How To Get Started In Python Programming

How to get Started in Python Programming

Starting in tech can pose a lot of questions and concerns. Some of these are, what career path one should take, what programs can one start with etc. Getting answers to some of these questions could help you gain clarity. Another thing worth considering while choosing to venture into a tech career is to take out time and understand what programs are obtainable in the industry. In regards to this article, the focus will be on Python.

Introduction to Python

According to Wikipedia, Python is a general-purpose programming language. What this simply means is that it can be used for a wide range of software development (applications, machine learning, mobile apps, etc.). This in turn informs why it is super popular among software developers. It is also one of the easiest programming languages a beginner can get into. So if the last statement describes you, you have very little to worry about. Python libraries provide beginners or just about anyone regardless of their level of competence with loads of solution-based approaches to any Python-related challenge. In summary, to understand what Python is all about, keep the following in mind. It is a free open-source programming language that is easy to use and can perform a wide variety of programming tasks.

Pros and Cons

You have gotten a bit of background on the programming language known as Python and it will be a healthy assumption to assert that you have heard about other programming languages. You might feel undecided as to which could be the right fit for you starting. That decision is entirely yours to take but it would help to know what makes Python stand tall and where it falls short among its peers, should you decide to proceed.

Pros- 

-It is free and it is an open-source programming language – Just like Java, C++, C#, Python does not require a license agreement to use and due to the large community of developers that use it, anyone can improve it. Hence it is open source. As long as your system meets the minimum requirement, you can hook it and you are good to go.

-Multipurpose use – If there is anything that should get you excited about Python, it is this particular feature. Python is widely known for its versatility. From web to mobile to machine learning, python takes on it like your favorite meal. In addition to that, python offers a much easier learning curve than its counterparts, which makes it very ideal for beginners.

-Huge Community Support – As a newbie, the tendency to feel lost and overwhelmed can be frustrating. Python has gained massive popularity with software developers and thus has created a huge community. This community boasts of a level of comfort in the relatively known that will make any newbie feel at home. The community members offer support and know-how to challenges any Python developer at any level of their career may face.

-Massive Libraries: As far as Python goes, it keeps getting better. Imagine having access to an enormous amount of resources, so massive that one could get lost in while trying to improve yourself. This can only be possible because of its claim as the most widely used and versatile programming language.

-Works well for creating prototypes – Because of how significantly easy Python is to learn, it makes it ideal for building prototypes. After which you can scale your project on any other programming language. This is very important for startups trying to bootstrap a project or operating on lean resources. 

Fun Fact: Pinterest, Disqus, Spotify, Dropbox, Uber, and Instagram to mention a few were built on Python with the help of the Django web development framework.

Cons

-Some of the major uses of Python include; AI and Machine Learning, Web and game development, Language Development, Data Analytics, Data Visualization, SEO, Design, and even Finance. 

-AI and Machine Learning: Starting with Python as a beginner and you want to try out with Machine Learning? Do not get overwhelmed too quickly by trying to consume too much information before trying things out. You should as a beginner be willing to take on small end-to-end projects to build your confidence. By applying machine learning to your datasets, you are building your projects.

According to Machine Learning Mastery, try taking these steps such as; defining the problem, preparing data, evaluating the algorithms, improving the results, and presenting it. They further stated that the best way to come to terms with a new platform or tool is to work through a machine learning project end-to-end and cover the key steps. Namely, from loading data, summarizing data, evaluating algorithms, and making some predictions. If you can successfully do that, you have a template that you can use on dataset after dataset. You can fill in the gaps such as further data preparation and improving result tasks later, once you have more confidence.

-Programming Languages – Before you proceed, you need to understand that this part is not for newbies, but if you have time to spare and the grind for extraordinary work, please jump on it. Aadit Ambedkar decided to create a simple programming language using Python. He called it TEN for Father’s Day and here is how he did it. After installing Python obviously, he installed Python packages that allowed him to convert Python files to exe. You can get a step-by-step procedure here. He then proceeded to create a stack-based programming language, which simply means a programming language built on a stack. The next step he then takes is to create a Syntax, which are rules that define a programming language. He goes on to describe his next actions;

“We need to open up the file containing our CUSTOM script. But, before we open the file, we need the file name. If you have ever compiled a Python script, you know the command you type is python <filename>.py. What we are doing is passing in the string <filename.py> to python.exe, and then python.exe is compiling that file. Python allows us to compile Python files with additional arguments passed in: python <filename>.py arg1 arg2 …. arg1, arg2, … are then passed into our Python script, which can use those arguments. To access those arguments, we use sys.argv. sys.argv is a list containing each additional argument. For the time being, we will just have 1 argument passed in, the file name of the CUSTOM script”. You can read all about it here.

Now, these two areas are just highlights of what Python can do for you, there are no methods that are cast in stone but there are principles to applying the knowledge you gain to build up experience for you. To help with that, here are 6 top sites to learn Python; Udemy, Coursera, Google’s Python Class, Microsoft’s Free Python Class, and Codecademy.

Salary Average of Python Software Developers – According to Indeed.com, the average salary of Python software developers around the world varies. For the US, it is around $110,311. In the UK, it is around £65,000. In Canada, it is around $95,000. In Nigeria, the going rate between entry-level and midlevel is around $3,213 – $11,100. Sorry did that make you cringe a bit? Look on the bright side, soon enough you could earn like your foreign counterparts. Of course, this will happen, if and when you choose to migrate.

Relevant Books that can give you a significant head start as a Python developer according to Hackr are:

Python Crash Course by Eric Matthews

-Automate the Boring Stuff with Python

-Learning Python

-Headfirst Python

-A Byte of Python

If you have read this far, how has your perception improved about taking on Python? 

One last nudge to help you over the decision curve. According to Springboard.com, the future of Python looks bright in 2021 and beyond. So get ready to take on 2022 with all the confidence of a mustard seed. Take that course, get that Python certification, and build projects. Your employers and the world are waiting for you.