# clawhdf5-netcdf4

Read NetCDF-4 files in pure Rust. NetCDF-4 files are HDF5 files with
conventions for dimensions, coordinate variables and attributes; this crate
reads them through the [`clawhdf5`](../clawhdf5/README.md) facade, with no
libnetcdf or libhdf5. Read-only: NetCDF-3 (classic) files are not HDF5 and
are not supported.

Not on crates.io yet; depend on it from git:

```toml
[dependencies]
clawhdf5-netcdf4 = { git = "https://git.redclaw.dev/quantumclaw/clawhdf5" }
```

## Usage

```rust,no_run
use clawhdf5_netcdf4::NetCDF4File;

let nc = NetCDF4File::open("climate.nc")?;
for dim in nc.dimensions()? {
    println!("{}: {} (unlimited = {})", dim.name, dim.size, dim.is_unlimited);
}
let mut temp = nc.variable("temperature")?;
let dims: Vec<&str> = temp.dimensions().iter().map(|d| d.name.as_str()).collect();
println!("{:?} over {:?}", temp.shape()?, dims);
let cf = temp.cf_attributes()?;
println!("units: {:?}", cf.units);
// scale_factor/add_offset applied; _FillValue and missing_value become NaN
let values: Vec<f64> = temp.read_f64()?;
# Ok::<(), clawhdf5_netcdf4::Error>(())
```

## API

| Item | What |
|---|---|
| `NetCDF4File` | `open`, `from_bytes`, `dimensions`, `variables`, `variable_names`, `variable` (a name or a path into a subgroup), `global_attrs`, `group` (a name or a path), `group_names`, `nc_properties`, and `hdf5_file` for the underlying `clawhdf5::File` |
| `NetCDF4Group` | the same for a sub-group (`dimensions`, `variables`, `variable_names`, `attrs`, nested `group`) |
| `Variable` | `name`, `shape`, `stored_shape`, `dimensions`, `nc_type`, `is_coordinate`, `attrs`, `cf_attributes`; `read_f64` (CF scale/offset and fill applied), `read_raw_f32`/`_f64`/`_i32`/`_i64`/`_u64`, `read_string`, `read_raw` |
| `Dimension` | `name`, `size`, `is_unlimited` (an unlimited dimension's `size` is its current length as netCDF-C reports it: the largest extent of the variables using it) |
| `CfAttributes` | CF convention attributes: `units`, `long_name`, `standard_name`, `fill_value` (`_FillValue`), `missing_value`, `scale_factor`, `add_offset`, `valid_range`, `calendar`, `axis` |
| `NcType` | the NetCDF type of a variable: an atomic type (`Byte` ... `UInt64`, `Float`, `Double`, `Char`, `String`) or the class of a user-defined one (`Enum`, `Compound`, `VLen`, `Opaque`); `#[non_exhaustive]` |

Groups, dimensions and variables are what netCDF-C 4.9.3 reports
(`libhdf5/hdf5open.c`), names, order and types included. The first call
that needs them reads the metadata of the whole file, as `nc_open` does:

- Order: a group's links in creation order when it tracks it (netCDF-4
  files do), else in name order (h5py's default); groups and variables in
  that order, dimensions by id.
- A dimension scale defines a dimension (its `_Netcdf4Dimid`, else the
  next free id; unlimited when its first axis is or its length is 0);
  scales that are only dimensions are not variables, and a dataset
  `_nc4_non_coord_<name>` is the variable `<name>`.
- A variable's dimensions are the ones the file names: the ids in its
  `_Netcdf4Coordinates` attribute (any group), else — when its first axis
  has one — the dimension scales its `DIMENSION_LIST` attaches, found in
  its group or a parent group.
- Otherwise (an HDF5 file not written by a netCDF library) its axes get
  netCDF-C's **phony dimensions** `phony_dim_<n>`: per axis, the first
  dimension of the variable's group with the same length and
  unlimitedness that an earlier axis of the variable does not use, else a
  new one. The numbers run file-wide, a group's subgroups before its own
  variables.
- Datasets of types netCDF-C cannot represent are not variables:
  references, bit fields, time and array types, and compounds, enums and
  VLENs over members or base types that are not netCDF atomic types (4-
  and 8-byte floats only) or types netCDF-C has read before in the file.
  Enum, compound, VLEN and opaque datasets are variables of those classes
  (netCDF4-python itself leaves out opaque ones).
- Two deliberate differences: floats of other than 4 or 8 bytes (half,
  bfloat16, 4/6/8-bit floats, `long double`) are `Float`/`Double` and
  read as numbers, where netCDF-C 4.9.3 on libhdf5 1.14.6 labels them
  `NC_STRING`; and an axis netCDF-C leaves without a dimension (an id or
  scale it cannot find, or no scale on an axis after a first one that has
  one, where it reads uninitialised memory) gets one by the phony rule.
- A variable along an unlimited dimension has the dimension's length:
  `shape` is that length, and the reads return that many values, the
  records the variable has not written as its fill value (`_FillValue`,
  else netCDF's default for the type; NaN from `read_f64`).
  `stored_shape` is the HDF5 dataset's extent.

No cargo features. Tests compare against files written by netCDF4-python,
h5py (with and without dimension scales, every HDF5 type class), h5netcdf
and xarray, with what netCDF4-python reads and with what netCDF-C itself
reports (`tests/interop_tests.rs`; `tests/netcdf_c_view.py` calls the
libnetcdf netCDF4-python bundles; the CI job requires them with
`CLAWHDF5_REQUIRE_INTEROP=1`; the h5netcdf cases skip when h5netcdf is not
installed). `tests/corpus_vs_netcdf_c.rs` compares every file of a corpus
netCDF-C opens, when `CLAWHDF5_NETCDF_CORPUS` names one: over the
conformance corpus, 420 of 429 files match (tank, 2026-09-29), and the
other 9 are explained in `tests/corpus_known_differences.txt`:

```sh
CLAWHDF5_NETCDF_CORPUS=conformance/.cache/corpus CLAWHDF5_PYTHON=$PWD/.venv/bin/python \
    cargo test -p clawhdf5-netcdf4 --test corpus_vs_netcdf_c -- --nocapture
```

The differences from netCDF-C, and what the HDF5 reader underneath cannot
read, are listed in [`docs/known-issues.md`](../../docs/known-issues.md).

## License

MIT