__all__ = ['python_to_notebook', 'Notebook'] import json import copy import warnings sample = """{ "metadata": { "name":"" }, "nbformat": 3, "nbformat_minor": 0, "worksheets": [ { "cells": [ { "cell_type": "code", "collapsed": false, "input": [ "%matplotlib inline" ], "language": "python", "metadata": {}, "outputs": [] } ], "metadata": {} } ] }""" def _remove_consecutive_duplicates(x): """Remove duplicates of elements appearing consecutively. Parameters ---------- x : list Input list. Returns ------- modified_x : list Output list, with no consecutive duplicates. Examples -------- >>> input = [1, 2, 3, 3, 4, 5, 6, 6] >>> output = remove_consecutive_duplicates(input) >>> output [1, 2, 3, 4, 5, 6] """ modified_x = [x[0]] + [x[i] for i in range(1, len(x)) if x[i] != x[i-1]] return modified_x class Notebook(): """ Notebook object for generating an IPython notebook from an example Python file. """ def __init__(self): # cell type code self.cell_code = { 'cell_type': 'code', 'collapsed': False, 'input': [ '# Code Goes Here' ], 'language': 'python', 'metadata': {}, 'outputs': [] } # cell type markdown self.cell_md = { 'cell_type': 'markdown', 'metadata': {}, 'source': [ 'Markdown Goes Here' ] } self.cell_type = {'input': self.cell_code, 'source': self.cell_md} self.valuetype_to_celltype = {'code': 'input', 'markdown': 'source'} def add_cell(self, value, cell_type='code'): """Add a notebook cell. Parameters ---------- value : str The actual content to be saved in the cell. cell_type : {'code', 'markdown'} The type of content. The default value will add a cell of type 'code'. """ if cell_type in ['markdown', 'code']: key = self.valuetype_to_celltype[cell_type] cells = self.template['worksheets'][0]['cells'] cells.append(copy.deepcopy(self.cell_type[key])) # assign value to the last cell cells[-1][key] = value else: warnings.warn('Unsupported cell type %s, data ignored' % cell_type) def json(self): """Dump the template JSON to string. Returns ------- str The template JSON converted to a string with a two char indent. """ return json.dumps(self.template, indent=2) def python_to_notebook(example_file, notebook_path): """Convert a Python file to an IPython notebook. Parameters ---------- example_file : str Path for source Python file. notebook_path : str Path for saving the notebook file (includes the filename). """ nb = Notebook() with open(example_file, 'r') as pythonfile: nb.template = json.loads(sample) nb.code = pythonfile.readlines() # Add an extra newline at the end, # this aids in extraction of text segments nb.code.append('\n') # Newline separated portions in example file, are sections. # Code and markdown written together in such a section are further # treated as different segments. Each cell has content from one # segment. docstring = False source = [] code = _remove_consecutive_duplicates(nb.code) for line in code: # A linebreak indicates a segment has ended. # If the text segment had only comments, ignore the blank source as # already added in cell type markdown if line == '\n': if source: # we've found text segments within the docstring if docstring: nb.add_cell(source, 'markdown') else: nb.add_cell(source, 'code') source = [] # if it's a comment elif line.strip().startswith('#'): line = line.lstrip(' #') nb.add_cell(line, 'markdown') elif line == '"""\n': if not docstring: docstring = True # Indicates, completion of docstring # add whatever in source to markdown (cell type markdown) elif docstring: docstring = False # Write leftover docstring if any left if source: nb.add_cell(source, 'markdown') source = [] else: # some text segment is continuing, so add to source source.append(line) with open(notebook_path, 'w') as output: output.write(nb.json())