@Antelox 9cfd5cfac3 - Improved the GitHub python binding workflow: (#2072)
- Added fullMode input in workflow_dispatch
    - Take decision whether to build either in debug or release mode and if to build for all python versions according to the commit message patterns
    - Set proper artifact names
    - Removed not needed steps
    - Compacted some steps in order to leverage more the matrix feature
    - Bumped cibuildwheel action to 2.22.0
    - Run actual regress tests in place of sample scripts
- Specify optional test install in pyproject.toml with proper requirements
- Derive package version from git tags
- Add GENERATORS env var support in setup.py to specify cmake generator and minor refactoring
- Minor cleanup/refactoring for the regress test suite
- Marked some regress tests with skipIf to skip them in case of old python versions
- Marked some failing regress tests to be checked with skipIf
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Unicorn Engine

pypi downloads Fuzzing Status

Unicorn is a lightweight, multi-platform, multi-architecture CPU emulator framework, based on QEMU.

Unicorn offers some unparalleled features:

  • Multi-architecture: ARM, ARM64 (ARMv8), M68K, MIPS, PowerPC, RISCV, SPARC, S390X, TriCore and X86 (16, 32, 64-bit)
  • Clean/simple/lightweight/intuitive architecture-neutral API
  • Implemented in pure C language, with bindings for Crystal, Clojure, Visual Basic, Perl, Rust, Ruby, Python, Java, .NET, Go, Delphi/Free Pascal, Haskell, Pharo, Lua and Zig.
  • Native support for Windows & *nix (with Mac OSX, Linux, Android, *BSD & Solaris confirmed)
  • High performance via Just-In-Time compilation
  • Support for fine-grained instrumentation at various levels
  • Thread-safety by design
  • Distributed under free software license GPLv2

Further information is available at http://www.unicorn-engine.org

License

This project is released under the GPL license.

Compilation & Docs

See docs/COMPILE.md file for how to compile and install Unicorn.

More documentation is available in docs/README.md.

Contact

Contact us via mailing list, email or twitter for any questions.

Contribute

If you want to contribute, please pick up something from our Github issues.

We also maintain a list of more challenged problems in milestones for our regular release.

Please send pull request to our dev branch.

CREDITS.TXT records important contributors of our project.

Description
No description provided
Readme 16 MiB
Languages
C 87.2%
Java 2.6%
Python 2.1%
Pawn 1.2%
Rust 0.9%
Other 5.9%