Frequently Asked Questions
What is Python?
Why is Python used in finance?
Should I use Python or Excel for data analysis?
Python is known as a versatile, general-purpose programming language. It is an open-source high-level language that’s easy to learn due to its use of plain English syntax. Due to numerous advantages (that we’ll address later), the multi-paradigm programming language lends itself well to varied use cases.
From its initial days in 2000, Python 2 came a long way from being a new kid on the block to becoming a favorite of programmers. With Python 2.7 being the last major upgrade back in 2010, Python 2’s end-of-life date was January 1, 2020.
Python 3 was released as an upgrade to Python 2 in 2008 and the two versions co-existed for around a decade. Today, Python 3 is used by 95% of Python developers. If you’re in the market for Python developers, you might favor Python 3 over Python 2.
But, what exactly is the debate when it comes to Python 2 vs. Python 3? And is Python 2 still relevant? Read on and you might be surprised by the answer.
What Is Python 2?
Python 2.0 was meant to bring more inclusivity and coding literacy to the masses. Before its release in 2010, Python was largely supported by its creator Guido van Rossum who developed the original version of the language in 1991.
With Python 2, Rossum opened up Python's development and improvement to the larger developer community. As the community contributed to future releases and improved upon its codebase, Python 2 grew to become one of the most commonly used languages in the world.
Python 2 took the language’s original objective of spreading coding literacy to another level due to its array of improvements over previous versions.
It has also played a major role in the development of languages like Perl and Ruby and is used by organizations like Netflix, Spotify, Reddit, Uber, and Instagram today.
What Is Python 3?
Python 3 was released in 2008. It sought to improve upon Python 2 without making radical changes with a new 2.x release. Hence, Python 3 came about as a separate branch of the overall Python ecosystem. By design, Python 3 is backward incompatible with Python 2.
The user base of Python is split between Python 2 and 3 depending on differences in use cases and their willingness to undertake complex migrations.
From web development and computer graphics to machine learning and data analytics, the two versions of Python were suited to different use cases. Even now, Python 2 is preferred over Python 3 when coding for computer graphics, games, and mobile development.
Although some features of Python 3 have been brought over to Python 2 to facilitate easy migration to Python 3, the process still requires considerable effort.
What Are the Differences Between Python 2 and Python 3?
With Python 3 being such a major departure from Python 2, there are bound to be major differences between the two versions.
- Backwards compatibility: While Python 2 code can be ported to Python 3 with some effort, Python 3 is not backwards compatible with Python 2.
- Syntax: Python 2 has a more complicated syntax and is more difficult to understand compared to Python 3, though the syntaxes are similar.
- Modern usage: Python 2’s usage has virtually ceased while Python 3 is more popular than ever and is used by 95% of Python developers.
- Application: Python 2 is preferred for select use cases like mobile development and computer graphics while for everything else, Python 3 is still the version of choice.
- ‘Print’: While Python 2 considered ‘print’ a statement, Python 3 considers it a function.
- Storage of strings: Python 2 stores strings in ASCII by default while Python 3 stores them in Unicode.
- Integer division: Python 2 delivers an integral value when dividing integers whereas Python 3 delivers floating-point values,(e.g., 9 divided by 4 will yield 2 in Python 2 but 2.5 in Python 3).
- Exceptions: Python 2 encloses exceptions in notations whereas Python 3 encloses them in parentheses.
- Variable leakage: Variables are mutable in Python 2 (e.g., when used inside a for-loop). But in Python 3, variable values are not changeable.
- Iteration: In Python 2, the xrange() function is used for iterations but in Python 3, the new function Range() is used instead.
Why Move To Python 3?
Python 2.7, released in 2010, didn’t see any successor, and support for Python 2 was scheduled to end on January 1, 2020. That date has come and gone, and with it, Python 2 has officially become obsolete.
So, as an enterprise, should you move to Python 3? Yes, absolutely.
Python 3 is the modern version of the language and apart from enjoying the variety of benefits listed before, it’s the more secure and up-to-date version. If you’re still running Python 2, your systems are prone to security issues and bugs.
