Code: Alles auswählen
# A program to batch-compute the number of prime numbers below each of the given numbers in the input set
# TODO: Extend get_primes() to utilize caching
# TODO: Modify code to use more appropriate data structures where possible
from functools import lru_cache, wraps
from timeit import repeat
from datetime import datetime, timedelta
# from functools import timed_lru_cache, lru_cache, wraps
# cache = TTLCache(maxsize=100, ttl=86400)
# @lru_cache(maxsize=2000)
def memoize(function):
memo = {}
@wraps(function)
def wrapper(*args):
try:
return memo[args]
except KeyError:
rv = function(*args)
memo[args] = rv
return rv
return wrapper
# @memoize
def is_prime(n):
sieved = []
factor = 2
while factor * factor <= n + 1:
if factor not in sieved:
for i in range(factor*factor, n + 1, factor):
sieved.append(i)
factor += 1
return n not in sieved
# @lru_cache(maxsize=8)
"""
def timed_lru_cache(seconds: int, maxsize: int = 128):
def wrapper_cache(func):
func = lru_cache(maxsize=maxsize)(func)
func.lifetime = timedelta(seconds=seconds)
func.expiration = datetime.utcnow() + func.lifetime
@wraps(func)
def wrapped_func(*args, **kwargs):
if datetime.utcnow() >= func.expiration:
func.cache_clear()
func.expiration = datetime.utcnow() + func.lifetime
return func(*args, **kwargs)
return wrapped_func
return wrapper_cache
"""
# @timed_lru_cache(10)
# @cached(cache)
# @timed_lru_cache(10)
# @timed_lru_cache(maxsize=16)
# @lru_cache(maxsize=2000)
@memoize
def get_primes(n):
return [p for p in range(1, n) if is_prime(p)]
if __name__ == 'builtins' or __name__ == '__main__':
input_data = [6843, 1028, 3324]
for n in input_data:
result = get_primes(n)
print(f'Found {len(result)} primes below {n}')
