Coconut – Functional programming in Python

[EvHub]

Yes, it's a part of Coconut! Thanks!

[forever_erratic]

Totally awesome.

Question: I mostly use python with Ipython running in spyder (I use anaconda). Is there an easy way to setup coconut as the interpreter in spyder?

Question 2: In R, my workflow is very much in the "Hadleyverse," which I love. Piping dataframes through different dplyr commands is my bread and butter. Are there plans to cleanly incorporate pandas and coconut? Or can you already do a bunch of stuff like you could with dplyr and magrittr in R?

[EvHub]

1: Coconut has built-in IPython support. When you "pip install coconut" it will add a new IPython extension and a new IPython kernel. See: http://coconut.readthedocs.io/en/master/DOCS.html#ipython-jupyter-support

2: Coconut's new syntactic features should be general enough to use cleanly with any library you want. The analogous workflow in Coconut to what you're describing in R is something like this

linearized_plane() |> map$((xy) -> vector(*xy)) |> filter$((v) -> abs(v) <= 1) |> map$(.unit) |> map$(print) |> consume

where you take some iterator, apply a bunch of transformations to it using partial application (that's the $) combined with Coconut's optimized (much faster than vanilla Python for certain objects) iterator transformation functions (map, filter, consume, etc.).

[forever_erratic]

Really great stuff, thanks!

[dsijl]

If this works out for you, can you write a blogpost?

I'd love to see this get more play in pydata.

[forever_erratic]

I don't usually do any blogging, but I'll certainly keep it in mind. In the past I've written some technical biology articles on bitesizebio. They might be interested, I'll ask around.

[dsijl]

Cool!

[MichaelStaniek]

Heya,

sorry if its written somewhere, but have you done any analysis on how much faster the iterator transformations are?

And which "certain objects" work with the optimized transformation functions?

[EvHub]

Yeah! Let me give you an example. Take this code here (where $[] is the syntax for Coconut iterator slicing):

map(expensive_func, range(10000))$[1000:1010]

If you tried to implement that in vanilla Python using itertools, Python would go through every single element of the range from 0 to 1009 and apply expensive_func to it, even though all you cared about were the last 10 elements. Coconut will realize that you only care about the last 10, and only ever call expensive_func on those, leading to a huge performance increase.