Python 3 also has a much larger community that regularly fixes bugs and works on newer releases to improve the functionality and stability of its codebase. You get access to better performance and always-updated features.
Python 3 was developed as a more readable and easier-to-comprehend version of the language.
Why Stay With Python 2?
While Python 2 is obsolete now and poses security and stability concerns if you're still running it on your systems, there might still be a reason to stay with it.
Many companies have applications written in Python 2 and don’t want to migrate to Python 3 for fear of breaking the applications. Migration does tend to be an effort-heavy task and requires not just time but also a significant monetary investment.
Maintaining such legacy applications means retention of Python 2 code alongside efforts to adopt Python 3 for newer development tasks.
Which Version Is Better: Python 2 or Python 3?
After going over the differences between the two versions of Python and the reasons to ‘stay or move’, one could wonder which one is the better version.
Advantages of Python 3
Python 3, by all means, is the better version of the two. The Python 2 vs. Python 3 debate doesn’t really hold water owing to the vast improvements Python 3 has over Python 2.
In addition to performance, syntax, and all other quality-of-life improvements, Python 3 is also the better option in terms of security and reliability. The ever-growing Python 3 community ensures bugs are readily fixed and newer features are introduced regularly.
Advantages of Python 2
Python 2 does lend itself better in some use cases, as we discussed above. If you’re working with computer graphics, games, or mobile development, it’s worth checking out Python 2.
For developers, perhaps the only other reason to learn or work with Python 2 is to get skilled in Python 3 migration. Moreover, companies require Python 2 developers for maintaining legacy Python 2 code.
How To Choose the Best Python Version To Use?
Python 3 might be the better version, objectively, but you still need to evaluate your needs and choose the best Python version for your project.
If you’re a fairly new organization, chances are that you’re not using Python 2. In that case, there’s fairly no reason to consider Python 2 unless you’re working with specific libraries that aren’t yet compatible with Python 3.
If you do have legacy Python 2 applications and don’t want to migrate to Python 3 yet, you can retain Python 2 and leverage developers for maintaining your codebase. But it’s recommended that you plan for migration to Python 3 as soon as possible. Also, try to choose Python 3 for all new development projects.
Regardless of your Python version, you’ll need to hire Python developers for development, migration, or simply maintenance projects.
Trio can help you hire world-class Python developers without investing thousands into a lengthy recruitment cycle.
When you partner with Trio, you don’t have to incur hiring costs, which can amount to a considerable percentage of a developer’s annual salary. Trio developers are well-trained, driven, and committed to the long run.
Moreover, you don’t need to handle HR functions like payroll, benefits, and compliance. Trio takes care of all of that for you.
Python is easy to pick up and learn, which also leads to a vast number of Python developers vying for in-demand Python roles. You need to thoroughly vet and interview the candidate pool to hire the right developers for your project. And that can sometimes take months.
Trio offers you plug-and-play recruitment and connects you with verified and senior Python developers from around the world. Contact us today to learn more about how we can help scale your next project to new heights.
5 min read
Python frameworks provide the basic infrastructure for developing a robust Python software application. Depending on the software project your team is trying to build, there are better and worse Python frameworks suited for its purpose.
Sources demonstrate that Python's popularity has been steadily increasing in the past decade or so, with approximately 15% of Stack Overflow questions tagged “python” in 2021.
And as such, the corresponding technologies of Python gain similar popularity. It is common to see questions like “What is a Python framework?” or side-by-side Python framework comparisons.
Today, you’ll learn about numerous Python frameworks to use for your software development project. But first, what is a Python framework? Stick around to find out!
What Is a Python Framework?
A Python framework, like any framework, cushions your software development project with a foundation or substructure to build on top of. To be clear, software frameworks render the generic functionality of the program you’re trying to create, so your developers don’t have to start from scratch.
Python frameworks in particular, will automate standard application building steps using the Python programming language. As a result, Python developers will save time on development and your business will benefit overall.
Where Is the Use of Python Most Recommended?
