<reponame>potassco/clorm
'''A plugin replacement for the ``clingo`` modules that wraps the key clingo
objects to integrate Clorm ``Predicate`` and ``FactBase`` interfaces. See the
`Clingo API <https://potassco.org/clingo/python-api/current/clingo.html#Model>`_
for more details.

'''

# TODO: For clorm v2.0 the raise_on_empty parameter in Model.facts() should be
#       moved to the second parameter position.

import io
import sys
import functools
import itertools
from collections.abc import Iterable, Iterator, Generator
from abc import ABCMeta
from .orm import *
from .util.wrapper import WrapperMetaClass, init_wrapper, make_class_wrapper

# I want to replace the original clingo - re-exporting everything in clingo
# except replacing the class overides with my version: _class_overides = [
# 'Control', 'Model', 'SolveHandle' ]. The following seems to work but I'm not
# sure if this is bad.

#------------------------------------------------------------------------------
# Reference to the original clingo objects so that when we replace them our
# references point to the originals.
#------------------------------------------------------------------------------
import clingo as oclingo
OModel=oclingo.Model
OSolveHandle=oclingo.SolveHandle
OControl=oclingo.Control

if oclingo.__version__ >= "5.5.0":
    from clingo.ast import parse_string
else:
    from clingo import parse_program

from clingo import *
__all__ = list([ k for k in oclingo.__dict__.keys() if k[0] != '_'])
__version__ = oclingo.__version__

# ------------------------------------------------------------------------------
# Helper function to smartly build a unifier if only a list of predicates have
# been provided.
# ------------------------------------------------------------------------------

def _build_unifier(unifier):
    if unifier is None: return None
    if isinstance(unifier, SymbolPredicateUnifier): return unifier
    return SymbolPredicateUnifier(predicates=unifier)


# ------------------------------------------------------------------------------
# Helper function to test that an attribute exists and corresponds to a function.
# ------------------------------------------------------------------------------

def _check_is_func(obj,name):
    if not callable(obj.__getattribute__(name)):
        raise AttributeError(("Wrapped object of type '{}' does not have "
                                  "a function '{}()'").format(type(obj),name))


# ------------------------------------------------------------------------------
# Wrap clingo.Model and override some functions
# ------------------------------------------------------------------------------

#class Model(OModel, metaclass=WrapperMetaClass):
class ModelOverride(object):
    '''Provides access to a model during a solve call.

    Objects mustn't be created manually. Instead they are returned by
    ``clorm.clingo.Control.solve`` callbacks.

    Behaves like ``clingo.Model`` but offers better integration with clorm facts
    and fact bases.

    '''

    def __init__(self, model,unifier=None):
        self._unifier = _build_unifier(unifier)
        _check_is_func(model,"symbols")
        init_wrapper(self,wrapped_=model)

    #------------------------------------------------------------------------------
    # Return the underlying model object
    #------------------------------------------------------------------------------
    @property
    def model_(self):
        '''Returns the underlying clingo.Model object.'''
        return self._wrapped

    #------------------------------------------------------------------------------
    # A new function to return a list of facts - similar to symbols
    #------------------------------------------------------------------------------

    def facts(self, *args, **kwargs):
        '''Returns a FactBase containing the facts in the model that unify with the
        SymbolPredicateUnifier.

        This function provides a wrapper around the ``clingo.Model.symbols``
        functions, but instead of returning a list of symbols it returns a
        FactBase containing the facts represented as ``clorm.Predicate``
        sub-class instances.

        Args:
           unifier(list | SymbolPredicateUnifier): used to unify and instantiate
              FactBase (Default: passed via the constructor if specified in the
              `clorm.clingo.Control` object)
           atoms: select all atoms in the model (Default: False)
           terms: select all terms displayed with #show statements (Default: False)
           shown: select all atoms and terms (Default: False)
           raise_on_empty: raise a ValueError if the resulting FactBase is empty
                           (Default: False)

