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The Python plugin, which links against libpython, and allows one to invoke arbitrary Python scripts from inside the compiler. The aim is to allow GCC plugins to be written in Python. The MELT plugin provides a high-level Lisp-like language to extend GCC. [71] The support of plugins was once a contentious issue in 2007. [72] C++ transactional memory
Configuration files are Python; user-written builds can leverage a general-purpose, cross-platform programming language Dependency analysis for C , C++ and Fortran Dependency analysis is extensible through user-defined scanners for other languages or file types; unlike GNU Compiler Collection (GCC) dependency analysis, SCons uses a regular ...
The GNU Debugger (GDB) ... As of version 7.0 new features include support for Python scripting [8] ... Using the GCC compiler on Linux, ...
The Boehm GC is used by many projects [8] that are implemented in C or C++ like Inkscape, as well as by runtime environments for a number of other languages, including Crystal, the Codon high performance python compiler, [9] the GNU Compiler for Java runtime environment, the Portable.NET project, Embeddable Common Lisp, GNU Guile, the Mono ...
Nuitka – a source-to-source compiler which compiles Python code to C/C++ executables, or source code. Numba – NumPy aware LLVM -based JIT compiler Pyjs – a framework (based on Google Web Toolkit (GWT) concept) for developing client-side Python-based web applications, including a stand-alone Python-to-JavaScript compiler, an Ajax framework ...
Research compilers are mostly not robust or complete enough to handle real, large applications. They are used mostly for fast prototyping new language features and new optimizations in research areas. Open64: A popular research compiler. Open64 merges the open source changes from the PathScale compiler mentioned.
Kati is Google's replacement of GNU Make, as of 2020 used in Android OS builds. It translates the makefile into ninja for faster incremental builds (similar to the cmake metatool). [33] Snakemake is a Python-driven implementation for compiling and running bioinformatics workflows. [34]
It supports GNU Compiler Collection (gcc), Clang, Visual C++ and other compilers, including non-traditional compilers such as Emscripten and Cython. [6] The project uses ninja as the primary backend buildsystem, but can also use Visual Studio or Xcode backends.