Python is a general-purpose, interpreted, object-oriented programming language. The designers of the language prioritized code readability whilst building Python, making the language highly productive.
Readability being an important part of Python’s founding philosophy, Python’s most salient representations of this tenet include its intuitive use of the English language and easily navigable code blocks.
Python’s prime asset is its significant white space, which developers use to isolate code blocks. This tactic encourages easy-to-read code and gives a more friendly appearance to the program compared to other programming languages that use special characters such as brackets.
Released in 1991 by Guido van Rossum, today Python is known as a “batteries included” language because of its large standard library. Python libraries describe pluggable pieces of code that you can work into your program with a simple function call.
The Python Standard Library is what comes with the language right out of the box. This library is notably extensive, with high-level data structures like dictionaries and lists, turtle graphics, and more.
The Python programming language performs well on both the front-end and back-end of development. Moreover, developers use Python to build a variety of software, from web development to machine learning to data science.
Much of Python’s capacity for a diverse array of programming capabilities involves its simplicity and its standard as well as additional libraries.
Python Framework vs. Python Library
Some people wonder about the difference between Python frameworks vs. Python libraries. Although they both offer developers operational functionalities, their similarities end when it comes to specificity and complexity.
For example, Python libraries are filled with dozens of useful functions for specific purposes, but there is not much complexity. Python libraries perform a simple task and are ultimately a small piece of a large puzzle.
Because frameworks work off a specific comprehension of what your application might look like, even more specificity is permissible. Complexity is the name of the game. Thus, a Python framework will outline the puzzle; the more complex the framework, the more outlining of the internal pieces.
The 3 Main Types of Python Frameworks
Python frameworks come in all shapes and sizes. Factors that may affect which framework you choose include scalability, expertise, and your business-specific goals.
Full Stack Framework
Full-stack frameworks are suitable for both back-end and front-end development. Web development consists of front-end tools for graphic user interface (UI) design and back-end services like databases, security protocols, and business logic.
Microframeworks are by definition lightweight. In some ways, it is the opposite of a full stack framework. Python’s official Flask documentation explains that the “micro” in microframework signifies that the framework’s “core [is] simple, but extensible”.
The components that are fundamental to a full stack framework like a database management system and certain security measures do not come naturally to a microframework.
While this might seem like a bad thing, it actually encourages flexibility for developers who want to leverage control over their software, only adding in the relevant third-party libraries when they’re completely necessary.
Related reading: Ruby vs. Python - Which Programming Language To Choose?
Asynchronous programs are event-driven. Rather than line by line operational handling where one function runs after the other, asynchronous code is non-blocking and doesn’t wait for one event to execute before starting another.
Because of this parallel programming technique, asynchronous frameworks allow for a profusion of high-performance concurrent connections via running on an async-capable server.
10 Awesome Examples of Python Applications
25 Python Frameworks To Use In 2023
In total, there are dozens and dozens of Python frameworks. But since you care about your time, here are 25 Python frameworks that stand out the most.
CubicWeb fits the definition of a full-stack framework. It is also a semantic framework. Semantic technologies rely on ontological and conceptual comprehension to understand data.
Though the typical model-view-controller (MVC) architecture is more commonly in use for developing UIs, CubicWeb uses the concept of cubes. Cubes join together to create an instance with configuration files, a database, and a web server.
AIOHTTP is an asynchronous framework as well as an HTTP client/server for asyncio. Though some of these words may seem foreign, the gist is that AIOHTTP allows your developers to build asynchronous clients and servers for your web application.
Dash is a microframework best suited for building analysis-oriented Python applications. The framework is a frequent choice for businesses that have stakes in machine learning and data science.
Bottle is another microframework. Fast and simple, its original design was specified for building application programming interfaces (APIs).
Like the best of microframeworks, Bottle emphasizes its lightweight build, namely by implementing everything into a single source file and relying on few dependencies. Other important features of Bottle include routing, template, utilities, and a built-in HTTP server.
