Python is one of the most popular programming languages that needs no introduction. In the past couple of decades, we have witnessed a significant level of evolution and advancement in the technological world. And it won't be wrong to say that Python has contributed to this evolution in monumental proportions.
Almost every developer today is opting for Python, and there's a good reason for it. In fact, there are "many" good reasons for it.
From Artificial Intelligence and Machine Learning to Data Science, Python suits almost every requirement and is hence so popular among developers.
Python is an extensively used, object-centric, interpreted, and high-level programming language with robust semantics. Guido van Rossum was the creator of Python, and he initially released the programming language on February 20, 1991. Now let's see what makes Python one of the most preferred choices in its realm:
Learning Python is an arduous challenge for some, while it is a piece of cake for others. But what's that one thing that differentiates the two groups? The most important thing is that the people successful at Python follow a set of sequences or a roadmap that others don't.
The roadmap to learning Python in 10 Easy Steps:
To begin with, you must first make it absolutely clear why you want to learn Python. Most individuals today turn towards Python by envisioning its potential and future growth. A few may decide to take up learning Python as a hobby or to stack it on top of their existing skills. Regardless of the reason, you should pen down why you want to learn Python and how you would implement your learnings in the near future. People don't pursue something unless they want something out of it. Also, writing down the reason why you're pursuing Python will also serve you as a source of motivation whenever you're feeling low or worse, deciding to quit.
When you have a powerful WHY or a stronger sense of purpose for pursuing something, it's very difficult for you to get off track and lose motivation. Many successful people and organisations follow the practice of acknowledging the WHY behind their work and then working towards it with a different level of enthusiasm. This not only makes the entire journey more exciting but also increases the chances that your efforts will come to fruition sooner rather than later.
Most developers get overwhelmed and nervous when they take a glance at the coding libraries and frameworks that seem complex at the beginning. Due to this, they create a perception that Python is difficult, it's too complicated, or it's beyond my capability. But almost all the time, these perceptions are fallacies. You don't have to learn each and every component of Python in one day. The best way to approach Python, or any other programming language for that matter, is that you should start with the fundamentals first. When you start by learning the fundamentals while eliminating all the fluff, you find that it is not that difficult. In fact, it is much easier than it seems. But if you do it the other way around, by learning about each and every component or the equivalent thereof, you end up feeling overwhelmed.
So the next time you switch on your computer to start with Python, ask yourself: What are the fundamentals? When you finally get the answer to this question, you'll realise that there are actually very few things that you need to focus on. Compound data structures, data types, conditionals, loops, functions, object-oriented programming, and libraries are some of the most common fundamentals of Python.
Now, you are at the point where you've written down your WHY and you're almost done with learning the fundamentals of Python. Now what? The last two steps are almost useless if you don't take action and start coding. Studying something in theory and implementing it in real life are two different worlds. Even though this sounds obvious, it is worth mentioning. When writing code, ensure that it is readable and understandable. Of course, if the hiring manager is viewing your code on GitHub, he or she needs to comprehend what you’ve done. In any other case, it would deteriorate your chances of getting shortlisted.
Consistency holds the centre stage when it comes to learning a new programming language or a new skill. No matter if your schedule is too hectic or if you have a good amount of time, make a habit of coding daily. Commitment towards learning Python is only possible if you show up daily and code on a regular basis. Muscle memory plays a significant role in learning programming. It develops patterns while you learn and helps you remember them the next time you code. Devoting a certain timeframe to coding on a daily basis will almost assuredly develop your muscle memory.
Although it may look intimidating initially, you can begin by coding for just 20-30 minutes daily and gradually accelerate as you gain momentum. The quality of your results depends on how consistent you are regarding coding.
