Experiments

counts(*, version=None, per_platform=False)

Retrieve the number of experiments assets in the metadata catalogue.

Parameters:

Name	Type	Description	Default
version	str | None	The version of the endpoint (default is None).	None
per_platform	bool	Whether to list counts per platform (default is False).	False

Returns:

Type	Description
int | dict[str, int]	The number experiments assets in the metadata catalogue. If the parameter per_platform is True, it returns a dictionary with platform names as keys and the number of experiments assets from that platform as values.

get_asset(*, identifier, version=None, data_format='pandas')

Retrieve metadata for a specific experiments.

Parameters:

Name	Type	Description	Default
identifier	int	The identifier of the experiments to retrieve.	required
version	str | None	The version of the endpoint (default is None).	None
data_format	Literal['pandas', 'json']	The desired format for the response (default is "pandas"). For "json" formats, the returned type is a json decoded type, in this case a dict.	'pandas'

Returns:

Type	Description
Series | dict	The retrieved metadata for the specified experiments.

get_asset_from_platform(*, platform, platform_identifier, version=None, data_format='pandas')

Retrieve metadata for a specific experiments identified by the external platform identifier.

Parameters:

Name	Type	Description	Default
platform	str	The platform where the experiments asset is retrieved from.	required
platform_identifier	str	The identifier under which the experiments is known by the platform.	required
version	str | None	The version of the endpoint (default is None).	None
data_format	Literal['pandas', 'json']	The desired format for the response (default is "pandas"). For "json" formats, the returned type is a json decoded type, in this case a dict.	'pandas'

Returns:

Type	Description
Series | dict	The retrieved metadata for the specified experiments.

get_assets_async(*, identifiers, version=None, data_format='pandas') async

Asynchronously retrieve metadata for a list of experiments identifiers.

Parameters:

Name	Type	Description	Default
identifiers	list[int]	The list of identifiers of the experiments to retrieve.	required
version	str | None	The version of the endpoint (default is None).	None
data_format	Literal['pandas', 'json']	The desired format for the response (default is "pandas"). For "json" formats, the returned type is a json decoded type, in this case a list of dicts.	'pandas'

Returns:

Type	Description
DataFrame | list[dict]	The retrieved metadata for the specified experiments.

get_content(*, identifier, distribution_idx=0, version=None)

Retrieve the data content of a specific experiments.

Parameters:

Name	Type	Description	Default
identifier	int	The identifier of the experiments asset.	required
distribution_idx	int	The index of a specific distribution from the distribution list (default is 0).	0
version	str | None	The version of the endpoint (default is None).	None

Returns:

Type	Description
bytes	The data content for the specified experiments.

get_list(*, platform=None, offset=0, limit=10, version=None, data_format='pandas')

Retrieve a list of experiments from the catalogue.

Parameters:

Name	Type	Description	Default
platform	str | None	Return metadata of experiments assets of this platform (default is None).	None
offset	int	The offset for pagination (default is 0).	0
limit	int	The maximum number of items to retrieve (default is 10).	10
version	str | None	The version of the endpoint (default is None).	None
data_format	Literal['pandas', 'json']	The desired format for the response (default is "pandas"). For "json" formats, the returned type is a json decoded type, i.e. in this case a list of dicts.	'pandas'

Returns:

Type	Description
DataFrame | list[dict]	The retrieved metadata in the specified format.

get_list_async(*, offset=0, limit=100, batch_size=10, version=None, data_format='pandas') async

Asynchronously retrieve a list of experiments from the catalogue in batches.

Parameters:

Name	Type	Description	Default
offset	int	The offset for pagination (default is 0).	0
limit	int	The maximum number of items to retrieve (default is 10).	100
batch_size	int	The number of items in a a batch.	10
version	str | None	The version of the endpoint (default is None).	None
data_format	Literal['pandas', 'json']	The desired format for the response (default is "pandas"). For "json" formats, the returned type is a json decoded type, in this case a list of dicts.	'pandas'

Returns:

Type	Description
DataFrame | list[dict]	The retrieved metadata in the specified format.

Raises:

Type	Description
ValueError	Batch size must be larger than 0.

search(*, search_query, platforms=None, offset=0, limit=10, search_field=None, get_all=True, version=None, data_format='pandas')

Search metadata for experiments type using the Elasticsearch endpoint of the AIoD metadata catalogue.

Parameters:

Name	Type	Description	Default
search_query	str	The string to be matched against the search fields.	required
platforms	list[str] | None	The platforms to filter the search results. If None, results from all platforms will be returned (default is None).	None
offset	int	The offset for pagination (default is 0).	0
limit	int	The maximum number of results to retrieve (default is 10).	10
search_field	None | Literal['name', 'issn', 'description_html', 'description_plain']	The specific fields to search within. If None, the query will be matched against all fields (default is None).	None
get_all	bool	If true, a request to the database is made to retrieve all data. If false, only the indexed information is returned. (default is True).	True
version	str | None	The version of the endpoint to use (default is None).	None
data_format	Literal['pandas', 'json']	The desired format for the response (default is "pandas"). For "json" formats, the returned type is a json decoded type, in this case a list of dict's.	'pandas'

Returns:

Type	Description
DataFrame | list[dict]	The retrieved metadata in the specified format.