from sacred.observers import MongoObserver
from sacred import Experiment
import random
import time

ex = Experiment("sacred_scopes", interactive=True)

ex.observers.append(MongoObserver(url='mongodb://admin:IUM_2021@172.17.0.1:27017', db_name='sacred'))
#ex.observers.append(MongoObserver(url='mongodb://mongo_user:mongo_password@localhost:27017',
 #                                 db_name='sacred'))  # Tutaj podajemy dane uwierzytelniające i nazwę bazy skonfigurowane w pliku .env podczas uruchamiania bazy.
# W przypadku instancji na Jenkinsie url będzie wyglądał następująco: mongodb://mongo_user:mongo_password_IUM_2021@localhost:27017
@ex.config
def my_config():
    recipient = "Świecie"
    greeting = "Witaj"

@ex.capture
def prepare_message(recipient, greeting):
    return "{0} {1}!".format(greeting, recipient)

@ex.main
def my_main(recipient, greeting, _run):
    print(prepare_message()) ## Nie musimy przekazywać wartości  
    counter = 0
    while counter < 20:
        counter+=1
        value = counter
        ms_to_wait = random.randint(5, 5000)
        time.sleep(ms_to_wait/1000)
        noise = 1.0 + 0.1 * (random.randint(0, 10) - 5)
        # This will add an entry for training.loss metric in every second iteration.
        # The resulting sequence of steps for training.loss will be 0, 2, 4, ...
        if counter % 2 == 0:
           _run.log_scalar("training.loss", value * 1.5 * noise, counter)
        # Implicit step counter (0, 1, 2, 3, ...)
        # incremented with each call for training.accuracy:
        _run.log_scalar("training.accuracy", value * 2 * noise)

ex.run()