Making explicit notes keeps you involved and active in the learning process while helping you avoid distractions. It also engages your mind and helps you organise information. As you make notes, you can understand what you were doing wrong and what you were doing right. This aids you in deciding and highlighting the key points while also making you recognize your weaknesses so you can improve. Organized notes serve you as a link between the code that you are planning to implement and the results that you're receiving. Notes make a distilled record for study, to which you can refer whenever you want. A set of distilled and concise notes from each coding session offers what you need to focus on, and review after coding. Research recommends that taking notes in a hand-written form is one of the most advantageous things you can do for long-term retention. This will be particularly beneficial for developers having the objective of choosing full-time development as a profession, as most interviews will require writing code on whiteboards.
Whenever you commence working on small programs and projects, writing by hand can help you with constructing your code before you turn to your desktop. You can save a substantial amount of time if you hand-write necessary functions and classes as well as how they will work out.
When you are in the learning process, it is crucial to take a step back and let the concepts infiltrate your mind. Productivity techniques like the Pomodoro are extensively used to boost productivity. Taking generous breaks is important for having effective coding sessions, especially when you are learning at a rate that you're usually not accustomed to.
Breaks are immensely beneficial when you are working on debugging. If you find a bug and can’t get to the bottom of what is going wrong, consider taking a break. Leave your computer for a while. Stretch a bit, go for a brisk walk, drink water, or just close your eyes and relax. This will definitely make you feel better and provide you with new energy.
Programming is a detail-oriented task and thus your code should specifically follow the conditions of the language and logic, as missing a small quotation mark can shatter everything. Hence, taking a break can revitalise and calm you so that you can work more efficiently.
Learning a programming language like Python may make you feel like you’re sprinting as fast as you can but aren't getting anywhere. The moment you feel like you have learned something, seven more things show up from nowhere. But when you track and evaluate your progress, you are able to concentrate on things that are really valuable and it helps you adapt. This reduces or even eliminates the barriers that may arise in the upcoming period. When you track your progress and reverse engineer, you are able to break down large targets into smaller steps, making the entire journey seamless. It also lessens the probability of failure. Without regular tracking of what and how you are working, you are unable to understand if the actions you are taking are really worth the effort.
For developers who are just starting out, there are many simple activities that can help you become skillful with Python, along with developing the muscle memory that we alluded to above. When you have a strong grip on fundamental data structures (lists, strings, sets, dictionaries), and object-oriented programming, it’s time for you to start building something.
How you build something is way more important than what you build. The process of building is really what will develop your knowledge base, viz. Python. You can learn as much theory as you want by reading Python blogs and articles. But your learning will be fruitful only while using Python to develop something. The solutions that you will build for specific problems are the real sources of learning.
There are many projects that you can experiment with. Check this source to discover projects (along with source code) that you can work on, whether you are a beginner or a seasoned developer.
Coding may sound like a lone wolf task, but it reaps the most benefits when you collaborate with other fellow developers. It is really important to surround yourself with folks who are learning Python. This will allow you to trade small tricks and tips you learn during the journey.
The internet has a plethora of opportunities for developers like you to connect with other individuals who are passionate about learning Python. You can find a bunch of communities on Facebook, Reddit, LinkedIn, and other platforms that will help you enhance your Python skills.
You can search for others' repositories on GitHub and contribute to their projects. This represents that you have the expertise it takes to be a collaborative team member by adding more value to existing projects.
Some of the most famous open-source Python projects you can contribute to are:
Pipenv: Python Development Workflow for Humans
Chatistics: Python scripts to parse your Messenger, Hangouts, and Telegram Chat Logs into DataFrames
Som-tcp: Solving the Traveling Salesman Problem using Self-Organizing Maps
Py2bpf: A python to bpf (Berkeley Packet Filter bytecode) converter
Python is a programming language that was valuable, is valuable, and will continue to be valuable for the future's technological growth. From small businesses to multi-billion dollar conglomerates, Python contributes to every segment of the economy. Artificial Intelligence, Machine Learning, and many such relevant domains need a pragmatic programming language like Python.
Hence, learning Python would enable you to cater to the future of technological evolution and will help you foster your career at the same time. Follow the steps given in the blog below to learn Python efficiently and share this blog with someone who aspires to be a Python developer. It will surely provide them with valuable insights on how to learn Python in the best way possible.