        '''
        nargs = list(args)
        nkwargs = dict(kwargs)
        if len(nargs) >= 1 and "unifier" in nkwargs:
            raise TypeError("facts() got multiple values for argument 'unifier'")
        if len(nargs) >= 5 and "raise_on_empty" in nkwargs:
            raise TypeError("facts() got multiple values for argument 'raise_on_empty'")

        raise_on_empty = nkwargs.pop("raise_on_empty",False)
        if len(nargs) >= 5: raise_on_empty = nargs.pop(4)
        unifier = nkwargs.pop("unifier",None)
        if len(nargs) >= 1: unifier = nargs.pop(0)

        if unifier is not None: unifier=_build_unifier(unifier)
        else: unifier=self._unifier
        if unifier is None:
            msg = "Missing a predicate unifier specification in function call " + \
                "(no default was given at model instantiation)"
            raise ValueError(msg)

        return unifier.unify(
            symbols=self._wrapped.symbols(*nargs,**nkwargs),
            raise_on_empty=raise_on_empty,
            delayed_init=True)

    #------------------------------------------------------------------------------
    # Overide contains
    #------------------------------------------------------------------------------

    def contains(self, fact):
        '''Return whether the fact or symbol is contained in the model. Extends
        ``clingo.Model.contains`` to allow for clorm facts as well as a clingo
        symbols.

        '''
        if isinstance(fact, Predicate):
            return self._wrapped.contains(fact.raw)
        return self._wrapped.contains(fact)


Model = make_class_wrapper(OModel, ModelOverride)

# ------------------------------------------------------------------------------
# Wrap clingo.SolveHandle and override some functions
# ------------------------------------------------------------------------------

class SolveHandleGenerator(Generator):
    def __init__(self, gen, unifier):
        self._gen = gen
        self._unifier = unifier

    def __iter__(self):
        return self
    def __next__(self):
        model = next(self._gen)
        if self._unifier:
            return Model(model,unifier=self._unifier)
        else:
            return Model(model)

    def throw(self,typ,val=None,tb=None):
        self._gen.throw(typ,val,tb)
    def send(self,value):
        self._gen.send(value)
    def close(self):
        self._gen.close()
    def __del__(self):
        if oclingo.__version__ >= "5.5.0":
            self._gen.__del__()


class SolveHandleOverride(object):
#class SolveHandle(OSolveHandle, metaclass=WrapperMetaClass):
    '''Handle for solve calls.

    Objects mustn't be created manually. Instead they are returned by
    ``clorm.clingo.Control.solve``.

    Behaves like ``clingo.SolveHandle`` but iterates over ``clorm.clingo.Model``
    objects.

    '''


    def __init__(self, handle,unifier=None):
        init_wrapper(self,wrapped_=handle)
        self._unifier = _build_unifier(unifier)

    #------------------------------------------------------------------------------
    # Return the underlying solvehandle object
    #------------------------------------------------------------------------------
    @property
    def solvehandle_(self):
        '''Access the underlying clingo.SolveHandle object.'''
        return self._wrapped

    #------------------------------------------------------------------------------
    # Overrides
    #------------------------------------------------------------------------------

    def __iter__(self):
        return SolveHandleGenerator(iter(self._wrapped), self._unifier)

    def __enter__(self):
        self._wrapped.__enter__()
        return self

    def __exit__(self, exception_type, exception_value, traceback):
        self._wrapped.__exit__(exception_type,exception_value,traceback)
        return None


SolveHandle = make_class_wrapper(OSolveHandle, SolveHandleOverride)


# ------------------------------------------------------------------------------
# Wrap clingo.Control and override some functions
# ------------------------------------------------------------------------------

# ------------------------------------------------------------------------------
# Helper functions to expand the assumptions list as part of a solve() call. The
# assumptions list is a list of argument-boolean pairs where the argument can be
# be a clingo symbol, or clorm predicate instance, or a collection of clingo
# symbols or clorm predicates. This needs to be expanded into a list of
# symbol-bool pairs.
# ------------------------------------------------------------------------------
def _expand_assumptions(assumptions):
    pos_assump = set()
    neg_assump = set()

    def _add_fact(fact,bval):
        nonlocal pos_assump, neg_assump
        if isinstance(fact, Predicate): raw = fact.raw
        else: raw = fact
        if bval: pos_assump.add(raw)
        else: neg_assump.add(raw)

    try:
        for (arg,bval) in assumptions:
            if isinstance(arg, Predicate):
                _add_fact(arg,bval)
            elif isinstance(arg, Iterable):
                for f in arg: _add_fact(f,bval)
            else:
                _add_fact(arg,bval)
    except (TypeError, ValueError) as e:
        raise TypeError(("Invalid solve assumptions. Expecting list of arg-bool "
                         "pairs (arg is a raw-symbol/predicate or a collection "
                         "of raw-symbols/predicates). Got: {}").format(assumptions))