Bottle works closer to hardware than other frameworks. However, you should opt for a more complex framework if you think your program might span longer than 500 lines of code.
CherryPy calls itself a minimalist framework. With CherryPy, you can create an entire application using the principles of object-orienting programming. As a result, development is faster and easier.
Yet another API-oriented framework is Falcon. Falcon is a minimalist microframework geared towards rapid application development. Developers can take advantage of Falcon to build RESTful APIs, app backends, and microservices without the burden of unnecessary abstractions.
Django is one of Python’s more popular Python frameworks. Being full stack in nature, Django comes equipped with the tools to build large and complex web applications.
Flask is historically in competition with Django. Django and Flask are the top two most popular Python frameworks. That said, they are wildly different.
Unlike Django, Flask is a microframework and does not hold any tools or functions that a third-party library can fulfill as essential to its packaging.
Giotto is a Python framework stressing the separation of concerns that the classic MVC architecture elicits. Because of Giotto’s generic implementation of views, models, and multiple pluggable controllers, the framework is a vessel for simplifying and shortening development.
Growler is both an asynchronous framework and a microframework. The framework uses Python’s asynchronous library, asyncio, along with middleware to process HTTP requests.
Pylons borrows the finest ingredients of Perl, Python, and Ruby to bring to life a full stack framework with a focus on rapid development. Similar to Flask, Pylons is lightweight and flexible.
Pyramid is a leading full stack Python framework. Scalability is its biggest asset as small and full-scale applications can depend on Pyramid for their development.
On its official website, Pyramid calls itself a “Goldilocks Solution: not too small, not too big, just right.”
Sanic shares similarities to Flask, but its asynchronicity makes it even faster than Flask. Benchmark tests show that Sanic can handle tens of thousands of requests per second.
Hug is a microframework for developing APIs. Labeled the fastest framework for Python 3, Hug is paving the way for the technology of the future.
Dubbed the “Super Powered Python Web Framework”, Morepath is an expressive model-driven microframework providing routing to its models.
Like with MVC patterns, models represent data and views represent the UI. In Morepath, an application consists of models which are routed to a URL path. Content is expressed to the web through views.
Initially developed to support a social media company named FriendFeed that has since been acquired by Facebook, Tornado is an asynchronous Python framework that can handle several thousand concurrent users at once with a non-blocking network I/O.
TurboGears has the versatility for use as a full stack framework or a microframework. The framework is data-driven, user-friendly, and extends a templating engine and an object-relational mapper (ORM).
Web2py was originally built as a teaching tool, but as a full stack framework, it is loaded with tons of features to do so much more. For instance, there are no requirements for installation and configuration; web2py is cross-platform; and it comes with its own integrated development environment (IDE).
FastAPI is a bit self-explanatory. It’s a modern Python framework for building APIs with features to speed up the development process. Much of its design owes it credit to Flask.
Grok leverages important programming principles such as ‘don’t repeat yourself’ (DRY) and ‘convention over configuration’ (CoC) to promote an agile development experience.
DRY strives to reduce repetition by standardizing abstractions. Likewise, CoC aims to decrease the grueling decision-making process for developers by starting them off with a conventional foundation to build up from so they can save time on configuration.
BlueBream is a Python framework that is most optimal for building medium and large applications. More than a framework, BlueBream is a server and library too. Some of its best features are its component architecture, transactional object database, and integrated security protocols.
Related reading: Python vs. Java - Side-By-Side Comparison
Quixote is a simple and flexible Python framework for designing web applications. Anyone with a good knowledge base in Python should thrive with Quixote.
Weppy — stylized as the lowercased “weppy” — is a full stack Python framework that centers simplicity. Its elegant syntax encourages developers to focus on the product the’re building rather than struggling to navigate the framework itself.
Zope is an application server and web framework. Its primary use case is for the development of content management systems (CMS).
How To Choose the Best Python Framework To Use
Using a Python framework is a sure-fire way to speed up and optimize development. Python frameworks are not a must, but it would also be unwise to neglect the opportunity to enhance your development process where at all possible.
