Python for Everyone: Mastering Python the Right Way
Published: 2022-03-02 16:23:44

**Python for Everyone**

Admittedly, Python is not my first language. As a natural result, my transition from other languages to Python have been extremely easy, considering the latter's ease of use, and memorability, in comparison to other languages. It's massive gain of popularity in recent years is no coincidence, and is actually a consequence of the perks I have mentioned, along with being beginner-friendly, yet also doubling up as a strong asset in more complex solutions such as big data analytics. At one point or another, all of us have had to break into something new- a career, a project, owning a house, or whatever it was. The consistent underlying theme is that unchartered paths are seldom easy, and can be very confusing for a beginner, so if you are going through that chaotic space, this is the article for you. And if you are not, this might just help you carve out a better stance for mastering python the right way.

**An Overview of Python**

Python is a high-level interpreted language that was created by Guido van Rossum, and named by Rossum after _Monty Python's Flying Circus_, a BBC comedic series of the 1970s. Perhaps due to its recent popularity, many people think Python is a new programming language. Contrary to this, Python was actually first released in 1991, and is even older than traditionally "old" languages such as Java. With the rise in needs such as programming in data science and machine learning, python has provided an easy go-to, for people not trained as programmers to get started. Additionally, older versions of Python could not address specific domains as competing languages could. Take for example Django, a python web-framework, which was created more than a decade after the release of python to simplify web development. However, as we move towards an automated world, where coding has become a sought-after skill, you cannot hate Python, as it provides an easy way to get started with programming. Now, how should you approach it?

**Python Learning Steps**

It is easy to get caught up in the vicious cycle of wanting to learn everything at once, but it is very important to not succumb to this temptation. One, because it never works, and two, it could leave you extremely disoriented. Instead, start small:

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## 1. Create a learning path.
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There is a lot to learn before you will have complete mastery of the language, and although this may seem daunting, it is no rocket-science. It is doable.

First, learn the basics. Create your "hello world" program in python, and if you are past the beginner status, look into the **variables, data types, keywords, identifiers, operators and built-in functions** (excluding print) that you can use regularly, and have those at your fingertips. After the fundamentals, examine real-world problems and be able to see how you can convert the normal human thought process and decision making, into codable language, such as **sequential processing, flow control,decision making with loops, relational operators,** and **boolean operators** in python.

Next, make sure you have your **data structures** to a T, because what's the point in knowing them theoretically if you are unable to implement them when and as needed? when you feel comfortable with data structures, both **user-built and pre-built**, make your way to **algorithms**, and deploy them in a way that makes your data structures exploit their full capability.

At the instance you can comfortably apply data structures practically in real-world use cases, it is time to have a deeper look into **functions**. Pre-built functions are there so you don't re-invent the wheel, and waste valuable coding time, but Python also allows for you to build your own functions to match unique use-cases. So look into this, while paying attention to the **scope** of each function, what **parameters** are, and how to use them, **recursive** and **lambda** functions, and decorators in python.

As Python is an Object Oriented Language, it uses **classes**, which allow for inheritance, and other features that make the language quire remarkable. Here, look into defining classes, using classes to create objects and instance data, using **constructors** to simplify coding, and how to use **class methods**.

After fully grasping the idea of classes in Python, move steadily to **errors and exception handling**, including the use of **try/catch/else/finally** to handle exceptions, look into ignoring exceptions, and explore the wide array of errors, such as **syntax, logical** and **semantic** errors, that will make you a better and faster programmer in the long-run.

You then have to be comfortable to **work with files**, such as opening, reading, and writing a file using Python code, and further look into **modules and packages of python**, **Regular Expressions** in Python, and finally, **Network Services**.

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## 2. Practice! Practice! Practice!
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That seems like a long list, but that is why I emphasize on taking small but sure steps. It is possible to build on becoming a better programmer by using the resources around you- YouTube has especially worked magic for me, by giving me a chance to improve my skills and learn a little of everything everyday through projects. Once you learn the basics, data structures and algorithms, I believe you are unstoppable. So take up those projects, and when you are stuck, Google is your best friend! Use Stack Overflow as a tool to learn, and not to just copy and paste code. And if you prefer reading to watching tutorials, you can always get yourself a copy of texts such as _Learn Python the Hard Way_ (It is a good one, don't mind the click-bait title). 

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## 3. Final Perspective
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In trying to become a master, you should be prepared to make and embrace your mistakes. Because after all, a master is only a master because they made mistakes, used those to make learning strides, and implemented this knowledge in avoiding mistakes. 

Rather than working your boots off trying to be master, however,  focus on gaining understanding, proficiency, and excellence in applying fundamental Python principles. I say this because although I understand that Python still has a long mileage to cover, any language has its hay days, and bad days. But if you master the fundamentals, and underlying principals, those are often consistent and can be shifted from one language to the next- Those are the things that remain steadfast even as tides change, and they will ensure you are competent for years to come.

Good luck, and happy coding!