import multiprocessing
from operator import add
import pickle
import random

import numpy as np

import pytest

from dask import compute, delayed
from dask.context import set_options
from dask.multiprocessing import get, _dumps, _loads, remote_exception
from dask.utils_test import inc


def test_pickle_globals():
    """ For the function f(x) defined below, the only globals added in pickling
    should be 'np' and '__builtins__'"""
    def f(x):
        return np.sin(x) + np.cos(x)

    assert set(['np', '__builtins__']) == set(
        _loads(_dumps(f)).__globals__.keys())


def bad():
    raise ValueError("12345")


def test_errors_propagate():
    dsk = {'x': (bad,)}

    try:
        get(dsk, 'x')
    except Exception as e:
        assert isinstance(e, ValueError)
        assert "12345" in str(e)


def test_remote_exception():
    e = TypeError("hello")
    a = remote_exception(e, 'traceback-body')
    b = remote_exception(e, 'traceback-body')

    assert type(a) == type(b)
    assert isinstance(a, TypeError)
    assert 'hello' in str(a)
    assert 'Traceback' in str(a)
    assert 'traceback-body' in str(a)


def make_bad_result():
    return lambda x: x + 1


def test_unpicklable_results_generate_errors():

    dsk = {'x': (make_bad_result,)}

    try:
        get(dsk, 'x')
    except Exception as e:
        # can't use type because pickle / cPickle distinction
        assert type(e).__name__ in ('PicklingError', 'AttributeError')


class NotUnpickleable(object):
    def __getstate__(self):
        return ()

    def __setstate__(self, state):
        raise ValueError("Can't unpickle me")


def test_unpicklable_args_generate_errors():
    a = NotUnpickleable()

    def foo(a):
        return 1

    dsk = {'x': (foo, a)}

    try:
        get(dsk, 'x')
    except Exception as e:
        assert isinstance(e, ValueError)

    dsk = {'x': (foo, 'a'),
           'a': a}

    try:
        get(dsk, 'x')
    except Exception as e:
        assert isinstance(e, ValueError)


def test_reuse_pool():
    pool = multiprocessing.Pool()
    with set_options(pool=pool):
        assert get({'x': (inc, 1)}, 'x') == 2
        assert get({'x': (inc, 1)}, 'x') == 2


def test_dumps_loads():
    with set_options(func_dumps=pickle.dumps, func_loads=pickle.loads):
        assert get({'x': 1, 'y': (add, 'x', 2)}, 'y') == 3


def test_fuse_doesnt_clobber_intermediates():
    d = {'x': 1, 'y': (inc, 'x'), 'z': (add, 10, 'y')}
    assert get(d, ['y', 'z']) == (2, 12)


def test_optimize_graph_false():
    from dask.callbacks import Callback
    d = {'x': 1, 'y': (inc, 'x'), 'z': (add, 10, 'y')}
    keys = []
    with Callback(pretask=lambda key, *args: keys.append(key)):
        get(d, 'z', optimize_graph=False)
    assert len(keys) == 2


@pytest.mark.parametrize('random', [np.random, random])
def test_random_seeds(random):
    def f():
        return tuple(random.randint(0, 10000) for i in range(5))

    N = 10
    with set_options(scheduler='processes'):
        results, = compute([delayed(f, pure=False)() for i in range(N)])

    assert len(set(results)) == N
