PyLLVMPass

Build LLVM passes in python! This library aims to provide a generic shared object that when passed into LLVM's optimizer will load arbitrary python modules to implement the pass.

Installation

# Currently depends on llvm-18 being installed
pip install llvmcpy
git clone https://github.com/aneeshdurg/pyllvmpass
cd pyllvmpass
cargo build
# Make sure that either LLVM_CONFIG is set in the environment or llvm-config is
# on the PATH.

Usage

To use, request an optimizer named pyllvmpass[<module name>] after loading the pyllvmpass shared object. For example, if you had a module named example_pass, either in the current directory as example_pass.py or as an installed library, you can do:

# Note that the module being loaded is supplied to pyllvmpass in the square
# brackets
opt --load-pass-plugin=./target/debug/libpypllvmpass.so --passes=pyllvmpass[example_pass] <inputs>...
# If you have multiple modules that you'd like to run as a pass you can include
# multiple instances of pyllvmpass[] above.

The module MUST define a function run_on_module that accepts the module being transformed as a llvmcpy.llvm.Module. See llvmcpy for API details. It is more or less a thin wrapper around the LLVM C API.

For our example in example_pass.py, we could do the following:

from llvmcpy.llvm import Module
def run_on_module(module: Module) -> int:
    print("hello from python!")
    src = module.print_module_to_string().decode()
    # Print the llvm IR
    print(src)

    # Any python code can be written here. Even interactive debugging with
    # breakpoint is possible!
    # breakpoint()

    # return 0 to indicate that all preserved analysis can be kept, and 1
    # otherwise
    return 0
    ...

Currently only ModulePasses are supported. See the test directory for examples that transform the IR.

Why does this exist?

I think having an interactive console is a great tool for learning new things. C++ and Rust struggle with being interactive due to their compiled nature. While I love coding in C++ and Rust, I think python is a very powerful language for prototyping, and having the choice to work in python lowers the barrier of entry to newcomers. However, the LLVM C API has a lot of limitations, so we might not ever see a lot of more involved LLVM passes ever written in anything except C++.