def update_exercise_master_metadata_formwise(separates, bundles, new_deadlines, new_drive):
for exercise in itertools.chain(*bundles.values(), separates):
filepath = os.path.join(exercise.dirpath, f'{exercise.key}.ipynb')
cells, metadata = ipynb_util.load_cells(filepath)
deadlines_cur = ipynb_metadata.master_metadata_deadlines(metadata)
deadlines = new_deadlines.get(exercise.key, deadlines_cur)
if deadlines != deadlines_cur:
logging.info(f'[INFO] Renew deadline of {exercise.key}')
drive_cur = ipynb_metadata.master_metadata_drive(metadata)
drive = new_drive.get(exercise.key, drive_cur)
if drive != drive_cur:
logging.info(f'[INFO] Renew Google Drive ID/URL of {exercise.key}')
metadata = ipynb_metadata.master_metadata(exercise.key, True, exercise.version, exercise.title, deadlines, drive)
ipynb_util.save_as_notebook(filepath, cells, metadata)
for dirpath, exercises in bundles.items():
dirname = os.path.basename(dirpath)
for exercise in exercises:
filepath = os.path.join(exercise.dirpath, f'{exercise.key}.ipynb')
cells, metadata = ipynb_util.load_cells(filepath)
deadlines_cur = ipynb_metadata.master_metadata_deadlines(metadata)
deadlines = new_deadlines.get(f'{dirname}/', deadlines_cur)
if deadlines != deadlines_cur:
logging.info(f'[INFO] Renew deadline of bundle {dirname}/{exercise.key}')
drive_cur = ipynb_metadata.master_metadata_drive(metadata)
drive = new_drive.get(f'{dirname}/', drive_cur)
if drive != drive_cur:
logging.info(f'[INFO] Renew Google Drive ID/URL of bundle {dirname}/{exercise.key}')
metadata = ipynb_metadata.master_metadata(exercise.key, True, exercise.version, exercise.title, deadlines, drive)
ipynb_util.save_as_notebook(filepath, cells, metadata)
def cleanup_exercise_master(exercise, new_version=None):
filepath = os.path.join(exercise.dirpath, f'{exercise.key}.ipynb')
cells, metadata = ipynb_util.load_cells(filepath, True)
cells_new = [x.to_ipynb() for x in ipynb_util.normalized_cells(cells)]
if new_version is None:
new_version = exercise.version
elif new_version == hashlib.sha1:
exercise_definition = {
'description': [x.to_ipynb() for x in exercise.description],
'answer_cell': exercise.answer_cell().to_ipynb(),
'instructive_test': [x.to_ipynb() for x in exercise.instructive_test],
}
m = hashlib.sha1()
m.update(json.dumps(exercise_definition).encode())
new_version = m.hexdigest()
else:
assert isinstance(new_version, str)
if new_version != exercise.version:
logging.info(f'[INFO] Renew version of {exercise.key}')
exercise.version = new_version
deadlines = ipynb_metadata.master_metadata_deadlines(metadata)
drive = ipynb_metadata.master_metadata_drive(metadata)
metadata_new = ipynb_metadata.master_metadata(exercise.key, True, exercise.version, exercise.title, deadlines, drive)
ipynb_util.save_as_notebook(filepath, cells_new, metadata_new)
def add_question_exists_into_answer_cell(filepath):
CONTENT_TYPE_REGEX = r'\*\*\*CONTENT_TYPE:\s*(.+?)\*\*\*'
cells, metadata = ipynb_util.load_cells(filepath)
for i, c in enumerate(cells):
if c['cell_type'] == 'markdown':
matches = list(
re.finditer(CONTENT_TYPE_REGEX, ''.join(c['source'])))
if not matches:
continue
key = matches[0][1]
if key == 'ANSWER_CELL_CONTENT' and all(
'QUESTION_EXISTS = False' not in x
for x in cells[i + 1]['source']):
print('Append QUESTION_EXISTS: ', filepath)
cells[i + 1]['source'][0:0] = [
'QUESTION_EXISTS = False # 質問がある場合は True にしてコメントに質問を記述\n',
'\n'
]
if key == 'SYSTEM_TESTCODE' and all(
'question_exists' not in x
for x in cells[i + 1]['source']):
print('Append question_exists: ', filepath)
cells[i + 1]['source'][-1] = cells[i + 1]['source'][-1] + '\n'
cells[i + 1]['source'].extend(
PRECHECK_QUESTION_EXISTS_TEMPLATE.splitlines(True))
ipynb_util.save_as_notebook(filepath, cells, metadata)
def create_bundled_intro(dirpath):
dirname = os.path.basename(dirpath)
try:
raw_cells, _ = ipynb_util.load_cells(os.path.join(dirpath, INTRODUCTION_FILE))
return list(ipynb_util.normalized_cells(raw_cells))
except FileNotFoundError:
return [ipynb_util.markdown_cell(f'# {os.path.basename(dirpath)}')]
def convert_master(filepath):
CONTENT_TYPE_REGEX = r'\*\*\*CONTENT_TYPE:\s*(.+?)\*\*\*'
cells, metadata = ipynb_util.load_cells(filepath)
for i, c in enumerate(cells):
if c['cell_type'] == 'markdown':
matches = list(
re.finditer(CONTENT_TYPE_REGEX, ''.join(c['source'])))
if not matches:
continue
key = matches[0][1]
if key in REWRITE_RULES:
c['source'] = REWRITE_RULES[key].splitlines(True)
if key == 'PLAYGROUND':
cells[i + 1]['source'] = ['judge_util.unittest_main()']
new_cells = []
deleting = False
for c in cells:
if c['cell_type'] == 'markdown':
matches = list(
re.finditer(CONTENT_TYPE_REGEX, ''.join(c['source'])))
if matches:
deleting = False
