#!/usr/bin/env python

import logging
import numbers

l = logging.getLogger("claripy.frontends.frontend")


class Frontend:
    def __init__(self):
        pass

    def __getstate__(self):
        return (True) # need to return something so that pickle calls setstate
    def __setstate__(self, s): #pylint:disable=unused-argument
        return

    def branch(self):
        c = self.blank_copy()
        self._copy(c)
        return c

    def blank_copy(self):
        c = self.__class__.__new__(self.__class__)
        self._blank_copy(c)
        return c

    def _blank_copy(self, c): #pylint:disable=no-self-use,unused-argument
        return

    def _copy(self, c): #pylint:disable=no-self-use,unused-argument
        return

    #
    # Stuff that should be implemented by subclasses
    #

    def eval_to_ast(self, e, n, extra_constraints=(), exact=None):
        """
        Evaluates expression `e`, returning a list of `n` concrete ASTs.

        :param e:                       the expression
        :param n:                       the number of ASTs to return
        :param extra_constraints:       extra constraints to consider when performing the evaluation
        :param exact:                   whether or not to perform an exact evaluation. Ignored by
                                        non-approximating backends.

        :return:                        list of concrete ASTs
        """
        return [ ast.bv.BVV(v, e.size()) for v in self.eval(e, n, extra_constraints=extra_constraints, exact=exact) ]


    def finalize(self):
        raise NotImplementedError("finalize() is not implemented")

    def merge(self, others, merge_conditions, common_ancestor=None):
        raise NotImplementedError("merge() is not implemented")

    def combine(self, others):
        raise NotImplementedError("combine() is not implemented")

    def split(self):
        raise NotImplementedError("split() is not implemented")

    def add(self, constraints):
        """
        Adds constraint(s) to constraints list.

        :param constraints:             constraint(s) to add

        :return:
        """
        raise NotImplementedError()

    def simplify(self):
        """
        Simplifies the stored constraints conjunction.
        """
        raise NotImplementedError()

    def check_satisfiability(self, extra_constraints=(), exact=None):
        """
        Checks the satisfiability of stored constraints conjunction.

        :param extra_constraints:       extra constraints to consider when checking satisfiability
        :param exact:                   whether or not to perform exact checking. Ignored by
                                        non-approximating backends.

        :return:                        'SAT' if the conjunction is satisfiable otherwise 'UNSAT'
        """
        raise NotImplementedError

    def satisfiable(self, extra_constraints=(), exact=None):
        """
        Checks if stored constraints conjunction is satisfiable.

        :param extra_constraints:       extra constraints to consider when checking satisfiability
        :param exact:                   whether or not to perform exact checking. Ignored by
                                        non-approximating backends.

        :return:                        True if the conjunction is satisfiable otherwise False
        """
        raise NotImplementedError()

    def eval(self, e, n, extra_constraints=(), exact=None):
        """
        Evaluates expression `e`, returning a tuple of `n` solutions.

        :param e:                       the expression
        :param n:                       the number of solutions to return
        :param extra_constraints:       extra constraints to consider when performing the evaluation
        :param exact:                   whether or not to perform an exact evaluation. Ignored by
                                        non-approximating backends.

        :return:                        tuple of python primitives representing results
        """
        raise NotImplementedError()

    def batch_eval(self, exprs, n, extra_constraints=(), exact=None):
        """
        Evaluates `exprs`, returning a list of tuples (one tuple of `n` solutions for expression).

        :param exprs:                   expressions
        :param n:                       the number of solutions to return
        :param extra_constraints:       extra constraints to consider when performing the evaluation
        :param exact:                   whether or not to perform an exact evaluation. Ignored by
                                        non-approximating backends.

        :return:                        list of tuples of python primitives representing results
        """
        raise NotImplementedError()

    def max(self, e, extra_constraints=(), signed=False, exact=None):
        """
        Evaluates `e`, returning its max possible value.

        :param e:                       the expression
        :param extra_constraints:       extra constraints to consider when performing the evaluation
        :param signed:                  whether the value should be treated as a signed integer
        :param exact:                   whether or not to perform an exact evaluation. Ignored by
                                        non-approximating backends.