    # Now returned a list of raw assumptions combining pos and neg
    pos = [ (raw,True) for raw in pos_assump ]
    neg = [ (raw,False) for raw in neg_assump ]
    return list(itertools.chain(pos,neg))

# ------------------------------------------------------------------------------
# Control class
# ------------------------------------------------------------------------------



class ControlOverride(object):
#class Control(OControl, metaclass=WrapperMetaClass):
    '''Control object for the grounding/solving process.

    Behaves like ``clingo.Control`` but with modifications to deal with Clorm
    facts and fact bases.

    Adds an additional parameter ``unifier`` to specify how any generated clingo
    models will be unified with the clorm Predicate definitions. The unifier can
    be specified as a list of predicates or as a SymbolPredicateUnifier object.

    An existing ``clingo.Control`` object can be passed using the ``control_``
    parameter.

    '''

    def __init__(self, *args, **kwargs):
        self._unifier = None
        if "unifier" in kwargs: self._unifier = _build_unifier(kwargs["unifier"])

        # Do we need to build a clingo.Control object or use an existing one. If
        # using existing one make sure the wrapped object has at least the
        # ground and solve functions.
        if len(args) == 0 and "control_" in kwargs:
            wrapped_=kwargs["control_"]
            _check_is_func(wrapped_,"solve")
            _check_is_func(wrapped_,"ground")
            init_wrapper(self,wrapped_=wrapped_)
        else:
            kwargs2 = dict(kwargs)
            if "unifier" in kwargs2: del kwargs2["unifier"]
            init_wrapper(self,*args,**kwargs2)

    #------------------------------------------------------------------------------
    # Return the underlying control object
    #------------------------------------------------------------------------------
    @property
    def control_(self):
        '''Returns the underlying clingo.Control object.'''
        return self._wrapped

    #------------------------------------------------------------------------------
    # Make the unifier a property with a getter and setter
    #------------------------------------------------------------------------------
    @property
    def unifier(self):
        """Get/set the unifier.

        Unifier can be specified as a SymbolPredicateUnifier or a collection of
        Predicates. Always returns a SymbolPredicateUnifier (or None).

        """
        return self._unifier

    @unifier.setter
    def unifier(self,unifier):
        self._unifier = _build_unifier(unifier)

    #------------------------------------------------------------------------------
    # A new function to add facts from a factbase or a list of facts
    #------------------------------------------------------------------------------
    def add_facts(self, facts):
        '''Add facts to the control object. Note: facts must be added before grounding.

           This function can take an arbitrary collection containing a mixture
           of ``clorm.Predicate`` and ``clingo.Symbol`` objects. A
           ``clorm.FactBase`` is also a valid collection but it can only contain
           ``clorm.Predicate`` instances.

        Args:
          facts: a collection of ``clorm.Predicate`` or ``clingo.Symbol`` objects

        '''
        control_add_facts(self._wrapped, facts)

    #------------------------------------------------------------------------------
    # Overide assign_external to deal with Predicate object and a Clingo Symbol
    #------------------------------------------------------------------------------
    def assign_external(self, external, truth):
        '''Assign a truth value to an external fact (or collection of facts)

        A fact can be a raw clingo.Symbol object, a clorm.Predicate instance, or
        a program literal (an int). If the external is a collection then the
        truth value is assigned to all elements in the collection.

        This function extends ``clingo.Control.release_external``.

        '''
        def _assign_fact(fact):
            if isinstance(fact, Predicate):
                self._wrapped.assign_external(fact.raw, truth)
            else:
                self._wrapped.assign_external(fact, truth)

        if isinstance(external, Iterable):
            for f in external: _assign_fact(f)
        else:
            _assign_fact(external)

    #------------------------------------------------------------------------------
    # Overide release_external to deal with Predicate object and a Clingo Symbol
    #------------------------------------------------------------------------------
    def release_external(self, external):
        '''Release an external fact (or collection of facts)

        A fact can be a raw clingo.Symbol object, a clorm.Predicate instance, or
        a program literal (an int). If the external is a collection then the
        truth value is assigned to all elements in the collection.

