importerror: numba needs numpy 1.21 or less ( Get Solution )

importerror_ numba needs numpy 1.21 or less

importerror: numba needs numpy 1.21 or less occurs while converting python code to Machine level code due to incompatibility of NumPy module. In this article, Firstly we will focus on the root cause and the solution for this. But Along with this, we will go one more level deeper to understand what is numba and why we use it in Industry.

 

importerror: numba needs numpy 1.21 or less ( Root cause and Fix ) –

The error statement is also self-explanatory. Numba only supports the lower version of numpy specifically 1.21. Although while creating this article the current version of the Numpy is 1.22.3. Now how will u check the current version in your system for NumPy ? Here is the command for the same.

numpy.__version__
numpy version
NumPy version

The best way to fix this is to downgrade the NumPy version.

Downgrading NumPy  t0 1.21 or lower Version –

We can use the pip package manager to downgrade the NumPy version. We need to mention the version of the package.

pip install numpy==1.21
importerror numba needs numpy 1.21 or less
importerror numba needs numpy 1.21 or less

 

Why do we use Numba?

Numba is a package to optimize the python code’s performance. We all know the interpreter converts High-level language to machine language. Here Python is built on the C programming language. Hence the software which is on the top of the C programming language is faster than python oriented programming language. In order to match or optimize the performance of python programming language, we either convert it to Cython or Numba package. It will convert code to close to machine level which ultimately provides faster computation.

We all know python is a too syntax-friendly programming language in comparison to C, FORTRON, or C++. By using this Numba or similar package we fill the gap between performance and coding complexity. I hope now you can easily resolve your bug. Also, we understood other related aspects of this.

 

Thanks

Data Science Learner Team 

 

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