Python is a programming language with dynamic semantics. It’s one of the most popular programming languages used in the tech industry right now. The TIOBE index, which ranks computer languages based on usage, frequently lists Python in the top five languages.
The reason why Python is so popular is that it’s relatively easy to work with and takes fewer lines of code to accomplish tasks, compared to other languages. With Python, you can read from a website, process texts or data formats like JSON, or crunch numbers faster without much hassle. Another advantage of learning Python is that even powerful enterprise-grade software can be built with it since it is so robust.
If you're looking to get started as a Python programmer, we've pulled together the skills you'll need to learn, and how you'll apply them in the real world.
Why Do So Many Programmers Prefer Python?
Python is used for web development, software development, mathematics, and system scripting. Programmers prefer Python because of the increased productivity it affords. Because there’s no compilation involved while coding with Python, the edit-test-debug cycle is rendered extremely quickly.
It’s also comparatively easier to debug Python programs. If an interpreter discovers errors or bugs in Python, it raises an exception instead of causing a segmentation fault. There is a source-level debugger inherent in Python that enables inspection of local and global variables, evaluation of arbitrary expressions, setting breakpoints, and stepping through the code line one-at-a-time. This means that Python has introspective power, which enhances its appeal among programmers and developers.
Another reason why Python is the go-to language for developers is that it works on several different platforms, from Windows to Mac to Linux. Additionally, its syntax is easy to learn since it’s similar to the English language. It also runs on an interpreter system, which means that codes written in Python can be executed right away after being written. This feature enables the prototyping to become quicker.
What Can You Do with Python?
You can use Python for a range of purposes, which makes it a truly versatile computer language. Below are some of the powerful programming actions you can undertake with Python.
Create Web Applications
You can use Python on a server to create web applications. This is a very useful function since the trend in the tech world is shifting more towards web applications and away from desktop-based applications. Earlier, web pages used to be static, which means that their content never changed. Most websites now offer web applications with dynamic pages that can change their content in multiple ways. Using Python to run these web applications, you can choose what content to expose the user to, and which action to take, through Python code.
A workflow is a sequence of tasks, or orchestrated and repeatable patterns of activity, that processes a set of data based on rules and conditions designed by the user. Simply put, you can automate your work and sit back while the machine performs its tasks with the instructions you’ve given it. With Python, you can perform several automation tasks, such as:
- searching for text in a file or across multiple files;
- searching the web and downloading online content;
- creating, updating, moving, and renaming files and folders;
- filling out online forms; and
- sending reminder emails and text notifications.
Handle Big Data
Every organization relies on large sets of data these days. Large data sets require large databases. Python has powerful tools that can be utilized to perform database programming. MySQL, Oracle, Sybase, and PostgreSQL are different databases supported by Python. It also supports Data Query Statements, Data Definition Language (DDL), and Data Manipulation Language (DML). Another widely used Python module is the Python DB API that offers a database application programming interface for database programming.
Top Python Programmer Skills
To become a successful Python programmer, you’ll need certain specific skills. Firstly, and most obviously, you’ll have to have strong knowledge and expertise in core Python. Develop your familiarity with its various aspects such as iterators, generators, exception handling, file handling, data types and variables, and data structures.
One of the most suitable fields of employment for a Python programmer is data science. So it makes sense to develop skills in data science along with Python so that by the time you’re proficient in Python, you’re ready for the data science job market. Some of the most relevant aspects of data science include:
- good knowledge of SQL;
- ability to use Python packages like Scikit learn, MatPlotib, and NumPy;
- cleaning data;
- data wrangling;
- data analysis;
- probability theory; and
- data visualization.
Machine Learning and Artificial Intelligence
Artificial Intelligence and Machine Learning are important aspects of data science. So you’ll definitely benefit from having excellent knowledge about machine learning algorithms, neural networks, gleaning insight from data, and collection of data from various sources.
Another important area within data science is deep learning. Deep learning is a sub-field of machine learning that teaches a computer or machine how to predict and classify data by filtering inputs through layers. You’ll need to learn neural network architecture and other deep learning concepts if you want to hone your skillset in this field. This includes audio processing, video processing, and natural language processing (NLP).
Good analytical skills will come in handy when you’re building websites, visualizing data sets, optimizing algorithms while coding, and writing clean codes to eliminate redundancies. Creativity, problem-solving, and solutions-oriented quick thinking will go a long way in making you a desirable candidate for companies.
Having strong communication skills is essential since you’ll be working with a team of developers and have to be able to not only communicate your ideas to others successfully but also interpret other’s communication correctly.
Other important technical skills you should develop to become a successful Python programmer are version control, front-end technologies knowledge, integrating multiple databases and data sources into a single system, knowledge of the server-side templating language, Python event-driven programming, good debugging abilities, an understanding of code versioning tools, database schemas creation abilities, and an understanding of multiple delivery platforms.
Tools Used by Python Programmers
Before you begin to build your specialization in Python, you should get acquainted with some of the most commonly used tools by Python programmers. The following are the most basic and popular tools intended for advanced developers specializing in Python. These tools have been created keeping different paradigms in mind, such as object-oriented programming, structured programming, and functional programming. Extensions can be used to widen the scope of their functionality.
BeeWare is a toolbox that aids in developing and debugging software in Python. Each tool in the BeeWare toolbox can be used independently, which is what differentiates it from an integrated development environment (IDE). Each of these tools can perform small tasks and they can all be used concurrently yet discretely for implementing large projects in Python. The individual tools in BeeWare are Cricket (a graphical tool for running unit tests), Bugjar (used for debugging code errors), and Duvet (a graphical interface used by developers to visualize the results the coverage of tests).
This is an integrated development environment (IDE) that has an in-built graphical user interface (GUI). It is used specifically for wxPython and consists of an object inspector, a debugger, integrated help, and inheritance hierarchies. It includes several tools that function separately. These tools are used to create and debug applications built with Python. These tools are Paleta, Instructor, Editor, and Explorer. The first two tools allow programmers and developers to access objects, while the editor allows them to access the source code of the application under development. The explorer tool allows you to browse and review data items.
Kickstart Your Python Programming Career
Ready to actually build something in Python? Check out our into to Python tutorial and learn the fundamentals by creating a tamagotchi style "Pypet" (or python-pet… you’ll see what we mean). Or find a bootcamp that works for you and get programming.