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Ira Gutnik is an accomplished Chief Marketing Officer (CMO) with a strong focus on technology and software development. With extensive experience in the field, Ira has established a reputation as a trusted thought leader in the industry.
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In the software development world, there are more than 100 programming languages that are jockeying for the attention of developers, CTOs, and product managers. While some of these languages are struggling to penetrate the market and maintain relevance, others have gained a solid reputation over time because of the unique features they offer their users. Among these, Python has earned a strong reputation as one of the best programming languages to use, but Is Python the best language for Startups ?
According to Statista, Python language is the world’s third most popular programming language (source). In fact, 38.9% of recruiters prefer hiring developers that have deep expertise in Python. So why is the Python language so good and popular among top startups and high-growth companies? And what challenges should be noted before getting started with Python?
This article will help you understand the pros and cons – and everything in between – of all things Python!
Want to skip to the end and save yourself the hassle of building a world class Python dev team?
Python was invented in 1994, two years before Java.
Python has become an extremely popular programming language because of its ease of use, simple syntax, wealth of libraries and frameworks, and code reusability. These features make coding with Python easy and cost-efficient for software development teams.
But it also has a number of domains where Python is the recognized leader, including:
Python is arguably the most heavily used programming language in the scientific computing and information fields. This is because it provides a variety of libraries, sources, and resources that come in handy for scientific research and data analysis, such as:
Machine learning encompasses machines imitating human actions in various things such as medical diagnosis, financial services, predictive analytics, image recognition, speech recognition, and even statistical arbitrage. This is made possible through Python’s PyTorch machine learning libraries and frameworks, which include two of the most well-known tools for clustering and model selection — TensorFlow and scikit-learn.
TensorFlow focuses on simplifying the creation of machine learning models for desktop, mobile, web, and cloud platforms for both novice and expert developers. Sci-kit-learn, also popularly known as sklearn, is a Python software machine learning library designed to work with Python’s scientific and numerical libraries, SciPy and NumPy.
Python is the closest candidate to be called the best programming language for AI (Source).
Python is also suitable for backend development because it offers numerous resources, including a wide range of web application frameworks. Depending on what you need for your web apps, a few to consider are Django, Flask, and others like Bottle, Tornado, Hug, and CherryPy.
Aside from that, Python is renowned for its simple syntax, shortcode length, and code reusability feature. These features make coding with Python easy and cost-efficient for business.
Python makes game development easy and less time-consuming. For instance, if you are creating a video game and decide to include a scripting image and thus create more flexibility, Python’s frame is the one you want in your backpocket. PyGame and other Python game libraries are perfect for this use case.
Do these terms sound more like names of hip bars than programming languages to you? Don’t worry—we speak Python.
Statistically, Python is the 4th most-used programming language in the world, with roughly 48% of developers employing it.
And besides the fact that it’s been around for over 30 years, there are lots of other good reasons that Python is so popular in the world. Below are the most prominent benefits that the Python programming language offers startups and high-growth companies:
Everyone likes free technology and Python does not disappoint on this front. Python operates an open-source and free-to-use model for individuals, as well as small, medium, and large-scale businesses. So don’t let cost be the reason you don’t choose Python…
In 2021, Statista estimated that there are approximately 10.1 million developers globally, and that number is increasing 15% per year. This means that finding developers that can deploy Python on your product’s behalf won’t be as hard or costly as using other platforms.
And this number is expected to grow even more: for the past decade, Python has maintained its position as the programming language developers desire to learn the most.
One big benefit Python offers software development teams is easy integration. In programming, Python is fondly referred to as a glue language because it can seamlessly integrate with a high number of other programming languages and technologies. The Python package index software repository creates a conducive environment for users to access numerous third-party modules, thus allowing them to integrate Python with other services seamlessly.
Python’s primary value proposition is simplicity, expressed in its lightning-fast development process. The reusable codes and resources made available (usually for free!) by Python’s large community makes coding in this language easier and faster than others. In fact, the speed of a single project rises by several times thanks to the availability of its broad range of applications.
As a result, it usually comes in handy for tech leaders who want to launch a new feature or product as soon as possible without blowing out timelines or budget.
Python provides top-notch libraries that you can utilize to save energy and time in the beginning stage of development. Furthermore, a large number of cloud media services provide cross-platform support via tools resembling libraries, which can be quite helpful. Python’s SciPy and NumPy, Django, and other widely used libraries are only a few examples. There are additional libraries with a particular specialty, such as scikit-learn for machine learning applications or nltk for natural language processing.
All of these ready-to-launch modules, packages, components, libraries, and frameworks are available on The Python Package Index website. All of this means that developers can substantially lower coding time by utilizing these resources, as many essential programming tasks have already been scripted and incorporated into the libraries. This helps lower the overall cost of the development and speeds up delivery time.
Bugs bloat software costs–plain and simple. Indeed, the Consortium for Information and Software Quality estimated that poor software quality cost US companies $2.08 trillion in 2020, meaning it’s likely even more now.
And it’s not just one industry that’s suffering—businesses across the board have experienced losses from buggy code, particularly in legacy systems.
Moreover, developers hate getting overwhelmed by bugs at the final stage of a product’s development. Thankfully, Python has this problem figured out—it includes a built-in frame that enables unit testing.
This feature allows developers to test small code fragments long before the application reaches the final stage. As a result, developers are faced with less bugs in the finished product. In addition, this feature allows developers to spend less time fishing out code flaws, producing higher quality codes, and increasing the product’s speed to market.
Python is versatile enough to be used in a wide range of environments, including those for hardware programming, web development, desktop programs, and mobile applications. As a result Python is typically more scalable than most contemporary languages.
Moreover, Python can be used in almost any setting without experiencing any performance issues. Also, the flexibility of the Python language allows programmers to experiment with new ideas quickly and efficiently.
