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16e6131f96
We introduce a new filter to implement custom commands in arbitrary containers. It becomes easy to write convenient ad-hoc commands that users will then be able to run either on Kubernetes or locally using a documented CLI. Pluggable jobs are declared as Click commands and are responsible for parsing their own arguments. See the new CLI_DO_COMMANDS filter. Close https://github.com/overhangio/2u-tutor-adoption/issues/75
31 lines
794 B
Python
31 lines
794 B
Python
from tutor.tasks import BaseTaskRunner
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from tutor.types import Config
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class Context:
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"""
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Context object that is passed to all subcommands.
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The project `root` is passed to all subcommands of `tutor`; that's because
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it is defined as an argument of the top-level command. For instance:
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$ tutor --root=... local run ...
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"""
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def __init__(self, root: str) -> None:
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self.root = root
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class BaseTaskContext(Context):
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"""
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Specialized context that subcommands may use.
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For instance `dev`, `local` and `k8s` define custom runners to run jobs.
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"""
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def job_runner(self, config: Config) -> BaseTaskRunner:
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"""
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Return a runner capable of running docker-compose/kubectl commands.
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"""
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raise NotImplementedError
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