def _create_hashable_nb(
self,
nb: nbf.NotebookNode,
compare_nb_meta=("kernelspec", ),
compare_cell_meta=None,
):
"""Create a notebook containing only content desired for hashing."""
nb = copy.deepcopy(nb)
nb.metadata = nbf.from_dict({
k: v
for k, v in nb.metadata.items()
if compare_nb_meta is None or (k in compare_nb_meta)
})
diff_cells = []
for cell in nb.cells:
if cell.cell_type != "code":
continue
diff_cell = nbf.from_dict({
"cell_type": cell.cell_type,
"source": cell.source,
"metadata": {
k: v
for k, v in cell.metadata.items()
if compare_cell_meta is None or (k in compare_cell_meta)
},
"execution_count": None,
"outputs": [],
})
diff_cells.append(diff_cell)
nb.cells = diff_cells
return nb
def merge_match_into_notebook(
self,
nb: nbf.NotebookNode,
nb_meta=("kernelspec", "language_info", "widgets"),
cell_meta=None,
) -> Tuple[int, nbf.NotebookNode]:
"""Match to an executed notebook and return a merged version
:param nb: The input notebook
:param nb_meta: metadata keys to merge from the cached notebook (all if None)
:param cell_meta: cell metadata keys to merge from cached notebook (all if None)
:raises KeyError: if no match is found
:return: pk, input notebook with cached code cells and metadata merged.
"""
pk = self.match_cache_notebook(nb).pk
cache_nb = self.get_cache_bundle(pk).nb
nb = copy.deepcopy(nb)
if nb_meta is None:
nb.metadata = cache_nb.metadata
else:
for key in nb_meta:
if key in cache_nb.metadata:
nb.metadata[key] = cache_nb.metadata[key]
for idx in range(len(nb.cells)):
if nb.cells[idx].cell_type == "code":
cache_cell = cache_nb.cells.pop(0)
if cell_meta is not None:
# update the input metadata with select cached notebook metadata
# then add the input metadata to the cached cell
nb.cells[idx].metadata.update(
{k: v for k, v in cache_cell.metadata.items() if k in cell_meta}
)
cache_cell.metadata = nb.cells[idx].metadata
nb.cells[idx] = cache_cell
return pk, nb
