Source code for ipypublish.preprocessors.split_outputs

import copy
import logging

import traitlets as traits
from nbconvert.preprocessors import Preprocessor
from nbformat.notebooknode import NotebookNode

[docs]def merge(a, b, path=None, overwrite=True): """merges b into a Examples -------- >>> from pprint import pprint >>> pprint(merge({'a':{'b':1},'c':3},{'a':{'b':2}})) {'a': {'b': 2}, 'c': 3} """ if path is None: path = [] for key in b: if key in a: if isinstance(a[key], dict) and isinstance(b[key], dict): merge(a[key], b[key], path + [str(key)], overwrite) elif a[key] == b[key]: pass # same leaf value elif overwrite: a[key] = b[key] # overwrite leaf value else: raise Exception('Conflict at %s' % '.'.join(path + [str(key)])) else: a[key] = b[key] return a
[docs]class SplitOutputs(Preprocessor): """ a preprocessor to split outputs into separate cells, merging the cell and output metadata, with output metadata taking priority """ split = traits.Bool(True, help="whether to split outputs").tag(config=True)
[docs] def preprocess(self, nb, resources): if not self.split: return nb, resources'splitting outputs into separate cells') final_cells = [] for cell in nb.cells: if not cell.cell_type == "code": final_cells.append(cell) continue outputs = cell.pop("outputs") cell.outputs = [] final_cells.append(cell) for output in outputs: meta = copy.deepcopy(cell.metadata) # don't need the code to output meta.get('ipub', NotebookNode({})).code = False # don't create a new slide for each output, # unless specified in output level metadata if 'slide' in meta.get('ipub', NotebookNode({})): meta.ipub.slide = True if meta.ipub.slide == 'new' else meta.ipub.slide meta = merge(meta, output.get('metadata', {})) new = NotebookNode({ "cell_type": "code", "source": '', "execution_count": None, "metadata": meta, "outputs": [output]}) final_cells.append(new) nb.cells = final_cells return nb, resources