Python and its applications
Why Python?
Reasons for its success
Python’s success stems from several of its characteristics. It is fast to learn, highly versatile, and expressive.
Being a high-level, concise language allows developers to write code quickly and reduce boilerplate.
Python is interpreted and highly portable, and projects like Cython can be used to build native extensions when performance is critical.
Python is often described as a “glue language” because it makes interoperability between different codebases straightforward. This helps mitigate the performance gap with compiled languages where necessary.
Another important factor is its large community. A rich ecosystem of libraries and many previously solved problems on sites like StackOverflow make it easier to build solutions.
Applications
Python is widely used in domains where rapid development and rich libraries are more important than raw performance. Example areas include:
- Data Science
- Loading, processing and plotting of data – Web development (backend)
- frameworks such as Django, Flask, and Sanic
- Scientific and Numeric Applications
- Modeling
- Artificial Intelligence and Machine Learning
- Image and Text processing
- Scripting
Python in numbers
Let’s look at some figures from the StackOverflow Developer Survey (2020).
Popularity
According to the survey, Python is among the most popular programming languages, after JavaScript and TypeScript.
User friendliness
Python is also highly rated in developer satisfaction (the “most loved” metric).
Salaries
Salary figures in the survey place Python developers in the mid-range (survey numbers vary by role, region and experience). Interpret these figures cautiously: pay depends heavily on job function and location.
