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gilch

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Why Hissp?

hissp.readthedocs.io

3 ポイント投稿者 gilch4 年前0 コメント

Show HN: I made a Lisp that transpiles to Python expressions

github.com

2 ポイント投稿者 gilch5 年前1 コメント

Covid 1/28: Muddling Through

thezvi.wordpress.com

1 ポイント投稿者 gilch5 年前0 コメント

Hissp

pypi.org

3 ポイント投稿者 gilch6 年前3 コメント

Hissp – A Lisp-Flavored Python

hissp.readthedocs.io

4 ポイント投稿者 gilch6 年前2 コメント

Learn to write Lisp macros in Python

hissp.readthedocs.io

4 ポイント投稿者 gilch6 年前0 コメント

Show HN: Hissp. It's Python with a Lissp

github.com

4 ポイント投稿者 gilch6 年前1 コメント

コメント

2 年前議論

C macros are just a text preprocessor. You could run the C preprocessor on a text file and have the result be Python code. Comments might be a little tricky, but it's doable. Or you can run a text file through a general-purpose one like m4.

For sum types we have enums, and for product types we have tuples (or namedtuples or dataclasses). Sugar could be done with decorators or metaclasses.

For Lisp macros, there's macropy and Hissp.

https://www.gnu.org/software/m4/

https://threeofwands.com/algebraic-data-types-in-python/

https://github.com/lihaoyi/macropy

https://github.com/gilch/hissp

2 年前議論

> I loved Lisp, but none of the lisps have anything like Python's ecology.

Try Hissp (https://github.com/gilch). Lisp programming and Python's ecosystem.

3 年前議論

No commits for a year? https://lolg.it/amber/amber Is it dead?

3 年前議論

Python is great for API discovery. `dir()` and `help()` are builtins. Use the REPL.

3 年前議論

That is the right answer. While some comparisons have been written already, they're somewhat out of date. Hissp could use a new writeup. Let me know if I can answer any questions about Hissp, and when your blog post is ready :) You can reach me at the Hissp community chat channel on Gitter's Matrix: https://gitter.im/hissp-lang/community -- share your Hissp experience or get support.

3 年前議論

As the Hissp author/maintainer, I'd be interested in hearing about your take on Hissp's practicality (or lack thereof) in more detail.

3 年前議論

Not accurate as worded. Python caches module imports in `sys.modules`, so all imports get the same one. A `reload()` will reuse the same dict object that was being used as the module's namespace, so everything with a reference to the module object will see the same namespace and get the updates.

3 年前議論

What? Yes you can. I do it all the time.

    import code; code.interact(local=vars(foo))

where `foo` is the module object you want to set as current. This launches a subREPL in that module's namespace. (EOF kills the subREPL and returns to main.)

Python has a debugger in the standard library that can also do post-mortem inspections.

3 年前議論

You might be interested in Hissp, a Lisp with access to the breadth of libraries available to Python. https://github.com/gilch/hissp

3 年前議論

> I would certainly take Python's huge ecosystem over Lisp's metaprogramming.

You can have both with Hissp. https://github.com/gilch/hissp

3 年前議論

A class of old-school AIs: https://en.wikipedia.org/wiki/Expert_system

I made a small one that classified dinosaurs in school.

3 年前議論

> wanted to expand beyond python. [...] Have been trying to learn about Lisp lately and feel like I've come to a similar dead end.

If you're already comfortable with Python, check out Hissp's tutorials (in the docs). It's a Lisp hosted on Python, so you can focus on the Lisp concepts without getting so bogged down by learning a new standard library at the same time.

https://github.com/glich/hissp

3 年前議論

I didn't really like "Learn You a Haskell". "Haskell Programming from First Principles" or "Haskell from the Very Beginning" might be more accessible.

3 年前議論

> I'm interested anything else strange from the lisp world if people have references.