To figure out which Python framework is best for your software project, start by evaluating the different types of frameworks you can choose from. Three major categories of frameworks stand out: full stack frameworks, microframeworks, and asynchronous frameworks.
Microframeworks are small yet flexible; full stack frameworks are complex yet scalable; and asynchronous frameworks amplify Python’s capacity for concurrency.
Once you pick which class of Python frameworks is a good fit, you can narrow your choices down by focusing on the frameworks themselves. Listed above are 25 different frameworks with different capabilities.
You should choose a Python framework based on scalability, speed, your developers’ expertise in deploying framework-specific skills, and a number of other considerations that may be conducive to your business.
Going through each and every Python framework probably isn’t worth your time. But what you’ve learned here can better help you pinpoint exactly what you need.
What is a Python framework? It’s a tool to empower your next Python project, but only if you use the right one.
There are a diverse bunch of Python frameworks out there for you that will give you and your software development team a head start on your 2022 project. The Python framework world is your oyster.
Having a good understanding of how your next project will work, even if you're not tech-savvy, will be crucial to choosing the optimal tech stack to support your development.
Research is never a bad thing and if you need to consult with some of the more qualified minds in the industry, there’s no shame in it. That’s why Trio is here to help.
Trio can guide you in choosing the best Python framework for your 2022 project as well as build the project itself using the parameters you set.
Contact Trio now to hire the best Senior Python Developers and start your project today!
8 min read
Companies using Python choose the language largely because of its ease of use and high-level capabilities.
Developers can use the Python programming language for a diverse range of applications from building web apps to creating games, and even machine learning.
Because of Python’s versatility and dexterity, companies using Python are often global in scale. To better understand how Python can be useful for your own business, take a look at these 16 global companies using Python:
- Industrial Light and Magic
Throughout this piece, you’ll learn more about Python as a programming language and how it is implemented into the tech stacks of various major companies. Keep reading!
What Is Python?
Python is a high-level general-purpose programming language. Although you can use Python for front-end development, most developers agree that Python works best for back-end development.
Some other important features of Python are that it is dynamically-typed, garbage-collected, and interpreted.
As an interpreted language, this means that Python doesn’t directly translate programming into machine code as compiled languages do. While the disadvantage of this is slower execution at runtime, it does allow for dynamic typing.
Dynamically typed languages perform type checking at runtime. This means that type errors occur only once developers run a program.
But on the plus side, dynamic typing usually elicits more flexibility and more concise coding. And coders do not have to declare a variable expressly.
With garbage collection, Python can automatically manage the memory in a program by dumping any objects that no longer need to be referenced.
These details are just the nooks and crannies of Python’s overall architecture. What drives the global companies using Python to choose this language over others is likely Python’s design philosophy.
Guido van Rossum started designing Python in the late 1980s taking careful note to emphasize code readability in its structure and syntax.
This emphasis naturally results in improved productivity for developers, thanks to the intuitiveness and simplicity of the language.
Python’s use of significant whitespace, rather than the brackets that other languages tend to use to parse blocks of code, stands out as one of the defining features of the language. It’s a utilitarian example of how Python’s design philosophy works with the language in practice.
There is even a document called the Zen of Python summarizing several guidelines behind Python's core philosophy.
What Are the Advantages of Using Python?
There are many advantages to using Python. Below are a few of the main advantages leading companies using Python to choose the language for their tech stack in the first place.
Python is easy in more than one way. It’s easy to read, nearly replicating the English language in composition. Likewise, it is easy to write.
Of course, developers who can understand the code they’re writing do much better than those who don’t.
Global companies using Python can rest assured that their developers are spending less time in Stack Overflow and more time developing.
But besides basic comprehension, code that is easier to write is by definition high-yielding. For example, it takes fewer lines of code to perform a task in Python than using another popular, high-level programming language like Java or C.
In consequence, businesses can speed up development time and decrease their time-to-market (TTM), giving them more leverage to keep up with the competition.
Related reading: Python vs. Java: Side-By-Side Comparison
Like most programming languages, Python is free. It’s also open-source, meaning developers can modify elements of the language to their needs. But more importantly, Python is popular.