if matches[0][1] in DELETED_FIELDS:
deleting = True
if not deleting:
new_cells.append(c)
ipynb_util.save_as_notebook(filepath, new_cells, metadata)
def generate_template(exercise):
FieldKey = build_autograde.FieldKey
CONTENT_TYPE_REGEX = r'\*\*\*CONTENT_TYPE:\s*(.+?)\*\*\*'
cells, metadata = ipynb_util.load_cells(
os.path.join(exercise.dirpath, exercise.key + '.ipynb'))
gen_cells = []
for i, c in enumerate(cells):
if c['cell_type'] == 'markdown':
matches = list(
re.finditer(CONTENT_TYPE_REGEX, ''.join(c['source'])))
gen_cells.append(c)
if not matches:
continue
key = getattr(FieldKey, matches[0][1])
if key == FieldKey.SYSTEM_TESTCODE:
gen_cells.append(generate_precheck_test_code(exercise))
given_test = generate_given_test_code(exercise)
gen_cells.extend(given_test)
gen_cells.append(generate_hidden_test_code(exercise))
if key == FieldKey.PLAYGROUND:
gen_cells.append(
ipynb_util.code_cell(
'judge_util.unittest_main()').to_ipynb())
else:
gen_cells.append(c)
filepath = os.path.join(exercise.dirpath, f'template_{exercise.key}.ipynb')
ipynb_util.save_as_notebook(filepath, gen_cells, metadata)
def load_exercise(dirpath, exercise_key):
raw_cells, metadata = ipynb_util.load_cells(os.path.join(dirpath, exercise_key + '.ipynb'))
version = ipynb_metadata.master_metadata_version(metadata)
fields = dict(split_cells_into_fields(FieldKey, raw_cells))
heading_regex = r'#+\s+(.*)'
description_first_line = fields[FieldKey.DESCRIPTION][0].source.strip().splitlines()[0]
title = re.fullmatch(heading_regex, description_first_line).groups()[0]
test_modules = interpret_testcode_cells(dirpath, fields.pop(FieldKey.SYSTEM_TESTCODE))
exercise_kwargs = {
'key': exercise_key, 'dirpath': dirpath, 'version': version, 'title': title, 'test_modules': test_modules,
**{f.name.lower(): cs[0] if f == FieldKey.ANSWER_CELL_CONTENT else cs for f, cs in fields.items()},
}
return Exercise(**exercise_kwargs)
def release_ipynb(master_path,
new_version,
new_deadlines,
new_drive,
form_dir=None):
key, ext = os.path.splitext(os.path.basename(master_path))
cells, metadata = ipynb_util.load_cells(master_path, True)
title = extract_first_heading(cells)
version = ipynb_metadata.master_metadata_version(metadata)
if new_version is None:
new_version = version
elif new_version == hashlib.sha1:
m = hashlib.sha1()
m.update(json.dumps(cells).encode())
new_version = m.hexdigest()
else:
assert isinstance(new_version, str)
if new_version != version:
logging.info(f'[INFO] Renew version of `{master_path}`')
version = new_version
deadlines_cur = ipynb_metadata.master_metadata_deadlines(metadata)
deadlines = new_deadlines.get(key, deadlines_cur)
if deadlines != deadlines_cur:
logging.info(f'[INFO] Renew deadline of `{master_path}`')
drive_cur = ipynb_metadata.master_metadata_drive(metadata)
drive = new_drive.get(key)
if drive != drive_cur:
logging.info(f'[INFO] Renew Google Drive ID/URL of `{master_path}`')
master_metadata = ipynb_metadata.master_metadata(key, False, version,
title, deadlines, drive)
ipynb_util.save_as_notebook(master_path, cells, master_metadata)
logging.info(f'[INFO] Released master `{master_path}`')
if form_dir:
form_path = os.path.join(form_dir, f'{key}.ipynb')
else:
form_path = os.path.join(os.path.dirname(master_path),
f'form_{key}.ipynb')
submission_metadata = ipynb_metadata.submission_metadata({key: version},
False)
ipynb_util.save_as_notebook(form_path, cells, submission_metadata)
logging.info(f'[INFO] Released form `{form_path}`')
def create_exercise_configuration(exercise: Exercise):
tests_dir = os.path.join(CONF_DIR, exercise.key)
os.makedirs(tests_dir, exist_ok=True)
cells = [x.to_ipynb() for x in itertools.chain(exercise.description, [exercise.answer_cell_content])]
_, metadata = ipynb_util.load_cells(os.path.join(exercise.dirpath, exercise.key + '.ipynb'), True)
ipynb_metadata.extend_master_metadata_for_trial(metadata, exercise.answer_cell_content.source)
ipynb_util.save_as_notebook(os.path.join(CONF_DIR, exercise.key + '.ipynb'), cells, metadata)
setting = judge_setting.generate_judge_setting(exercise.key, exercise.version, [stage for stage, _ in exercise.test_modules])
with open(os.path.join(tests_dir, 'setting.json'), 'w', encoding='utf-8') as f:
json.dump(setting, f, indent=1, ensure_ascii=False)
for stage, content in exercise.test_modules:
with open(os.path.join(tests_dir, f'{stage.name}.py'), 'w', encoding='utf-8', newline='\n') as f:
print(content, 'judge_util.unittest_main()', sep='\n', file=f)
for path in itertools.chain(*(stage.required_files for stage, _ in exercise.test_modules)):
dest = os.path.join(tests_dir, path)
os.makedirs(os.path.dirname(dest), exist_ok=True)
shutil.copyfile(os.path.join(exercise.dirpath, path), dest)