PrivateAIM Python Template

This repository serves as a template for Python-based analyzes within the PrivateAIM project. It comes preconfigured with tools for testing, building, linting and formatting your Python code.

Python sdk core

Startup

Every FLAME analysis starts by connecting itself to the other components of the flame platform and starting an Analysis REST-API. All of this is done simply by instancing a FlameSDK object.

from flame import FlameSDK

def main():
    flame = FlameSDK()
    # Your code here

if __name__ == "__main__":
    main()
   

During the creation of the FlameSDK object, the connection to the other components of the flame platform is established automatically.

Message Broker Client

Purpose

The Message Broker is a service for sending and receiving messages between nodes. It is used as a simplistic communication between nodes for control and small data exchange purposes. Note, that Volume Data like ML models should be exchanged using the Result Service.

List of available methods

• get_list_of_participants(self) -> List[nodeID]
  • Returns a list of all nodes participating in the analysis.
• send_message(self, receivers: List[nodeID], message: dict) -> None
  • Sends a message to all specified nodes.
• await_message(self, node_ids: List[nodeID], timeout: int = None) -> dict
  • Waits for messages from the specified nodes to arrive.
• get_list_of_messages(self) -> List[dict]
  • Returns a list of all messages that have arrived.

List of quality of life methods

• send_message_and_wait_for_responses(self, receivers: List[nodeID], message: dict, timeout: int = None) -> dict
  • Sends a message to the specified nodes and waits for responses.
• ask_status_nodes(self, timeout: int) -> Literal["online", "offline", "not_connected"]
  • Returns the status of all nodes.
• send_intermediate_result(self, receivers: List[nodeID], result: IOstream) -> None
  • Sends an intermediate result using Result Service and Message Broker.

Message structure

{
    "sender": "node_id",
    "time": "datetime",
    "message_number": "int",
    "data": "dict"
}

Result Service (temporary name "Result Client")

Purpose

The Result Service is a service for saving and exchanging results between nodes of one analysis and locally between different analyzes of the same Project.

List of available methods

• submit_final_result(self, result: IOstream) -> Request.Status
  • sends final result to the hub. Making it available for analysts to download. This method is only available for nodes for which the method get_role(self) returns "aggregator".
• save_intermediate_global_result(self, result: IOstream) -> result_id
  • saves intermediate result at the hub. Making it available for other nodes to download.
• save_intermediate_result_local(self, result: IOstream) -> result_id
  • saves intermediate result to the local storage. Making it available for later analyzes in the same Project.
• list_intermediate_local_results(self) -> List[result_info]
  • returns a list of all locally saved intermediate results.
• list_intermediate_global_results(self) -> List[result_info]
  • returns a list of all intermediate results saved on the hub.
• get_intermediate_global_result(self, result_id: str) -> IOstream
  • returns the global intermediate result with the specified id.
• get_intermediate_local_result(self, result_id: str) -> IOstream
  • returns the local intermediate result with the specified id.
• get_role(self) -> Literal["aggregator", "default"]
  • get the role of the node. "aggregator" means that the node can submit final results using "submit_final_result", else "default" if not.

list of quality of life methods

• TODO: store and retrieve specific data types like fhir, torch, pandas, numpy, etc.
• send_intermediate_result(self, receivers: List[nodeID], result: IOstream) -> None
  • Sends an intermediate result using Result Service and Message Broker.

Result structure local

{
  "result_id": "str",
  "result_name": "str",
  "analysis_id": "str",
  "result_size": "int",
  "result_time": "datetime",
  "result_owner": "str",
  "other": "dict"
}

Result structure hub

{
  "result_id": "str",
  "result_name": "str",
  "node_id": "str",
  "result_size": "int",
  "result_time": "datetime",
  "result_owner": "str",
  "other": "dict"
}

Data Source Client

Purpose

Data Source Client is a service for accessing data from different sources like FHIR or S3 linked to the project.

List of available methods

• get_data_client(self, data_id: str) -> data_client
  • Returns the data client for a specific fhir or S3 store used for this project.
• get_data_sources(self) -> List[data_source]
  • Returns a list of all data sources available for this project.

List of quality of life methods

``- get_fhir_data(self, queries: List[str]) -> List[dict]

• Returns the data from the FHIR store for each of the specified queries.
• get_s3_data(self, key: str, local_path: str) -> IOstream
  • Returns the data from the S3 store associated with the given key.``