This article is about Software Development
Python Went Mainstream with these Software Companies
By NIIT Editorial
Published on 27/04/2020
Python is arguably the most in-demand language of our times. It has built a niche following in both amateur programmers as well as seasoned coders. This is due to an easy to learn syntax for beginners and feasible maintenance charges for organizations. First envisaged in the 1980s as a successor to the ABC language, it was created by Guido Van Rossum and first released in 1991. It is a general-purpose, high-level programming language. The design principles behind Python’s architecture lay special emphasis on code-readability, making the source code short and easy to modify.
Features Contributing to its Likeability
As a result of all the features of Python that make it a crowd favourite, it has been widely used for commercial applications. Some of them are an inseparable part of our daily lives, but right before we jump to that, it would be wise to understand what feature of Python makes it a darling of the tech world.
Syntax is a structure of statements the collection of which gives the programming language its shape and form. This syntax varies from one language to another in computer programming. Python has a very simple and neat syntax. The code can be designed quickly and understood by even beginners. That is one of the reasons why students find Python easy to learn as well.
- Multi-Platform Compatibility
Python is the go-to choice for developers looking to make quick edits to the source code, test the same and rectify the results. It can be run on all major operating systems be it for smartphone or desktops. This includes Android, iOS, Windows as well as Linux.
- High-Level Language (HLL)
With high-level languages, coders only have to write the code. As mentioned in the previous point, HLLs are machine-independent, hence they will run on any device regardless of the operating system. Coders need not even worry about the system memory. Python comes with features like the garbage collector which automatically delete unreferenced objects from the code and allow maximum optimization of the CPU time. It is also highly integrating. You can easily incorporate Python with other programming languages such as C or C++.
- GUI Support
Graphical User Interface is an interface intended for users. Since its design is based on graphics, users can navigate using icons, cursors and buttons. In other words, graphics are used to make the user act such as click an icon and go to the next page of the application. Python offers resources to build impressive cross-platform GUIs.
- Extensive Libraries
In computers, a library is a collection of pre-compiled statements that a program can refer to. Coders use libraries so they don’t have to write the program from scratch. Just pointing the program to a library would do the job. Python offers its users a rich set of libraries.
Python is highly expressive and well-structured. While writing the code, a programmer must define through the code the action that the program must execute at runtime. A one liner-code of Python would mean much more than compared to a second programming language such as Java. This translates into fewer code volumes and faster project completion times.
- Software Testing
Test Automation refers to the use of programmable scripts to execute tests, without human intervention. The script checks for the components of the application that you want to test, the order of execution and the expected outcomes. Python offers various tools that make testing software much easier.
- Enterprise Application Integration
Python integrates easily with other programming languages such as C, C++ and Java. As a result of which it is the preferred language for application scripting. This flexibility, allows engineers to make appropriate extensions to already existing apps that were originally written in a different language.
(Few) Applications of Python
It is referred to as the process of creating websites. It might sound straightforward but considering that a website could be of various kinds, there is heavy work involved. For instance, a website could be static, whose information does not change and remains the same i.e. static for every viewer of the page. Or it could be dynamic, whose information changes depending upon the viewer, their visiting time, and local time-zone to name a few factors. Website development requires tools some of which being Python-based ease and improve the work of coders.
Django is an open-source (free to use) Python Web Framework that is built to enhance the front-end design of the application. It is a collection of Python libraries which allows rapid development and clean interfaces. It can be used for creating both front-ends and back-ends. Being incredibly fast, secure and scalable, it is much preferred by websites/applications (apps) that will attract heavy user traffic. Similarly, Pyramid is another Python framework used widely. Micro Frameworks are used to create effective but minimalist back-ends. Python excels in this department as well with its products Flask and Bottle.
Content Management Systems (CMS)
A CMS is a software application with point-and-click features used to create, moderate and manage content on a website. Common examples of it include Joomla, WordPress and Drupal. Python offers users advanced CMSs such as Plone and DjangoCMS.
Applications Built with Python
Thanks to the features listed above, Python has a huge online community that actively shares content regarding new developments in the language and how to best use them. Python was built with the motto which goes like ‘beautiful is better than ugly’ and ‘simple is better than complex’. As a developer, you can have the freedom to try out multiple approaches with both object-oriented and functional programming. For such reasons, household names of the tech industry have trusted the language for its word. Some of the leading companies using Python are mentioned below.
1. Facebook with Python
The company is synonymous with the words “social media”. In fact, with its acquisition of both Instagram and WhatsApp, Facebook is social media. With 2.5 billion active users on its parent social networking platform, the demand on the tech-side is gargantuan. Return on investments is a key factor for it to deploy enterprise-scale use of computing languages. Yet, as per an official post, 21% of Facebook’s infrastructural codebase is created on Python. Tasks including but not limited to network setups, automated maintenance schedules, server imaging and fault detection are performed using Python at Facebook.
2. Instagram with Python
Now, a Facebook subsidiary, the photo-sharing platform has 1 billion+ monthly active users. Yet even in the stages of development, its engineers used Python’s Django Framework to give the right aesthetics to the mobile app. Such was the passion of the development team that they could be the poster child with the banner Python for organizations.
To this date, Django and Python’s other applications find a valid use case in Instagram’s source code. Being highly scalable with the ability to stay secure has not just Instagram but others going gaga about the language, as we find out next.
