Python is a powerful, high-level, object-oriented language that can be used to build any application. It was developed by Guido van Rossum in the 1980s when he envisioned a successor to the ABC language. Subsequently, the world got its first Python release in 1991.
Python was created from the ground up to be one of the easiest languages to learn. Its development was based on a set of design philosophies enshrined in the document The Zen of Python. Among the many principles are “readability counts” and “beautiful is better than ugly.”
As a result, Python has an incredibly simple syntax that’s very close to English, thus making it intuitive for beginners to understand. An added benefit of this is that Python is also very readable, facilitating debugging and collaboration between developers.
But despite the perceived simplicity, Python is used in many complex applications. For example, it’s a favorite among data scientists and mathematicians for building their software without getting bogged down with the programming.
The reason for this phenomenon is two-fold.
The first is that it’s incredibly fast to program in Python. Thanks to the ease of use and readability, developers can easily churn out advanced software in record time. This is also a boon for rapidly testing ideas through prototypes and MVPs (minimum viable products).
The other is that Python is highly extensible. In reality, the language only has a small core, with most of its functionality included as modules and third-party libraries. This allows developers to build applications without having to code key functions from scratch. Thus, Python code tends to be concise. And thanks to Python’s big community, chances are that there’s already a library for virtually any function you need.
Python, of course, isn’t without its cons. One of the biggest is speed. Python is interpreted line by line, which can lead to slower execution. This makes it less ideal for real-time applications where speed is paramount.
Not surprisingly, the speed issue also makes Python less popular for mobile applications. Now, there are libraries like Kivy and BeeWare that facilitate the development and performance of iOS and Android apps using Python. However, the performance is still inferior compared to languages like Java and Swift.
Python also supports asynchronous programming, albeit indirectly through coroutines. Though not as efficient, Python’s approach seems to be good enough for large-scale apps like YouTube.
Python is the preferred language if you plan to enter into “number-crunching” applications like data science and artificial intelligence. This is also why it’s a popular language for fintech, especially when financial modeling and forecasting are involved. Not to mention Python is also a popular language for enterprise-level web development and ERP systems.
In the end, it all comes down to your project and needs. Unfortunately, knowing which programming tool to pick isn’t always straightforward. It’s better to get the advice and opinion of an experienced developer to guide you through the process.
Expedition Co. is not just a developer you hire for a project, but a true collaborator to bring your vision to life. We flesh out the requirements, product, and launch plan to ensure that your web project has the best chance to succeed. And as a full-stack developer, we know the best tools for your front and back-end needs.
Interested in collaborating with us? Get in touch today to learn more about our web development services, and let’s start a conversation.