Skip to main content

A fluent API for OceanProtocol algorithms

Project description

ocean-runner

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

Installation

pip install ocean-runner
# or
uv add ocean-runner

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.
            """

            runtime: "dev",
            """
            Runtime mode. "dev" to run normally, "test" to run pytest
            """
        )
        """
        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, must have format: ["abc..90"]
  • TRANSFORMATION_DID Algorithm DID, must have format: abc..90
  • SECRET Algorithm secret.
  • BASE_DIR (optional, default="/data"): Base path to the OceanProtocol data directories.
  • RUNTIME (optional, default="dev"): Runtime mode

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

ocean_runner-0.2.9.tar.gz (4.9 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

ocean_runner-0.2.9-py3-none-any.whl (6.7 kB view details)

Uploaded Python 3

File details

Details for the file ocean_runner-0.2.9.tar.gz.

File metadata

  • Download URL: ocean_runner-0.2.9.tar.gz
  • Upload date:
  • Size: 4.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.0.1 CPython/3.12.8

File hashes

Hashes for ocean_runner-0.2.9.tar.gz
Algorithm Hash digest
SHA256 f22f2004f4c51bfaef078308328a5a19a0ca5dca16d474935d4dbadec2807279
MD5 259ac491d2c714ca7fba315766556c4a
BLAKE2b-256 6b343de2567145c0805967d6f71b3026333198d07c37e3411315b3ffcf42c4c6

See more details on using hashes here.

File details

Details for the file ocean_runner-0.2.9-py3-none-any.whl.

File metadata

  • Download URL: ocean_runner-0.2.9-py3-none-any.whl
  • Upload date:
  • Size: 6.7 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.0.1 CPython/3.12.8

File hashes

Hashes for ocean_runner-0.2.9-py3-none-any.whl
Algorithm Hash digest
SHA256 3ccb214b276e9d03852697026bf691350dc25f30899ee0b76c0751909ea4e5f6
MD5 7e1b6aa390171325477d473f3229bf38
BLAKE2b-256 71a04c9aa3572f3736581b8e7acceec4a5f35d9146858e49c3950430583a36a0

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page