How to beat Python’s pip: A brief intro

How to beat Python’s pip: A brief intro

How to beat Python’s pip: A brief intro. I will briefly discuss an approach that helped to resolve versions of libraries for applications faster than pip’s resolution algorithm.

The Python’s package installer, pip, is known to have issues when resolving software stacks. In the upcoming series of articles, I will briefly discuss an approach that helped to resolve versions of libraries for applications faster than pip’s resolution algorithm. Moreover, the resolved software stacks are scored based on various aspects to help with shipping high-quality software.

Python is one of the most growing programming languages out there. There is no doubt it’s becoming the programming language of choice for data science, machine learning engineers or software developers. In my eyes, Python code is a pseudo-code that simply runs — easy to write, easy to maintain. Creating an API server using Flask, making data analysis in Jupyter notebooks or creating a neural network using TensorFlow, these all can be easily written in a few lines of code. Any performance-critical parts can be optimized thanks to CPython’s C API. Python is a very effective weapon in anyone’s inventory.

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