tenshift-core 0.1.3

Thread-safe, backpressure-aware data loading pipeline for iterative processing
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# tenshift-core

<p align="center">
<a href="https://crates.io/crates/tenshift-core"><img src="https://img.shields.io/crates/v/tenshift-core.svg" alt="crates.io"></a>
<a href="https://docs.rs/tenshift-core"><img src="https://img.shields.io/docsrs/tenshift-core" alt="docs.rs"></a>
<a href="LICENSE"><img src="https://img.shields.io/badge/license-MIT-blue.svg" alt="MIT"></a>
</p>

Thread-safe, backpressure-aware data loading pipeline for iterative processing. The core engine of the tenshift ML data loading ecosystem.

## Installation

```bash
cargo add tenshift-core
```

## Quick Example

```rust
use tenshift_core::{Pipeline, sample::{Sample, Tensor}, sources::MemorySource};

let samples: Vec<Sample> = (0..10_000)
    .map(|i| Sample::new()
        .with("x", Tensor::f32(&vec![i as f32; 784], vec![1, 28, 28]))
        .with("y", Tensor::i64(&[i as i64 % 10], vec![1])))
    .collect();

let mut iter = Pipeline::from_source(MemorySource::new("mnist", samples))
    .workers(4)
    .shuffle(1000)
    .batch(32)
    .prefetch(4)
    .start()?;

for batch in &mut iter {
    // Process batch of 32 samples
}
# Ok::<(), tenshift_core::error::Error>(())
```

## Architecture Overview

```text
Source thread ──▶ N worker threads ──▶ Collector thread ──▶ Consumer
   (I/O)          (parallel map)       (shuffle/batch)      (User)
```

- Bounded channels provide backpressure
- RAII cleanup on drop  -  no zombie processes
- Zero-copy `Arc` tensor passing between threads
- Optional io_uring acceleration via `wireshift` feature

## Extension Guide

### Add a Data Source

```rust
use tenshift_core::{source::{Source, SourceIterator}, error::Result, sample::Sample};

struct MySource;

impl Source for MySource {
    fn open(&self) -> Result<Box<dyn SourceIterator>> { unimplemented!("return your iterator here") }
    fn name(&self) -> &str { "my-source" }
}
```

### Add a Transform

```rust
use tenshift_core::{transform::{Transform, TransformResult}, sample::Sample};

struct Normalize;

impl Transform for Normalize {
    fn apply(&self, sample: Sample) -> TransformResult {
        TransformResult::Sample(sample)
    }
    fn name(&self) -> &str { "normalize" }
}
```

Community contributions welcome for Parquet, HuggingFace Hub, S3/GCS sources.

## License

MIT. Copyright 2026 Corum Collective LLC.