xet-core enables huggingface_hub to utilize xet storage for uploading and downloading to HF Hub. Xet storage provides chunk-based deduplication, efficient storage/retrieval with local disk caching, and backwards compatibility with Git LFS. This library is not meant to be used directly, and is instead intended to be used from huggingface_hub.
♻ chunk-based deduplication implementation: avoid transferring and storing chunks that are shared across binary files (models, datasets, etc).
🤗 Python bindings: bindings for huggingface_hub package.
↔ network communications: concurrent communication to HF Hub Xet backend services (CAS).
🔖 local disk caching: chunk-based cache that sits alongside the existing huggingface_hub disk cache.
- cas_client: communication with CAS backend services, which include APIs for Xorbs and Shards.
- cas_object: CAS object (Xorb) format and associated APIs, including chunks (ranges within Xorbs).
- cas_types: common types shared across crates in xet-core and xetcas.
- chunk_cache: local disk cache of Xorb chunks.
- chunk_cache_bench: benchmarking crate for chunk_cache.
- data: main driver for client operations - FilePointerTranslator drives hydrating or shrinking files, chunking + deduplication here.
- error_printer: utility for printing errors conveniently.
- file_utils: SafeFileCreator utility, used by chunk_cache.
- hf_xet: Python integration with Rust code, uses maturin to build hfxet Python package. Main integration with HF Hub Python package.
- mdb_shard: Shard operations, including Shard format, dedupe probing, benchmarks, and utilities.
- merkledb: Xorb hash creation.
- merklehash: DataHash type, 256-bit hash, widely used across many crates.
- parutils: Provides parallel execution utilities relying on Tokio (ex. parallel foreach).
- progress_reporting: offers ReportedWriter so progress for Writer operations can be displayed.
- utils: general utilities, including singleflight, progress, serialization_utils and threadpool.
To build xet-core, look at requirements in GitHub Actions CI Workflow for the Rust toolchain to install. Follow Rust documentation for installing rustup and that version of the toolchain. Use the following steps for building, testing, benchmarking.
Many of us on the team use VSCode, so we have checked in some settings in the .vscode directory. Install the rust-analyzer extension.
Build:
cargo build
Test:
cargo test
Benchmark:
cargo bench
Linting:
cargo clippy -r --verbose -- -D warnings
Formatting (requires nightly toolchain):
cargo +nightly fmt --manifest-path ./Cargo.toml --all
- Create Python3 virtualenv:
python3 -mvenv ~/venv - Activate virtualenv:
source ~/venv/bin/activate - Install maturin:
pip3 install maturin ipython - Go to hf_xet crate:
cd hf_xet - Build:
maturin develop - Test:
ipython
import hfxet
hfxet.upload_files()
hfxet.download_files()
From hf_xet directory:
MACOSX_DEPLOYMENT_TARGET=10.9 maturin build --release --target universal2-apple-darwin --features openssl_vendored
Note: You may need to install x86_64: rustup target add x86_64-apple-darwin
Unit-tests are run with cargo test, benchmarks are run with cargo bench. Some crates have a main.rs that can be run for manual testing.
Please join us in making xet-core better. We value everyone's contributions. Code is not the only way to help. Answering questions, helping each other, improving documentation, filing issues all help immensely. If you are interested in contributing (please do!), check out the contribution guide for this repository.
- Technical Blog posts
- Git is for Data 'CIDR paper
- History: xet-core is adapted from xet-core, which contains deep git integration, along with very different backend services implementation.
