argopy.data_fetchers.gdac_data.GDACArgoDataFetcher

class GDACArgoDataFetcher(gdac: str = '', ds: str = '', cache: bool = False, cachedir: str = '', dimension: str = 'point', errors: str = 'raise', parallel: bool = False, progress: bool = False, api_timeout: int = 0, **kwargs)

Manage access to Argo data from a GDAC server

Warning

This class is a prototype not meant to be instantiated directly

__init__(gdac: str = '', ds: str = '', cache: bool = False, cachedir: str = '', dimension: str = 'point', errors: str = 'raise', parallel: bool = False, progress: bool = False, api_timeout: int = 0, **kwargs)

Init fetcher

Parameters:

• gdac (str (optional)) – Path to the local or remote directory where the ‘dac’ folder is located

• ds (str (optional)) – Dataset to load: ‘phy’ or ‘bgc’

• cache (bool (optional)) – Cache data or not (default: False)

• cachedir (str (optional)) – Path to cache folder

• dimension (str, default: 'point') – Main dimension of the output dataset. This can be “profile” to retrieve a collection of profiles, or “point” (default) to have data as a collection of measurements. This can be used to optimise performances.

• errors (str (optional)) – If set to ‘raise’ (default), will raise a NetCDF4FileNotFoundError error if any of the requested files cannot be found. If set to ‘ignore’, the file not found is skipped when fetching data.

• parallel (bool, str, distributed.Client, default: False) –

  Set whether to use parallelization or not, and possibly which method to use.

  Possible values:

  • False: no parallelization is used

  • True: use default method specified by the parallel_default_method option

  • any other values accepted by the parallel_default_method option

• progress (bool (optional)) – Show a progress bar or not when fetching data.

• api_timeout (int (optional)) – Server request time out in seconds. Set to OPTIONS[‘api_timeout’] by default.

Methods

__init__([gdac, ds, cache, cachedir, ...])	Init fetcher
clear_cache()	Remove cached files and entries from resources opened with this fetcher
cname()	Return a unique string defining the constraints
dashboard(**kw)	Return 3rd party dashboard for the access point
filter_data_mode(ds, **kwargs)	Apply xarray argo accessor filter_data_mode method
filter_points(ds)
filter_qc(ds, **kwargs)
filter_researchmode(ds, *args, **kwargs)	Filter dataset for research user mode
filter_variables(ds, *args, **kwargs)	Filter variables according to dataset and user mode
init(*args, **kwargs)	Initialisation for a specific fetcher
pre_process(ds, *args, **kwargs)
to_xarray([errors])	Load Argo data and return a xarray.Dataset
transform_data_mode(ds, **kwargs)	Apply xarray argo accessor transform_data_mode method
uri_mono2multi(URIs)	Convert mono-profile URI files to multi-profile files

Attributes

cachepath	Return path to cache file(s) for this request
data_source
sha	Returns a unique SHA for a specific cname / fetcher implementation
uri	Return the list of files to load