cherry

Cherry is a python library for building blockchain data pipelines.

It is designed to make building production-ready blockchain data pipelines easy.

Getting Started

See getting started section of the docs.

Features

• Pure python library. Don't need yaml, SQL, toml etc.
• High-level datasets API and flexible pipeline API.
• High-performance, low-cost and uniform data access. Ability to use advanced providers without platform lock-in.
• Included functionality to decode, validate, transform blockchain data. All implemented in rust for performance.
• Write transformations using polars, pyarrow, datafusion, pandas, duckdb or any other pyarrow compatible library.
• Schema inference automatically creates output tables.
• Keep datasets fresh with continuous ingestion.
• Parallelized, next batch of data is being fetched while your pre-processing function is running, while the database writes are being executed in parallel. Don't need to hand optimize anything.
• Included library of transformations.
• Included functionality to implement crash-resistance.

Data providers

Provider	Ethereum (EVM)	Solana (SVM)
HyperSync	✅	❌
SQD	✅	✅
Yellowstone-GRPC	❌	✅

Supported output formats

• ClickHouse
• Iceberg
• Deltalake
• DuckDB
• Arrow Datasets
• Parquet

Usage examples

• Ethereum(EVM) examples
• Solana(SVM) examples

Logging

Python code uses the standard logging module of python, so it can be configured according to python docs.

Set RUST_LOG environment variable according to env_logger docs in order to see logs from rust modules.

To run an example with trace level logging for rust modules:

RUST_LOG=trace uv run examples/path/to/my/example

Development

This repo uses uv for development.

• Format the code with uv run ruff format
• Lint the code with uv run ruff check
• Run type checks with uv run pyright
• Run the tests with uv run pytest

Core libraries we use for ingesting/decoding/validating/transforming blockchain data are implemented in cherry-core repo.

License

Licensed under either of

• Apache License, Version 2.0 (LICENSE-APACHE or http://www.apache.org/licenses/LICENSE-2.0)
• MIT license (LICENSE-MIT or http://opensource.org/licenses/MIT)

at your option.

Contribution

Unless you explicitly state otherwise, any contribution intentionally submitted for inclusion in the work by you, as defined in the Apache-2.0 license, shall be dual licensed as above, without any additional terms or conditions.

Sponsors