argopy.stores.s3store

argopy.stores.s3store#

class s3store(*args, **kwargs)[source]#

By default, the s3store will use AWS credentials available in the environment.

If you want to force an anonymous session, you should use the anon=True option.

In order to avoid a no credentials found error, you can use:

>>> from argopy.utils import has_aws_credentials
>>> fs = s3store(anon=not has_aws_credentials())
__init__(*args, **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__(*args, **kwargs)

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

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)

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

protocol

File system name, one in fsspec.registry.known_implementations
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