def network_parameters():
conn, cursor = data.connect_db(db=mysql)
required_params = ['datetime']
model_params = request.args.to_dict()
params_check = api_lib.params_checker(
required_params=required_params,
model_params=model_params,
input_type='url').params_exist_populated()
if not params_check.check:
return api_lib.request_sender(
data=None, status_code=400,
message=params_check.message).get_response()
# Query database for given data
network = data.get_network(cursor=cursor, time=model_params['datetime'])
response = api_lib.request_sender(
data=network, status_code=200,
message=params_check.message).get_response()
conn.close()
return response
def model_json():
# TODO update this with the framework used for GET above or just delete so we're not doubling up on everything
required_params = ['id']
if request.method == 'POST':
model_params = request.get_json()
# list of dictionaries
if isinstance(model_params, list):
for item_params in model_params:
params_check = api_lib.params_checker(
required_params=required_params,
model_params=item_params,
input_type='json').params_exist_populated()
if not params_check.check:
return api_lib.request_sender(
data=None,
status_code=400,
message=params_check.message).get_response()
# dictionary
elif isinstance(model_params, dict):
params_check = api_lib.params_checker(
required_params=required_params,
model_params=item_params,
input_type='json').params_exist_populated()
if not params_check.check:
return api_lib.request_sender(
data=None, status_code=400,
message=params_check.message).get_response()
return api_lib.request_sender(
data=data, status_code=200,
message=params_check.message).get_response()
else:
raise api_lib.request_sender(data=None,
status_code=400,
message='Something went wrong')
def classify_parameters():
conn, cursor = data.connect_db(db=mysql)
required_params = ['datetime', 'origin', 'dest']
model_params = request.args.to_dict()
params_check = api_lib.params_checker(
required_params=required_params,
model_params=model_params,
input_type='url').params_exist_populated()
if not params_check.check:
return api_lib.request_sender(
data=None, status_code=400,
message=params_check.message).get_response()
# Query database for given data then classify
train_X, train_Y = data.get_classify_train_data(
cursor=cursor, start_date=model_params['datetime'], time_interval=20)
predict_X = data.get_classify_predict_data(
cursor=cursor,
time=model_params['datetime'],
origin=model_params['origin'],
destination=model_params['dest'])
# Check to make sure we have data
if predict_X is not None:
prediction = model.classify_fit_predict(X_train=train_X,
y_train=train_Y,
X_predict=predict_X)
else:
# We can't make a prediction without all the data
prediction = None
response = api_lib.request_sender(
data=prediction, status_code=200,
message=params_check.message).get_response()
conn.close()
return response