Python
Getting Started with Python | A Beginner’s Guide
Table of Contents
Introduction
Welcome to Codesick, fully updated for Python in this series, you’ll learn real-world Python programming techniques, illustrated with useful and interesting examples. Whether you’re a new programmer or a professional software developer looking to dive into a new language, this series will teach you all the practical Python that you need to get started on projects of your own. No matter what your ultimate goals may be, if you work with a computer at all, then you’ll soon be finding endless ways to improve your life by automating tasks and solving problems through Python programs that you create.
What Is Python?
Python is a high-level, interpreted, and general-purpose programming language. It was created by Guido van Rossum and first released in 1991. Python is known for its simplicity, readability, and versatility, making it a popular choice for beginners and experienced developers alike. Here are some key characteristics and features of Python.
- High-level Language:
Python is a high-level programming language, meaning it abstracts many low-level details and provides a clean and simple syntax.
- Interpreted Language:
Python is an interpreted language, which means that the Python code is executed line by line by an interpreter, rather than being compiled into machine code beforehand.
- Object-Oriented:
Python supports object-oriented programming (OOP) principles, allowing developers to organize code using classes and objects.
- Readable and Expressive Syntax:
Python emphasizes readability with a clean and straightforward syntax. This reduces the cost of program maintenance and development.
- Extensive Standard Library:
Python comes with a comprehensive standard library that provides modules and packages for various tasks, simplifying development by offering pre-built functionality.
- Dynamic Typing:
Python is dynamically typed, meaning the data type of a variable is determined at runtime. This allows for more flexibility but requires careful handling of data types.
- Cross-Platform Compatibility:
Python is cross-platform, meaning code written in Python can run on different operating systems with little to no modification.
- Community Support:
Python has a large and active community of developers, contributing to its rich ecosystem of libraries, frameworks, and tools. This community support makes it easier to find solutions and resources.
- Open Source:
Python is an open-source language, which means its source code is freely available for modification and redistribution.
What Is Python Used For?
Python is the fourth most popular programming language, according to Stack Overflow’s 2022 Developer Survey, with respondents stating that they use it for development work over 50% of the time. Python is frequently used for data analysis, data visualization, task automation, and the development of software and websites. Python is widely used by non-programmers, including scientists and accountants, for a variety of everyday tasks, like organizing finances.
- Web Development:
Frameworks: Python has powerful web development frameworks like Django and Flask that enable developers to build scalable and robust web applications.
- Data Science and Machine Learning:
Libraries: Python is a dominant language in data science and machine learning with libraries like NumPy, Pandas, Matplotlib, Seaborn, scikit-learn, TensorFlow, and PyTorch.
- Artificial Intelligence (AI) and Natural Language Processing (NLP):
Libraries: Python is widely used for AI and NLP tasks with libraries such as NLTK, spaCy, and Gensim.
- Automation and Scripting:
Task Automation: Python is used for automating repetitive tasks, handling files, and system operations due to its simplicity and readability.
- Desktop Applications:
GUI Development: Python can be employed for creating desktop applications with graphical user interfaces (GUIs) using libraries like Tkinter or PyQt.
- Cybersecurity:
Penetration Testing: Python is widely used for penetration testing and developing scripts for cybersecurity tasks.
- Scientific and Numeric Computing:
SciPy: Python is employed for scientific computing, simulations, and mathematical modeling using libraries like SciPy.
Why is Python so popular?
- Simple Syntax:
Python’s syntax is designed to be readable and concise, resembling natural language. This simplicity makes it easier for both beginners and experienced developers to understand and write code quickly.
- Versatility:
Python is a versatile language that can be applied to various domains, including web development, data science, machine learning, artificial intelligence, automation, scripting, and more. Its adaptability makes it a go-to choose for a wide range of projects.
- Beginner-Friendly:
Python is known for its beginner-friendly nature. The syntax is clear and easy to grasp, making it an excellent language for individuals who are new to programming.
- Open Source:
Python is an open-source programming language, which means it is freely available for use, distribution, and modification.
- Rich Ecosystem of Libraries:
Python has an extensive collection of modules and libraries, offering pre-built solutions for various tasks. These libraries, such as NumPy, Pandas, TensorFlow, and Django, contribute to the language’s functionality and efficiency.
- Active Community:
Python has a large and active community of developers who contribute to forums, discussion groups, and collaborative projects. Community support provides a valuable resource for problem-solving, knowledge sharing, and continuous learning. It also ensures that the language remains up-to-date and relevant.
- Ease of Learning and Teaching:
Python’s simplicity not only makes it easy for beginners to learn but also facilitates effective teaching. It is commonly used in educational settings to introduce programming concepts due to its readability and straightforward syntax.
Learning by Doing
This series is all about learning by doing, so be sure to actually type in the code snippets you encounter in the article. For best results, we recommend that you avoid copying and pasting the code examples. You’ll learn the concepts better and pick up the syntax faster if you type out each line of code yourself. Plus, if you screw up which is totally normal and happens to all developers on a daily basis the simple act of correcting typos will help you learn how to debug your code.
The next chapter is about how to set it up in Python on your desktop.