aind-codeocean-utils 0.1.5

Generated from aind-library-template

aind-codeocean-utils

Library to contain useful utility methods to interface with Code Ocean.

Installation

To use the package, you can install it from pypi:

pip install aind-codeocean-utils

To install the package from source, in the root directory, run

pip install -e .

To develop the code, run

pip install -e .[dev]

Usage

The package includes helper functions to interact with Code Ocean:

CodeOceanJob

This class enables one to run a job that:

1. Registers a new asset to Code Ocean from s3
2. Runs a capsule/pipeline on the newly registered asset (or an existing assey)
3. Captures the run results into a new asset

Steps 1 and 3 are optional, while step 2 (running the computation) is mandatory.

Here is a full example that registers a new ecephys asset, runs the spike sorting capsule with some parameters, and registers the results:

import os

from aind_codeocean_api.codeocean import CodeOceanClient
from aind_codeocean_utils.codeocean_job import (
    CodeOceanJob, CodeOceanJobConfig
)

# Set up the CodeOceanClient from aind_codeocean_api
CO_TOKEN = os.environ["CO_TOKEN"]
CO_DOMAIN = os.environ["CO_DOMAIN"]

co_client = CodeOceanClient(domain=CO_DOMAIN, token=CO_TOKEN)

# Define Job Parameters
job_config_dict = dict(
    register_config = dict(
        asset_name="test_dataset_for_codeocean_job",
        mount="ecephys_701305_2023-12-26_12-22-25",
        bucket="aind-ephys-data",
        prefix="ecephys_701305_2023-12-26_12-22-25",
        tags=["codeocean_job_test", "ecephys", "701305", "raw"],
        custom_metadata={
            "modality": "extracellular electrophysiology",
            "data level": "raw data",
        },
        viewable_to_everyone=True
    ),
    run_capsule_config = dict(
        data_assets=None, # when None, the newly registered asset will be used
        capsule_id="a31e6c81-49a5-4f1c-b89c-2d47ae3e02b4",
        run_parameters=["--debug", "--no-remove-out-channels"]
    ),
    capture_result_config = dict(
        process_name="sorted",
        tags=["np-ultra"] # additional tags to the ones inherited from input
    )
)

# instantiate config model
job_config = CodeOceanJobConfig(**job_config_dict)

# instantiate code ocean job
co_job = CodeOceanJob(co_client=co_client, job_config=job_config)

# run and wait for results
job_response = co_job.run_job()

This job will:

1. Register the test_dataset_for_codeocean_job asset from the specified s3 bucket and prefix
2. Run the capsule a31e6c81-49a5-4f1c-b89c-2d47ae3e02b4 with the specified parameters
3. Register the result as test_dataset_for_codeocean_job_sorter_{date-time}

To run a computation on existing data assets, do not provide the register_config and provide the data_asset field in the run_capsule_config.

To skip capturing the result, do not provide the capture_result_config option.

Contributing

Linters and testing

There are several libraries used to run linters, check documentation, and run tests.

• Please test your changes using the coverage library, which will run the tests and log a coverage report:

coverage run -m unittest discover && coverage report

• Use interrogate to check that modules, methods, etc. have been documented thoroughly:

interrogate .

• Use flake8 to check that code is up to standards (no unused imports, etc.):

flake8 .

• Use black to automatically format the code into PEP standards:

black .

• Use isort to automatically sort import statements:

isort .

Pull requests

For internal members, please create a branch. For external members, please fork the repository and open a pull request from the fork. We'll primarily use Angular style for commit messages. Roughly, they should follow the pattern:

<type>(<scope>): <short summary>

where scope (optional) describes the packages affected by the code changes and type (mandatory) is one of:

• build: Changes that affect build tools or external dependencies (example scopes: pyproject.toml, setup.py)
• ci: Changes to our CI configuration files and scripts (examples: .github/workflows/ci.yml)
• docs: Documentation only changes
• feat: A new feature
• fix: A bugfix
• perf: A code change that improves performance
• refactor: A code change that neither fixes a bug nor adds a feature
• test: Adding missing tests or correcting existing tests

Semantic Release

The table below, from semantic release, shows which commit message gets you which release type when semantic-release runs (using the default configuration):

Commit message	Release type
fix(pencil): stop graphite breaking when too much pressure applied	Patch Fix Release, Default release
feat(pencil): add 'graphiteWidth' option	Minor Feature Release
perf(pencil): remove graphiteWidth option BREAKING CHANGE: The graphiteWidth option has been removed. The default graphite width of 10mm is always used for performance reasons.	Major Breaking Release (Note that the BREAKING CHANGE: token must be in the footer of the commit)

Documentation

To generate the rst files source files for documentation, run

sphinx-apidoc -o doc_template/source/ src 

Then to create the documentation HTML files, run

sphinx-build -b html doc_template/source/ doc_template/build/html

More info on sphinx installation can be found here.