Python Programming

• Default to User Installation Because Normal Site Packages Are Not Writeable

  “When trying to install Python packages, you may sometime encounter “default to user installation because normal site-packages are not writeable” error. In this attempt, we will explain why this error occurs and how we can resolve it.”

• Pip Clear Cache

  Pip is the most popular and versatile package installer for Python. It offers a command-line utility that allows you to manage Python packages easily. Using pip, you can perform actions such as downloading, installing, updating, and uninstalling packages with simple commands. Pip uses a caching mechanism that allows you to download and install Python packages faster. It works by storing a cache of the downloaded packages on the local wheel. The caching mechanism allows pip to improve the download and installation of the packages. This is because pip does not need to download already existing packages. In some cases, pip may not need to redownload a package when updating if it already exists in the cache. This tutorial will discuss how to work with the pip cache, how to manage the pip cache using various commands, and how to clear it when you need to start afresh.

• No Module Named Matplotlib

  This guide will discuss the “No module named matplotlib” error in Python: why it occurs, and how to resolve it in different environments.

• NumPy np.where Multiple Conditions

  “In this tutorial, you will learn the various methods you can use to specify multiple conditions using the np.where() function.”

• Matplotlib Font Size

  Frequently, you may need to customize the default font size in the plots created with matplotlib. Thankfully, matplotlib has extensive support for text manipulation, including font size adjustment and more.

• 10 Best and Essential Python Tools for Data Science in 2022

  Python is at its peak popularity due to its easy-to-understand syntax and versatile libraries. With that in mind, using Python tools for data science isn’t surprising. Data scientists do not have an easy job. They have to understand tons of complex ideas and polish existing data in order to interpret them. To make things easier, Python tools containing various libraries exist to deal with such tedious tasks. For instance, data scientists have to analyze a large number of data and follow through with several processes to come to their conclusion. That means a lot of repetition is undoubtedly at play here – and python tools come in handy right at this point.

• Pretty Print JSON Python

  “JSON or JavaScript Object Notation is a lightweight data exchange format that is widely adopted by modern applications. Whether you are working in NoSQL databases or fetching API data, you will encounter JSON. It is a heavily adopted language due to its simplicity but strict schema. This helps to reduce errors while still retaining human readability.

• Pandas Convert Column to Int

  Pandas is a free and open-source Python library that provides fast, flexible, and expressive data structures that make working with scientific data easy. Pandas is one of Python’s most valuable data analysis and manipulation packages. It offers features such as custom data structures that are built on top of Python. This article will discuss converting a column from one data type to an int type within a Pandas DataFrame.

• No Module Named ‘TensorFlow’

  TensorFlow is a free and open-source library for machine learning and artificial intelligence. It offers a vast collection of tools and utilities that makes the process of machine learning and AI more intuitive and fun. TensorFlow is cross-platform and can be installed on any machine running Linux, macOS, Linux, Android, or a JavaScript engine. In some instances, you may face a “No Module Named TensorFlow” error when attempting to use TensorFlow in your application. Throughout this guide, we will explore various scenarios of why this error occurs and how you can resolve it.

openSUSE Micro could be your next container OS

openSUSE Micro is a new Linux distribution geared toward hosting containerized workloads with automated administration and patching. With this open-source, purpose-built operating system you’ll have an environment specifically designed for workloads that would benefit from transactional updates. This rolling-release distribution could be just the thing your company needs. openSUSE Micro aims to be predictable, scalable, reliable and flexible. With this new take on containerized deployments, you don’t have to learn a new package format (as it uses standard openSUSE RPMs), there are no size limitations and it can be rolled out easily and repeatedly.

Red Hat Satellite 6.10.7 has been released

We are pleased to announce that Red Hat Satellite 6.10.7 is generally available as of July 6, 2022. Red Hat Satellite is part of the Red Hat Smart Management subscription that makes it easier for enterprises to manage patching, provisioning, and subscription management of Red Hat Enterprise Linux infrastructure.