This repository features the basemodels for job manifest data consumed by hmt-escrow.

Docker

In order to get going you need Docker installed on your computer.

Getting started

First build the image that contains all the code and dependencies:

docker compose build

Run the tests:

docker compose run basemodels ./bin/test

Lint the python files:

docker compose run basemodels ./bin/lint

Manual

Setup the environment

virtualenv -p python3 venv
source venv/bin/activate

Run the tests:

pytest tests

Lint the python files:

yapf --diff ./basemodels/__init__.py ./test.py
mypy ./basemodels/__init__.py ./test.py --ignore-missing-imports

How to use model

Using the new model (based on pydantic library)

import basemodels
from pydantic.v1 import ValidationError

model = {
    'job_mode': 'batch',
    'request_type': 'image_label_area_select',
    'unsafe_content': False,
    'task_bid_price': 1,
    ...
}
# Validate model on creation
try:
   manifest = basemodels.Manifest(**model)
except ValidationError as e:
   print(e.json())
# Or creating model without validation
manifest = basemodels.Manifest.model_construct(**model)
# See https://pydantic-docs.helpmanual.io/usage/models/#creating-models-without-validation

Note for maintainers: Deploying to PyPi

The tags will need to be pushed to master via a user that has the proper privileges (see the contributors of this repo).

Versioning should follow the semver versioning methodology and not introduce breaking changes on minor or patch-level changes.

Manual deploy to PyPi

In root folder

• virtualenv -p python3 venv
• source venv/bin/activate
• pipenv install --dev
• pip install twine
• python3 setup.py sdist bdist_wheel
• twine upload dist/*

Have a question?

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License

MIT © HUMAN Protocol 2020