#Python import
import time
from datetime import datetime

# Functions
# Python imports
import time
import string
import hashlib
#Package import
from pymemcache import serde
from pymemcache.client import base as base_memcache

# Constants:
zconsts_TIMES = 100
zconsts_FAKE_DELAY = 5

# Functions definition
def fetch_from_db(key):
    # In this function we will simulate a slow database query
    time.sleep(zconsts_FAKE_DELAY)
    # Return hashed key
    return str(hashlib.md5(key.encode("utf-8")))

def get_cache_client():
    return base_memcache.Client("10.82.1.3:11211", serde=serde.pickle_serde)

def get_cached_object(CacheClient, key):
    message = CacheClient.get(key, None)
    if not message:
        # we dont have it on cache, we will have to look for it to Database:
        message = fetch_from_db(key)
        # After fetching we store it on cache:
        CacheClient.set(key, message)
    # At this point we have the message
    return message

#Launch!
if __name__ == "__main__":
    key = "Testing"
    # Instance MemCache client for every cert_sender process
    CacheClient = get_cache_client() # This could be in a lot of places of a project
    CacheClient.delete(key) # To avoid already existing key
    # Run testing
    performance = {}
    for x in range(zconsts_TIMES):
        check_time = datetime.now()
        get_cached_object(CacheClient, key) # We fetch our item
        performance[x] = (datetime.now() - check_time).total_seconds()

    # Show some results
    print("Results:")
    print(f"First time took {performance[0]:.4f}s fetching from database")
    print("At this point we set the key on Cache to retrieve value from there\n")
    print(f"All the next {zconsts_TIMES-1} fetchs should be faster")
    for idx in range(1, zconsts_TIMES):
        print(f"{idx} time\t Took {performance[idx]:.4f}s fetching from Cache")