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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
43 lines
1.4 KiB
Python
43 lines
1.4 KiB
Python
from tutor import env
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from tutor.types import Config
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class BaseTaskRunner:
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"""
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A task runner is responsible for running bash commands in the right context.
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Commands may be loaded from string or template files. The `run_task` method must be
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implemented by child classes.
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"""
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def __init__(self, root: str, config: Config):
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self.root = root
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self.config = config
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def run_task_from_template(self, service: str, *path: str) -> None:
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command = self.render(*path)
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self.run_task(service, command)
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def run_task_from_str(self, service: str, command: str) -> None:
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rendered = env.render_str(self.config, command).strip()
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self.run_task(service, rendered)
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def render(self, *path: str) -> str:
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rendered = env.render_file(self.config, *path).strip()
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if isinstance(rendered, bytes):
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raise TypeError("Cannot load job from binary file")
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return rendered
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def run_task(self, service: str, command: str) -> int:
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"""
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Given a (potentially large) string command, run it with the
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corresponding service. Implementations will differ depending on the
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deployment strategy.
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"""
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raise NotImplementedError
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class BaseComposeTaskRunner(BaseTaskRunner):
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def docker_compose(self, *command: str) -> int:
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raise NotImplementedError
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