#!/usr/bin/env python
# -*- coding: utf-8 -*-

from __future__ import (division, print_function, absolute_import,
                        unicode_literals)

__all__ = ["MPIPool"]

# If mpi4py is installed, import it.
try:
    from mpi4py import MPI
except ImportError:
    MPI = None


class _close_pool_message(object):
    def __repr__(self):
        return "<Close pool message>"


class _function_wrapper(object):
    def __init__(self, function):
        self.function = function


def _error_function(task):
    raise RuntimeError("Pool was sent tasks before being told what "
                       "function to apply.")


class MPIPool(object):
    """
    A pool that distributes tasks over a set of MPI processes. MPI is an
    API for distributed memory parallelism.  This pool will let you run
    emcee without shared memory, letting you use much larger machines
    with emcee.

    The pool only support the :func:`map` method at the moment because
    this is the only functionality that emcee needs. That being said,
    this pool is fairly general and it could be used for other purposes.

    Contributed by `Joe Zuntz <https://github.com/joezuntz>`_.

    :param comm: (optional)
        The ``mpi4py`` communicator.

    :param debug: (optional)
        If ``True``, print out a lot of status updates at each step.

    :param loadbalance: (optional)
        if ``True`` and ntask > Ncpus, tries to loadbalance by sending
        out one task to each cpu first and then sending out the rest
        as the cpus get done.
    """
    def __init__(self, comm=None, debug=False, loadbalance=False):
        if MPI is None:
            raise ImportError("Please install mpi4py")

        self.comm = MPI.COMM_WORLD if comm is None else comm
        self.rank = self.comm.Get_rank()
        self.size = self.comm.Get_size() - 1
        self.debug = debug
        self.function = _error_function
        self.loadbalance = loadbalance
        if self.size == 0:
            raise ValueError("Tried to create an MPI pool, but there "
                             "was only one MPI process available. "
                             "Need at least two.")

    def is_master(self):
        """
        Is the current process the master?

        """
        return self.rank == 0

    def wait(self):
        """
        If this isn't the master process, wait for instructions.

        """
        if self.is_master():
            raise RuntimeError("Master node told to await jobs.")

        status = MPI.Status()

        while True:
            # Event loop.
            # Sit here and await instructions.
            if self.debug:
                print("Worker {0} waiting for task.".format(self.rank))

            # Blocking receive to wait for instructions.
            task = self.comm.recv(source=0, tag=MPI.ANY_TAG, status=status)
            if self.debug:
                print("Worker {0} got task {1} with tag {2}."
                      .format(self.rank, task, status.tag))

            # Check if message is special sentinel signaling end.
            # If so, stop.
            if isinstance(task, _close_pool_message):
                if self.debug:
                    print("Worker {0} told to quit.".format(self.rank))
                break

            # Check if message is special type containing new function
            # to be applied
            if isinstance(task, _function_wrapper):
                self.function = task.function
                if self.debug:
                    print("Worker {0} replaced its task function: {1}."
                          .format(self.rank, self.function))
                continue

            # If not a special message, just run the known function on
            # the input and return it asynchronously.
            result = self.function(task)
            if self.debug:
                print("Worker {0} sending answer {1} with tag {2}."
                      .format(self.rank, result, status.tag))
            self.comm.isend(result, dest=0, tag=status.tag)

    def map(self, function, tasks):
        """
        Like the built-in :func:`map` function, apply a function to all
        of the values in a list and return the list of results.

        :param function:
            The function to apply to the list.

        :param tasks:
            The list of elements.

        """
        ntask = len(tasks)

        # If not the master just wait for instructions.
        if not self.is_master():
            self.wait()
            return

        if function is not self.function:
            if self.debug:
                print("Master replacing pool function with {0}."
                      .format(function))

            self.function = function
            F = _function_wrapper(function)

            # Tell all the workers what function to use.
            requests = []
            for i in range(self.size):
                r = self.comm.isend(F, dest=i + 1)
                requests.append(r)

            # Wait until all of the workers have responded. See:
            #       https://gist.github.com/4176241
            MPI.Request.waitall(requests)

        if (not self.loadbalance) or (ntask <= self.size):
            # Do not perform load-balancing - the default load-balancing
            # scheme emcee uses.

            # Send all the tasks off and wait for them to be received.
            # Again, see the bug in the above gist.
            requests = []
            for i, task in enumerate(tasks):
                worker = i % self.size + 1
                if self.debug:
                    print("Sent task {0} to worker {1} with tag {2}."
                          .format(task, worker, i))
                r = self.comm.isend(task, dest=worker, tag=i)
                requests.append(r)

            MPI.Request.waitall(requests)

            # Now wait for the answers.
            results = []
            for i in range(ntask):
                worker = i % self.size + 1
                if self.debug:
                    print("Master waiting for worker {0} with tag {1}"
                          .format(worker, i))
                result = self.comm.recv(source=worker, tag=i)
                results.append(result)

            return results

        else:
            # Perform load-balancing. The order of the results are likely to
            # be different from the previous case.
            for i, task in enumerate(tasks[0:self.size]):
                worker = i+1
                if self.debug:
                    print("Sent task {0} to worker {1} with tag {2}."
                          .format(task, worker, i))
                # Send out the tasks asynchronously.
                self.comm.isend(task, dest=worker, tag=i)

            ntasks_dispatched = self.size
            results = [None]*ntask
            for itask in range(ntask):
                status = MPI.Status()
                # Receive input from workers.
                result = self.comm.recv(source=MPI.ANY_SOURCE,
                                        tag=MPI.ANY_TAG, status=status)
                worker = status.source
                i = status.tag
                results[i] = result
                if self.debug:
                    print("Master received from worker {0} with tag {1}"
                          .format(worker, i))

                # Now send the next task to this idle worker (if there are any
                # left).
                if ntasks_dispatched < ntask:
                    task = tasks[ntasks_dispatched]
                    i = ntasks_dispatched
                    if self.debug:
                        print("Sent task {0} to worker {1} with tag {2}."
                              .format(task, worker, i))
                    # Send out the tasks asynchronously.
                    self.comm.isend(task, dest=worker, tag=i)
                    ntasks_dispatched += 1

            return results

    def bcast(self, *args, **kwargs):
        """
        Equivalent to mpi4py :func:`bcast` collective operation.
        """
        return self.comm.bcast(*args, **kwargs)

    def close(self):
        """
        Just send a message off to all the pool members which contains
        the special :class:`_close_pool_message` sentinel.

        """
        if self.is_master():
            for i in range(self.size):
                self.comm.isend(_close_pool_message(), dest=i + 1)

    def __enter__(self):
        return self

    def __exit__(self, *args):
        self.close()
