If you happen to work in one of these areas, it’s worth giving TypeScript a shot. And if you
Every craft has a set of tools that are needed to do the work. This is especially true in software development. Jeff Bezos has a great quote that says: “We first change our tools and then our tools change us.” Without tools, developers wouldn’t be able to do get their work done as efficiently.
There are a few other differences, like the fact that TypeScript has anonymous functions and asynchronous functions. Anonymous functions are a key feature of functional programming, which can make a program more efficient with big data loads.
Many data scientists deal with asynchronous and parallel programming. You might already be considering writing your next project in TypeScript rather than Python. Whether that’s a good idea depends on many other factors, though.
That leaves parallel programming and asynchronous programming on the table. Even though you can pull both of these things off in both languages, there is a big difference: in Python, you need to use particular libraries for the task. In TypeScript, all libraries are asynchronous from the core. And since the latter is a bit more functional by default, it’s often a tiny bit easier to do parallel programming.
On the other hand, Python has been adding more and more features of functional programming, too. And when it comes to data science, machine learning, and more, Python is at the forefront of frontiers.
Features like generics and static typing make it easier to do functional programming in TypeScript than in Python. This could be an advantage because demand for functional code is growing due to developments in data science, parallel programming, asynchronous programming, and more.