npyz 0.8.0

NumPy file format (de-)serialization. Fork of outdated npy-rs.
Documentation
# npyz

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Numpy format (`*.npy`) serialization and deserialization.

[**NPY**](https://docs.scipy.org/doc/numpy-dev/neps/npy-format.html) is a simple binary data format.
It stores the type, shape and endianness information in a header,
which is followed by a flat binary data field. This crate offers a simple, mostly type-safe way to
read and write `*.npy` files. Files are handled using iterators, so they don't need to fit in memory.

`npyz` is a fork and successor of the seemingly-dead [`npy`](https://github.com/potocpav/npy-rs).

[API Documentation on docs.rs](https://docs.rs/npyz)

## Usage

```toml
[dependencies]
npyz = "0.8"
```

You also may be interested in enabling some features:

```toml
[dependencies]
npyz = {version = "0.7", features = ["derive", "complex", "npz", "arrayvec"]}
```

Data can now be read from a `*.npy` file:

```rust
fn main() -> Result<(), Box<dyn std::error::Error>> {
    let bytes = std::fs::read("test-data/plain.npy")?;

    // Note: In addition to byte slices, this accepts any io::Read
    let npy = npyz::NpyFile::new(&bytes[..])?;
    for number in npy.data::<f64>()? {
        let number = number?;
        eprintln!("{}", number);
    }
    Ok(())
}
```

For further examples and information on:
* Reading `npy` files,
* Writing `npy` files,
* Working with structured arrays,
* Interop with the `ndarray` crate,
* NPZ files and scipy sparse matrices,

please see the [documentation on the root module](https://docs.rs/npyz).

## Relation to similar crates

The name `npyz` is actually an abbreviation.  Here is the full name of the crate:

> `npy` plus npz support, and a lot of other features that are frankly a lot more important than npz—not to mention the fact that npz support isn't even actually included in the first release—but I had to call it something, okay

To clarify, `npyz` is a fork of Pavel Potoček's [`npy` crate](https://github.com/potocpav/npy-rs).  The original `npy` supported structured arrays with derives, but had many, many limitations.

Compared to `npy`, `npyz` has:

* Support for multidimensional arrays.
* Support for big endian files.
* Support for `Complex`, strings and bytestrings.
* A more versatile reading API based on `std::io::Read`, so you can read directly from e.g. a [`zip::read::ZipFile`]https://docs.rs/zip/latest/zip/read/struct.ZipFile.html.  The original API required a `&[u8]`, with the expectation that a user can use a memmap for large files.
* Writing APIs based on `std::io::Write`.

Originally, ~~`nippy`~~ `npyz` was a place for me to protype new features with reckless abandon before finally making a PR to `npy`, but even my first few foundational PRs have yet to be merged upstream.  I believe Pavel has a good head on their shoulders and a great attention to detail, and I appreciated their initial response on my PRs, but nearly two years have passed since the last time I have heard from them. Therefore, I've decided to go forward and publish the fork.

## License

`npyz` is Copyright 2021 Michael Lamparski, and provided under the terms of the MIT License.

`npyz` is based off of `npy`.  `npy` is Copyright 2018 Pavel Potoček, which was provided under the terms of the MIT License.