Python How To’s
A collection of small, useful, how to’s for Python.
Deepchecks: Testing Machine Learning Models
In the evolving landscape of machine learning, ensuring model quality and reliability has become as crucial as model development itself. Deepchecks emerges as a powerful open-source Python library designed specifically to address this need, offering comprehensive validation and testing for machine learning models. This article explores how Deepchecks works, its key features, and how data […]
Read MorePython reduce(): A Detailed Guide for Functional Python Programming
Python gives you a lot of in-built functions to make functional programming easier for you. One of those functions is the “reduce()”. Python reduce() function is part of the “functools” module. This is used to apply a function cumulatively to a sequence, reducing it to a single result. Today, in this guide, let us explain […]
Read MoreZipp: Explanation, Examples, and Applications
Zipp is a well-known Python library. In Python, handling ZIP archives is a task you will be doing very often, especially when you work with compressed data. With Python’s built-in “zipfile” module already providing basic features for creating, reading, writing, and extracting ZIP files, it needs an interface similar to that of “-pathlib” for easy […]
Read MorePython Main Function: Understanding and Using if __name__ == “__main__”
The Python “main” construct i.e., if __name__ == “__main__”, plays an important role in controlling the execution of all your Python scripts. It allows you to differentiate between script execution as a standalone program or as an imported module. Understanding how the Python main function works is essential for writing modular and reusable Python code. […]
Read MorePandoc and Python: Document Converter Simplified
Pandoc is a well-known, powerful, and flexible document conversion tool that lets you convert files between different markup formats like Markdown, HTML, LaTeX, and PDF. It is commonly used to publishing workflows, academic writing, and software documentation. Today, let us take you through this tool, how it works, its key features, how to use it with […]
Read MoreDask: Detailed Guide for Scalabale Computing
Dask is a Python library that scales from single machines to large clusters. In simple words, it is a parallel computing library. It is designed to append Python’s existing libraries like NumPy, pandas, and scikit-learn to handle larger-than-memory computations efficiently. The Dask Python library gives you dynamic task scheduling and distributed computing benefits. This […]
Read MoreHow To Speed Up Your Website With VPS Servers Using Python
Time is money, especially when it comes to websites. When pages load slowly, users lose interest, and search engines lower their rankings. Pay attention to VPS servers if you want your website to work faster. They provide the necessary power and flexibility to manage resources effectively. Users can also integrate the tool into various technologies. […]
Read MoreHow Full Stack Development Can Boost Your Career
Imagine this: you’re at a tech conference, mingling with other professionals, and the buzzword on everyone’s lips is “full stack development.” You might be wondering, is it just another tech trend, or can it really catapult your career to new heights? Full stack development might sound overwhelming at first, but what if it’s the key […]
Read MoreHow to Fix “Python Setup.py egg_info” Error (Error Code 1)
Introduction When installing Python programs with pip, “python setup.py egg_info” failed with error code 1 error. This stops the installation and is frustrating for beginners. Obsolete or missing dependencies, difficulties with pip or setup tools, or a damaged Python environment frequently cause the problem. Fortunately, there are straightforward fixes. This article will explain why this […]
Read MorePython Try Except: Handling Errors Like a Pro
Python Try Except: Handling Errors Like a Pro Master handling errors in Python Try except like a pro. First, identify the error-prone operations for your try block. Use multiple except blocks for specific exceptions and implement finally blocks for critical cleanup. Keep code concise and specify exception types for clarity. Avoid bare except clauses and […]
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