Python – Importance
Why Python is Important Programming Language? Python is powerful and fast, plays well with others, runs everywhere, is friendly & easy to learn and is Open.
Well, you can find the above answer everywhere. But how does exactly it matters in real programming world?
- Python is more than capable of large-scale web development with Django
- Pygame is a fantastic resource for learning Python and Game mechanics
- Amateur robotics community loves Python, it is the best language for the job
- Artificial Intelligence, Machine learning, and Data Science in the enterprise are well managed with Python
- A larger developer community
Why Big Companies are Adapting Python?
Python is known for its easier syntax and for being faster to program with than other traditional languages, such as Java or C++. Programmers are able to do as much with 10 lines of Python code as they are with 20 lines of Java, and with less chance of making mistakes. Given how regulated the fintech industry is becoming, it becomes clear why a lower error rate would be important to fintech companies.
2. Software development costs and time to market
Today, a company’s most expensive resource is its employees’ time. As a competitive start-up, you have to watch your bottom line. In most cases, you’ll have angel investors and clients observing you and expecting the same. As a dynamically typed language, Python offers tech industries a much faster alternative to languages that are statically typed.
Python is fast, Python offers quicker deployment and less required code. When you’re on a budget and need to validate your product on the market immediately, the right server-side language becomes more important.
3. Open-source libraries
One of Python’s major advantages as a programming language is the availability of a large number of libraries and tools. As a key language for mathematical programming, which is important for finance companies, Python offers many financial and fintech libraries. Look below for a list of some of the libraries used by fintech companies.
Python libraries for fintech:
- SciPy (library for scientific and technical computing)
- NumPy (fundamental package for scientific computing)
- pandas (flexible and powerful data analysis/manipulation library)
- pyalgotrade (algorithmic trading library)
- pyrisk (common financial risk and performance)
- zipline (a Pythonic algorithmic trading library)
- quantecon.py (library for quantitative economics)
- pyfolio (portfolio and risk analytics)
- pybitcointools (commonsense Bitcoin-themed Python ECC library)
- finmarketpy (library for backtesting trading strategies and analyzing financial markets)
- scikit-learn (machine learning algorithms)
As an open source programming language, Python helps you to curtail software development cost significantly. You can even use several open source Python frameworks, libraries and development tools to curtail development time without increasing development cost. You even have option to choose from a wide range of open source Python frameworks and development tools according to your precise needs. For instance, you can simplify and speedup web application development by using robust Python web frameworks like Django, Flask, Pyramid, Bottle and Cherrypy. Likewise, you can accelerate desktop GUI application development using Python GUI frameworks and toolkits like PyQT, PyJs, PyGUI, Kivy, PyGTK and WxPython.
4. Data Science at its best
“Python is known to be an intuitive language that’s used across multiple domains in computer science,” the report stated. “It’s easy to work with, and the data science community has put the work in to create the plumbing it needs to solve complex computational problems. It could also be that more companies are moving data projects and products into production. R is not a general purpose programming language like Python.”
Python is currently among the fastest-growing programming languages in the world, largely due to the ease of learning involved, the explosion of data science and artificial intelligence (AI) in the enterprise, and the large developer community around it.
5. Scalability with Web Framework
Django – Python’s web framework is most popular and emerging. Talking about its scalability, there isn’t any single place that collects information about traffic on Django built sites, so I’ll have to take a stab at it using data from various locations. First, we have a list of Django sites on the front page of the main Django project page and then a list of Django built sites at djangosites.org. Going through the lists and picking some that I know have decent traffic we see:
- Instagram: What Powers Instagram: Hundreds of Instances, Dozens of Technologies.
- Pinterest: Alexa rank 27 (03 Feb 2019) and 250 Million users in 2018
- Bitbucket: 200TB of Code and 2.500.000 Users
- Disqus: Serving 400 million people with Python.
- curse.com: 600k daily visits.
- tabblo.com: 44k daily visits, see Ned Batchelder’s posts Infrastructure for modern web sites.
- chesspark.com: Alexa rank about 179k.
- pownce.com (no longer active): alexa rank about 65k. Mike Malone of Pownce, in his EuroDjangoCon presentation on Scaling Django Web Apps says “hundreds of hits per second”. This is a very good presentation on how to scale Django, and makes some good points including (current) shortcomings in Django scalability.
- HP had a site built with Django 1.5: ePrint center. However, as for novemer/2015 the entire website was migrated and this link is just a redirect. This website was a world-wide service attending subscription to Instant Ink and related services HP offered (*).
Web framework with combination of Python-Django is also great place to develop our skills and business needs.
Python an exceptionally solid and flexible language that has many different applications and is very welcoming to newcomers. If you’re planning on going on to a long programming career and learning multiple languages, you’ll continually find uses for Python if it’s in your toolbox.