Python’s versatility and wide-ranging frameworks that fit into most programming tasks mean it can be used for a wide range of tasks other than software development. It especially helps make the work of researchers, data scientists, data engineers, QA engineers, and DevOps specialists seamless. And outside of the software industry, Python is utilized for statistical arbitrage, medical diagnosis, and financial analysis.
One of the most vibrant programming language communities in the software development world is the one for Python developers. Because Python was developed more than 30 years ago, it has had plenty of time for the community to evolve and mature which helps programmers, developers, and coders at all levels, from novice to expert.
Learners and developers of all ages and ability levels have access to a wealth of documentation, guides, and video tutorials for the Python programming language, which they may use to further their understanding and expertise. And if they ever run into a problem with the Python language, they have a huge resource pool at their disposal.
Python has readability ingrained in its core, as the usage of extensive indentation and its design philosophy emphasizes code readability. Python’s syntax makes its code more like plain English, unlike most other programming languages. This similarity between Python and English makes it easier for many people to learn, read, and remember versus other programming languages.
And Python even takes it a step further by helping Python writers create clean, understandable code. Python can also be used to create large, commercial applications because it offers scripting.
Because Python has a more straightforward syntax than any other programming language, it is regarded as the most expressive and user-friendly of its peer group. Python is thus recommended for those who are new to the field because it is simple to learn and utilize, making it possible to write and execute code quickly.
The Python programming language is highly portable, hence its use within virtually every current operating system for laptops. For instance, if you already have Python code written for Windows and wish to execute it on Linux, Unix, or Mac, you can do so without making any modifications or changes to the code. This is because of the high-level nature of the language and the fact that it is interpreted. Thus, writing the same program in different versions for many platforms is unnecessary.
Three of the biggest topics in modern computer science—Cloud Computing, Machine Learning, and Big Data—all use Python extensively. AI, data science, robotics, ML and other cutting-edge technical fields all heavily rely on Python as one of (if not the) core programming language.
With more programmers and developers using Python for its numerous applications (such as Deep Learning, Data Science, Artificial Intelligence and more), it is now regarded as the primary programming language taught in schools and colleges.
Schools and universities teach the Python language because it is now a critical component of software development. This also creates a virtuous cycle in that the more students that know Python the more colleges will want to teach it, further expanding the programming language’s popularity.
Developing prototypes of testing and debugging tools, as well as dynamic and static analyses, can be implemented quickly and efficiently using Python. Also, Python’s speedy development and sturdy design make it a good choice for creating Minimum Viable Products (MVPs), which aid entrepreneurs and startup folks in making fast iterations based on early customer feedback.
Python also offers a vast infrastructure to handle programs, solve constraints, and parse data. All told, the product completion process is sped up by including ready-to-use packages and modules.
There is a package for everything in Python—if you need something, it likely already exists. In fact, you can find more than 147,000 packages if you visit Python’s package repository, also affectionately known as The Cheese Shop.
In short, developers benefit from not having to constantly build functionality from scratch on Python. The packages can easily be used and implemented for any project you desire, regardless of the experience level of the developer.
Get the very best of the very best Python developers.
Though the Python programming language offers a cornucopia of advantages, nothing in life is perfect. So if you choose it, keep these hitches in mind to avoid running into difficulties while programming:
For startups and high growth companies, finding the right programming language is critical. Compared to other programming languages, Python stands out as the most popular programming language and the favorite for beginners. The table below shows the key differences between Python and other programming languages.
Finding experienced Python developers to build your world-beating software is essential. And on this front you have a range of options, with each having their pros and cons:
There are lots of freelance Python developers on various online platforms like Upwork, LinkedIn, and Freelancer. But since they only work part-time for you, timelines are hard to manage and you can’t totally control the outcome. Moreover, freelancers often churn frequently, meaning you won’t have consistency of development over time.
Creating a Python team in your home country is a great option if you can afford it since it enables close collaboration. But outside of the typically higher salary expense of hiring onshore, an even bigger challenge is finding available Python developers in the first place given the stiff competition for this skillset.
You could decide to outsource your Python development to a company that will handle the entire process from start to finish. But these work-for-hire agencies usually have a short term mentality when they are building code (since they primarily do project-based work), resulting in lower quality code or at least code that is not built from the beginning with scale in mind. Moreover, since you don’t control the team, you have little say in which developers come on and off your project.
If you want to find great Python developers that are 100% dedicated to you – and at rates you can afford – then go global with TurnKey. We can assemble a team that is built around your unique needs, timelines, budget, and culture–and one that is constructed for the long-term.
In short, offshoring offers all the benefits of the options above, with none of the downsides. With TurnKey developers in either Eastern Europe or Latin America (you choose what’s right for you!), you get a team that you fully control and that are committed to your goals and objectives.
And all of this is paired with our white glove customer service. If there is any problem at any time, just pick up the phone and speak with our Silicon Valley-based account team. Thus, you never have to worry about being left in the dark by an offshore or outsourcing agency again.
If you’re ready, we’re ready. Let’s build a powerhouse Python team together.
The top use cases for Python are Machine Learning and AI, Data Science, Game Development and Backend Development. But Python's versatility and abundant pre-built frameworks means that the language can be used for a broad range of applications.
Python is usually preferred by startups since it allows you to create sophisticated software with relative ease. The syntax is clear, the code structure is straight to the point, and writing within Python is simple. As a result, Python helps speed up release of the app or feature being developed.
Due to its slow processing speed compared to other programming languages, Python is not regarded as being an ideal language for creating mobile apps or for multi-threaded software development. Moreover, the Python programming language's database access layer is rudimentary compared to other languages, making it a more difficult choice for companies that need seamless interaction with complex legacy data.
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