This is a native implementation of NetCDF in the Go language. It supports the CDF file format fully, and has limited support for the HDF5 format. It's not a wrapper. There's no C or C code underneath this. It is pure Go code. It benefits from the the sandboxing and garbage collection that Go provides, so is safer to use in a production environment.

The API is mainly intended for reading files, though there is support for writing CDF files. To read files, please use the generic Open and New() interface, rather than any lower layer interfaces.

The goal of the API is to be easy to use, and some functionality may be compromised because of that.

Most types are what you what you would expect and map one-to-one to Go language types. The only tricky ones are bytes, unsigned bytes and strings. The NetCDF byte type is signed and the Go language byte type is unsigned, so the proper mapping is for NetCDF bytes to become Go int8s. Conversely, the NetCDF ubyte becomes the Go uint8.

The char type in NetCDF is meant for strings, but char is a scalar in NetCDF and Go has no scalar character type, just a string type to represent character strings. So, the mapping of NetCDF char is to Go string as the closest fit. Scalar characters in NetCDF will be returned as strings of length one. Scalar characters cannot be written to NetCDF with this API; they will always be written as strings of length one.

Also note, that while it is normal to use the int type in Go, this type cannot be written to NetCDF. int32 should be used instead.

package main

import (
    "fmt"
    "github.com/batchatco/go-native-netcdf/netcdf"
)

func main() {
    // Open the file
    nc, err := netcdf.Open("data.nc")
    if err != nil {
        panic(err)
    }
    defer nc.Close()

    // Read the NetCDF variable from the file
    vr, _ := nc.GetVariable("latitude")
    if vr == nil {
        panic("latitude variable not found")
    }

    // Cast the data into a Go type we can use
    lats, has := vr.Values.([]float32)
    if !has {
        panic("latitude data not found")
    }
    for i, lat := range lats {
        fmt.Println(i, lat)
    }
}

It is similar, but supports subgroups.

package main

import (
    "fmt"
    "github.com/batchatco/go-native-netcdf/netcdf"
)

func main() {
    // Open the file
    ncf, err := netcdf.Open("data.nc")
    if err != nil {
        panic(err)
    }
    defer ncf.Close()

    // This is the only thing different about HDF5 from CDF
    // in this implementation.
    nc, err := ncf.GetGroup("/raw")
    if err != nil {
        panic(err)
    }
    defer nc.Close()

    // Read the NetCDF variable from the file
    vr, _ := nc.GetVariable("latitude")
    if vr == nil {
        panic("latitude variable not found")
    }

    // Cast the data into a Go type we can use
    lats, has := vr.Values.([]float32)
    if !has {
        panic("latitude data not found")
    }
    for i, lat := range lats {
        fmt.Println(i, lat)
    }
}

package main

import (
  "github.com/batchatco/go-native-netcdf/netcdf/api"
  "github.com/batchatco/go-native-netcdf/netcdf/cdf"
  "github.com/batchatco/go-native-netcdf/netcdf/util"
)

func main() {
    cw, err := cdf.OpenWriter("newdata.nc")
    if err != nil {
        panic(err)
    }

    latitude := []float32{32.5, 64.1}
    dimensions := []string{"sounding_id"}
    attributes, err := util.NewOrderedMap(
        []string{"comment"},
        map[string]interface{}{"comment": "Latitude indexed by sounding ID"})
    if err != nil {
        panic(err)
    }
    variable := api.Variable{
        latitude,
        dimensions,
        attributes}
    err = cw.AddVar("latitude", variable)
    if err != nil {
        panic(err)
    }
    // Close will write out the data and close the file
    err = cw.Close()
    if err != nil {
        panic(err)
    }
}

Unlimited data types are not supported. The only exception is that a one dimensional empty slice will be written out as unlimited, but currently zero length. For writing out variables with dimensions greater than one to work, extra information would need to be passed in to know the sizes of the other dimensions, because they cannot be guessed based upon the information in the slice. This doesn't seem like all that important of a feature though, and it would clutter the UI, so it is not implemented.

The HDF5 code is quite hacky, but it has run though several unit tests, with good coverage, and should be pretty solid. Performance has not been looked at yet though, so it is likely slower than the alternative.

It's working well enough that I feel it is okay to publish it now. I'll continue to work on it. I can clean up the code and make it run faster, for example. Feedback is welcome.

Some of the exotic HDF5 types are actually implemented, but the interfaces to them mostly hidden. Variables of these types will get parsed and returned in an unsupported format. If you want to play with it, fine. If there's enough demand, I can expose the interfaces.

If you want to run the HDF5 unit tests, you will need netcdf installed and specifically, the ncdump and ncgen commands. You will also need the HDF5 package, and specifically the h5dump and h5repack commands. These are both available as an Ubuntu packages.

$ sudo apt-get install netcdf-bin
$ sudo apt-get install hdf5-tools