class Submitter:
def __init__(self, compete, work_dir, default_submission_id=0):
self.kaggle_api = KaggleApi()
self.kaggle_api.authenticate()
self.work_dir = work_dir
self.compete = compete
self.default_submission_id = default_submission_id
def submit(self,
predicted: pd.DataFrame,
file_name='submission.csv',
message=None,
save_model=True,
model=None,
model_name=None,
submit=True,
submission_id=None,
submission_name=None,
open_in_browser=False):
# Folder and files
if submission_id is None:
submission_id = self.default_submission_id
self.default_submission_id += 1
submission_folder_name = ' '.join(
[str(submission_id), ' -- ', submission_name])
new_folder_path = self.work_dir + f'/{submission_folder_name}'
if not os.path.exists(new_folder_path):
os.mkdir(new_folder_path)
# Save model
if model_name is None:
model_name = str(model)
if save_model:
with open(f'{new_folder_path}/{model_name}.pickle',
'wb') as pickle_file:
pickle.dump(model, pickle_file)
# Submission
predicted.to_csv(f'{new_folder_path}/{file_name}', index=False)
if message is None:
if model is None:
message = file_name
else:
message = str(model)
with open(new_folder_path + '/message.txt', 'w') as message_file:
message_file.write(' '.join(
[str(submission_id), ' -- ', submission_name, '\n', message]))
message_file.close()
# Upload
if submit:
print('Uploading submission...')
command = f'kaggle competitions submit -c {self.compete} -f "{new_folder_path}/{file_name}" -m "{message}"'
print(command)
output = os.system(command)
print('Output: ', output)
# Open in browser
if open_in_browser:
webbrowser.open(
f'https://www.kaggle.com/c/{self.compete}/submissions', new=2)
def check_submission(self):
last_submission = self.kaggle_api.competitions_submissions_list(
self.compete)[0]
print('Description: ', last_submission['description'])
print('Date: ', last_submission['date'])
print('Status: ', last_submission['status'])
print('Score: ', last_submission['publicScore'])
class Submission:
def __init__(self,
compete,
name,
work_dir,
description=None,
create_readme=False):
self.id = str(time.time())
self.compete = compete
self.name = f'{name} - {self.id}'
self.description = description
if work_dir[-1] == '/':
self.new_folder_path = work_dir + self.name
else:
self.new_folder_path = work_dir + '/' + self.name
self.kaggle_api = KaggleApi()
self.kaggle_api.authenticate()
if not os.path.exists(self.new_folder_path):
os.mkdir(self.new_folder_path)
self.readme = Readme(self.name,
self.description) if create_readme else None
def save_model(self, model, file_name=None):
if file_name is None:
file_name = str(model).replace('\\', '')
with open(f'{self.new_folder_path}/{file_name}.pickle',
'wb') as pickle_file:
pickle.dump(model, pickle_file)
def save_keras_model(self,
model,
file_name=None,
save_format='pickle',
save_summary_to_readme=True,
*args,
**kwargs):
from tensorflow.keras import Model
if not isinstance(model, Model):
raise Exception(f'Model should be instance of keras.Model')
if file_name is None:
file_name = str(model).replace('\\', '')
if save_summary_to_readme:
summary = io.StringIO()
model.summary(print_fn=lambda s: print(s, file=summary))
if self.readme is None:
raise Exception("'create_readme' should be True")
self.readme.model_summary = summary.getvalue()
if save_format == 'pickle':
with open(f'{self.new_folder_path}/{file_name}.pickle',
'wb') as pickle_file:
pickle.dump(model, pickle_file)
elif save_format == 'config':
with open(f'{self.new_folder_path}/{file_name}.json',
'w') as config_file:
json.dump(model.get_config(), config_file)
elif save_format == 'h5':
model.save(f'{self.new_folder_path}/{file_name}', *args, **kwargs)
else:
raise Exception('Undefined save_format')
return self
def save_predictions(self,
predictions,
columns,
index,
file_name='predictions.csv'):
pd.DataFrame(dict(zip(columns, [index, predictions]))) \
.to_csv(f'{self.new_folder_path}/{file_name}', index=False)
return self
def open_in_browser(self):
webbrowser.open(f'https://www.kaggle.com/c/{self.compete}/submissions',
new=2)
return self
def submit(self, predictions_file_name='predictions.csv'):
print('Uploading submission...')
command = f'kaggle competitions submit -c {self.compete} -f "{self.new_folder_path}/{predictions_file_name}" -m "{self.description}"'
print(command)
output = os.system(command)
print()
print('Output: ', output)
return self
def check_results(self, timeout=5):
time.sleep(timeout)
last_submission = self.kaggle_api.competitions_submissions_list(
self.compete)[0]
if self.readme is not None:
self.readme.score = last_submission['publicScore']
self.readme.date = last_submission['date']
self.readme.status = last_submission['status']
print('Description: ', last_submission['description'])
print('Date: ', last_submission['date'])
print('Status: ', last_submission['status'])
print('Score: ', last_submission['publicScore'])
return self
def save_readme(self):
readme_file = open(f'{self.new_folder_path}/README.md', 'w')
readme_file.write(self.readme.markdown())
return self
