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-1.0.1-cp310-cp310-macosx_11_0_arm64.whl.
File metadata
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- Upload date:
- Size: 373.1 kB
- Tags: CPython 3.10, macOS 11.0+ ARM64
- Uploaded using Trusted Publishing? Yes
- Uploaded via: twine/6.1.0 CPython/3.13.7
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Provenance
The following attestation bundles were made for lakeops-1.0.1-cp310-cp310-macosx_11_0_arm64.whl:
Publisher:
publish.yml on hoaihuongbk/lakeops
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Permalink:
hoaihuongbk/lakeops@4c7d252714a45af258e31a1fce054fde074c23b0 -
Branch / Tag:
refs/tags/v1.0.1 - Owner: https://github.com/hoaihuongbk
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