lomas_client package

Subpackages

• lomas_client.libraries package
  • Submodules
  • lomas_client.libraries.diffprivlib module
    • DiffPrivLibClient
      • DiffPrivLibClient.cost()
      • DiffPrivLibClient.query()
  • lomas_client.libraries.opendp module
    • OpenDPClient
      • OpenDPClient.cost()
      • OpenDPClient.query()
  • lomas_client.libraries.smartnoise_sql module
    • SmartnoiseSQLClient
      • SmartnoiseSQLClient.cost()
      • SmartnoiseSQLClient.query()
  • lomas_client.libraries.smartnoise_synth module
    • SmartnoiseSynthClient
      • SmartnoiseSynthClient.cost()
      • SmartnoiseSynthClient.query()
  • Module contents

Submodules

lomas_client.client module

class lomas_client.client.Client(url: str, user_name: str, dataset_name: str)

Bases: object

Client class to send requests to the server.

Handle all serialisation and deserialisation steps

get_dataset_metadata() → LomasRequestModel | None

This function retrieves metadata for the dataset.

Returns:

A dictionary containing dataset metadata.

Return type:

Optional[LomasRequestModel]

get_dummy_dataset(nb_rows: int = 100, seed: int = 42) → DummyDsResponse | None

This function retrieves a dummy dataset with optional parameters.

Parameters:

• nb_rows (int, optional) –

  The number of rows in the dummy dataset.

  Defaults to DUMMY_NB_ROWS.

• seed (int, optional) –

  The random seed for generating the dummy dataset.

  Defaults to DUMMY_SEED.

Returns:

A Pandas DataFrame

representing the dummy dataset.

Return type:

Optional[DummyDsResponse]

get_initial_budget() → InitialBudgetResponse | None

This function retrieves the initial budget.

Returns:

A dictionary

containing the initial budget.

Return type:

Optional[InitialBudgetResponse]

get_previous_queries() → List[dict] | None

This function retrieves the previous queries of the user.

Raises:

ValueError – If an unknown query type is encountered during deserialization.

Returns:

A list of dictionary containing the different queries on the private dataset.

Return type:

Optional[List[dict]]

get_remaining_budget() → RemainingBudgetResponse | None

This function retrieves the remaining budget.

Returns:

A dictionary

containing the remaining budget.

Return type:

Optional[RemainingBudgetResponse]

get_total_spent_budget() → SpentBudgetResponse | None

This function retrieves the total spent budget.

Returns:

A dictionary containing

the total spent budget.

Return type:

Optional[SpentBudgetResponse]

lomas_client.constants module

lomas_client.http_client module

class lomas_client.http_client.LomasHttpClient(url: str, user_name: str, dataset_name: str)

Bases: object

A client for interacting with the Lomas API.

post(endpoint: str, body: LomasRequestModel, read_timeout: int = 10) → Response

Executes a POST request to endpoint with the provided JSON body.

Parameters:

• endpoint (str) – The API endpoint to which the request will be sent.

• body_json (dict, optional) – The JSON body to include in the POST request. Defaults to {}.

• request_model – (BaseModel, optional): The pydantic model to validate the body_json against. Must be non-null if body_json contains data.

• read_timeout (int) – number of seconds that client wait for the server to send a response. Defaults to DEFAULT_READ_TIMEOUT.

Returns:

The response object resulting from the POST request.

Return type:

requests.Response

lomas_client.utils module

lomas_client.utils.raise_error(response: Response) → str

Raise error message based on the HTTP response.

Parameters:

res (requests.Response) – The response object from an HTTP request.

Raises:

Server Error –

lomas_client.utils.validate_model_response(response: Response, response_model: Any) → Any

Validate and process a HTTP response.

Parameters:

response (requests.Response) – The response object from an HTTP request.

Returns:

Model for responses requests.

Return type:

response_model

lomas_client.utils.validate_synthesizer(synth_name: str, return_model: bool = False)

Validate smartnoise synthesizer (some model are not accepted).

Parameters:

• synth_name (str) – name of the Synthesizer model to use.

• return_model (bool) – True to get Synthesizer model, False to get samples

Raises:

ValueError – if a synthesizer or its parameters are not valid

Module contents