Python is a high-level, server-side programming language for websites and mobile apps, the only programming language that makes it easy to play around with ML. Due to Python’s dense syntax and readability, developers able to express a concept easier than they can, using other languages.
A bit of Python history
Python appeared to replace the ABC language. It was created by Guido van Rossum and named after “Monty Python’s Flying Circus” show. Introduced in 1991, Python version 0.9.0 incorporated many ideas from the languages that existed at that time: for example, the module system was taken from the Modula-3 language. Elements of functional programming like map, filter, and reduce appeared in the language in version 1.0. Python was initially positioned as a “language for everyone,” with the emphasis on code readability and concise syntax. In version 2.0 there appeared famous “list comprehensions”, borrowed from SETL and Haskell languages. Python as a language has been continuously evolving since the beginning of its existence. At the moment, the developers use mostly language versions starting with “3”.
What’s special about Python?
Python is an interpretable, object-oriented, high-level programming language with dynamic typing, automatic memory management and convenient high-level data structures such as dictionaries and lists. The language supports classes, modules, and multi-threaded computing. Python has a simple and expressive syntax and supports several programming paradigms: structural, object-oriented, functional and aspect-oriented.
Python is also very famous for its use in Machine Learning and Artificial Intelligence. One of the main reasons why Python is used for machine learning is that it has many frameworks and ML libraries that simplify the process of writing code and reduce development time. When working with Python, a developer does not need to pay much attention to writing code: he can concentrate on solving more complex problems associated with machine learning processes.
Python is often used for:
- System Utilities.
- Websites (Django, Flask, Pyramid, Tornado, TurboGears).
- Applications for scientific calculations (NumPy, SciPy).
- Desktop applications (Tkinter, PyQt, wxPython).
- Games (Pygame).
- Mobile applications (kivy).
The most famous solutions developed with Python
Python is one of the most popular and promising language tools, based on numerous ratings and analysis of the software development market. It is quite simple, and therefore learning a language does not take too much time. Let’s see what companies use Python:
- Google uses Python in its search engine.
- Companies like Intel, Cisco, Hewlett-Packard, Seagate, Qualcomm, and IBM use Python to test the hardware.
- YouTube Video Sharing is largely based on Python.
- The NSA uses Python to encrypt and analyze intelligence.
- JPMorgan Chase, UBS, Getco and Citadel use Python to forecast the financial market.
- The popular BitTorrent software for sharing files is written in Python.
- The popular App Engine web framework from Google uses Python as an application programming language.
- NASA, Los Alamos, JPL, and Fermilab use Python for scientific computing.
Python popularity in 2020
Python is the only programming language that has shown a steady upward trend over the past five years. Machine learning (ML), artificial intelligence (AI), Big Data, and robotics rely on Python. The serious task of software development of 2020 is cybersecurity that also is accomplished with Python. This programming language also continues to considered to be one of the most popular languages of introductory courses at universities.
Python pros and cons
Advantages of Python:
- It has a large standard library and a huge ecosystem;
- It is free to use and distribute;
- It can be easily integrated with other languages and platforms;
- It is very easy to learn;
- Its design is clean and object-oriented;
- Its speed and productivity always increase;
- It is perfect for AI and machine learning solutions.
Disadvantages of Python:
- There are no such access modifiers as: protected, private and public.
- It isn’t so fast in comparison to other languages.
Why UppLabs chose Python?
We choose Python as it is suitable for developing any projects on different platforms. It can be found on the web, on mobile devices, in applications, solutions related to machine learning (neural networks and artificial intelligence), and even as an embedded system.
More reasons to use Python for our projects:
- Python has many ready libraries for solving various problems
- The simple syntax of the Python language helps the developer test complex algorithms with a minimum waste of time for project implementation.
- There are many useful resources about Python where a programmer can get help and advice at any stage of the development.
- Python helps combine different types of data. Moreover, Python is especially convenient for those developers who write most of the code using the IDE.