Hissp just released version 0.4.0. It compiles Python tuples to Python expressions and has multiple readers with different characteristics, not all of which are based on S-expressions.

https://github.com/gilch/hissp/discussions/182

3 年前議論

Clojure has had pretty remarkable stability over the years. Maybe Common Lisp even more so, since it's based on a standard that hasn't been updated.

3 年前議論

One can learn a lot about programming by talking to ChatGPT. Sure, it has a bad habit of making stuff up, but you can run the code to see if it works.

3 年前議論

> And last but not least, what should I do about the fact that I have never used smartphones (iPhone/Android) and I have no interest in them, when the vast majority of my students will only have such a "computer"?

Android is basically Linux, which is great for development. You can install the Termux app (https://github.com/termux/termux-app) on Android phones, then you have a shell and a decent package manager. You can install compilers and interpreters and text editors. Python, Emacs, and so forth. (And shell is a scripting language in its own right.) The Play Store version of Termux is kind of crippled, so you'd want to sideload. It might be easiest to sideload the F-Droid store first and install from there. Recent versions of Android (12+) also aggressively kill processes to save battery life, which makes Termux much less usable. It takes some technical know-how to turn that off, but there are instructions linked in the Termux repo.

I'm less familiar with the iPhones, but they're a lot more locked down. I'd expect Android phones to be more common because they're cheaper, but sufficiently old iPhones are not that expensive either. There are some iOS IDE apps, but I don't think they're quite as complete as Termux can be.

Single-board computers like the Raspberry Pi are fairly cheap and can run Linux. I think even iPhone users can ssh into a server. Linux is multi-user, so students could share. Simple command-line apps don't require a very powerful computer by modern standards.

There are also a number of online IDEs that would only require a decent web browser. Some of them might be compatible with iPhone Safari. I'd consider JupyterLite, which is free and runs entirely in-browser. https://github.com/jupyterlite/jupyterlite

3 年前議論

It occurred to me that ChatGPT (or the like) might be able to help students find their mistaken assumptions without taking as much of your time, at least if it's in a well-known language like Python. Being able to dialogue with these new AIs will probably become an important programmer skill anyway. However, if they use it as a crutch to avoid developing their own mental models, it could be net harmful. An outright ban is probably unwarranted, but they eventually need to be able to code without the assistance. If you have a small enough number of students, you could pair program (another important programmer skill) with each individually.

3 年前議論

If I could send a message to my past self on the topic, I might have told myself to start with Common Lisp, Scheme, Python or Smalltalk (maybe Squeak), rather than the BASIC, C++, and C# that I started with. (C++ was too complicated. BASIC is maybe too primitive by modern standards, although assembly might have been worth learning early. C# was better but had too much ceremony for even a simple Hello World.) I might also tell myself to actually read the textbooks rather than just watch lectures.

There are so many details one has to get right in one's head to program at all, that non-programming experience doesn't prepare one for. E.g. the assignment operator isn't symmetric like the equality boolean operator (in most languages). This is not how it works in math. The simpler the language you start with, the easier it is to model in one's head.

Having a simple language with a REPL is super useful for getting this straight--if you don't know what it does, you quickly test the assumptions. Go through lots of small examples. Have the students predict and write down what the output will be, then run it and have them explain why they were surprised. This should help you diagnose where their mental models are wrong. Tell them to assume the bugs live in the programmer's mental model, not in the compiler. Flip the classroom if you need more time for this. (I.e. pre-record the lectures, and have them watch them as the homework, and work on the exercises during class time.)

Explain the language's memory model. What lives on the stack or on the heap? How are arguments passed? What's a copy and what's a mutation? Diagram on the blackboard. Write assumptions down. Human working memory is extremely limited. The gifted students might have seven registers to work with, when they're concentrating. If they're learning the language itself, or talking to you at the same time, there isn't much left to program with. Those with more average IQ might not have anything left at all. Have them start with pseudocode, and iteratively break it down to the level that it can be mechanically translated into the language. Offload everything you can.

3 年前議論

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