How to Become a Python Developer

How to become a Python Developer?
How to become a Python Developer?

With every industry or business focusing on integrating new technologies such as AI, ML, and data science, Python developers’ need increases exponentially. For the last one-decade, Python has become very popular amongst the Computer Science communities, and because of market demand, there is a surge in Python Developers. Python is popular among developers because it supports many IDEs, frameworks, APIs, and libraries for development in the AI, data science domain. If you are new to Python and want to see your career designation as a Python Developer in that case, you are reading the right article. The article mentions everything you should know about How to Become a Python Developer and the required skill set.

Who is a Python Developer?

Who is Python Developer
Who is Python Developer

Before we jump to the meat of this article, let’s look at a vague definition of Who is a Python developer? — “A Python Developer is a person who uses Python Programming language to build, deploy, implement or debug a project.”. This definition of Python developer is right, but it does not cover all the aspects of being a Python developer. According to this definition, even a complete beginner who just has learned how to write simple syntax in Python is also a Python Developer. However, he/she can call himself/herself a Python Developer, but there is a lot in Python we need to learn before we call ourselves a Python Developer. I have mentioned all the necessary skill sets (technical and non-technical) to be a Python developer. Let’s read them below.

Python Programming Language

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Python is a high-level Programming Language, and like other high-programming languages, its code and syntax are human-readable. Programming in Python feels like you are writing some line by line instruction for a program. Its syntax is so easy even a non-programmer can understand what the code is trying to say.

The object-oriented language was developed by Guido Van Rossum and released in 1991 to write a clear code for all project sizes. Python supports multi-paradigm programming, including functional, imperative, structured, reflective, and object-oriented programming. And among these five paradigms, object-oriented is the major one because right now, the developers widely use OOPs concepts to solve real-world problems. OOPs, provide concepts like class, objects, inheritance, polymorphism, abstraction, and encapsulation, which can be used to represent and solve real-world entities.

As I have already mentioned, Python is a high-level programming language, but computers cannot understand the code written in high-level, so it requires a translator. A computer translator is a software program that converts the high-level programming code to a low level so the computer can execute it. There are three types of translators: compiler, interpreter, and assembler. Python uses an interpreter as a translator tool to convert its high-level code to a low level and execute it.

Why Learn Python?

Python is loved by most programmers, data scientists for its versatility, and object-oriented features. As discussed earlier, it has a huge demand for building AI and ML-based applications; apart from this, it also serves many web and mobile application industries. Although there are a plethora of reasons to jump into learning this language, let us briefly see them here below:

Features of Python Programming

Here are some Python programming features because you should know what makes Python a globally popular programming language.

  • Easy to write Code: Python is the foremost programming language with the easiest coding syntax. You do not need any prior programming language to write code in Python.

Python Developer Skill Sets

If you use Python to write, debug, deploy, and test your program, model, or application, you will be considered a Python Developer. Python is a versatile language, and there are various Job roles and domains associated with this robust programming language. For example, using Python, you can be a software developer, web-developer, data science engineer, AI, ML engineer, or a deep learning engineer. It does not matter in which domain you use Python; you will be designated as a Python developer. But some technical and non-technical skill sets distinguish your Python developer role in the IT industry.

Let’s look at all the technical and non-technical skill sets you require to become a Python Developer.

  • Core Python Programming

Core Python Programming

It does not matter what job-role or domain you want to associate with in the future. You need to be an expert in basic or core Python programming. Whether you are looking for a Python web-development or Python data science career, you need to go through core Python programming. If you miss this phase of Python or ignore some of its essential concepts, then you will be finding Python as the most daunting and complicated programming language to code with. Because it’s only the core Python, which has easy syntax, as you move further to advance concepts, Python becomes a tricky language. Only those who are well acquainted with its basic concepts can code well in Python.

Technical Skills

  • Python Variables and Data Types (int, float, str)

Non-Technical Skills

  • Basic Math Knowledge

Python Web Developer

Python is well known for its powerful web-frameworks. A web-framework is a tool that is used to build a web application. Django and Flask are the two most popular Python frameworks, and with more than 52K stars on GitHub, Django has become the second most starred web-framework repository. To become a Python web developer, you should possess the knowledge of any Python web-frameworks with the front-end trinity HTML, JavaScript, and CSS. Apart from these technical skills, a web-developer is supposed to know all about servers and networking.

Technical Skills

  • Core Python Programming

Non-Technical Skills

  • Basic Mathematics

Python Data Science Engineer

For the last five years, Python has been widely used for data science projects and models. With core or standard Python, we cannot create complex data science models, but luckily Python has many open-source libraries. Data Science deals with a massive set of data. Here, programming skills are not enough; one needs to be well acquainted with high-school mathematical concepts like statistics, applied math, probability, algebra, etc.

