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Once we switch over to myst-nb / jupyter-book, the glue functionality will be idea for cross-lecture numerical comparisons involving solution methods for dynamic programming.
For example, in our discussion of the optimal growth model and elsewhere, we compare different algorithms in different lectures. To compare execution speed without repeating code, we can glue/paste results from other lectures.
everybody should think about the name of the tool ("glue") and whether it is the right word to use both in the python library, as well as in the markdown...would love to hear your thoughts over in executablebooks/MyST-NB#110
mmcky
transferred this issue from QuantEcon/lecture-python
Feb 9, 2021
Once we switch over to myst-nb / jupyter-book, the glue functionality will be idea for cross-lecture numerical comparisons involving solution methods for dynamic programming.
https://myst-nb.readthedocs.io/en/latest/use/glue.html
For example, in our discussion of the optimal growth model and elsewhere, we compare different algorithms in different lectures. To compare execution speed without repeating code, we can glue/paste results from other lectures.
CC @najuzilu @Harveyt47 (and @choldgraf since the application might be interesting).
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