        This function extends ``clingo.Control.release_external``.

        '''
        def _release_fact(fact):
            if isinstance(fact, Predicate):
                self._wrapped.release_external(fact.raw)
            else:
                self._wrapped.release_external(fact)

        if isinstance(external, Iterable):
            for f in external: _release_fact(f)
        else:
            _release_fact(external)

    #---------------------------------------------------------------------------
    # Overide solve and if necessary replace on_model with a wrapper that
    # returns a clorm.Model object. Also because of the issue with using the
    # keyword "async" as a parameter in Python 3.7 (which forced clingo 5.3.1+
    # to switch to using "async_") we have to use a complicated way to work out
    # function parameters. At some point will drop support for older clingo and
    # can simplify this function.
    # ---------------------------------------------------------------------------
    def solve(self, *args, **kwargs):
        '''Run the clingo solver.

        This function extends ``clingo.Control.solve()`` in two ways:

        1) The ``assumptions`` argument is generalised so that in the list of
        argument-boolean pairs the argument can be be a clingo symbol, or clorm
        predicate instance, or a collection of clingo symbols or clorm
        predicates.

        2) It produces either a ``clorm.clingo.SolveHandle`` wrapper object or a
        ``clorm.clingo.Model`` wrapper objects as appropriate (depending on the
        ``yield_``, ``async_``, and ``on_model`` parameters).

        '''

        # Build the list of valid arguments; using the correct "async" or
        # "async_" parameter based on the clingo version.  Note: "async" is a
        # keyword for Python 3.7+.
        async_keyword="async"
        if oclingo.__version__ > '5.3.1': async_keyword="async_"

        posnargs = ["assumptions","on_model","on_statistics",
                    "on_finish","yield_",async_keyword]
        validargs = set(posnargs)

        # translate all positional arguments into keyword arguments.
        if len(args) > len(posnargs):
            raise TypeError(("solve() takes {} positional arguments but {}"
                             "were given").format(len(posnargs),len(args)))
        nkwargs = {}
        for idx,arg in enumerate(args): nkwargs[posnargs[idx]] = arg

        for k,v in kwargs.items():
            if k not in validargs:
                raise TypeError(("solve() got an unexpected keyword "
                                 "argument '{}'").format(k))
            if k in nkwargs:
                raise TypeError(("solve() got multiple values for "
                                 "argument '{}'").format(k))
            nkwargs[k] = v

        # generate a new assumptions list if necesary
        if "assumptions" in nkwargs and nkwargs["assumptions"] is not None:
            nkwargs["assumptions"] = _expand_assumptions(nkwargs["assumptions"])

        # generate a new on_model function if necessary
        if "on_model" in nkwargs and nkwargs["on_model"] is not None:
            on_model=nkwargs["on_model"]
            @functools.wraps(on_model)
            def on_model_wrapper(model):
                if self._unifier: return on_model(Model(model, self._unifier))
                else: return on_model(Model(model))
            nkwargs["on_model"] =  on_model_wrapper

        # Call the wrapped solve function and handle the return value
        # appropriately
        result = self._wrapped.solve(**nkwargs)
        if ("yield_" in nkwargs and nkwargs["yield_"])  or \
           (async_keyword in nkwargs and nkwargs[async_keyword]):
            if self._unifier: return SolveHandle(result,unifier=self._unifier)
            else: return SolveHandle(result)
        else:
            return result


    def __getattr__(self,attr):
        return getattr(self._wrapped,attr)


Control = make_class_wrapper(OControl, ControlOverride)

#------------------------------------------------------------------------------
# This is probably bad practice... Modify the original clingo docstrings so that
# when I generate the autodoc with clingo being mocked it installs a reference
# to the original clingo docs.
#
# UPDATE: I'm confused what the autodoc mocking is doing (or not doing). I'm
# sure I had it working but now seems to be failing. Adding more hacks :(
# ------------------------------------------------------------------------------

