avx_arrow/
lib.rs

1//! # avx-arrow - Native Columnar Format
2//!
3//! Native columnar data format optimized for avxDB and Brazilian scientific computing.
4//!
5//! ## Features
6//!
7//! - **Scientific Types**: Quaternions, Tensors, Complex, Spinors
8//! - **High Performance**: Zero-copy, SIMD-optimized
9//! - **avxDB Native**: Direct integration
10//!
11//! ## Quick Start
12//!
13//! ```rust
14//! use avx_arrow::{Schema, Field, DataType, RecordBatch};
15//! use avx_arrow::array::Int64Array;
16//!
17//! let schema = Schema::new(vec![
18//!     Field::new("id", DataType::Int64),
19//! ]);
20//!
21//! let ids = Int64Array::from(vec![1, 2, 3]);
22//! let batch = RecordBatch::try_new(schema, vec![Box::new(ids)])?;
23//! # Ok::<(), avx_arrow::ArrowError>(())
24//! ```
25
26#![warn(missing_docs)]
27#![warn(clippy::all)]
28
29pub mod array;
30pub mod compute;
31pub mod datatypes;
32pub mod error;
33pub mod record_batch;
34pub mod simd;
35pub mod compression;
36
37#[cfg(feature = "scientific")]
38pub mod scientific;
39
40#[cfg(feature = "ipc")]
41pub mod ipc;
42
43// Re-exports
44pub use datatypes::{DataType, Field, Schema};
45pub use error::{ArrowError, Result};
46pub use record_batch::RecordBatch;
47
48/// Library version
49pub const VERSION: &str = env!("CARGO_PKG_VERSION");
50
51#[cfg(test)]
52mod tests {
53    use super::*;
54
55    #[test]
56    fn test_version() {
57        assert!(!VERSION.is_empty());
58        assert!(VERSION.starts_with("0."));
59    }
60}
61
62
63
64
65
avx_arrow/lib.rs

avx_arrow/
lib.rs
