Why learn Python? Year-after-year, Python is one of the most in-demand programming languages for companies. Like most popular programming languages, Python’s popularity didn’t come until years after the language was created. Designed by Guido van Rossum, Python was initially introduced in 1991. By the end of 2000, Python 2.0 was released and the language entered it’s prime because of it’s adaptability and broad use.
What’s behind Python’s popularity?
Python is one of the most loved programming languages by developers, data scientists, software engineers, and even hackers because of its versatility, flexibility, and object-oriented features. Many of the web and mobile applications we enjoy today is because of Python’s abundant libraries, various frameworks, vast collections of modules, and file extensions. Not only that, Python is great for building micro-project to macro enterprise web services as well as on supporting other types of programming languages.
Although it’s a high-level language and can do complex tasks, Python is easy to learn and has a clean syntax. Therefore, its recommendable for both beginners and experienced programmers. Also, there are plenty of ways on how to learn Python; you can do self-study, enroll yourself in coding bootcamp or school or watch online tutorials. The choice is yours to make!
The Top 7 Uses of Python
With its near perfection beauty, Python is named as one of the top-picked programming languages of most universities and industries. What makes it irresistible is it’s broad applications to other fields and limitless possibilities to create amazing things out of scratch.
A lot of its popularity is credited to the rise of AI and Machine Learning technologies in the global market. As of February 23, 2019, the average salary for a Python developer is $115,217 per year in the United States, making it one of the most popular and lucrative careers today.
Indeed, there are many reasons why you should learn Python. And to understand deeper its scope and benefits, here are the Top 7 uses of Python.
Python can be used on the following:
Multiple Programming Paradigm
Artificial Intelligence (AI) and Data Science Researches
Web Application and Internet Development
Database Easy Access, Interface Customization, and Quick System Integration
Last year, Python Software Foundation worked again with JetBrains to conduct the annual Python Developers Survey. It aims to identify the latest trends in Python web development. Over 20,000 developers participated from more than 150 different countries to help in mapping out an accurate, up-to-date landscape of the Python community.
1. Multiple Programming Paradigms
Python has the upper hand when it comes to supporting a number of programming paradigms like object-oriented programming, functional programming, empirical programming, and structured programming. Python can be used to develop both large and small applications. You can use it to engineer and produce various applications such as; game, android, multi-software and web applications. Thanks to it’s dynamic and strongly typed nature that helps in earlier error detections.
Moreover, Python has built-in functions to test variable types and proper usage. It also has automatic memory management for managing and dealing with several dynamic storage management which is useful for sharing, segmentation, preallocation or caching.
2. Web Testing
Python is the best choice for programmers in testing website applications and other related web interfaces before launching it on live sites to avoid bugs and errors. It has a built-in unit test framework called “PyUnit” that assure your code works as expected. Aside from test automation, Python unittest supports setup sharing and code tests shutdown, test aggregation, test collections, and test reporting. Its impressive string manipulation and easy shell access make it an extremely beneficial language for smooth automating repetitive tasks.
3. Data Extraction
Another beautiful feature of Python is Data Extraction or Web Scraping. It is a process to retrieve and organize data from different sources on the web and turn them into valuable ones. Python has many web scraping tools (e.g., Selenium, urllib2) and frameworks (e.g., Scrappy) that can efficiently retrieve online data or webpage content, not to mention its very robust standard library (e.g., BeautifulSoup, Requests) that can provide highly functional tools suited to do varied tasks aside from data extraction. Also, web scrapers are convenient for machine learning projects, data retrieval, SEO ranking, marketing and sales campaigns, e-commerce data collection, etc.
4. Artificial Intelligence (AI) and Data Science
Nowadays, most data scientists and software engineers use Python to conduct further studies, and researches on Artificial Intelligence (AI) and Data Science. It can be used across other domains and technologies, which is a huge advantage. It’s not surprising for it is an interpreted language; users can directly run the program without compiling data into machine language before execution. This makes Python codes comprehensive and easy to be interpreted by an emulator or a virtual machine.
Besides, it’s very explicit that it beats other OOP languages for the least code programming language. According to Cuelogic, a company that develops software globally to help startups companies, “Python has Prebuilt Libraries like Numpy for scientific computation, Scipy for advanced computing and Pybrain for machine learning (Python Machine Learning) making it one of the best languages For AI and Data Science.”
Furthermore, big data and analytics can be presented using Python’s data visualization tools. Some of the most used tools to create appealing statistical data graphs and interactive graphical plots are Pandas, Seaborn, Bokeh, Pygal, and Plotly.
5. Web Application and Internet Development
No one can deny the extent of Python’s success, not just on web applications but also in internet development. The technological advancement brought by Python applications and products changed the way we build and design things.
For example, Python web frameworks (e.g., CherryPy, Django, Flask, etc.) provide developers extensive libraries and modules which makes their work easier. It speeds up content management, database access, error tracking, function-call mapping, profiling, data authorization, and other crucial processes.
Because of its compatibility with multiple systems and platforms, Python’s popularity is most evident on application development. Here are the 16 Famous Companies That Uses Python.
6. Database Easy Access, Interface Customization, and Quick System Integration
Want to access databases easily? Python will do the job for you. Two of its strong points are allowing users to customize interfaces (like in MySQL, Oracle, Server, Durus, ZOBD, SQLite, etc.) and access other databases quickly.
Also, through Python interface connection with databases, users can observe how databases are created and edited in real time, how they can be embedded on applications and how they work on fixed records.
Moreover, Python integration and flexibility allows it to run with other programming languages. Some examples of Python implementations with other languages:
Jython – Python integrated with Java.
CPython – Python integrated with C.
RubyPython – Python integrated with C.
Python is living up to its name when it comes to cybersecurity fierceness. With powerful third-party libraries (e.g., Nmap, Yara, Requests, etc.) to choose from, it can respond to security threats faster than other languages. For example, it can run a penetration test on web application and can detect system breaches which is helpful for IT security professionals. You can even build an impenetrable application using its strong typing script, rapid prototyping and iteration, and digital forensic capabilities to avoid cyber exploitation caused by hackers.
Coding Dojo Python Bootcamps
At Coding Dojo, we offer a wide range of online and onsite courses to learn Python. Here are the topics and technologies we offer to help students become an excellent Python developer.
TECHNOLOGIES: Python • MySQL • Flask • Ajax • APIs • Django
TOPICS: OOP in Python • SQL Queries & ERD Diagrams • Web Security Basics • CRUD Operations • MVC Framework & Design Patterns • Application Deployment • Algorithms in Python • Test-driven Development