Control.__doc__ += OControl.__doc__
Control.assign_external.__doc__ += OControl.assign_external.__doc__
Control.release_external.__doc__ += OControl.release_external.__doc__
Control.solve.__doc__ += OControl.solve.__doc__
Model.__doc__ += OModel.__doc__
Model.contains.__doc__ += OModel.contains.__doc__
SolveHandle.__doc__ += OSolveHandle.__doc__

#------------------------------------------------------------------------------
# main
#------------------------------------------------------------------------------
if __name__ == "__main__":
    raise RuntimeError('Cannot run modules')

'''A plugin replacement for the ``clingo`` modules that wraps the key clingo
objects to integrate Clorm ``Predicate`` and ``FactBase`` interfaces. See the
`Clingo API <https://potassco.org/clingo/python-api/current/clingo.html#Model>`_
for more details.

'''

# TODO: For clorm v2.0 the raise_on_empty parameter in Model.facts() should be
#       moved to the second parameter position.

import io
import sys
import functools
import itertools
from collections.abc import Iterable, Iterator, Generator
from abc import ABCMeta
from .orm import *
from .util.wrapper import WrapperMetaClass, init_wrapper, make_class_wrapper

# I want to replace the original clingo - re-exporting everything in clingo
# except replacing the class overides with my version: _class_overides = [
# 'Control', 'Model', 'SolveHandle' ]. The following seems to work but I'm not
# sure if this is bad.

#------------------------------------------------------------------------------
# Reference to the original clingo objects so that when we replace them our
# references point to the originals.
#------------------------------------------------------------------------------
import clingo as oclingo
OModel=oclingo.Model
OSolveHandle=oclingo.SolveHandle
OControl=oclingo.Control

if oclingo.__version__ >= "5.5.0":
    from clingo.ast import parse_string
else:
    from clingo import parse_program

from clingo import *
__all__ = list([ k for k in oclingo.__dict__.keys() if k[0] != '_'])
__version__ = oclingo.__version__

# ------------------------------------------------------------------------------
# Helper function to smartly build a unifier if only a list of predicates have
# been provided.
# ------------------------------------------------------------------------------

def _build_unifier(unifier):
    if unifier is None: return None
    if isinstance(unifier, SymbolPredicateUnifier): return unifier
    return SymbolPredicateUnifier(predicates=unifier)


# ------------------------------------------------------------------------------
# Helper function to test that an attribute exists and corresponds to a function.
# ------------------------------------------------------------------------------

def _check_is_func(obj,name):
    if not callable(obj.__getattribute__(name)):
        raise AttributeError(("Wrapped object of type '{}' does not have "
                                  "a function '{}()'").format(type(obj),name))


# ------------------------------------------------------------------------------
# Wrap clingo.Model and override some functions
# ------------------------------------------------------------------------------

#class Model(OModel, metaclass=WrapperMetaClass):
class ModelOverride(object):
    '''Provides access to a model during a solve call.

    Objects mustn't be created manually. Instead they are returned by
    ``clorm.clingo.Control.solve`` callbacks.

    Behaves like ``clingo.Model`` but offers better integration with clorm facts
    and fact bases.

    '''

    def __init__(self, model,unifier=None):
        self._unifier = _build_unifier(unifier)
        _check_is_func(model,"symbols")
        init_wrapper(self,wrapped_=model)

    #------------------------------------------------------------------------------
    # Return the underlying model object
    #------------------------------------------------------------------------------
    @property
    def model_(self):
        '''Returns the underlying clingo.Model object.'''
        return self._wrapped

    #------------------------------------------------------------------------------
    # A new function to return a list of facts - similar to symbols
    #------------------------------------------------------------------------------

    def facts(self, *args, **kwargs):
        '''Returns a FactBase containing the facts in the model that unify with the
        SymbolPredicateUnifier.

        This function provides a wrapper around the ``clingo.Model.symbols``
        functions, but instead of returning a list of symbols it returns a
        FactBase containing the facts represented as ``clorm.Predicate``
        sub-class instances.

