In my experience, high-level languages like Python not only reduce application development time, they also improve maintenance time (which may be even more important). And it definitely doesn't make any sense for you to start programming an implementation of lists and dictionaries in C for your application, when you already have them implemented in other languages natively.
Python does not reduce application development time because of list datatype; but because of good availability of large-granularity libraries: meaning, it is simple to do a large task by a simple call to a library.
A honest question though: if application developer writes 20 lines of Python, which runs 100 000 lines of C code, is the application "written in Python" or "written in C"?
And that question is relevant because Python is really an interesting exception. Most other programming languages can implement their own core libraries in said language itself. For example, Erlang libraries can be written in Erlang. C# libraries can be written in C#. Rust libraries can be written in Rust. Ada libraries can be written in Ada.
But Python libraries are written in C, and this is because Python and its runtime is colossally inefficient; and while it is often said that speed is not always primary aim, when something is really 100 to 1000 times slower, that is too slow. So Python really is
frontend to C libraries. Which, when you think about it, kinda makes sense, because:
In that context "easily usable" excluded C and C++.
this is kinda true. Especially for inexperienced programmers or very small projects (throwaway code), integrating existing C (and C++ is much worse) libraries is somewhat tedious. You can get used to it but I understand the need for a "C frontend", what Python really is. It allows mixing very large granules (like, a library which does a lot of image processing on a single call) and mid-sized granules (like matrix operations) of library operations,
all written in C. And because the granularity is large enough, execution speed is decent: CPU is mostly executing native binary code (compiled from C) and only occasionally coming back to the Python interpreter.
As soon as you try to do so-called
systems programming on Python - or develop a new algorithm from scratch which has to do customized data crunching e.g. a lot of looping or recursion - you realize that Python is completely incapable of doing that. But you can do it in C, and add Python bindings to it.
The reason for Python's popularity is not that it's "better than C". Hundreds of languages are "better than C". Python is popular because it has efficient way of C bindings. Python gives easy access to software written in C, without having to write C.