Python's value to me has always been that it's easier to get things done, not it's speed. One time when I was interviewing a candidate for a coding job, the candidate said she loved Python the most "because you can just yell at it and it'll work."
It's both the breadth of the standard library and ecosystem, and the simple language design, that make developing things in Python faster for me.
Doing problems on Project Euler has been an education for me in how algorithm matters more than speed. Lots and lots of people spend hours writing long C++ codes that are easily beaten by a few lines of Python. It certainly goes the other way too, and the wrong algorithm in Python is even that much slower and more painful than the right algorithm in C++. But when the right algorithm is used and the problem is solved in a few milliseconds, it really doesn't matter which language uses more CPU cycles, all that matters is whether you saw the insight that let you skip 99% of the search space, and how much time you spend writing code.
It's both the breadth of the standard library and ecosystem, and the simple language design, that make developing things in Python faster for me.
Doing problems on Project Euler has been an education for me in how algorithm matters more than speed. Lots and lots of people spend hours writing long C++ codes that are easily beaten by a few lines of Python. It certainly goes the other way too, and the wrong algorithm in Python is even that much slower and more painful than the right algorithm in C++. But when the right algorithm is used and the problem is solved in a few milliseconds, it really doesn't matter which language uses more CPU cycles, all that matters is whether you saw the insight that let you skip 99% of the search space, and how much time you spend writing code.