        Args:
           unifier(list | SymbolPredicateUnifier): used to unify and instantiate
              FactBase (Default: passed via the constructor if specified in the
              `clorm.clingo.Control` object)
           atoms: select all atoms in the model (Default: False)
           terms: select all terms displayed with #show statements (Default: False)
           shown: select all atoms and terms (Default: False)
           raise_on_empty: raise a ValueError if the resulting FactBase is empty
                           (Default: False)

        '''
        nargs = list(args)
        nkwargs = dict(kwargs)
        if len(nargs) >= 1 and "unifier" in nkwargs:
            raise TypeError("facts() got multiple values for argument 'unifier'")
        if len(nargs) >= 5 and "raise_on_empty" in nkwargs:
            raise TypeError("facts() got multiple values for argument 'raise_on_empty'")

        raise_on_empty = nkwargs.pop("raise_on_empty",False)
        if len(nargs) >= 5: raise_on_empty = nargs.pop(4)
        unifier = nkwargs.pop("unifier",None)
        if len(nargs) >= 1: unifier = nargs.pop(0)

        if unifier is not None: unifier=_build_unifier(unifier)
        else: unifier=self._unifier
        if unifier is None:
            msg = "Missing a predicate unifier specification in function call " + \
                "(no default was given at model instantiation)"
            raise ValueError(msg)

        return unifier.unify(
            symbols=self._wrapped.symbols(*nargs,**nkwargs),
            raise_on_empty=raise_on_empty,
            delayed_init=True)

    #------------------------------------------------------------------------------
    # Overide contains
    #------------------------------------------------------------------------------

    def contains(self, fact):
        '''Return whether the fact or symbol is contained in the model. Extends
        ``clingo.Model.contains`` to allow for clorm facts as well as a clingo
        symbols.

        '''
        if isinstance(fact, Predicate):
            return self._wrapped.contains(fact.raw)
        return self._wrapped.contains(fact)


Model = make_class_wrapper(OModel, ModelOverride)

# ------------------------------------------------------------------------------
# Wrap clingo.SolveHandle and override some functions
# ------------------------------------------------------------------------------

class SolveHandleGenerator(Generator):
    def __init__(self, gen, unifier):
        self._gen = gen
        self._unifier = unifier

    def __iter__(self):
        return self
    def __next__(self):
        model = next(self._gen)
        if self._unifier:
            return Model(model,unifier=self._unifier)
        else:
            return Model(model)

    def throw(self,typ,val=None,tb=None):
        self._gen.throw(typ,val,tb)
    def send(self,value):
        self._gen.send(value)
    def close(self):
        self._gen.close()
    def __del__(self):
        if oclingo.__version__ >= "5.5.0":
            self._gen.__del__()


class SolveHandleOverride(object):
#class SolveHandle(OSolveHandle, metaclass=WrapperMetaClass):
    '''Handle for solve calls.

    Objects mustn't be created manually. Instead they are returned by
    ``clorm.clingo.Control.solve``.

    Behaves like ``clingo.SolveHandle`` but iterates over ``clorm.clingo.Model``
    objects.

    '''


    def __init__(self, handle,unifier=None):
        init_wrapper(self,wrapped_=handle)
        self._unifier = _build_unifier(unifier)

    #------------------------------------------------------------------------------
    # Return the underlying solvehandle object
    #------------------------------------------------------------------------------
    @property
    def solvehandle_(self):
        '''Access the underlying clingo.SolveHandle object.'''
        return self._wrapped

    #------------------------------------------------------------------------------
    # Overrides
    #------------------------------------------------------------------------------

    def __iter__(self):
        return SolveHandleGenerator(iter(self._wrapped), self._unifier)

    def __enter__(self):
        self._wrapped.__enter__()
        return self

    def __exit__(self, exception_type, exception_value, traceback):
        self._wrapped.__exit__(exception_type,exception_value,traceback)
        return None


SolveHandle = make_class_wrapper(OSolveHandle, SolveHandleOverride)


# ------------------------------------------------------------------------------
# Wrap clingo.Control and override some functions
# ------------------------------------------------------------------------------

