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Library for building blockchain pipelines

Project description

cherry

PyPI Telegram Documentation GitHub

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

Supported output formats

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

Usage 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

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

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