When I first started using Python around 1999, it didn't even have list comprehensions. Code was extremely consistent across projects and programmers because there really was only one way to do things. It was refreshing, especially compared to Perl. It was radical simplicity.
Over the decade and a half since then, the Python maintainers have lost sight of the language's original elegance, and instead have pursued syntactical performance optimizations and sugar. It turns out that Python has been following the very same trail blazed by C++ and Perl, just a few years behind.
(At this point Python (especially with the 2 vs. 3 debacle) has become so complex, so rife with multiple ways to do even simple things that for a small increase in complexity, I can just use C++ and solve bigger problems faster.)
It's certainly up for debate whether named tuples and enums, various kinds of metaprogramming and decorators might be making the language more complex for fairly little gain... but this article talks about the `enumerate` function, about string formatting and dictionary comprehensions. Simple, straightforward stuff with no downsides.
But syntax matters! When you're writing stuff all day,
a = [_ * 2 for _ in range(10)]
is a lot more pleasant than:
a = []; for _ in range(10): a.append(_ * 2)
It also gives Python a lot more information about your actual intent. Suppose "range(10)" were actually "giant_list". Hypothetically, the list comprehension could pre-allocate len(giant_list) elements instead of calling list.append that many times. That's potentially a huge performance win.
You see Python as getting more complex. I see it as getting less complex by giving concise alternatives to common idioms.
When I first started using Python around 1999, it didn't even have list comprehensions. Code was extremely consistent across projects and programmers because there really was only one way to do things. It was refreshing, especially compared to Perl. It was radical simplicity.
Over the decade and a half since then, the Python maintainers have lost sight of the language's original elegance, and instead have pursued syntactical performance optimizations and sugar. It turns out that Python has been following the very same trail blazed by C++ and Perl, just a few years behind.
(At this point Python (especially with the 2 vs. 3 debacle) has become so complex, so rife with multiple ways to do even simple things that for a small increase in complexity, I can just use C++ and solve bigger problems faster.)