# ------------------------------------------------------------------------------
# Helper functions to expand the assumptions list as part of a solve() call. The
# assumptions list is a list of argument-boolean pairs where the argument can be
# be a clingo symbol, or clorm predicate instance, or a collection of clingo
# symbols or clorm predicates. This needs to be expanded into a list of
# symbol-bool pairs.
# ------------------------------------------------------------------------------
def _expand_assumptions(assumptions):
    pos_assump = set()
    neg_assump = set()

    def _add_fact(fact,bval):
        nonlocal pos_assump, neg_assump
        if isinstance(fact, Predicate): raw = fact.raw
        else: raw = fact
        if bval: pos_assump.add(raw)
        else: neg_assump.add(raw)

    try:
        for (arg,bval) in assumptions:
            if isinstance(arg, Predicate):
                _add_fact(arg,bval)
            elif isinstance(arg, Iterable):
                for f in arg: _add_fact(f,bval)
            else:
                _add_fact(arg,bval)
    except (TypeError, ValueError) as e:
        raise TypeError(("Invalid solve assumptions. Expecting list of arg-bool "
                         "pairs (arg is a raw-symbol/predicate or a collection "
                         "of raw-symbols/predicates). Got: {}").format(assumptions))

    # Now returned a list of raw assumptions combining pos and neg
    pos = [ (raw,True) for raw in pos_assump ]
    neg = [ (raw,False) for raw in neg_assump ]
    return list(itertools.chain(pos,neg))

# ------------------------------------------------------------------------------
# Control class
# ------------------------------------------------------------------------------



class ControlOverride(object):
#class Control(OControl, metaclass=WrapperMetaClass):
    '''Control object for the grounding/solving process.

    Behaves like ``clingo.Control`` but with modifications to deal with Clorm
    facts and fact bases.

    Adds an additional parameter ``unifier`` to specify how any generated clingo
    models will be unified with the clorm Predicate definitions. The unifier can
    be specified as a list of predicates or as a SymbolPredicateUnifier object.

    An existing ``clingo.Control`` object can be passed using the ``control_``
    parameter.

    '''

    def __init__(self, *args, **kwargs):
        self._unifier = None
        if "unifier" in kwargs: self._unifier = _build_unifier(kwargs["unifier"])

        # Do we need to build a clingo.Control object or use an existing one. If
        # using existing one make sure the wrapped object has at least the
        # ground and solve functions.
        if len(args) == 0 and "control_" in kwargs:
            wrapped_=kwargs["control_"]
            _check_is_func(wrapped_,"solve")
            _check_is_func(wrapped_,"ground")
            init_wrapper(self,wrapped_=wrapped_)
        else:
            kwargs2 = dict(kwargs)
            if "unifier" in kwargs2: del kwargs2["unifier"]
            init_wrapper(self,*args,**kwargs2)

    #------------------------------------------------------------------------------
    # Return the underlying control object
    #------------------------------------------------------------------------------
    @property
    def control_(self):
        '''Returns the underlying clingo.Control object.'''
        return self._wrapped

    #------------------------------------------------------------------------------
    # Make the unifier a property with a getter and setter
    #------------------------------------------------------------------------------
    @property
    def unifier(self):
        """Get/set the unifier.

        Unifier can be specified as a SymbolPredicateUnifier or a collection of
        Predicates. Always returns a SymbolPredicateUnifier (or None).

        """
        return self._unifier

    @unifier.setter
    def unifier(self,unifier):
        self._unifier = _build_unifier(unifier)

    #------------------------------------------------------------------------------
    # A new function to add facts from a factbase or a list of facts
    #------------------------------------------------------------------------------
    def add_facts(self, facts):
        '''Add facts to the control object. Note: facts must be added before grounding.

           This function can take an arbitrary collection containing a mixture
           of ``clorm.Predicate`` and ``clingo.Symbol`` objects. A
           ``clorm.FactBase`` is also a valid collection but it can only contain
           ``clorm.Predicate`` instances.

        Args:
          facts: a collection of ``clorm.Predicate`` or ``clingo.Symbol`` objects

        '''
        control_add_facts(self._wrapped, facts)

    #------------------------------------------------------------------------------
    # Overide assign_external to deal with Predicate object and a Clingo Symbol
    #------------------------------------------------------------------------------
    def assign_external(self, external, truth):
        '''Assign a truth value to an external fact (or collection of facts)

        A fact can be a raw clingo.Symbol object, a clorm.Predicate instance, or
        a program literal (an int). If the external is a collection then the
        truth value is assigned to all elements in the collection.

        This function extends ``clingo.Control.release_external``.

