ocean-runner 0.2.2

A fluent API for OceanProtocol algorithms

ocean-runner

Ocean Runner is a package that brings a fluent API for APP creation and running in the scope of OceanProtocol.

Usage

Minimal Example

import random
from ocean_runner import Algorithm, Config


Algorithm().run(lambda _: random.randint()).save_results()    

To use minimally the API, you can just provide a callback to the run method, defaulting for the rest of behaviours. This code snippet will:

• Read the OceanProtocol JobDetails from the environment variables and use default file paths.
• Generate a random integer.
• Store the result in a "result.txt" file within the default outputs path.

Tuning

Application Config

The application configuration can be tweaked by passing a Config instance to its' constructor.

Algorithm(
    Config(
        custom_input: ... # dataclass
        # Custom algorithm parameters dataclass.
        
        error_callback: ... # Callable[[Exception], None]
        # Callback to run on exceptions.
        
        logger: ... # type: logging.Logger
        # Custom logger to use.

        source_paths: ... # type: Iterable[Path]
        # Source paths to include in the PATH
        
        environment: ... 
        # type: ocean_runner.Environment. Mock of environment variables.
    )
)

import logging


@dataclass
class CustomInput:
    foobar: string 


logger = logging.getLogger(__name__)


Algorithm(
    Config(
        custom_input: CustomInput,
        """
        Load the Algorithm's Custom Input into a CustomInput dataclass instance.
        """

        error_callback: lambda ex: logger.exception(ex),
        """
        Run this callback when an exception is caught
        NOTE: it's not recommended to catch exceptions this way. Should re-raise and halt the execution.
        """

        source_paths: [Path("/algorithm/src")],
        """
        Source paths to include in the PATH. '/algorithm/src' is the default since our templates place the algorithm source files there.
        """

        logger: logger,
        """
        Custom logger to use in the Algorithm.
        """

        environment: Environment(
            base_dir: "./_data",
            """
            Custom data path to use test data.
            """

            dids: '["17feb697190d9f5912e064307006c06019c766d35e4e3f239ebb69fb71096e42"]',
            """
            Dataset DID.
            """

            transformation_did: "1234",
            """
            Random transformation DID to use while testing.
            """

            secret: "1234",
            """
            Random secret to use while testing.
            """
        )
        """
        Should not be needed in production algorithms, used to mock environment variables, defaults to using env.
        """
    )
)

Default behaviours

Default implementations

As seen in the minimal example, all methods implemented in Algorithm have a default implementation which will be commented here.

(
    Algorithm()
    
        """
        Default constructor, will use default values of Config.
        """
    
    .validate()
    
        """
        Will validate the algorithm's job detail instance, checking for the existence of:
        - `job_details.ddos` 
        - `job_details.files`
        """

    .run()

        """ 
        Has NO default implementation, must pass a callback that returns a result of any type.
        """

    .save_results()

        """
        Stores the result of running the algorithm in "outputs/results.txt"
        """

)

Job Details

To load the OceanProtocol JobDetails instance, the program will read some environment variables, they can be mocked passing an instance of Environment through the configuration of the algorithm.

Environment variables:

• DIDS: Input dataset(s) DID's.
• TRANSFORMATION_DID: Algorithm DID.
• SECRET: Algorithm secret.
• BASE_DIR (optional, default='/data'): Base path to the OceanProtocol data directories.