All the above characteristics contribute to the fact that the language is in high demand. Python is accessible, both in usage and syntax. And all the companies using Python only further this cyclical chain of demand and implementation.
Popular technologies strive because of their large and dedicated communities which offer tactical solutions to developers in need.
For your own benefit, note that an in-demand language will guarantee that you have a large pool of Python developers to choose from for your next Python project. The larger the pool, the less difficult it will be to find bonafide talent.
Judging from the growing list of global companies using Python, it’s clear that Python is scalable.
In this regard, Python’s utility for a wide array of applications truly shines. First of all, Python supports multiple programming paradigms, including structured, procedural, functional, and object-oriented programming (OOP).
OOP and class structures often serve as the foundation for large-scale software applications.
Python also has sound libraries for machine learning and artificial intelligence, exemplifying just how far-reaching the language is.
Data science is another subject in which Python excels, with financial technology routinely relying on the Python language.
Not to mention, Python is conducive for game development as well, with big names like Sims 4 and Eve Online owing their existence to the infamous Python.
In short, Python can do many things and most of the things Python can do are objectively exceptional.
16 Global Companies Using Python
Now that you have a greater understanding of what Python is and what it can do for your business, you can heed a closer analysis of how other companies are using Python.
Hopefully, Google needs little to no explanation. In fact, it’s fairly safe to bet that you’re using a product of Google, whether that’s your search engine, web browser, or both.
Python is one of Google’s official server-side languages, along with C++, Java, and Go.
Peter Norvig, the director of research at Google, and former director of search quality maintains that, “Python has been an important part of Google since the beginning, and remains so as the system grows and evolves.”
Facebook, the social network that doesn’t get enough credit for coining the ‘poke’, is one of the many companies using Python.
With a net worth of nearly 900 billion US dollars as of May 18, 2021, Facebook has gained mass popularity over the years. Therefore, understanding the technology behind Facebook’s success is essential.
The use of Python on Facebook’s back-end is mostly for production engineering, a specific sector of development at Facebook that combines systems and software engineering.
Essentially, the production engineering team is responsible for making sure that well over two billion people around the world can depend on Facebook to run smoothly. Python plays a pretty big part in this process.
Quora is a mix between a social media network and a question-and-answer platform.
Ironically, a question posted to Quora about the programming languages in use for the website prompted a reply from Adam D’ Angelo, the CEO of Quora himself.
D’ Angelo asserted that using Python was simply less “painful” than writing programs in another language like Java.
At the time, Quora engineers also believed that Python would evolve with the website, or in other words — scale up.
Considering that in 2020, Quora was able to garner 300 unique users per month to visit its platform, this certainly isn’t far from the truth.
Day by day, PayPal is helping people keep their money safe through convenient and secure transactions via the PayPal platform.
PayPal uses Python across its entire infrastructure and one of the most shared articles on Python, “10 Myths of Enterprise Python” is credited to the official PayPal Engineering writers on Medium.
Thus, if you enjoy using PayPal, keep in mind that PayPal is yet another global company using Python.
Though the name Stripe may seem unfamiliar, you might be using Stripe more than you know. Stripe is a fintech startup giving companies the ability to accept online payments.
Major companies such as Amazon and Lyft utilize Stripe as part of their platforms, making Stripe a major company itself; it is also another of the dozens of global companies using Python.
Using Python, Stripe built its application programming interface (API) for cross-compatibility with mobile applications and websites.
Instagram offers an alternative medium for social media where content is largely visual. Most of Instagram’s business logic relies on Python.
In software development, business logic refers to the operations occurring on the back-end that facilitate the exchange of data between the database and user interface (UI).
To put it simply, Python has a central role in how Instagram operates, powering the interactions of over a billion users daily.
Long gone are the days where you have to be worried about your phone, or even better, your MP3 player, running out of space because of all the music you have in storage.
Instead, there’s Spotify, which permits users to stream music for free. Spotify uses Python for its back-end services and for data analysis.
