Python and its applications explained in less than 800 words
Python applications in the real world
- Data Analysis
- Financial Analysis
- Artificial Intelligence
- Machine Learning
- Game Development
- Desktop and Mobile Application development
- Server-side language for API and Backend development
Python is a high-level, general-purpose programming language. It was conceived in the late 1980s by Guido van Rossum at Centrum Wiskunde & Informatica (CWI) in the Netherlands as a successor to the ABC programming language, which was inspired by SETL, capable of exception handling and interfacing with the Amoeba operating system. Its implementation began in December 1989, and the first version came out around 1991.
Python uses whitespace indentation, rather than curly brackets or keywords, to delimit blocks. An increase in indentation comes after certain statements. On the other hand, a decrease in indentation signifies the end of the current block.
Thus, the program’s visual structure accurately represents its semantic structure. Some other languages use indentation this way, but indentation has no semantic meaning in most. The recommended indent size is four spaces.
Since it’s a very flexible and powerful language, its usage is not limited at all. It can be used in Data Analysis, Financial Analysis, Artificial Intelligence and Machine Learning, Game Development, Desktop and Mobile Application development, and even as a server-side language for API and Backend development.
Python’s popularity is on the rise, and it’s taking over other languages on its own merits.
Ten real examples of Python’s usage
One of the most popular desktop applications made with Python is Dropbox’s desktop client. The company started to use Python on their project because of its simplicity and scalability and actually managed to convince Guido Van Rossum himself to join the company.
The social image-sharing website uses Python in its backend, namely the Django Framework.
Amazon uses Python for its recommendation system and system analysis.
Since the Pinterest developers were more acquainted with Python, they decided to build most of the social media platform with it, although they’ve experimented with other languages and technologies throughout the years.
As Quora co-founder and CEO Adam D’Angelo explains, in the late 2000s, the team didn’t want to use PHP. They saw what happened with Facebook, which needed to invest a lot of money and resources to get rid of this legacy software.
Once again, Quora founders didn’t overthink it. They just knew Python. They considered Java, C#, and Scala for a while but went for Python because of the development speed. They just wanted to launch their MVP as fast as possible, and Python was still the best at doing it.
The founders of the peer-to-peer ride-sharing company had to choose between Ruby and Python. They went for the latter because the Uber platform needs to perform many calculations.
The app’s backend predicts the demand and supply, traffic and arrival times, and Python is a better solution for mathematical calculations.
Python is also easier to learn for the developers than Ruby, which solves a massive problem for Silicon Valley companies, where it’s so challenging to hire software engineers.
Thanks to Spotify, long gone are the days of chasing down MP3s on Limewire or Soulseek, looking for torrents on obscure invite-only websites, or listening to low-quality rips on YouTube. Instead, they use Python a lot for the backend, analytics, and the suggestion algorithm.
What Spotify did for music, Netflix did for video. Having started as a DVD-by-mail service, they’re now a high-tech leader, providing streaming video content to hundreds of millions of subscribers.
One of Netflix’s strengths is its powerful recommendation and analytics engine, allowing the company not just to provide you with recommendations but also to predict what content they should order and focus on.
Google loves Python so much that they rewrote their entire web crawler, originally coded in Java, in Python. Web crawlers gather information from web pages and organize them in the search index. This crawler is who we appeal to when we optimize a webpage for search engines. Early Googlers made thestatement: “Python where we can, C++ where we must.”
They’ll use C++ for parts of software that need to be faster or have better control of memory and Python where they want rapid deployment and easy maintenance.
Facebook uses Python for production engineering. Over 21% of Facebook’s code is written in Python. The simplicity of the language allows Facebook engineers to interact with their APIs easily and speed up their engineering process by using libraries. They also use it to maintain libraries and infrastructure, hardware imaging, a binary distribution, and operational automation. Essentially, Python powers the bridge between Facebook’s network devices, automatic service failure remedies, scheduled maintenance, testing, and server maintenance.
Originally published at https://angry.ventures.