Cell-level caching
还没有人认领这个 Issue。
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- 难度
- 5/5
- 预计耗时
- 一周以上
- 新手友好度
- 25/100
调研方向
首先审查 ipykernel 的 notebook 执行路径和所引用的 akernel 方法，包括其使用 Python 的 ast 模块比较缓存的单元格输入和输出。将该设计与 knitr 的缓存模型进行比较，并明确缓存应如何服务于 Quarto 和 JupyterBook。完成此任务需要就 ipykernel 的单元格级缓存设计达成一致，包括何时可以跳过执行，以及如何确定有效性。
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描述
Often we want to visualize the content of the notebook for example as an HTML and also recompute it to check its validity. This ensures that the notebook is runnable and also shows the desired output. However, running a notebook is very time-consuming. It would be great if we had some cell-level cache that would speed up repeated executing of the notebook.
@davidbrochart in his project akernel (asynchronous kernel) solved a similar issue. He approached it by parsing inputs and outputs of the cached cell using ast module. He could then skip the execution of the particular time-consuming cell, if the outputs were cached and the inputs hasn't changed from the previous execution. I hope I didn't misinterpret it. @davidbrochart please comment on any of my mistake.
An inspiration could also be taken from knitr from R, who has this implementation available.
Could we get something like this for ipykernel? Many popular projects would benefit from this improvement, such as Quarto or JupyterBook.
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