evhub/coconut

Simple, elegant, Pythonic functional programming.

Evan Hubinger

@evhub

@henningsway Theoretically, VSCode supports TextMate syntax highlighting, which already exists for Coconut here—though I don't know how to get VSCode to use that file (I don't use VSCode myself). If you figure it out, I'd appreciate it if you could create a package or at least put the instructions here and I'll add them to the documentation.

kobarity

@kobarity

@evhub, I just published a VSCode extension kobarity.coconut based on your Coconut.tmLanguage. Thanks for your great work.
Actually, another extension based on the older version of Coconut.tmLanguage already exists, but it seems not maintained.
My new extension supports syntax highlighting on Coconut files and in Coconut code block in Markdown.

kobarity

@kobarity

@henningsway, I tried VSCode Insiders and could select Coconut kernel. First I installed the extensions Jupyter, Python and Coconut. Then I connected to a remote Jupyter server, and selected the Coconut kernel.

Evan Hubinger

@evhub

Thanks @kobarity! I'll add that to the documentation.

Uroš Nedić

@urosn

Does Coconut support typeclasses?
Does Coconut suppory Unicode function names (combined with infix notation we can do very modern things)?

Evan Hubinger

@evhub

@urosn For typeclass-like syntax, you can use addpattern to match a different function depending on the input type, e.g.

match def to_json(x is str) = repr(x)
addpattern def to_json(x is int) = str(x)
addpattern def to_json(x is list) = x |> map$(to_json) |> list |> str

For unicode function names, Coconut supports PEP 3131 if given --target 3 (or above) and also supports a host of unicode alternatives to built-in operators.

Evan Hubinger

@evhub

Currently, as per PEP 3131, non-alphanumeric variable names are disallowed, though Coconut could theoretically add support for them if there's a compelling use case—feel free to raise an issue for that if you want it.

Also, for typeclasses, you can always just use typeclasses or something, though addpattern is probably going to be better than any library like that if you're working in Coconut.

fakuivan

@fakuivan

Hello

I'm using coconut as a replacement for the python kernel on jupyter

It's been great so far

There were some issues with the specs in kernel.json though, I installed coconut with pip3.9, but the argv array only refered to "python" and not "python3.9" or to the full path

Also, is there an analogue to toolz's valmap function?

fakuivan

@fakuivan

coconut is great, thanks for making this c:

Evan Hubinger

@evhub

@fakuivan If you run coconut --jupyter, it should automatically install a coconut kernel for the version that you run that command under. As for valmap, you can use fmap:

def valmap(val_func, input_dict) = input_dict |> fmap$((k, v) -> (k, val_func(v)))

fakuivan

@fakuivan

Wait
Does fmap know to destructure (the key, value) tuple?

the (key, value)*

Evan Hubinger

@evhub

yep! that's how fmap works on abc.Mapping objects.

servadestroya

@servadestroya

Hello

Is it possible to define fmap on new types?

Like addpattern fmap(f, obj is MyClass) = obj.map(f)

oh I see

the fmap dunder

it would be nice to have fmap be a pattern matched function so that this functionality could be added to third party libraries

Evan Hubinger

@evhub

@servadestroya __fmap__ is the way to do it, yep. If you want to add fmap support to a third-party object, you can always monkey-patch in an __fmap__ with

def ThirdPartyObject.__fmap__(self, func) = ...

Alternatively, if you want to use pattern-matching, you could also just define your own new fmap with

match def my_fmap(obj is ThirdPartyObject, func) = ...
addpattern def my_fmap(obj, func) = fmap(obj, func)

Pedro Queiroga

@pedroqueiroga

Hello friends, is this a bug?

>>> [-1] + rest = [-1,2,3,4]

CoconutParseError: parsing failed (line 1)

Coconut: Version 1.5.0 [Fish License] running on Python 3.9.2 and Cython cPyparsing v2.4.5.0.1.2

Evan Hubinger

@evhub

@pedroqueiroga Definitely a bug, but I just tested it on the latest coconut-develop and it looks like it's already fixed, so just pip install -U coconut-develop to get the fix.

anthonymccanny

@anthonymccanny

Hey all, I'm really new to coconut, and I think this is the right place for this question, but if I'm wrong, let me know.
Is there anyway in coconut to pipe an object and then call a method of that object, passing one of that objects' attributes as an argument of the method?
This question really arises from using pipes with pandas where I want to use a pipe to process a dataframe, and in that pipe change the index of that dataframe and then later access this new index as an argument within a .groupby() call or something similar. Of course I could assign a new dataframe variable, and complete this task but I was hoping there was a way to avoid it.
Here is a simple (and useless) example of what I'd like to do:

class A_Class:
    attribute = 1

    def method (self, argument):
        print(f"The argument is {argument}")

an_object = A_Class()

an_object |> \
.method(.attribute)

Output: The argument is operator.attrgetter('attribute')
My Desired Output: The argument is 1

Is there anyway to do what I'm trying to do? Am I misunderstanding something crucial? Thank you!

Evan Hubinger

@evhub

@anthonymccanny I think you probably just want to use a lambda for that case—so maybe something like:

result = (
    an_object
    |> o -> o.method(o.attribute)
)

anthonymccanny

@anthonymccanny

Thank you Evan! That is a great idea that I hadn't considered.

