information in wheel format. The Wheel contains all the metadata and files for python to install the package. Thus it allows faster installation and more stability. Most of  the coders use it for distribution of the packages in an efficient way.

python wheel offical website
python wheel offical website

 

What causes error: failed building wheel for NumPy error

Most of the time this type of error comes when there is a NumPy version released. The current NumPy releases do not support the specific Python version. So the wheel format file is unable to install the version of the Numpy in your system. And it causes the failed building wheel for numpy error.

Solution for the failed building wheel for NumPy ( Step by Step )

The solution for the error failed building wheel for NumPy is very simple. I will discuss different ways to solve this type of error. Before we do anything we need to make sure that we have the necessary build tools installed already. Like for Windows, we must have Microsoft Visual C++ Build Tools and Linux users must have build-essential python3-dev in the system.

Solution 1: Upgrade the pip

The first solution to remove this error is to first upgrade the pip command. After upgrading try to install the NumPy version using the pip command.

Step 1 :

Here is the command to upgrade pip and setuptools as the first step.

pip install --upgrade pip setuptools wheel

step 2:

But make sure to check the version of python. If the version is 3. xx then use the pip3 command and if it is 2. xx then use the pip command.

Use the below command to check the version of Python.

python --version
Checking Python version before installing spacy
Checking the Python version before installing spacy

Step 3:

Use the below command to install the NumPy.

For python3.xx

pip3 install numpy

For python 2. xx

pip install numpy

My system has Python 3. xx so I will use the pip3 command.

Install numpy using the pip3 command
Install numpy using the pip3 command

Solution 2: Install the specific NumPy version

If you are still getting the error after applying solution 1 then you have to check which version of the Numpy is supported by python. In this case, you have to downgrade the NumPy version.

For example, let’s say the current Numpy version is 1.19 and it is not supported by Python. Then you have to check the version of the NumPy supported by Python. Let’s say it is 1.18 then you will install it using the below command.

pip3 install numpy==1.18
Install the specific version of numpy
Install the specific version of numpy

It will successfully install the NumPy and you will not get the failed building wheel for NumPy.

Solution 3 : Upgrade the Python version –

If you are bound to use the same Numpy version because of some functionality constraint then the only option is to change the Interpreter/environment version

1. Linux or Similar OS use the below command.

sudo apt update
sudo apt install python-version

python-version is the version you want or require.

2. For Windows users you can simply download the latest version setup and reinstall the same.

Conclusion

Numpy is a great package if you want to do computational work on datasets. These are the ways that can solve the error.

I hope you have liked this tutorial. If you are still getting errors then you can contact us for more help.

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Meet Sukesh ( Chief Editor ), a passionate and skilled Python programmer with a deep fascination for data science, NumPy, and Pandas. His journey in the world of coding began as a curious explorer and has evolved into a seasoned data enthusiast.
 
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