semvec/pypi-packages huggingface dataset:
llvm-ir-dataset-utils 0.2
Infrastructure to build LLVM IR-based Datasets.
License: Apache-2.0
Requires Python: <3.11,>=3.9

<h1 align='center'>LLVM-IR Dataset Utilities</h1>

This repository contains utilities to construct large LLVM IR datasets from
multiple sources.

## Getting Started

To get started with the dataset construction utilities, we'd suggest to use the
packaged [pipenv](https://pipenv.pypa.io), or the packaged [poetry](https://python-poetry.org/)
to isolate the Python from your system isolation or other environments.

### Pipenv

To get started with pipenv, you then have to

```bash
pipenv install
```

or if you seek to utilize the packaged lockfile

```bash
pipenv sync
```

After that you are ready to activate the environment, and install the dataset construction utilities into it

```bash
pipenv shell && pip install .
```

In case you want to develop the package, this becomes

```bash
pipenv shell && pip install -e .
```

### Poetry

To get started with poetry, you then have to

```bash
poetry install
```

which will draw the exact software version from the packaged lockfile, and install the editable version of the
dataset construction utilities into the environment. To only install the dependencies, you can run

```bash
poetry install --no-root
```

To then develop inside of poetry's virtual environment, we can launch a shell with

```bash
poetry shell
```

## Creating First Data

To create your first small batch of IR data you then have to run from the root directory of the package

```bash
python3 ./llvm_ir_dataset_utils/tools/corpus_from_description.py \
  --source_dir=/path/to/store/dataset/to/source \
  --corpus_dir=/path/to/store/dataset/to/corpus \
  --build_dir=/path/to/store/dataset/to/build \
  --corpus_description=./corpus_descriptions_test/manual_tree.json
```

> Beware! You'll need to have a version of `llvm-objcopy` on your `$PATH`. If you are missing `llvm-objcopy`, an easy way to obtain it is by downloading an llvm-release from either your preferred package channel such as `apt`, `dnf` or `pacman`, or build llvm from [source](https://github.com/llvm/llvm-project) where only the LLVM project itself needs to be enabled during the build, i.e. `-DLLVM_ENABLE_PROJECTS="llvm"`.

You'll then receive a set of `.bc` files in `/path/to/store/dataset/to/corpus/tree`, which you can convert with `llvm-dis` into LLVM-IR, i.e. from inside of the folder

```bash
llvm-dis *.bc
```

> Last steps into the dataloader to be described here.

## Corpus Description

> Basics of the corpus description to be outlined here to easily enable someone to point the package at a new source.

## IR Sources

The package contains a number of builders to target the LLVM-based languages, and extract IR:

- Individual projects (C/C++)
- Rust crates
- Spack packages
- Autoconf
- Cmake
- Julia packages
- Swift packages