argopy.stores.argo_index_pd.indexstore_pandas

class indexstore_pandas(host: str = 'https://data-argo.ifremer.fr', index_file: str = 'ar_index_global_prof.txt', convention: str | None = None, cache: bool = False, cachedir: str = '', timeout: int = 0)

Argo GDAC index store using pandas.DataFrame as internal storage format.

With this store, index and search results are saved as pickle files in cache

__init__(host: str = 'https://data-argo.ifremer.fr', index_file: str = 'ar_index_global_prof.txt', convention: str | None = None, cache: bool = False, cachedir: str = '', timeout: int = 0) → object

Create an Argo index file store

Parameters:

• host (str, default: https://data-argo.ifremer.fr) – Local or remote (ftp or http) path to a dac folder (GDAC structure compliant). This takes values like: ftp://ftp.ifremer.fr/ifremer/argo, ftp://usgodae.org/pub/outgoing/argo or a local absolute path.

• index_file (str, default: ar_index_global_prof.txt) –

  Name of the csv-like text file with the index.

  Possible values are standard file name: ar_index_global_prof.txt, argo_bio-profile_index.txt or argo_synthetic-profile_index.txt.

  You can also use the following shortcuts: core, bgc-b, bgc-s, respectively.

• convention (str, default: None) –

  Set the expected format convention of the index file. This is useful when trying to load index file with custom name. If set to None, we’ll try to infer the convention from the index_file value.

  Possible values: ar_index_global_prof, argo_bio-profile_index, or argo_synthetic-profile_index.

  You can also use the keyword: core, bgc-s, bgc-b.

• cache (bool, default: False) – Use cache or not.

• cachedir (str, default: OPTIONS['cachedir']) – Folder where to store cached files

• timeout (int, default: OPTIONS['api_timeout']) – Time out in seconds to connect to a remote host (ftp or http).

Methods

__init__([host, index_file, convention, ...])	Create an Argo index file store
cachepath(path)	Return path to a cached file
clear_cache()	Clear cache registry and files associated with this store instance.
load([nrows, force])	Load an Argo-index file content
read_params([index])	Return list of unique PARAMETERs in index or search results
read_wmo([index])	Return list of unique WMOs in search results
records_per_wmo([index])	Return the number of records per unique WMOs in search results
run([nrows])	Filter index with search criteria
search_cyc(CYCs[, nrows])	Search index for cycle numbers
search_lat_lon(BOX[, nrows])	Search index for a rectangular latitude/longitude domain
search_lat_lon_tim(BOX[, nrows])	Search index for a rectangular latitude/longitude domain and time range
search_parameter_data_mode(PARAMs[, ...])	Search index for profiles with a parameter in a specific data mode
search_params(PARAMs[, logical, nrows])	Search index for one or a list of parameters
search_tim(BOX[, nrows])	Search index for a time range
search_wmo(WMOs[, nrows])	Search index for floats defined by their WMO
search_wmo_cyc(WMOs, CYCs[, nrows])	Search index for floats defined by their WMO and specific cycle numbers
to_dataframe([nrows, index, completed])	Return index or search results as pandas.DataFrame
to_indexfile(outputfile)	Save search results on file, following the Argo standard index formats

Attributes

N_FILES	Number of rows in search result or index if search not triggered
N_MATCH	Number of rows in search result
N_RECORDS	Number of rows in the full index
backend	Name of store backend
cname	Return the search constraint(s) as a pretty formatted string
convention	Convention of the index (standard csv file name)
convention_supported	List of supported conventions
convention_title	Long name for the index convention
ext	Storage file extension
search_path	Path to search result uri
search_type	Dictionary with search meta-data
sha_df	Returns a unique SHA for a cname/dataframe
sha_h5	Returns a unique SHA for a cname/hdf5
sha_pq	Returns a unique SHA for a cname/parquet
shape	Shape of the index array
uri	List of URI from search results
uri_full_index	List of URI from index