from collections import namedtuple
from collections import deque
from collections import Counter
import numpy as np
import random
import itertools

Record = namedtuple('Record', 'easy medium nightmare')
len_window = 1000

def data_stream():
    random_generator = random.Random(42)
    easy = 0
    for _ in range(10000000):
        easy += random_generator.randint(0, 2)
        #medium = random_generator.randint(0, 256 - 1) # counter
        #nightmare = random_generator.randint(0, 1000000000 - 1) # deque

        yield Record(
            easy=easy,
            #medium=medium,
            #nightmare=nightmare
        )

def easy_stream():
    for record in data_stream():
        yield record.easy

def medium_stream():
    for record in data_stream():
        yield record.medium

def nightmare_stream():
    for record in data_stream():
        yield record.nightmare


def get_tuple_windows_mean_and_disp(stream):
    window = deque()
    mean = 0
    sum_sqrs = 0
    for val in itertools.islice(stream(),0,len_window):
        window.append(val)
        mean += val
        sum_sqrs += val*val
    mean /= len_window
    sum_sqrs /= len_window
    yield (mean, sum_sqrs - mean*mean)
    for next_value in stream():
        mean += (next_value - window[0]) / len_window
        sum_sqrs += (next_value*next_value - window[0]*window[0]) / len_window
        window.popleft()
        window.append(next_value)
        yield (mean, sum_sqrs - mean*mean)

def get_tuple_windows_statistics(stream):
    if stream.__name__ == 'easy_stream':
        window = deque(itertools.islice(stream(),0,len_window))
        yield ( window[0], (window[len_window//2] + window[len_window//2 - 1])/2, window[-1])
        for next_value in stream():
            window.popleft()
            window.append(next_value)
            yield (window[0], (window[len_window//2] + window[len_window//2 - 1])/2, window[-1]
 #   if stream.__name__ == 'medium_stream':
 #       window =