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.
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, 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.equals(df2)
The same table can also be loaded using the core Rust crate:
use deltalake::{open_table, DeltaTableError};
use url::Url;
#[tokio::main]
async fn main() -> Result<(), DeltaTableError> {
// open the table written in python
let delta_path = Url::from_directory_path("/abs/data/delta").unwrap();
let table = open_table(delta_path).await?;
// show all active files in the table
let files: Vec<_> = table.get_file_uris()?.collect();
println!("{files:?}");
Ok(())
}
You can also try Delta Lake in Docker at DockerHub | Docker Repo
Get Involved
The delta-rs team is committed
to providing a welcoming community.
Integrations
Libraries and frameworks that interoperate with delta-rs - in alphabetical order.
Features
View the complete feature table.