Gianpiero Cea

@GianpieroCea

Hi everyone, I am super new to Coconut and from what I can see it seems amazing. Anyway , my goal would be to use coconut for doing data science , I am very jealous of R's dplyr style pipes and so coconut seem to fix. I am pretty sure I am not the only one (I can see the question above is on how to work with a pandas DataFrame). My question: is there any tutorial for coconut with a focus on doing data science ? I do like the case studies on the documentation but they are very much "computer sciencey" in style, which is absolutely fine, is just that if you don't have a too strong background in functional programming I think it's difficult to see the advantage that coconut can bring to doing data science. Looking forward to hear your opinion on this :)

Evan Hubinger

@evhub

@GianpieroCea I don't know of any Coconut tutorial that specifically focuses on data science--you could try going through this tutorial (https://hmcfabfive.github.io/coconut-tutorial/) though, which isn't specifically focused on data science but might be more of what you're looking for.

Gianpiero Cea

@GianpieroCea

not what I was looking for but definitely a nice resource I had not seen before. If someone that has been using coconut to do data science for a while and has a blog post or something on best practices or cool example of coconut in action I would still like to see it. Thanks a lot Evan.

Ishaan Verma

@lazyprop

Hi! I was looking for a VI-Mode for the Coconut REPL. I couldn't find any such configuration option in the documentation or the FAQ. I took a look at the source and there is prompt_vi_mode in constants.py and it is initially set to false. How do I set it to true? (without changing the source obviously)

Also, I find it weird that Coconut doesn't use GNU Readline like the Python REPL. Just out of curiosity, is there any specific reason for that?

Evan Hubinger

@evhub

@lazyprop You should raise an issue for adding a flag/environment variable for enabling vi mode; it should be pretty easy since it's just that constant that you found. The reason for using prompt toolkit over readline is primarily for the syntax highlighting, though it's also just generally a pretty good prompt framework--it's the same framework that's used by Jupyter console.

Ishaan Verma

@lazyprop

alright I'll raise an issue and maybe open a PR

vip-ehowlett

@vip-ehowlett

Does Coconut support discriminated unions?

Evan Hubinger

@evhub

@vip-ehowlett No—Coconut just uses Python's type system (with a couple extra bells and whistles), which doesn't support anything like that.

vip-ehowlett

@vip-ehowlett

That's a shame. Disc. unions are one of my favorite features. Really liking coconut, though. I feel like just having pipe operators makes downloading it worth it. There's so much conciseness that comes from them.

What's the state of the language server implementation? I have some highlighting but almost no type-hinting in VSC. I've never tried to implement one but is that something you're looking for help on?

Evan Hubinger

@evhub

@vip-ehowlett If you have an idea for what a discriminated union implementation might look like in Coconut, feel free to raise an issue for it—that's definitely something I'd be interested in looking at trying to add. As for the language server, a language server isn't something I'm working on now or planning on working on in the near-term future, but it's definitely something I'd be pretty excited about having—I'd be happy to at least provide some guidance. Theoretically, it shouldn't be that hard, since you can just use an existing Python language server and map the results back and forth between the Python source and the compiled Coconut, but there could still be a lot of issues there like getting the right column mappings, compilation latency being an issue, etc. Also, if you want to take a look at the existing VSC package that just provides syntax highlighting, you can find that here.

vip-ehowlett

@vip-ehowlett

We could for sure use a lot of the Python language server, however, on top of what you said, I also see an issue with code completion/type inferencing when using the superset.

As for the implementation of disc. unions, that'd be a little clunky. Trying to think of something that'd run in all versions, we'd compile a class with an array of the field names and then when we match, we'd essentially just be matching on values in that array for which we can return self.field. I'm pretty sure type inferencing on that would be out the window, though.

Evan Hubinger

@evhub

@vip-ehowlett What would that discrete union implementation give you that something like

data Empty()
data Leaf(n)
data Node(l, r)

Tree = (Empty, Leaf, Node)

def size(Tree()) = 0
def size(Tree(_)) = 1
def size(Tree(_, _)) = 2

doesn't give you?

vip-ehowlett

@vip-ehowlett

You have to know the structure of the tuple with this. I"m not sure how often the case would be, but with the other implementation, you can just match on the name of the tag.

Evan Hubinger

@evhub

@vip-ehowlett Coconut can also do

Tree = (Empty, Leaf, Node)

def size(t is Tree) = 1 + sum(map(size, t))

where you don't have to know the structure of the tuple, if that would solve your use case.

vip-ehowlett

@vip-ehowlett

It might.

I usually use discriminated unions to wrap possible function arguments. Below is what I was hoping for.

possible_args = ( option1: str, option2: int, option3: MyCustomDeeplyNestedObject )

def my_function( args : possible_args ) :
     match args:
         case str instance_variable: exprs / stmnts on strings
         case int instance_variable: exprs / stmnts on ints
         case MyCustomDeeplyNestedObject instance_variable: exprs / stmnts on MyCustomDeeplyNestedObject

But I'm not sure if I can use is in that match statement. That would be checking to make sure the variable refers to the same object reference, right?

Where communities thrive

People

Repo info

Activity