Data lake operations toolkit
Project description
LakeOps
A modern data lake operations toolkit working with multiple table formats (Delta, Iceberg, Parquet) and engines (Spark, Polars) via the same APIs.
Features
- Multi-format support: Delta, Iceberg, Parquet
- Multiple engine backends: Apache Spark, Polars (default)
- Storage operations: read, write
To learn more, read the user guide.
Quick Start
Installation
pip install lakeops
Sample Usage
from pyspark.sql import SparkSession
from lakeops import LakeOps
from lakeops.core.engine import SparkEngine
# Init Spark session and create LakeOps instance
spark = SparkSession.builder.getOrCreate()
engine = SparkEngine(spark)
ops = LakeOps(engine)
# Read data from table name
df = ops.read("s3://local/test/table", format="parquet")
# Write data to table name
ops.write(df, "s3://local/test/table", format="parquet")
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File details
Details for the file lakeops-0.2.0-cp310-cp310-macosx_11_0_arm64.whl.
File metadata
- Download URL: lakeops-0.2.0-cp310-cp310-macosx_11_0_arm64.whl
- Upload date:
- Size: 367.7 kB
- Tags: CPython 3.10, macOS 11.0+ ARM64
- Uploaded using Trusted Publishing? Yes
- Uploaded via: twine/6.1.0 CPython/3.12.9
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Provenance
The following attestation bundles were made for lakeops-0.2.0-cp310-cp310-macosx_11_0_arm64.whl:
Publisher:
publish.yml on hoaihuongbk/lakeops
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Statement:
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https://in-toto.io/Statement/v1 -
Predicate type:
https://docs.pypi.org/attestations/publish/v1 -
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lakeops-0.2.0-cp310-cp310-macosx_11_0_arm64.whl -
Subject digest:
0b3bccbe790d850eaabb84660443fa412b51286858dce862f48e51aef6a1d6aa - Sigstore transparency entry: 366545974
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Permalink:
hoaihuongbk/lakeops@f1ead75a4ea04abf6414558506c022daa7e5bee5 -
Branch / Tag:
refs/tags/v0.2.0 - Owner: https://github.com/hoaihuongbk
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public
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Token Issuer:
https://token.actions.githubusercontent.com -
Runner Environment:
github-hosted -
Publication workflow:
publish.yml@f1ead75a4ea04abf6414558506c022daa7e5bee5 -
Trigger Event:
release
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