Toolz is really a game changer since it allows you to write elegant functional code (lazy evaluations, currying, pipes, parallelism) in Python which feels native.

As python has the "batteries included" philosophy, such useful gems should be included into the standard library...

I will kind of disagree.

While having stuff in stdlib can be convenient, it all tends to be where active development goes to die. Compare httplib with something like Requests.

The comparison would be with urllib.request:

https://docs.python.org/3/library/urllib.request.html

Which right there recommends Requests, but for simple tasks it's kind of unfortunate that people bring in a library dependency.

Can anyone comment on the efficiency or lack thereof of toolz?

It uses `itertools` internally very heavily, which means if you generally are using generators and such, you maintain those benefits, as well as get to work with infinite sequences, etc.

If you do find a `toolz` function to be too slow, there's always the `cytoolz` versions.

cytoolz’s frequencies was around 10x as fast as using a vanilla dict and counting elements manually, which was in turn twice as fast as collections.Counter when I measured them a few years ago.

It’s solid work.

How does cytoolz performance compare with toolz under PyPy?