# GSV interface
A tool for accessing the GSV data from `FDB` and converting it into `xarray`.
## Core idea
The current approach can be summarized in three steps:
1. Use `pyfdb` to request data from the `FDB`. This will return a `pyfdb.Dataretriever` file-like object from which you can read all GRIB messages matching a given request.
2. Use `eccodes-python` to decode the necessary information of each GRIB message (data, coordinates, attributes...). A custom iterator (`MessageIterator`) is used to iterate over each message in the `pyfdb.DataRetriever` object.
3. If requested by the user, interpolate the result to a regular LonLat grid of choice.
All requested messages are packed in a single `xarray.Dataset` object and returned to the user.
## Installation instructionss
The `gsv-interface` package is available to install through pip. It can be installed with the folloeing command:
```
pip install gsv-interface
```
## Checking installation
Top check the installation was succesfull run Python and try to import `gsv`.
```
>>> import gsv
>>> gsv.__version__
```
This should print the version number of the chosen release.
## Dependencies
The followin non-Python libraries are required:
- ecCodes: https://github.com/ecmwf/eccodes
- fdb: https://github.com/ecmwf/fdb
This tool depends on the following Python modules, which are automatically installed though `pip`.
- "pyfdb==0.1.2",
- "numpy",
- "xarray",
- "eccodes",
- "healpy",
- "dask",
- "netcdf4",
- "cfgrib",
- "sparse",
- "cdo",
- "smmregrid==0.1.1",
- "polytope-client",
- "pyyaml",
- "jinja2",
- "packaging"
## Documentation
Docs based on sphinx can be found in the `docs/` directory of the repository.
Build dependencies for the docs can be installed with the following command (it's recommended to run it in a clean environment):
```
pip install -r requirements.txt
```
Then the docs can be built with:
```
make html
```
The resulting html docs can be then found in:
```
docs/build/html/index.html
```
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