3. Google with Python
Now designated as Alphabet, Google’s association with Python goes back to its founding days and also stretches to its parallel ventures (discussed later). The search engine relied on both Python and C++ to create its core search algorithms. Its programmers used Python actively for log analysis, code review tools and build systems. Google tapped into Python’s encyclopaedic base of libraries to leverage the Google Data Python Client Library, Google AdWords API Python Client Library and Google APIs Client Library for Python. The company’s online site for hosting i.e. code.google.com along with many machine learning and AI projects have been undertaken in Python. The fact that Python is used in companies like Google, merits it an elusive pedestal.
4. Spotify with Python
Spotify heads the music streaming industry. The mobile app has one of the most vibrant and aesthetically pleasing interfaces you could expect from a music app. In an official post, its partners shared their experience working with Python and its business applications. Spotify used Python for backend services and data analysis. Over 80% of the app’s backend services depend on Python. It accelerates development timeframes with faster turn-around-times and error rectification. Spotify also uses Hadoop, which is although written in Java yet programs can be coded in Python. In times of heavy-business hours, Spotify reports running as many as 6,000 Python processes within the Hadoop Cluster.
5. IBM with Python
IBM is a key contributor to the global tech industry with its history and achievements going back 108 years. From mainframes to laptops (Think Pads) and now Artificially Intelligent Watson computer, its contribution to computer science as we know it spans the length and breadth of human life. Python has a System Development Toolkit (SDK) for Watson. What’s more, IBM has dedicated an online learning space to educate professionals about using Python with IBM Bluemix, the company’s cloud platform.
6. Reddit with Python
The original code for Reddit was written in Common Lisp. It was later re-written using Python back in December 2005 owing to its huge library repository and development flexibility. Due to this, it would not be wrong to say that Reddit is one of the most successful Python based companies in the world. The Web framework that was used to develop the website is still available as an open-source project, web.py. Being run on Python between the years 2008 to 2017, Reddit was technically an open-source project and all of its libraries and code base was available on GitHub.
7. Netflix with Python
Another significant name amongst the companies using Python is Netflix. The underpinning technology for Netflix’s customized personal recommendations is predictive analytics. Moreover, the developers have to pay extra attention to engage audiences through design elements. All this is and more have been off-loaded to Python. This includes communication tools to exchange data with AWS servers, and storing critical information with Python-Memcached and pycasa. The programming language is also used for data science for monitoring the quality of organizational data, and ensuring the correct data movement and syncing. Engineers also appreciate the design flexibility that Python accords to visualize data.
8. Dropbox with Python
On its IPO date on March 2018, Dropbox was valued at $9.2 Billion. Dropbox was so serious about using Python that they poached its creator Guido Van Rossum from Google. In essence, Dropbox is a Python based software company. A few of the changes that he and his team effectuated at Dropbox were to enable sharing of data stories amongst users of the Dropbox community. Its client-side programs are programmed in Python while taking the support of the libraries on Mac and Windows to deliver a seamless experience. The Dropbox engineers have also released an API in Python that lets external developers evaluate the present mindset of the Dropbox tech team.
How long does it take to learn Python?
Python is an easy language to learn due to its clean code. But to define a timeline in which you can learn it is very subjective. To accurately state the time required for your learning curve depends on your objective. Are you learning the language to simply expand your C.V or do you plan to be an expert?
For an average learner who gives 2–3 hours to practicing Python regularly, can get around the basic understanding of it in approximately 6-8 weeks. For an expert level knowledge this timeline can stretch well into months and years.
To begin using Python, download a version of it from this link. Don’t make the amateurish mistake of downloading the latest release i.e. 3.8., different versions of Python offer different workability. Not all the libraries are compatible with release 3.8 due to which you might have to make-do with an older version.
Next, choose an Integrated Development Environment (IDE) to work on. IDEs offer over the top convenience that is head and shoulders above standard text editors.
As you continue learning Python you would discover that it is especially suited to designing front-ends and automation algorithms. This could be a new career in the making for you and we know you’ll enjoy it.
Jobs after learning Python
Once you’ve given enough time to the language and have reached a threshold at which you can code mainstream software applications, a gamut of Python jobs could be open to you:
You would have heard of software developers, but the type and kind of Python jobs have grown so much that IT corporations have begun allocating designations to them. Being a Python developer is one such profile. As a subject matter expert of Python you could:
- Create websites using Python
- Code algorithms for automation and data science
- Use python for cryptography
- Develop games
- Create audio/video applications
FYI, from a long list of things, the aforementioned are just some of the applications of Python.
These are professionals that code algorithms to process chunks of structured/unstructured data and look for patterns. The findings are used to make business decisions and maximise returns. Likewise, Python Programming can be applied to data visualizations and present complex information in an easy-to-consume format.
Research Analysis differs from data analysis in that the former requires professionals to perform end-to-end data mining operations. Therefore, such workers are also expected, quite naturally, to possess operational knowledge of the domain they work in. For instance, KRAs of a financial research analyst will differ from a marketing research analyst. Nevertheless, Python programming is immensely used for purposes suited to such roles.
Amongst all the other Python jobs, perhaps this is the most renowned and respected. It has to be mentioned here that data science is a vast field and python just a subset, which requires additional specialities. Nevertheless, Python is utilized in companies at an appreciable level. In addition to that, a data scientist would gather data, mine data, perform data modelling, and then communicate results to stakeholders.
Python is not a fad but a materializing reality as shown by some of its popular use cases within the past decade and a half. The adoption trajectory of this language is only forecasted to rise and endorse massive employment opportunities for new-age coders in its wake. Are you still a sceptic or convinced of jumping onto the bandwagon? Add Python as a recognized skill-set to your credentials and expand your employability quotient. .
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