one-more-re-nightmare
py4cl
Our great sponsors
one-more-re-nightmare | py4cl | |
---|---|---|
11 | 21 | |
133 | 221 | |
0.8% | - | |
4.2 | 2.3 | |
9 months ago | 6 months ago | |
Common Lisp | Common Lisp | |
BSD 2-clause "Simplified" License | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
one-more-re-nightmare
-
Regular Expressions make me feel like a powerful wizard- that's not a good thing
Depends on your regex engine, and your non-regex solution. My engine (shameless self-plug https://github.com/telekons/one-more-re-nightmare) rivals hand-written automata, having to load each character more-or-less* only once, and throws in vectorisation for simple search loops too. I would not want to write or maintain the generated code.
-
Don't be lazy this month!
one-more-re-nightmare used to let you write Σ, but I then tried to search Greek stuff with it and it went wrong. So now there's...$ for all characters (since that's not used for end-of-line assertions).
-
When a young programmer who has been using C for several years is convinced that C is the best possible programming language and that people who don't prefer it just haven't use it enough, what is the best argument for Lisp vs C, given that they're already convinced in favor of C?
One trick is that Common Lisp can generate and compile code at runtime, whereas static languages typically do not have a compiler available at runtime. This lets you make your own lazy person's JIT/staged compiler, which is useful if some part of the problem is not known at compile-time. Such an approach has been used at least for array munging, type munging and regular expression munging.
-
Tutorial Series to learn Common Lisp quickly
> One of my favorite examples is the regex library cl-ppcre. Thanks to the nature of Lisp, the recognizer for each regex you create can be compiled to native code on compiler implementations of CL.
That is not true - cl-ppcre generates a chain of closures. Experimental performance is in the same ballpark as typical "bytecode" interpreting regex implementations.
(Disclosure: I wrote another regex library at <https://github.com/telekons/one-more-re-nightmare>, which does do native code compilation.)
-
The self-hosted Zig compiler can now successfully compile itself
Someone else didn't tell me that before, so it can't be true. But I don't publish papers on toys, nor do I think toy projects are awfully fast. Though the x86-64 backend I wrote was in someone else's repository and thus was several PRs :(
-
Most interesting languages to learn (from)?
Regular expressions
-
Is regex really fast in CL?
Also try this https://github.com/telekons/one-more-re-nightmare
-
Why You Should Learn Lisp In 2022?
A Common Lisp system has the compiler around at runtime, so if you can figure out how to profitably stage/specialise a computation, then you can roll your own cheap JIT of sorts. This can be useful for array munging and regular expressions at the least. You can do this in C, of course but you would need to use another compiler as a library (e.g. LLVM, TCC, libgccjit) or write your own (e.g. PCRE2's sljit).
-
LISP with GC in 436 bytes
Agree to disagree - I don't have the energy to remember operator precedence. One file from the regular expression compiler has most of the rewrite rules I read from the papers, except in S-expression syntax. There were a few bugs due to misreading precedence. Also c.f. Gerald Sussman talking about physics notation being a pain in the butt.
-
The one-more-re-nightmare regular expression compiler
It's all part of the library. Everything about regular expression types is in this file.
py4cl
-
Need recommendation for IPC with Go
py4cl and cl4py rely on uiop:launch-program and python's subprocess respectively. These are portable to the extent uiop and subprocess are portable and do not require any additional installation.
-
Lisp-Stick on a Python
If you want to use Python libs from CL, see py4cl: https://github.com/bendudson/py4cl the other way around, calling your efficient CL library from Python: https://github.com/marcoheisig/cl4py/ There might be more CL libraries than you think! https://github.com/CodyReichert/awesome-cl (or at least a project sufficiently advanced on your field to join forces ;) )
-
The German School of Lisp (2011)
FYI you can call Python from CL: https://github.com/bendudson/py4cl and CL from Python: https://github.com/marcoheisig/cl4py/
If you don't know Emacs, see other editors: https://lispcookbook.github.io/cl-cookbook/editor-support.ht... If you want the more Smalltalk-like experience I'd go with the free LispWorks version: it has many GUI panes that allow to watch and discover the state of the program.
I personally couldn't stay long with Hylang. You won't get CL niceties: more language features, performance, standalone binaries, interactive debugger (all the niceties of an image-based development)…
-
Plotting
I ended up using a fair bit of matplotlib through college and with colleagues. I too don't want to use python, but I also don't like throwing away its libraries, and I'm too lazy to invest in other* plotting ecosystems. In effect, I use up using matplotlib through py4cl/2.
-
numericals - Performance of NumPy with the goodness of Common Lisp
Note that it is not my aim to replace the python ecosystem; I think that is far too lofy a goal to be of any good. My original intention was to interoperate with python through py4cl/2 or the likes, but felt that one needs a Common Lisp library for "small" operations, while "large" operations can be offloaded to python libraries through py4cl/2.
-
Good Lisp libraries for math
If performance is absolutely not a concern, then third option is using python libraries through py4cl/2. To put it differently, if calling python from lisp is not the bottleneck, then this is a feasible option.
-
Why Hy?
I encourage people to try out Common Lisp because, unlike with Hy, you will get: speed, ability to build binaries, truly interactive image-based development (yes, more interactive than ipython), more static type checks, more language features (no closures in Hy last time I checked), language stability… To reach to Python libs, you have https://github.com/bendudson/py4cl My comparison of Python and CL: https://lisp-journey.gitlab.io/pythonvslisp/
-
Tutorial Series to learn Common Lisp quickly
> Not sure if such a thing already exists for CL
couple of solutions exist for this
https://github.com/bendudson/py4cl
https://github.com/pinterface/burgled-batteries
- Calling Python from Common Lisp
-
(define (uwu) (display "nya~\n"))
Ahh, makes sense. Well, if you ever wanna steal some of python's thunder, libpython-clj worked great for me lol. Supposedly py4cl fills a similar role in Common Lisp.
What are some alternatives?
Revise.jl - Automatically update function definitions in a running Julia session
py4cl2 - Call python from Common Lisp
SICL - A fresh implementation of Common Lisp
magicl - Matrix Algebra proGrams In Common Lisp.
zig - General-purpose programming language and toolchain for maintaining robust, optimal, and reusable software.
cl-cuda - Cl-cuda is a library to use NVIDIA CUDA in Common Lisp programs.
cl-ppcre - Common Lisp regular expression library
hy - A dialect of Lisp that's embedded in Python
oakc - A portable programming language with a compact intermediate representation
libpython-clj - Python bindings for Clojure
Petalisp - Elegant High Performance Computing
coalton - Coalton is an efficient, statically typed functional programming language that supercharges Common Lisp.