        :return:                        max possible value
        """
        raise NotImplementedError()

    def min(self, e, extra_constraints=(), signed=False, exact=None):
        """
        Evaluates `e`, returning its min possible value.

        :param e:                       the expression
        :param extra_constraints:       extra constraints to consider when performing the evaluation
        :param signed:                  whether the value should be treated as a signed integer
        :param exact:                   whether or not to perform an exact evaluation. Ignored by
                                        non-approximating backends.

        :return:                        min possible value
        """
        raise NotImplementedError()

    def solution(self, e, v, extra_constraints=(), exact=None):
        """
        Checks if `v` is a possible solution to `e`.

        :param e:                       the expression
        :param v:                       the value
        :param extra_constraints:       extra constraints to consider when performing the evaluation
        :param exact:                   whether or not to perform an exact evaluation. Ignored by
                                        non-approximating backends.

        :return:                        True if it is a possible solution otherwise False
        """
        raise NotImplementedError()

    def is_true(self, e, extra_constraints=(), exact=None):
        """
        Checks if `e` can only (and TRIVIALLY) evaluate to True. If this function returns True,
        then the expression cannot ever be False, regardless of constraints or anything else.
        If the expression returns False, then the expression might STILL not ever be False; it's just
        that we can't trivially prove it. In other words, a return value of False gives you no
        information whatsoever.


        :param e:                       the expression
        :param extra_constraints:       extra constraints to consider when performing the evaluation
        :param exact:                   whether or not to perform an exact evaluation. Ignored by
                                        non-approximating backends.

        :return:                        True if it can only evaluate to True otherwise False
        """
        raise NotImplementedError()

    def is_false(self, e, extra_constraints=(), exact=None):
        """
        Checks if `e` can only (and TRIVIALLY) evaluate to False. If this function returns True,
        then the expression cannot ever be True, regardless of constraints or anything else.
        If the expression returns False, then the expression might STILL not ever be True; it's just
        that we can't trivially prove it. In other words, a return value of False gives you no
        information whatsoever.

        :param e:                       the expression
        :param extra_constraints:       extra constraints to consider when performing the evaluation
        :param exact:                   whether or not to perform an exact evaluation. Ignored by
                                        non-approximating backends.

        :return:                        True if it can only evaluate to False otherwise False
        """
        raise NotImplementedError()

    def downsize(self): #pylint:disable=no-self-use
        pass

    #
    # Some utility functions
    #

    def _concrete_value(self, e): #pylint:disable=no-self-use
        if isinstance(e, numbers.Number):
            return e
        else:
            return None
    _concrete_constraint = _concrete_value

    def _constraint_filter(self, c): #pylint:disable=no-self-use
        return c

    @staticmethod
    def _split_constraints(constraints, concrete=True):
        """
        Returns independent constraints, split from this Frontend's `constraints`.
        """

        splitted = [ ]
        for i in constraints:
            splitted.extend(i.split(['And']))

        l.debug("... splitted of size %d", len(splitted))

        concrete_constraints = [ ]
        variable_connections = { }
        constraint_connections = { }
        for n,s in enumerate(splitted):
            l.debug("... processing constraint with %d variables", len(s.variables))

            connected_variables = set(s.variables)
            connected_constraints = { n }

            if len(connected_variables) == 0:
                concrete_constraints.append(s)

            for v in s.variables:
                if v in variable_connections:
                    connected_variables |= variable_connections[v]
                if v in constraint_connections:
                    connected_constraints |= constraint_connections[v]

            for v in connected_variables:
                variable_connections[v] = connected_variables
                constraint_connections[v] = connected_constraints

        unique_constraint_sets = set()
        for v in variable_connections:
            unique_constraint_sets.add((frozenset(variable_connections[v]), frozenset(constraint_connections[v])))

        results = [ ]
        for v,c_indexes in unique_constraint_sets:
            results.append((set(v), [ splitted[c] for c in c_indexes ]))

        if concrete and len(concrete_constraints) > 0:
            results.append(({ 'CONCRETE' }, concrete_constraints))

        return results

from . import ast
