Skip to content
/ delta-rs Public
forked from delta-io/delta-rs

A native Rust library for Delta Lake, with bindings into Python

License

Notifications You must be signed in to change notification settings

BnMcG/delta-rs

 
 

Repository files navigation

delta-rs logo

A native Rust library for Delta Lake, with bindings to Python
Python docs · Rust docs · Report a bug · Request a feature · Roadmap

Deltalake Crate Deltalake Deltalake #delta-rs in the Delta Lake Slack workspace

The Delta Lake project aims to unlock the power of the Deltalake for as many users and projects as possible by providing native low-level APIs aimed at developers and integrators, as well as a high-level operations API that lets you query, inspect, and operate your Delta Lake with ease.

Source Downloads Installation Command Docs
PyPi Downloads pip install deltalake Docs
Crates.io Downloads cargo add deltalake Docs

Table of contents

Quick Start

The deltalake library aims to adopt patterns from other libraries in data processing, so getting started should look familiar.

from deltalake import DeltaTable
from deltalake.write import write_deltalake
import pandas as pd

# write some data into a delta table
df = pd.DataFrame({"id": [1, 2], "value": ["foo", "boo"]})
write_deltalake("./data/delta", df)

# Load data from the delta table
dt = DeltaTable("./data/delta")
df2 = dt.to_pandas()

assert df == df2

The same table can also be loaded using the core Rust crate:

use deltalake::{open_table, DeltaTableError};

#[tokio::main]
async fn main() -> Result<(), DeltaTableError> {
    // open the table written in python
    let table = open_table("./data/delta").await?;

    // show all active files in the table
    let files = table.get_files();
    println!("{files}");

    Ok(())
}

You can also try Delta Lake docker at DockerHub | Docker Repo

Get Involved

We encourage you to reach out, and are commited to provide a welcoming community.

Integrations

Libraries and frameworks that interoperate with delta-rs - in alphabetical order.

Features

The following section outlines some core features like supported storage backends and operations that can be performed against tables. The state of implementation of features outlined in the Delta protocol is also tracked.

Cloud Integrations

Storage Rust Python Comment
Local done done
S3 - AWS done done requires lock for concurrent writes
S3 - MinIO done done requires lock for concurrent writes
S3 - R2 done done requires lock for concurrent writes
Azure Blob done done
Azure ADLS Gen2 done done
Micorosft OneLake open open
Google Cloud Storage done done

Supported Operations

Operation Rust Python Description
Create done done Create a new table
Read done done Read data from a table
Vacuum done done Remove unused files and log entries
Delete - partitions done Delete a table partition
Delete - predicates done Delete data based on a predicate
Optimize - compaction done done Harmonize the size of data file
Optimize - Z-order done done Place similar data into the same file
Merge open open
FS check done Remove corrupted files from table

Protocol Support Level

Writer Version Requirement Status
Version 2 Append Only Tables open
Version 2 Column Invariants done
Version 3 Enforce delta.checkpoint.writeStatsAsJson open
Version 3 Enforce delta.checkpoint.writeStatsAsStruct open
Version 3 CHECK constraints open
Version 4 Change Data Feed
Version 4 Generated Columns
Version 5 Column Mapping
Version 6 Identity Columns
Version 7 Table Features
Reader Version Requirement Status
Version 2 Collumn Mapping
Version 3 Table Features (requires reader V7)

About

A native Rust library for Delta Lake, with bindings into Python

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Rust 86.5%
  • Python 10.8%
  • TLA 2.3%
  • Makefile 0.2%
  • Shell 0.1%
  • Batchfile 0.1%