Tips for Beginners on Learning Python
<h2>Choose the Right Python Version to Learn</h2>
When starting to learn Python, one of the first decisions is which Python version to focus on - Python 2 or Python 3. As of 2020, Python 3 is the recommended option for beginners. Python 2 will no longer be updated and supported after 2020, so it's best to avoid older Python 2 tutorials and resources. Python 3 introduced significant changes like making print a function and improvements to object-oriented programming. Most Python code today utilizes Python 3 syntax and features.
<h2>Use Online Tutorials and Courses to Start</h2>
As a beginner, online tutorials and courses offer the most convenient way to start learning Python. Platforms like CodeAcademy, DataCamp, LinkedIn Learning, and Udemy have extensive Python programming courses for all levels. These interactive courses provide web-based Python compilers so you can try coding examples right inside your web browser. This hands-on practice as you learn is invaluable. You can also find great free introductory resources on YouTube channels like Corey Schafer and freeCodeCamp.
<h2>Learn Python Syntax and Variables</h2>
When first starting out in Python, get familiar with basic Python syntax and structure. Unlike other languages like C++ and Java, Python doesn't use curly braces to delimit blocks of code. Instead, Python uses whitespace indentation to indicate scope and code blocks. Pay attention to properly indenting with either tabs or 4 spaces when coding in Python. This whitespace requirement helps make Python very readable.
You should also learn how to declare and use variables in Python. For example, initializing a variable is as easy as writing my_variable_name = value. The convention is to use lower_case_with_underscores for variable names. You can reassign variables to new objects later in your code too. Python is a dynamically typed language, meaning you don't need to declare variable types. The interpreter will infer the underlying data type automatically.
<h2>Understand Basic Data Types like Strings, Integers, and Booleans</h2>
When first getting started in Python, it's important to understand some of the basic data types you will be working with most frequently. For example, to represent text and string data in Python there is a str class. You can use single, double, or triple quotes around string values. Integers like 0, -1, 1 are treated as int objects. Floating point decimal numbers get classified as float data types in Python. You can write expressions with mathematical operators on these number objects. Logical or truth data types are represented by the bool class, which can hold values of either True or False. You can build more complex data structures by composing these primitive built-in types.
<h2>Use Operators, Branching, Loops and Functions</h2>
Mastering the basic building blocks of Python programming will equip you to start writing scripts and programs. Operators in Python like +, -, *, / allow you to perform computations and execute math logic in your code. Branching statements like if-else let you codify decision trees and branching logic. Loops structures like for and while help you repeat tasks iteratively. Functions empower you to break apart code into reusable blocks that abstract complexity into descriptive names. Writing your own functions by using the def keyword is key. You can have functions accept input arguments and return output. Functions structure code organization and decomposition.
<h2>Practice Everything by Coding Simple Programs</h2>
With the fundamentals covered, practicing writing actual Python scripts and programs will test and reinforce your understanding. Trying basic coding exercises like odd/even detection, prime factorization, fibonacci sequence generation, or number guessing games allows you to apply what you've learned. Start by flowcharting the logic on paper, then translate it into actual Python code. Use scaffolding tools like comments, parameter names, and good structure to craft clean, readable code. The key is tackling small simple projects first before attempting complex code. Slowly ramp up program sophistication over time. Hard-code values first before introducing other inputs.
<h2>Learn how to Debug and Troubleshoot</h2>
An essential skill for any aspiring developer is debugging abilities. Bugs and runtime crashes are inevitable when writing code. Learning systematic debugging approaches separate coding amateurs from professionals. Best practices dictate adding print statements in code to inspect variable values to isolate issues. Using built-in Python exceptions and traces can also surface helpful context clues. Trying code in a Python interpreter prompt first aids in incremental testing. Leveraging IDE debugging features like breakpoints, watches, and step execution should become part of your debugging knowledge repertoire as well. Debugging discipline helps train the critical troubleshooting muscles all coders need.
<h2>Use the Python Standard Library and Modules</h2>
While Python's standard library may seem unexciting compared to trendier third party packages, it contains very useful modules to learn. For example, Python's csv module can parse and process CSV data. Object serializers like json and pickle convert in-memory objects to convenient text formats. Math modules have extra numerical and statistical functions missing from the basic math package. Unittest provides a testing framework to build test cases against your code. Modules like datetime, time, os, sys, and subprocess assist with system tasks. Random and string generate test data. IO handling code lives in modules like fileinput and StringIO/BytesIO. Always check standard library docs to avoid re-inventing existing functionality.
<h2>Explore Third Party Packages like NumPy and Pandas</h2>
While Python's out-of-the-box standard library offers much useful functionality, the true power of Python shines through third party packages and frameworks. NumPy introduces high-performance multidimensional arrays and mathematical functions tailored for scientific computing. Pandas provides versatile data structures and analysis tools for data science and analytics. GUI packages like Tkinter ship built-in with Python, while PyQt offers more customizable UI development features. Web frameworks like Django and Flask facilitate easier web application development. Natural language processing toolkits like NLTK handle lingustics processing capabilities. The Python Package Index (PyPI) offers over 200,000 additional libraries to explore as you expand your programming skill set!
<h2>Build a Project to Apply Your Skills</h2>
Once you establish basic proficiency in Python, you should test your abilities by coding an end-to-end project. This allows you to apply all the foundational building blocks in unison - variables, data types, branching, loops, functions, etc while structuring deliverables. Ideas include simple games, web scrapers, productivity tools, machine learning algorithms, mobile apps, etc. Start by stubbing out the steps involved before implementing iteratively. If you only understand Python basics in isolation, it will prove challenging to assemble them into complex programs. By simulating real development environments, you train your brain to systematically break down and solve programming challenges using Python.
<h2>Never Stop Learning - Python has Great Depth</h2>
Even after progressing from a coding novice to an intermediate Python developer, recognize there is always more to learn. Python is an incredibly vast language spanning web development, data science, artificial intelligence/machine learning, scientific computing, and scripting. You need to continually expand your Python knowledge repertoire to unlock its full potential. This means developing code regular to retain existing skills. Additionally, exploring new Python libraries exposes additional possibilities. Subscribe to Python newsletters and developer communities to stay aware of the latest advances. Signing up for an annual Python conference also accelerates learning by networking with other Python devotees. A lifelong commitment to learning Python unlocks unlimited possibilities.