"""Tests for ray.util.multiprocessing that can run on a shared Ray cluster fixture.

Tests that require a standalone Ray cluster (for example, testing ray.init or shutdown
behavior) should go in test_multiprocessing_standalone.py.
"""
import multiprocessing as mp
import os
import platform
import queue
import random
import sys
import tempfile
import time
from collections import defaultdict

import pytest

import ray
from ray._common.test_utils import SignalActor
from ray.util.multiprocessing import JoinableQueue, Pool, TimeoutError


@pytest.fixture(scope="module")
def ray_init_4_cpu_shared():
    yield ray.init(num_cpus=4)
    ray.shutdown()


@pytest.fixture
def pool_4_processes(ray_init_4_cpu_shared):
    pool = Pool(processes=4)
    yield pool
    pool.terminate()
    pool.join()


@pytest.fixture
def pool_4_processes_python_multiprocessing_lib():
    pool = mp.Pool(processes=4)
    yield pool
    pool.terminate()
    pool.join()


def test_initializer(ray_init_4_cpu_shared):
    def init(dirname):
        with open(os.path.join(dirname, str(os.getpid())), "w") as f:
            print("hello", file=f)

    with tempfile.TemporaryDirectory() as dirname:
        num_processes = 4
        pool = Pool(processes=num_processes, initializer=init, initargs=(dirname,))

        assert len(os.listdir(dirname)) == 4
        pool.terminate()
        pool.join()


def test_close(pool_4_processes):
    def f(signal):
        ray.get(signal.wait.remote())
        return "hello"

    signal = SignalActor.remote()
    result = pool_4_processes.map_async(f, [signal for _ in range(4)])
    assert not result.ready()
    pool_4_processes.close()
    assert not result.ready()

    # Signal the head of line tasks to finish.
    ray.get(signal.send.remote())
    pool_4_processes.join()

    # close() shouldn't interrupt pending tasks, so check that they succeeded.
    result.wait(timeout=10)
    assert result.ready()
    assert result.successful()
    assert result.get() == ["hello"] * 4


def test_terminate(pool_4_processes):
    def f(signal):
        return ray.get(signal.wait.remote())

    signal = SignalActor.remote()
    result = pool_4_processes.map_async(f, [signal for _ in range(4)])
    assert not result.ready()
    pool_4_processes.terminate()

    # terminate() should interrupt pending tasks, so check that join() returns
    # even though the tasks should be blocked forever.
    pool_4_processes.join()
    result.wait(timeout=10)
    assert result.ready()
    assert not result.successful()
    with pytest.raises(ray.exceptions.RayError):
        result.get()


def test_apply(pool_4_processes):
    def f(arg1, arg2, kwarg1=None, kwarg2=None):
        assert arg1 == 1
        assert arg2 == 2
        assert kwarg1 is None
        assert kwarg2 == 3
        return 1

    assert pool_4_processes.apply(f, (1, 2), {"kwarg2": 3}) == 1
    with pytest.raises(AssertionError):
        pool_4_processes.apply(
            f,
            (
                2,
                2,
            ),
            {"kwarg2": 3},
        )
    with pytest.raises(Exception):
        pool_4_processes.apply(f, (1,))
    with pytest.raises(Exception):
        pool_4_processes.apply(f, (1, 2), {"kwarg1": 3})


def test_apply_async(pool_4_processes):
    def f(arg1, arg2, kwarg1=None, kwarg2=None):
        assert arg1 == 1
        assert arg2 == 2
        assert kwarg1 is None
        assert kwarg2 == 3
        return 1

    assert pool_4_processes.apply_async(f, (1, 2), {"kwarg2": 3}).get() == 1
    with pytest.raises(AssertionError):
        pool_4_processes.apply_async(
            f,
            (
                2,
                2,
            ),
            {"kwarg2": 3},
        ).get()
    with pytest.raises(Exception):
        pool_4_processes.apply_async(f, (1,)).get()
    with pytest.raises(Exception):
        pool_4_processes.apply_async(f, (1, 2), {"kwarg1": 3}).get()

    # Won't return until the input ObjectRef is fulfilled.
    def ten_over(args):
        signal, val = args
        ray.get(signal.wait.remote())
        return 10 / val

    signal = SignalActor.remote()
    result = pool_4_processes.apply_async(ten_over, ([signal, 10],))
    result.wait(timeout=0.01)
    assert not result.ready()
    with pytest.raises(TimeoutError):
        result.get(timeout=0.01)

