matten-data

Experimental (0.20.x family). A scope-locked companion crate (RFC-033). The table-to-Tensor API (CSV ingestion, schema summary, column selection, missing-value handling, explicit numeric conversion) is available as of v0.20.1 (RFC-034, RFC-035). The API may change before beta; pin the minor version.

Part of the matten workspace — see it for the full family.

Overview

matten-data is a tiny helper for the boring step between table-like input and a numeric matten::Tensor:

use matten_data::Table;

let csv = "sales,cost,note\n10,2,a\n20,,b\n30,4,c";
let tensor = Table::from_csv_str(csv)?
    .select_columns(["sales", "cost"])?   // pick numeric columns, by name
    .fill_missing(0.0)?                    // clean missing values explicitly
    .try_numeric()?                        // strict, explicit conversion
    .to_tensor()?;                         // -> matten::Tensor, shape [3, 2]

assert_eq!(tensor.shape(), &[3, 2]);
assert_eq!(tensor.as_slice(), &[10.0, 2.0, 20.0, 0.0, 30.0, 4.0]);
# Ok::<(), matten_data::MattenDataError>(())

Output shape is [rows, selected_columns]; row order is the input row order and column order is the requested selection order. See examples/ for a runnable version.

Not a dataframe library

matten-data is not a dataframe library. It deliberately has no joins, group-by, pivot, query DSL, lazy execution, indexing / loc / iloc, rolling or window operations, datetime engine, categorical dtype system, or large-data streaming.

For dataframe, query, or large-data workloads use Polars, DataFusion, Pandas, or another dataframe/query tool. matten-data is a small conversion helper for application-validated or trusted data, not a CSV firewall or malicious-input sandbox.

Relationship to core `dynamic`

Core matten's dynamic feature is value-level ingestion (mixed values inside a Tensor, with explicit try_numeric()). matten-data is table-level preparation (headers, named columns, schema summary, table-shaped missing-value policy) whose end goal is a numeric Tensor. It may use core dynamic internally but does not expose a second computation engine.

Status and scope

Maturity: experimental. The API (when added) may change; pin the version.
Scope lock: table-to-Tensor preparation only (RFC-033, RFC-042).
Dependency direction: matten-data depends on core matten; core never depends on matten-data (enforced by the dependency-boundary CI check).
Safe Rust only: #![forbid(unsafe_code)].

Dependency style

This crate depends on matten. When the public API lands, official examples will import Tensor from matten directly:

use matten::Tensor;
use matten_data::Table;

Declare both matten and this crate in your Cargo.toml (RFC-032).

Compatibility

SemVer: pre-1.0 (0.x). Shares the matten family version (RFC-030).
MSRV: Rust 1.85 (edition 2024).

matten-data 0.20.5