API Reference

Here you can find all learnware interfaces.

Market

class learnware.market.LearnwareMarket

Market for Learnware

# Provide some python examples
learnmarket = LearnwareMarket()
add_learnware(learnware_name: str, model_path: str, stat_spec_path: str, properties: dict, desc: str) → Tuple[str, bool]

Add a learnware into the market.

Note

Given a prediction of a certain time, all signals before this time will be prepared well.

Parameters:

  • learnware_name (str) – Name of new learnware.

  • model_path (str) – Filepath for learnware model, a zipped file.

  • stat_spec_path (str) – Filepath for statistical specification, a ‘.npy’ file. How to pass parameters requires further discussion.

  • properties (dict) – property for new learnware, in dictionary format.

  • desc (str) – Brief desciption for new learnware.

Returns:

str indicating model_id, bool indicating whether the learnware is added successfully.

Return type:

Tuple[str, bool]

Raises:

FileNotFoundError – file for model or statistical specification not found

delete_learnware(id: str) → bool

deleted a learnware from market

Parameters:

id (str) – id of learnware to be deleted

Returns:

True if the target learnware is deleted successfully.

Return type:

bool

Raises:

Exception – Raise an excpetion when give id is NOT found in learnware list

get_learnware_by_ids(id: str | List[str]) → Learnware | List[Learnware]

Get Learnware from market by id

Parameters:

id (Union[str, List[str]]) – Given one id or a list of ids as target.

Returns:

Return a Learnware object or a list of Learnware objects based on the type of input param.

  • The returned items are search results.

  • ’None’ indicating the target id not found.

Return type:

Union[Learnware, List[Learnware]]

get_property_list() → dict

Return all properties available

Returns:

All properties in dictionary format

Return type:

dict

reload_market(market_path: str, property_list_path: str, load_mode: str = 'database') → bool

Reload the market when server restared.

Parameters:

  • market_path (str) – Directory for market data. ‘_IP_:_port_’ for loading from database.

  • property_list_path (str) – Directory for available properties. Should be a json file.

  • load_mode (str, optional) – Type of reload source. Currently, only ‘database’ is available. Defaults to ‘database’, by default “database”

Returns:

A flag indicating whether the market is reload successfully.

Return type:

bool

Raises:

  • NotImplementedError – Reload method NOT implemented. Currently, only loading from database is supported.

  • FileNotFoundError – Loading source/property_list NOT found. Check whether the source and property_list are available.

search_learnware(target_properties: dict | None = None, target_stat_specification: str | None = None) → Tuple[Any, Dict[str, List[Any]]]

Search Learnware based on properties and statistical specification.

  • Return random learnwares when both target_properties and target_stat_specification is None

  • Search only based on properties when target_stat_specification is None

  • Filter through properties and rank according to statistical specification otherwise

Parameters:

  • target_properties (dict, optional) – Properties selected by user, by default None

  • target_stat_specification (str, optional) – statistical specification uploaded by user, by default None

Returns:

return two items:

  • first is recommended combination, None when no recommended combination is calculated or statistical specification is not provided.

  • second is a list of matched learnwares

Return type:

Tuple[Any, Dict[str, List[Any]]]

Raises:

FileNotFoundError – Give file path is empty.

update_learnware(id: str) → bool

Update Learnware with id and content to be updated. Empty interface. TODO

Parameters:

id (str) – id of target learnware.

Learnware

class learnware.learnware.Learnware(id: str, name: str, model_path: str, specification: Specification, desc: str)

Specification

class learnware.specification.Specification
class learnware.specification.StatSpecification