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From html 2 original ipynb file
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# requires python3 | |
from bs4 import BeautifulSoup | |
import json | |
import urllib.request | |
def html2ipynb(sourceHtml, targetIpynb): | |
dictionary = {'nbformat': 4, 'nbformat_minor': 1, 'cells': [], 'metadata': {}} | |
print("html2ipynb") | |
print("Source (html) : '%s'" % sourceHtml) | |
print("Target (ipynb) : '%s'" % targetIpynb) | |
response = open(sourceHtml, encoding='utf-8') | |
text = response.read() | |
soup = BeautifulSoup(text, 'lxml') | |
for d in soup.findAll("div"): | |
if 'class' in d.attrs.keys(): | |
for clas in d.attrs["class"]: | |
if clas in ["text_cell_render", "input_area"]: | |
# code cell | |
if clas == "input_area": | |
cell = {} | |
cell['metadata'] = {} | |
cell['outputs'] = [] | |
# this removes all empty lines | |
# new_source = "\n".join([s for s in d.get_text().splitlines() if s.strip()]) | |
new_source = d.get_text().splitlines() | |
# remove first line if empty | |
if not new_source[0].strip(): | |
new_source = new_source[1:] | |
# remove last lines if empty | |
if not new_source[-1].strip(): | |
new_source = new_source[0:-1] | |
cell['source'] = "\n".join(new_source) | |
cell['execution_count'] = None | |
cell['cell_type'] = 'code' | |
dictionary['cells'].append(cell) | |
else: | |
cell = {} | |
cell['metadata'] = {} | |
cell['source'] = [d.decode_contents()] | |
cell['cell_type'] = 'markdown' | |
dictionary['cells'].append(cell) | |
open(targetIpynb, 'w').write(json.dumps(dictionary)) | |
response.close() | |
print("'%s' successfully written" % targetIpynb) | |
# html2ipynb for all *.html in the source dir | |
import os | |
sourceDir = os.path.join("__Referencias", "02 python", "Teoría") | |
targetDir = os.path.join("ML con Python") | |
for f in os.listdir(sourceDir): | |
if f.endswith(".html"): | |
fname = f[0:-5] | |
sourceHtml = os.path.join(sourceDir, f) | |
targetIpynb = os.path.join(targetDir, fname + ".ipynb") | |
html2ipynb(sourceHtml, targetIpynb) |
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