argopy.stores.httpstore_erddap_auth

class httpstore_erddap_auth(cache: bool = False, cachedir: str = '', login: str | None = None, payload: dict = {'password': None, 'user': None}, auto: bool = True, **kwargs)

__init__(cache: bool = False, cachedir: str = '', login: str | None = None, payload: dict = {'password': None, 'user': None}, auto: bool = True, **kwargs)

Create a file storage system for Argo data

Parameters:

• cache (bool (False))

• cachedir (str (from OPTIONS))

• **kwargs ((optional)) – Other arguments passed to fsspec.filesystem

Methods

__init__([cache, cachedir, login, payload, auto])	Create a file storage system for Argo data
cachepath(uri[, errors])	Return path to cached file for a given URI
clear_cache()	Remove cache files and entry from uri open with this store instance
connect()
curateurl(url)	Possibly replace server of a given url by a local argopy option value
download_url(url[, n_attempt, max_attempt, ...])	URL data downloader
exists(path, *args, **kwargs)
expand_path(path)
get_auth_client(**kwargs)
glob(path, **kwargs)
open(path, *args, **kwargs)
open_dataset(url[, errors])	Open and decode a xarray dataset from an url
open_json(url, **kwargs)	Return a json from an url, or verbose errors
open_mfdataset(urls[, max_workers, method, ...])	Open multiple urls as a single xarray dataset.
open_mfjson(urls[, max_workers, method, ...])	Open multiple json urls
read_csv(url, **kwargs)	Read a comma-separated values (csv) url into Pandas DataFrame.
register(uri)	Keep track of files open with this instance
store_path(uri)

Attributes

cached_files
connected
protocol	File system name, one in fsspec.registry.known_implementations