Maintenance updates #94
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corviday
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corviday
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Looks good to me.
I especially like all the poe scripts and the documentation of them, a lot of thought went into that.
| # Development | ||
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| This `docker-compose` is set up for development purposes. It will up a dev instance of `quail` with production settings. All you are required to do is to add the following lines to `birdhouse-config/env.local` running on `dev03`: | ||
| This `docker-compose` is set up for development purposes. It will up a dev instance of `quail` with production settings. All you are required to do is to add the following lines to `birdhouse-config/env.local` running on `marble-dev01`: |
| - Push it: `git push` | ||
| - Push tag: `git push --tags` | ||
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| See the [bumpversion](https://pypi.org/project/bumpversion/) documentation for details. |
| prepare-notebooks Download the output sanitizer config for notebook tests | ||
| test-notebooks Run all local notebook tests with sanitized output | ||
| test-notebooks-local Run notebook tests locally using nbval with sanitization | ||
| docs Convert notebooks to HTML for documentation |
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Lots of tasks, good documentation of them. 👍
| name = "quail" | ||
| version = "0.7.1" | ||
| description = "A Web Processing Service for Climate Data Analysis." | ||
| authors = [{ name = "Nikola Rados", email = "nrados@uvic.ca" }] |
| env = { LOCAL_URL = "http://localhost:5000" } | ||
| help = "Run notebook tests locally using nbval with sanitization" | ||
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| # [tool.poe.tasks.test-notebooks-prod] |
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I left them commented out because local manual runs are more practical for development. Redeploying to Marble is tedious and nbval sometimes shows failures that pass fine in JupyterLab.
| "output_type": "stream", | ||
| "text": [ | ||
| "Using quail on https://docker-dev03.pcic.uvic.ca/twitcher/ows/proxy/quail/wps\n" | ||
| "Using quail on https://marble-dev01.pcic.uvic.ca/twitcher/ows/proxy/quail/wps\n" |
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Probably a question for another PR, but should this be configured dynamically?
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This essentially is, when viewed through the notebook preview it is the output text from running:
url = get_target_url("quail")
print(f"Using quail on {url}")
| { | ||
| "cell_type": "code", | ||
| "execution_count": 1, | ||
| "execution_count": 12, |
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I'm just curious what the deal with all the changed execution_counts is?
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This is metadata referring to how many times a cell has executed. This could be relevant for non-linear executing notebooks, but it isn't important here. We could create a pre-commit action to clean up metadata and simplify future reviews. I'll open an issue for that improvement.
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