The Python calendar module provides several ways to generate calendars for Python programs. It also includes a variety of functions for working with calendar data as strings, numbers, and datetime objects. In this tutorial, you’ll learn how to use the calendar module to create and customize calendars with Python. By the end of this tutorial, you’ll be able to: Display calendars in your terminal with Python Create plain text and HTML calendars Format calendars for specific locales and display conventions […]

Python has several basic data types that are built into the language. With these types, you can represent numeric values, text and binary data, and Boolean values in your code. So, these data types are the basic building blocks of most Python programs and projects. In this tutorial, you’ll learn only the basics of each data type. To learn more about a specific data type, you’ll find useful resources in the corresponding section. Python’s Basic Data Types Python has several […]

Python has a complete set of built-in exceptions that provide a quick and efficient way to handle errors and exceptional situations that may happen in your code. Knowing the most commonly used built-in exceptions is key for you as a Python developer. This knowledge will help you debug code because each exception has a specific meaning that can shed light on your debugging process. You’ll also be able to handle and raise most of the built-in exceptions in your Python […]

When you develop a self-contained Python script, you might not notice anything unusual about your directory structure. However, as soon as your project becomes more complex, you’ll often decide to extract parts of the functionality into additional modules or packages. That’s when you may start to see a __pycache__ folder appearing out of nowhere next to your source files in seemingly random places: project/ │ ├── mathematics/ │ │ │ ├── __pycache__/ │ │ │ ├── arithmetic/ │ │ ├── […]

PyTorch vs TensorFlow: What’s the difference? Both are open-source Python libraries that use graphs to perform numerical computations on data in deep learning applications. Both are used extensively in academic research and commercial code. Both are extended by a variety of APIs, cloud computing platforms, and model repositories. If they’re so similar, then how do you decide which one is best for your project? You’ll start by taking a close look at both platforms, beginning with the slightly older TensorFlow. […]