Preview for Mira context #114
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mattprintz
reviewed
Mar 21, 2024
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| with open(filename, "rb") as f: | ||
| data = f.read() | ||
| enc = base64.b64encode(bytes(data)) | ||
| return enc.decode("utf-8") |
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This will actually leave files in the "jupyter" user's home directory, since subkernels currently actually run as a normal kernel in the same environment. We probably don't want to create clutter.
We should probably delete these files after we read them, or write to a IOBuffer so the contents are all in memory.
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| __state = locals() | ||
| __models = {} | ||
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| for model in {{model_vars}}: | ||
| model: str | ||
| __models[model] = {"text/plain": repr(__state[model]), "image/png": __visualize_model(model, __state[model])} | ||
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| del __state |
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By using jinja templating, I think we can clean this up to something like the following.
(Note: I haven't really tested this, so don't take this as a solved solution.)
As you can see, instead of generating and reading from a locals() dict, we are just generating code that access the variables directly.
Suggested change
| __state = locals() | |
| __models = {} | |
| for model in {{model_vars}}: | |
| model: str | |
| __models[model] = {"text/plain": repr(__state[model]), "image/png": __visualize_model(model, __state[model])} | |
| del __state | |
| __models = { | |
| {% for model_var in model_vars %} | |
| "{{model_var}}": {"text/plain": repr({{model_var}}), "image/png": __visualize_model("{{model_var}}", {{model_var}})} | |
| {% endfor %} | |
| } |
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Adds preview support for Mira modelling context.