    # Fulfill the ObjectRef.
    ray.get(signal.send.remote())
    result.wait(timeout=10)
    assert result.ready()
    assert result.successful()
    assert result.get() == 1

    signal = SignalActor.remote()
    result = pool_4_processes.apply_async(ten_over, ([signal, 0],))
    with pytest.raises(ValueError, match="not ready"):
        result.successful()

    # Fulfill the ObjectRef with 0, causing the task to fail (divide by zero).
    ray.get(signal.send.remote())
    result.wait(timeout=10)
    assert result.ready()
    assert not result.successful()
    with pytest.raises(ZeroDivisionError):
        result.get()


def test_map(pool_4_processes):
    def f(index):
        return index, os.getpid()

    results = pool_4_processes.map(f, range(100))
    assert len(results) == 100

    pid_counts = defaultdict(int)
    for i, (index, pid) in enumerate(results):
        assert i == index
        pid_counts[pid] += 1

    # Check that the functions are spread somewhat evenly.
    for count in pid_counts.values():
        assert count > 20

    def bad_func(args):
        raise Exception("test_map failure")

    with pytest.raises(Exception, match="test_map failure"):
        pool_4_processes.map(bad_func, range(10))


def test_map_async(pool_4_processes):
    def f(args):
        index, signal = args
        ray.get(signal.wait.remote())
        return index, os.getpid()

    signal = SignalActor.remote()
    async_result = pool_4_processes.map_async(f, [(i, signal) for i in range(1000)])
    assert not async_result.ready()
    with pytest.raises(TimeoutError):
        async_result.get(timeout=0.01)
    async_result.wait(timeout=0.01)

    # Send the signal to finish the tasks.
    ray.get(signal.send.remote())
    async_result.wait(timeout=10)
    assert async_result.ready()
    assert async_result.successful()

    results = async_result.get()
    assert len(results) == 1000

    pid_counts = defaultdict(int)
    for i, (index, pid) in enumerate(results):
        assert i == index
        pid_counts[pid] += 1

    # Check that the functions are spread somewhat evenly.
    for count in pid_counts.values():
        assert count > 100

    def bad_func(index):
        if index == 50:
            raise Exception("test_map_async failure")

    async_result = pool_4_processes.map_async(bad_func, range(100))
    async_result.wait(10)
    assert async_result.ready()
    assert not async_result.successful()

    with pytest.raises(Exception, match="test_map_async failure"):
        async_result.get()


def test_starmap(pool_4_processes):
    def f(*args):
        return args

    args = [tuple(range(i)) for i in range(100)]
    assert pool_4_processes.starmap(f, args) == args
    assert pool_4_processes.starmap(lambda x, y: x + y, zip([1, 2], [3, 4])) == [4, 6]


def test_callbacks(pool_4_processes, pool_4_processes_python_multiprocessing_lib):
    Queue = JoinableQueue if platform.system() == "Windows" else queue.Queue
    callback_queue = Queue()

    def callback(result):
        callback_queue.put(result)

    def error_callback(error):
        callback_queue.put(error)

    # Will not error, check that callback is called.
    result = pool_4_processes.apply_async(
        callback_test_helper, ((0, [1]),), callback=callback
    )
    assert callback_queue.get() == 0
    result.get()

    # Will error, check that error_callback is called.
    result = pool_4_processes.apply_async(
        callback_test_helper, ((0, [0]),), error_callback=error_callback
    )
    assert isinstance(callback_queue.get(), Exception)
    with pytest.raises(Exception, match="intentional failure"):
        result.get()

    # Ensure Ray's map_async behavior matches Multiprocessing's map_async
    process_pools = [pool_4_processes, pool_4_processes_python_multiprocessing_lib]

    for process_pool in process_pools:
        # Test error callbacks for map_async.
        test_callback_types = ["regular callback", "error callback"]

        for callback_type in test_callback_types:
            # Reinitialize queue to track number of callback calls made by
            # the current process_pool and callback_type in map_async
            callback_queue = Queue()

            indices, error_indices = list(range(20)), []
            if callback_type == "error callback":
                error_indices = [2, 10, 15]
            result = process_pool.map_async(
                callback_test_helper,
                [(index, error_indices) for index in indices],
                callback=callback,
                error_callback=error_callback,
            )
            callback_results = None
            result.wait()

            callback_results = callback_queue.get()
            callback_queue.task_done()

            # Ensure that callback or error_callback was called only once
            assert callback_queue.qsize() == 0

            if callback_type == "regular callback":
                assert result.successful()
            else:
                assert not result.successful()

            if callback_type == "regular callback":
                # Check that regular callback returned a list of all indices
                for index in callback_results:
                    assert index in indices
                    indices.remove(index)
                assert len(indices) == 0
            else:
                # Check that error callback returned a single exception
                assert isinstance(callback_results, Exception)


def callback_test_helper(args):
    """
    This is a helper function for the test_callbacks test. It must be placed
    outside the test because Python's Multiprocessing library uses Pickle to
    serialize functions, but Pickle cannot serialize local functions.
    """
    time.sleep(0.1 * random.random())
    index = args[0]
    err_indices = args[1]
    if index in err_indices:
        raise Exception("intentional failure")
    return index