What’s more, Spotify sponsors international Python conferences, namely PyCon and Euro Python. From this, you can infer that Spotify is very eager about its use of Python.
Netflix is a content platform where users can binge-watch TV shows and films of all kinds from a singular web app. Users access Netflix from a smartphone, tablet, smart TV, or even a video game console.
The fact that Netflix is using Python is well-known and well-advertised. Several tech-oriented news sites have spoken enthusiastically about how Netflix uses Python, including Netflix’s very own tech blog.
Python is a facet of many internal structures of Netflix, including but not limited to:
- Open Connect, a content delivery network (CDN)
- Demand Engineering, a component of Netflix’s network availability that works to prevent latencies and improve user experience (UX)
- Experimentation, a platform to perform AB tests and other experiments
- CORE, a team that uses data analysis to alert relevant parties about system issues
- Animation & VFX, a subsection of Netflix for creating animated content and video effects
Uber started as a rideshare service with the aim to make passengers feel more secure in addition to extending convenience at a cheap rate.
Since, Uber has expanded its services to UberEats, a food delivery service.
Reddit is a bit of an underdog in the social networking community. Reserved for those who enjoy the pleasures of cruising internet black holes, Reddit is a network of communities formatted as a plethora of discussion forums and related subforums.
Steve Huffman and Alexis Ohanian, the two surviving co-founders of Reddit — Aaron Swarts being the third — presented at PyCon in 2009, naming Python’s large assortment of libraries as one of the reasons Reddit continues to use Python.
When Dropbox first became a technology of regular use, it was one of the original cloud services to go mainstream. Through Dropbox, users can host files of almost any sort and access them through the internet.
Engineers at Dropbox use Python for many reasons; the language’s cross-platform support, ease of learning, and readability are its biggest strengths.
The best way to describe Pinterest is to call it an online scrapbook. Users on Pinterest can share their interests by way of visual pins that depict their hobbies, design ideas, lifestyle inspirations, and more.
It might be hard to imagine that NASA is another name on the list of global companies using Python, but it is.
NASA, or the National Aeronautics and Space Administration, primarily uses Python in their Workflow Automation System (WAS) for shuttle mission planning and data management.
Python’s ease of use permits NASA to meet project specifications without being set back by unnecessary complexities.
NASA also uses Python for a number of other projects which can be found on their website summarizing NASA’s open-source projects.
Instacarts grants the average person the comfort of home-delivered goods. Grocery delivery was never so accessible.
With Instacart using Python and Ruby on its back-end, the logistics of allocating shoppers to buyers in an orderly and timely manner is not any more difficult than solving 2 + 2. (Okay, that’s an exaggeration, but you get the idea.)
Lyft is Uber’s doppelganger, if you will. But depending on the person, pricing, and location, there are different preferences all around as to whether Lyft or Uber can get the job done — that is, getting people from point A to point B.
In short, Lyft uses a lot of Python. The evidence? Roy Williams, the tech lead manager at Lyft, gets down to the dirt and grit of programming in Python on many of his Medium articles for Lyft Engineering.
16. Industrial Light and Magic
Star Wars fans should be glad to learn more trivia facts behind the franchise’s success. Industrial Light and Magic, for instance, is a visual effects company founded by the notorious George Lucas.
Without a doubt, Industrial Light and Magic, was and is a VIP in the making of the Star Wars films.
Python was a key element in moving towards more CGI-intensive filmmaking. Computer-generated images (CGIs) are the result of a revolutionary digital transformation that all science fiction lovers should be grateful for.
If the success of a major company serves as any justification for how well your business can use Python successfully, then hopefully these 16 global companies using Python served their purpose well.
Python is a developer favorite amongst programming languages because it has the ability to do grand things without overly complicating the code itself.
Figuring out what tools will ultimately further your business’s growth is a big decision. But you will need to have the right developers to use those tools, just the same.
Looking for qualified and experienced Python developers? Look no further. Trio is here to help.
Contact Trio now to hire senior Python developers!
8 min read