CrossHair
hissp
CrossHair | hissp | |
---|---|---|
8 | 29 | |
948 | 331 | |
- | - | |
9.2 | 9.1 | |
11 days ago | 3 months ago | |
Python | Python | |
GNU General Public License v3.0 or later | Apache 2.0 |
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.
CrossHair
-
Try CrossHair while working other Python projects
Writing some Python for Hacktoberfest? Try out CrossHair while you do that and get credit for a blog post too! https://github.com/pschanely/CrossHair/issues/173
-
What are some amazing, great python external modules, libraries to explore?
CrossHair, Hypothesis, and Mutmut for advanced testing.
-
Formal Verification Methods in industry
When you say "formal verification methods", what kind of techniques are you interested in? While using interactive theorem provers will most likely not become very widespread, there are plenty of tools that use formal techniques to give more correctness guarantees. These tools might give some guarantees, but do not guarantee complete functional correctness. WireGuard (VPN tunnel) is I think a very interesting application where they verified the protocol. There are also some tools in use, e.g. Mythril and CrossHair, that focus on detecting bugs using symbolic execution. There's also INFER from Facebook/Meta which tries to verify memory safety automatically. The following GitHub repo might also interest you, it lists some companies that use formal methods: practical-fm
-
Klara: Python automatic test generations and static analysis library
The main difference that Klara bring to the table, compared to similar tool like pynguin and Crosshair is that the analysis is entirely static, meaning that no user code will be executed, and you can easily extend the test generation strategy via plugin loading (e.g. the options arg to the Component object returned from function above is not needed for test coverage).
-
Pynguin – Allow developers to generate Python unit tests automatically
Just in case you are looking for an alternative approach: if you write contracts in your code, you might also consider crosshair [1] or icontract-hypothesis [2]. If your function/method does not need any pre-conditions then the the type annotations can be directly used.
(I'm one of the authors of icontract-hypothesis.)
[1] https://github.com/pschanely/CrossHair
[2] https://github.com/mristin/icontract-hypothesis
-
Programming in Z3 by learning to think like a compiler
There's a tool for verification of Python programs based on contracts which uses Z3: https://github.com/pschanely/CrossHair
You can use it as part of your CI or during the development (there's even a neat "watch" mode, akin to auto-correct).
- Diff the behavior of two Python functions
-
Finding Software Bugs Using Symbolic Execution
Looking at some of your SMT-based projects, I'd love to compare your SMT solver notes with my mine from working on https://github.com/pschanely/CrossHair
Sadly, there aren't a lot of resources on how to use SMT solvers well.
hissp
- Hissp
-
2 line tic tac toe
Hissp is a Python library that can compile a whole program into one Python expression.
-
What's the most hilarious use of operator overloading you've seen?
If you want Python to be as customizable as Lissp, check out Hissp (and Hebigo).
-
Pythoneers here, what are some of the best python tricks you guys use when progrmming with python
Hissp is really cool for metaprogramming Python. There's also macropy, but it's harder to use.
-
Lush – Lisp-like language for deep learning designed by Yann LeCun
I prefer https://github.com/gilch/hissp, where Hy has to use shims to pretend statements are expressions, Hissp just targets the expression subset in the first place. (though as you mentioned, hy has a lot of literature and support around it, where as you're going to have to find your own way around hissp)
-
A Python-compatible statically typed language erg-lang/erg
No shortage of options, e.g. Dg, Mochi, Coconut, and Hebigo (based on Hissp[1]).
[1]: https://github.com/gilch/hissp
-
Other than having a wider range of libraries and beingthus being more "general purpose" and "practical" is there anything that makes Python an intrinsically better programming language than Lisp?
If you want Lisp metaprogramming plus Python ecosystem, check out Hissp
- Lisp.py
-
What are some amazing, great python external modules, libraries to explore?
Hissp is really interesting. Read through the docs and you'll understand Python more deeply. It works well with Toolz and Pyrsistent.
- Why Hy?
What are some alternatives?
pynguin - The PYthoN General UnIt Test geNerator is a test-generation tool for Python
hy - A dialect of Lisp that's embedded in Python
icontract-hypothesis - Combine contracts and automatic testing.
hy-lisp-python - examples for my book "A Lisp Programmer Living in Python-Land: The Hy Programming Language"
angr - A powerful and user-friendly binary analysis platform!
libpython-clj - Python bindings for Clojure
alive2 - Automatic verification of LLVM optimizations
coalton - Coalton is an efficient, statically typed functional programming language that supercharges Common Lisp.
klee - KLEE Symbolic Execution Engine
femtolisp - a lightweight, robust, scheme-like lisp implementation
miasm - Reverse engineering framework in Python
incanter - Clojure-based, R-like statistical computing and graphics environment for the JVM