Why Python is awesome, its applications and advantages
Python was developed by Guido Von Rossum in 1989.
Since then, It started developing itself and won the love of developers. Now it is in lead for the title of most popular programming language.
What is so special about Python?
- Python is super easy to learn.
- Its syntax resembles very much to English language which enhances code readability.
- Its a high level language. It takes fewer lines of code.
- It is dynamically typed, you don’t have to declare data types. Python does it for you in runtime.
- It is an Interpreted language, you don’t have to first compile the code and then run it. You just run it, all the debugging is done in run time.
Less development time, huge community and a variety of libraries is what make python a must go option.
Who uses Python?
- Python is one the server side languages at Google. C++, Java and Go being other preferences
- Instagram is completely built on Django, most popular backend framework in Python.
- Spotify and Netflix uses Python for data analysis and backend services.
These are to name a few. Python is continuously growing expanding its kingship. If you want more.
What can i use Python for?
You will be really shocked and believe me, it’ll be an instant love.
Web development
You can built web applications at a rapid rate. Few of frameworks are Django, Flask and pyramid. Django is so abstract and high level that brings everything a developer needed onto to the table. On the other hand Flask is actually a mini-library. In Django you to do the Django way but Flask offers more customisation.
Game development
You can built interactive games in both 3d and 2d. Pygame, PyKyra, Pyglet are few frameworks for game development in Python.
Few top games that uses python(not entirely built using python). Battlefield 2 uses Python for logic and server controls. World of Tanks , Eve Online and Sims 4 uses Python for side tasks. Not every game is completely built using a single language. Game development need languages to talk to severs, hardware and other data analysis functionalities as well. Python is not that great for game development but its place for side tasks cannot be neglected.
Machine Learning and Artificial Intelligence
AI is something of a buzzword these days, but the truth is that it all comes down to algorithms, code, and logic. All new startups want to include AI in their projects in one or the other way, or just for the name sake. Because “AI included” gives a different weightage to that product. With AI constantly growing and being developed it is opening a huge market for AI experts. With AI possibilities are limitless.
“AI is likely to be the best or worst thing to happen to humanity” — Stephen Hawking
AI has such power and python is most preferred language as it makes building the logic and model much simple and easier. Scikit-learn, machine learning library in python makes is easy to build classifiers and models. Tensorflow and Keras are used in building neural networks.
Data science and data visualisation
Data is wealth. OK… what data am I talking about. Assume, You run a blog site. You are getting good traffic and earning well. You have following data of users from different parts of the world. Age Group, location, preferred content and time of usage. If you could analyse this data and provide what the user wants instead of general suggestions. Don’t you think user traffic and user opinion will be positive. Data is huge, you can’t manually go through those data. This is where Data science comes in.
Data structures and libraries provided by Python makes data processing and analysis easy. Pandas, Numpy and SciPy are libraries for data processing. Graphical representation of data gives better understanding of data. Matplotlib and Seaborn are few libraries for data visualisation. If you can see the application of Data Science, then you should be able to understand why there is a lot of demand for data science engineers.
Data Science is a huge domain, Machine learning is used for making prediction and business modals.
Computer Vision and Natural Language Processing
The technology that makes self driving cars possible is computer vision. Chat bots are possible because of natural language processing(NLP). Computer vision is not only used in self driving cars. It can used anywhere where a camera or some sensor to 3d map is involved. Combined with machine learning possibilities are limitless. Face recognition, self driving cars, in manufacturing line to detect faulty products, medical diagnosis, transportation, character recognition, object recognition and the list goes on.
OpenCV is a great library for computer vision in Python.
NLP is the processing of training computer to understand the language we humans speak naturally. It’s applications are text classification, sentiment analysis etc. NLP changes the way we interact with machines. If we could talk to them like any other human being, we would never have to use our fingers to interact with them anymore. Its cool right…
Nltk is used for Natural Language Processing in Python
Computer Vision and NLP gets its true from Machine learning.
Desktop and Mobile Application development
Python provides many libraries for development of Desktop and Mobile applications as well. PyQt, Tkinter, WxPython and Kivy are few of them. If you want to use python everywhere you can go with these libraries. We don’t get to see much of the well known applications built using python but here are list of application built using Wxpython. Mobile apps can be built using Kivy. Kivy is a cross platform application development toolkit that runs on Linux, Windows, Mac, Android, IOS and Raspberry Pi. Here is a list of apps built using Kivy.
Web Scraping
If you could gather the data from other websites and make necessary changes and strategies to your business modal. Data you would want to extract are social media sentiments, E-commerce price comparision, Investment analysis, job listings, etc. One way is, you could go to each website in search of data which is time consuming and nearly impossible with the number of site growing. Web scraping makes this process automated. Beautiful soup and Scrapy are few libraries for data scraping. Web scraping can get you huge amounts of data in short time but it puts load on the server, that is why many sites don’t allow web scraping.
Embedded Application programming
Embedded devices are a piece of hardware which servers a particular or general functionality. Smart watches, kettles, ovens, washing machines and all other electronic appliances run with the help of embedded devices(Micro-controllers). These electronic boards are typically programmed in C or C++. Python is mostly built on C. Python can be used for programming these hardware boards. Most famous micro-controller boards such as Raspberry Pi, Arduino and Esp can be programmed in python. Raspberry Pi’s default language is Python. Python being a high level language it is not suitable for boards with constraints. Micropython is created for the very purpose of programming these hardware boards. It preserves all the advantages that python provides to programmers.
These days all devices are being connected to internet and are becoming smart. Fitness bands, Watches, Ovens, Television, Thermostats etc. A new field called the Internet Of Things has emerged. Powerful hardware available at cheap prices is making a ground breaking change in how we use electronic devices. This is creating a lot of job market for IOT engineers.
Conclusion
Python is a must know language, if you want make your career in technology. Top trending tech fields are Artificial Intelligence, Data Science and IOT. Python is a must language in all of them. After looking at what python can do, I though of building all my projects in python. But that doesn’t work out. Even though i want to python everywhere, but there are other better solutions in some fields. I suggest you to pick the most suited language for your project.
Do Python wherever possible and use other languages wherever necessary
Stay Curious… Stay Creative…
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