@pytest.mark.parametrize("use_iter", [True, False])
def test_imap(pool_4_processes, use_iter):
    def f(args):
        time.sleep(0.1 * random.random())
        index = args[0]
        err_indices = args[1]
        if index in err_indices:
            raise Exception("intentional failure")
        return index

    error_indices = [2, 10, 15]
    if use_iter:
        imap_iterable = iter([(index, error_indices) for index in range(20)])
    else:
        imap_iterable = [(index, error_indices) for index in range(20)]
    result_iter = pool_4_processes.imap(f, imap_iterable, chunksize=3)
    for i in range(20):
        result = result_iter.next()
        if i in error_indices:
            assert isinstance(result, Exception)
        else:
            assert result == i

    with pytest.raises(StopIteration):
        result_iter.next()


def test_imap_fail_on_non_iterable(pool_4_processes):
    def fn(_):
        pass

    non_iterable = 3

    with pytest.raises(TypeError, match="object is not iterable"):
        pool_4_processes.imap(fn, non_iterable)

    with pytest.raises(TypeError, match="object is not iterable"):
        pool_4_processes.imap_unordered(fn, non_iterable)


@pytest.mark.parametrize("use_iter", [True, False])
def test_imap_unordered(pool_4_processes, use_iter):
    signal = SignalActor.remote()

    error_indices = {2, 7}

    def f(index):
        if index == 0:
            ray.get(signal.wait.remote())

        if index in error_indices:
            raise Exception("intentional failure")

        return index

    if use_iter:
        imap_iterable = range(10)
    else:
        imap_iterable = list(range(10))

    in_order = []
    num_errors = 0
    result_iter = pool_4_processes.imap_unordered(f, imap_iterable, chunksize=1)
    for i in range(10):
        result = result_iter.next()
        if len(in_order) == 0:
            # After the first result is back, send the signal to unblock index == 0.
            # This guarantees that the results come in out of order.
            ray.get(signal.send.remote())

        if isinstance(result, Exception):
            in_order.append(True)
            num_errors += 1
        else:
            in_order.append(result == i)

    # Check that the results didn't come back all in order.
    # This is guaranteed not to happen because we blocked index == 0 until at least one
    # other result was available.
    assert not all(in_order)
    assert num_errors == len(error_indices)

    with pytest.raises(StopIteration):
        result_iter.next()


def test_imap_timeout(pool_4_processes):
    """Test the timeout parameter to imap."""
    signal = SignalActor.remote()

    def f(index):
        if index == 0:
            ray.get(signal.wait.remote())
        return index

    # index == 0 will block, so the first call to get a result should time out.
    result_iter = pool_4_processes.imap(f, range(10))
    with pytest.raises(TimeoutError):
        result_iter.next(timeout=0.5)

    # Unblock index == 0, then all results should come back in order.
    ray.get(signal.send.remote())
    for i in range(10):
        assert result_iter.next() == i

    with pytest.raises(StopIteration):
        result_iter.next()


def test_imap_unordered_timeout(pool_4_processes):
    """Test the timeout parameter to imap_unordered."""
    signal = SignalActor.remote()

    def f(index):
        if index == 0:
            ray.get(signal.wait.remote())
        return index

    # index == 0 will block, but imap_unordered will return results as they're ready,
    # so we will get some results before the timeout occurs. After unblocking
    # index == 0, the results should all come back correctly (in an arbitrary order).
    results = []
    got_timeout = False
    result_iter = pool_4_processes.imap_unordered(f, range(10), chunksize=1)
    while len(results) < 10:
        try:
            index = result_iter.next(timeout=0.5)
            if not got_timeout:
                # Prior to getting the timeout, none of the results should be
                # index == 0, which is blocked.
                assert index != 0

            results.append(index)
        except TimeoutError:
            # We should only get exactly one timeout and it should happen after getting
            # other un-blocked results first.
            assert not got_timeout
            assert len(results) > 0
            got_timeout = True
            ray.get(signal.send.remote())

    with pytest.raises(StopIteration):
        result_iter.next()

    # The results should not have come back in order because index == 0 was blocking.
    assert results != list(range(10)), results


if __name__ == "__main__":
    sys.exit(pytest.main(["-sv", __file__]))