#! /usr/bin/env python
# -*- coding: utf-8 -*-
# vim:fenc=utf-8
#
# Copyright © 2017 lafrite <lafrite@Poivre>
#
# Distributed under terms of the MIT license.


from random import choice


def build_variable_scope(rd_variables, rejected, min_max, variables_scope):
    """ Build variables scope from incomplete one

    :param rd_variables: list of random variables to generate
    :param rejected: Rejected values for the generator 
    :param min_max: (min, max) limits in between variables will be generated
    :param variables_scope: rejected and min_max define for individual variables
    :return: complete variable scope

    :example:
    >>> completed = build_variable_scope(["a", "b", "c", "d"], [0], (-10, 10),
    ...                      {"a": {"rejected": [0, 1]},
    ...                       "b": {"min_max": (-5, 0)},
    ...                       "c": {"rejected": [2], "min_max": (0, 5)}})
    >>> complete = {'a': {'rejected': [0, 1], 'min_max': (-10, 10)}, 
    ...             'b': {'rejected': [0], 'min_max': (-5, 0)},
    ...             'c': {'rejected': [2], 'min_max': (0, 5)},
    ...             'd': {'rejected': [0], 'min_max': (-10, 10)}}
    >>> completed == complete
    True
    """
    complete_scope = variables_scope.copy()
    for v in rd_variables:
        try:
            complete_scope[v]
        except KeyError:
            complete_scope[v] = {"rejected": rejected, "min_max": min_max}
        else:
            try:
                complete_scope[v]["rejected"]
            except KeyError:
                complete_scope[v]["rejected"] = rejected
            try:
                complete_scope[v]["min_max"]
            except KeyError:
                complete_scope[v]["min_max"] = min_max
    return complete_scope

    
def random_generator(
    rd_variables, conditions=[], rejected=[0], min_max=(-10, 10), variables_scope={}
):
    """ Generate random variables

    :param rd_variables: list of random variables to generate
    :param conditions: condition over variables
    :param rejected: Rejected values for the generator (default [0])
    :param min_max: (min, max) limits in between variables will be generated
    :param variables_scope: rejected and min_max define for individual variables
    :return: dictionnary of generated variables

    :example:
    >>> gene = random_generator(["a", "b"], 
    ...                  ["a > 0"],
    ...                  [0], (-10, 10),
    ...                  {"a": {"rejected": [0, 1]},
    ...                   "b": {"min_max": (-5, 0)}})
    >>> gene["a"] > 0
    True
    >>> gene["a"] != 0
    True
    >>> gene["b"] < 0
    True
    >>> gene = random_generator(["a", "b"], 
    ...                  ["a % b == 0"],
    ...                  [0, 1], (-10, 10))
    >>> gene["a"] not in [0, 1]
    True
    >>> gene["b"] in list(range(-10, 11))
    True
    >>> gene["a"] % gene["b"]
    0
    """
    complete_scope = build_variable_scope(
        rd_variables, rejected, min_max, variables_scope
    )
    choices_list = {
        v: list(
            set(
                range(
                    complete_scope[v]["min_max"][0], complete_scope[v]["min_max"][1] + 1
                )
            ).difference(complete_scope[v]["rejected"])
        )
        for v in rd_variables
    }

    # quantity_choices = reduce(lambda x,y : x*y,
    #                           [len(choices_list[v]) for v in choices_list])
    # TODO: améliorer la méthode de rejet avec un cache |dim. mai 12 17:04:11 CEST 2019

    generate_variable = {v: choice(choices_list[v]) for v in rd_variables}

    while not all([eval(c, __builtins__, generate_variable) for c in conditions]):
        generate_variable = {v: choice(choices_list[v]) for v in rd_variables}

    return generate_variable