Technical Skills

  • Core Python Programming

Non-Technical Skills

  • Basic Math Skills

Machine Learning and AI with Python

Both Machine Learning and Artificial Intelligence are the submodules of data science. If you want to be associated with these two technologies, you have to be an expert in machine learning and data science algorithms. Fortunately, Python has a myriad of ML and AI libraries that comes with built-in ML algorithms. In ML and Artificial Intelligence Engineering, you will rely more on your Mathematical and Non-technical skills than your Programming.

Technical Skills

  • Machine Learning Algorithms

Non-Technical Skills

  • Expert in Basic Math

Deep Learning with Python

Deep Learning is a subfield of machine learning, so to be efficient in deep learning or to become a deep learning engineer, you have to go through machine learning. Deep Learning requires you to be fluent with all the Python machine learning libraries and artificial neural networks.

Technical Skills

  • Expert in Python Core Programming

Non-Technical Skill

  • Expert in Basic Math

Python Basic Data Structures

Whether you want to build a web-application or a data science model with Python, you first need to learn basic concepts and syntax. And the first step of learning a programming language starts with learning its basic syntax and its built-in data types.

Let’s look at all the Python primitive variables, built-in data type, and syntax and try to get an overview of the language.

Variable in Python

The concept of variables in Python is similar to the variables we use in mathematics. Variables in programming languages are also known as Identifiers. A variable is a container for a data value. To represent a variable in Python, we use an arbitrary variable name with a data value.

Example

x = 100

Here x is the variable name, and 100 is the variable data value.

In the above example, we used an arbitrary variable name x, but there are 33 reserved keywords in Python, which we can not use as a variable name.

Python Reserved Keywords

  1. and

Python Built-in Primitive Data types

There are 4 Primitive built-in data types in Python

  • int (integers numbers)

The int data type represents the integer numerical values with no decimal numbers.

Example

>>> x = 100
>>> type(x)
<class ‘int’>

The float data type represents the decimal points number values.

Example

>>> y = 100.23
>>> type(y)
<class ‘float’>

The str represents the string value, and all the string values can be defined using single or double-quotes.

Example

>>> string = “Hello World”
>>> type(string)
<class ‘str’>

The bool data type represents the True or False value.

>>> z = True
>>> type(z)
<class ‘bool’>

Python Non-Primitive Data Structure

There are four major Python inbuilt non-primitive data structures

  • list

A list is mutable and ordered Python data structure.

Example

>>> my_list = [1, “two”, 3.0, False]
>>> my_list
[1, ‘two’, 3.0, False]

A tuple is an immutable and ordered Python Data structure

Example

>>> my_tup = (1, “two”, 3.0, False)
>>> my_tup
(1, ‘two’, 3.0, False)

A set is a mutable and unordered Python data structure which only store unique data.

Example

>>> my_set = {1,1, “two”, 3.0, False}
>>> my_set
{False, 1, 3.0, ‘two’}

A dictionary is a mutable and unordered Data structure which store data in key-value pair.

Example

>>> my_dict= {1:”One”, 2:”two”}
>>> my_dict
{1: ‘One’, 2: ‘two’}

Python Libraries and Frameworks

The standard Python is a minimal language and does not offer developers many things to work with. But all thanks to Python open-source libraries and frameworks, which make Python the most significant programming language.

Python comes with a built-in package manager “pip,” a terminal command capable of installing, updating, and uninstalling Python libraries. The reason behind Python’s versatility is its libraries and framework. Python has libraries for almost every IT domain. From web-development to deep learning, you can find the perfect library for your Python Project.

Here is a list of Top Python Libraries and Frameworks

  • TensorFlow (library) (Machine Learning and Data Science)

Python Projects

Learning a Programming language is one thing and building a project using what you have learned is entirely different. Many new developers focus on learning new Python syntax and libraries rather than doing a project, which is not recommended unless you master what you have known before. If you are done with core python, before moving further and learning a new Python library, build some projects to scale your learning. When you build a project or a small program on what you have learned, you find out what you have learned so far and how you can use the basic concepts and data structures to build logic. Because learning any programming language syntax is not what companies are looking for, a developer must know how to build a project and, more importantly, solve problems using coding and logic.

To help you begin with, below is a list of Python projects based on levels:

Core Python Projects (console-based)

  • Hangman Game

Python Web Developer Projects (Django, Flask)

  • Sending Mail with Python

Python Data Science and Machine Learning Projects

  • Fake News Detection Model

Conclusion

To be a Python developer, you just need to keep upgrading your Python skills with time and keep working on Python projects. It would be naïve to call yourself a Python developer only by learning basic Python concepts. Python is an ocean of unlimited opportunities and libraries, and it has something for everyone and every domain.

I am a professional technical content writer with expertise in writing about programming, cloud, DevOps, Data Science & AI, and other emerging technologies.

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