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LPython

LPython is a Python compiler. It is in heavy development, currently in pre-alpha stage. Some of the goals of LPython:

  • The best possible performance for numerical array oriented code
  • Run on all platforms
  • Compile a subset of Python and be Python compatible
  • Explore how to design it so that it can be eventually used with any Python code
  • Fast compilation
  • Excellent user friendly diagnostic messages: error, warnings, hints, notes, etc.
  • Ahead of time compilation to binaries and interactive usage (Jupyter notebook)
  • Able to transform the Python code to C++, Fortran and other languages

And more.

Installation

LPython works on Windows, macOS and Linux.

Install Conda

If you do not have Conda already installed, please follow the instructions here to install Conda on your platform:

https://github.com/conda-forge/miniforge/#download

Linux

sudo apt install binutils-dev

Windows

Install Visual Studio (MSVC), for example the version 2022, you can download the Community version for free from: https://visualstudio.microsoft.com/downloads/.

Launch the Miniforge prompt from the Desktop.

In the shell, initialize the MSVC compiler using:

call "C:\Program Files\Microsoft Visual Studio\2022\Community\Common7\Tools\VsDevCmd" -arch=x64

You can optionally test that MSVC works by:

cl /?
link /?

Both commands must print help (several pages).

Build LPython

Clone LPython

git clone https://github.com/lcompilers/lpython.git
cd lpython

Linux and MacOS

  • Create a Conda environment using the pre-existing file:

    conda env create -f environment_unix.yml
    conda activate lp
  • Generate files that are required for the build and build in Debug Mode:

    ./build0.sh
    ./build1.sh

Windows

  • Create a Conda environment using the pre-existing file:
    conda env create -f environment_win.yml
    conda activate lp
  • Generate files that are required for the build and build in Release Mode:
    call build0.bat
    call build1.bat
  • Tests and examples
    ctest
    inst\bin\lpython examples\expr2.py
    inst\bin\lpython examples\expr2.py -o a.out
    a.out

Tests (Linux or MacOs):

Run tests:

ctest
./run_tests.py

Run integration tests:

cd integration_tests
./run_tests.sh

Speed up Integration Test on Macs

Integration tests run slowly because Apple checks the hash of each executable online before running. You can turn off that feature in the Privacy tab of the Security and Privacy item of System Preferences, Developer Tools, Terminal.app, "allow the apps below to run software locally that does not meet the system's security policy."

Examples (Linux or MacOs)

You can run the following examples by hand in a terminal:

./src/bin/lpython examples/expr2.py
./src/bin/lpython examples/expr2.py -o expr
./expr
./src/bin/lpython --show-ast examples/expr2.py
./src/bin/lpython --show-asr examples/expr2.py
./src/bin/lpython --show-cpp examples/expr2.py
./src/bin/lpython --show-llvm examples/expr2.py
./src/bin/lpython --show-c examples/expr2.py

Contributing

We welcome contributions from anyone, even if you are new to open source. It might sound daunting to contribute to a compiler at first, but please do, it is not complicated. We will help you with any technical issues and help improve your contribution so that it can be merged.

To contribute, submit a Pull Request (PR) against our repository at:

https://github.com/lcompilers/lpython

and don't forget to clean your history, see example.

Please report any bugs you may find at our issue tracker: https://github.com/lcompilers/lpython/issues. Or, even better, fork the repository on GitHub and create a PR. We welcome all changes, big or small, and we will help you make a PR if you are new to git.

If you have any questions or need help, please ask us at Zulip (project chat) or our mailinglist.

See the CONTRIBUTING document for more information.

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  • C++ 81.8%
  • Python 12.8%
  • C 1.6%
  • CMake 1.2%
  • Yacc 1.1%
  • Jupyter Notebook 0.9%
  • Other 0.6%