rust-data-processing 0.1.4

Schema-first ingestion (CSV, JSON, Parquet, Excel) into an in-memory DataSet, plus Polars-backed pipelines, SQL, profiling, validation, and map/reduce-style processing.
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rust-data-processing

Rust library: schema-first ingestion (CSV, JSON, Parquet, Excel with Cargo features) into an in-memory DataSet, plus Polars-backed pipelines, optional SQL, profiling, validation, and map/reduce-style processing.

This file is the crate README shown on crates.io and at the top of docs.rs (Rust-only). The repository’s README.md is the full monorepo overview (including Python).

Documentation

Link
Rust API (module tree) Use the crate index on this docs.rs page (left sidebar).
Repository github.com/vihangdesai2018-png/rust-data-processing
Markdown API overview API.md (shipped in this crate)
Rust examples & cookbook docs/rust/README.md
HTML site (Rust + Python pages) GitHub Pages — use Rust (rustdoc) for this crate; setup if the site is empty.

Quick start (Rust)

use rust_data_processing::ingestion::{ingest_from_path, IngestionOptions};
use rust_data_processing::types::{DataType, Field, Schema};

let schema = Schema::new(vec![
    Field::new("id", DataType::Int64),
    Field::new("name", DataType::Utf8),
]);
let _ds = ingest_from_path("path/to/data.csv", &schema, &IngestionOptions::default())
    .expect("ingest");

More patterns: docs/rust/README.md.

Features (Cargo)

  • default: includes sql (Polars-backed SQL via polars-sql).
  • excel: Excel workbook ingestion (calamine).
  • sql: Polars SQL (on by default; use default-features = false to drop).
  • db_connectorx: optional DB → Arrow → DataSet.
  • arrow / serde_arrow: Arrow interop helpers.

Full list: Cargo.toml [features].

License

MIT OR Apache-2.0 - see LICENSE-MIT and LICENSE-APACHE.