Python bindings for rust-data-processing: schema-first CSV/JSON/Parquet/Excel ingestion into an in-memory DataSet.
Project description
rust-data-processing
Python bindings for the rust-data-processing crate: schema-first ingestion from CSV, JSON, Parquet, and Excel into an in-memory DataSet, with profiling, validation, Polars-backed pipelines, and SQL.
This page is the PyPI project description (Python-only). Clone the repository for developer setup, Rust sources, and the full monorepo README.
Install
pip install rust-data-processing
Requires Python 3.10+.
Quick start
import rust_data_processing as rdp
schema = [
{"name": "id", "data_type": "int64"},
{"name": "name", "data_type": "utf8"},
]
ds = rdp.ingest_from_path("path/to/data.csv", schema, {"format": "csv"})
print("rows", ds.row_count())
report = rdp.profile_dataset(ds, {"head_rows": 50, "quantiles": [0.5]})
print("profile rows sampled", report["row_count"])
validation = rdp.validate_dataset(
ds,
{"checks": [{"kind": "not_null", "column": "id", "severity": "error"}]},
)
print("checks", validation["summary"]["total_checks"])
Documentation
| Link | |
|---|---|
| Python examples (HTML, pdoc) | GitHub Pages — examples |
| Python API (HTML, pdoc) | GitHub Pages — Python |
| Python API (markdown) | API.md in the repository |
| Combined site (landing + Rust rustdoc) | GitHub Pages — home |
| Rust crate API | docs.rs/rust-data-processing |
| Repository | github.com/vihangdesai2018-png/rust-data-processing |
License
MIT OR Apache-2.0 - see LICENSE-MIT and LICENSE-APACHE in the repository.
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