from datetime import datetime, timedelta
from decimal import Decimal
from functools import partial

flatten = lambda l: [item for sublist in l for item in sublist]

def flatmap(f, items):
        return list(map(f, items))


def datetime_range(start, end, delta, dt_format='%Y-%m-%d %H:%M:%S'):
    reverse_head = end
    [start, end] = [datetime.strptime(x, dt_format) for x in [start, end]]

    def _datetime_range(start, end, delta):
        current = start
        while current < end:
            yield current
            current += delta

    reverse_tail = [dt.strftime(dt_format) for dt in _datetime_range(start, end, delta)]
    return reverse_tail + [reverse_head]

def last_index(l):
    return len(l)-1

def retrieve_state(l, offset):
    return l[last_index(l) + offset + 1]

def bound_norm_random(rng, low, high):
    # Add RNG Seed
    res = rng.normal((high+low)/2,(high-low)/6)
    if (res<low or res>high):
        res = bound_norm_random(rng, low, high)
    return Decimal(res)

def env_proc(trigger_step, update_f):
    def env_step_trigger(trigger_step, update_f, step):
        if step == trigger_step:
            return update_f
        else:
            return lambda x: x
    return partial(env_step_trigger, trigger_step, update_f)


# accept timedelta instead of timedelta params
def time_step(dt_str, dt_format='%Y-%m-%d %H:%M:%S', days=0, minutes=0, seconds=30):
    dt = datetime.strptime(dt_str, dt_format)
    t = dt + timedelta(days=days, minutes=minutes, seconds=seconds)
    return t.strftime(dt_format)

# accept timedelta instead of timedelta params
def ep_time_step(s, dt_str, fromat_str='%Y-%m-%d %H:%M:%S', days=0, minutes=0, seconds=1):
    if s['mech_step'] == 0:
        return time_step(dt_str, fromat_str, days, minutes, seconds)
    else:
        return dt_str