        '''
        def _assign_fact(fact):
            if isinstance(fact, Predicate):
                self._wrapped.assign_external(fact.raw, truth)
            else:
                self._wrapped.assign_external(fact, truth)

        if isinstance(external, Iterable):
            for f in external: _assign_fact(f)
        else:
            _assign_fact(external)

    #------------------------------------------------------------------------------
    # Overide release_external to deal with Predicate object and a Clingo Symbol
    #------------------------------------------------------------------------------
    def release_external(self, external):
        '''Release an external fact (or collection of facts)

        A fact can be a raw clingo.Symbol object, a clorm.Predicate instance, or
        a program literal (an int). If the external is a collection then the
        truth value is assigned to all elements in the collection.

        This function extends ``clingo.Control.release_external``.

        '''
        def _release_fact(fact):
            if isinstance(fact, Predicate):
                self._wrapped.release_external(fact.raw)
            else:
                self._wrapped.release_external(fact)

        if isinstance(external, Iterable):
            for f in external: _release_fact(f)
        else:
            _release_fact(external)

    #---------------------------------------------------------------------------
    # Overide solve and if necessary replace on_model with a wrapper that
    # returns a clorm.Model object. Also because of the issue with using the
    # keyword "async" as a parameter in Python 3.7 (which forced clingo 5.3.1+
    # to switch to using "async_") we have to use a complicated way to work out
    # function parameters. At some point will drop support for older clingo and
    # can simplify this function.
    # ---------------------------------------------------------------------------
    def solve(self, *args, **kwargs):
        '''Run the clingo solver.

        This function extends ``clingo.Control.solve()`` in two ways:

        1) The ``assumptions`` argument is generalised so that in the list of
        argument-boolean pairs the argument can be be a clingo symbol, or clorm
        predicate instance, or a collection of clingo symbols or clorm
        predicates.

        2) It produces either a ``clorm.clingo.SolveHandle`` wrapper object or a
        ``clorm.clingo.Model`` wrapper objects as appropriate (depending on the
        ``yield_``, ``async_``, and ``on_model`` parameters).

        '''

        # Build the list of valid arguments; using the correct "async" or
        # "async_" parameter based on the clingo version.  Note: "async" is a
        # keyword for Python 3.7+.
        async_keyword="async"
        if oclingo.__version__ > '5.3.1': async_keyword="async_"

        posnargs = ["assumptions","on_model","on_statistics",
                    "on_finish","yield_",async_keyword]
        validargs = set(posnargs)

        # translate all positional arguments into keyword arguments.
        if len(args) > len(posnargs):
            raise TypeError(("solve() takes {} positional arguments but {}"
                             "were given").format(len(posnargs),len(args)))
        nkwargs = {}
        for idx,arg in enumerate(args): nkwargs[posnargs[idx]] = arg

        for k,v in kwargs.items():
            if k not in validargs:
                raise TypeError(("solve() got an unexpected keyword "
                                 "argument '{}'").format(k))
            if k in nkwargs:
                raise TypeError(("solve() got multiple values for "
                                 "argument '{}'").format(k))
            nkwargs[k] = v

        # generate a new assumptions list if necesary
        if "assumptions" in nkwargs and nkwargs["assumptions"] is not None:
            nkwargs["assumptions"] = _expand_assumptions(nkwargs["assumptions"])

        # generate a new on_model function if necessary
        if "on_model" in nkwargs and nkwargs["on_model"] is not None:
            on_model=nkwargs["on_model"]
            @functools.wraps(on_model)
            def on_model_wrapper(model):
                if self._unifier: return on_model(Model(model, self._unifier))
                else: return on_model(Model(model))
            nkwargs["on_model"] =  on_model_wrapper

        # Call the wrapped solve function and handle the return value
        # appropriately
        result = self._wrapped.solve(**nkwargs)
        if ("yield_" in nkwargs and nkwargs["yield_"])  or \
           (async_keyword in nkwargs and nkwargs[async_keyword]):
            if self._unifier: return SolveHandle(result,unifier=self._unifier)
            else: return SolveHandle(result)
        else:
            return result


    def __getattr__(self,attr):
        return getattr(self._wrapped,attr)


Control = make_class_wrapper(OControl, ControlOverride)

#------------------------------------------------------------------------------
# This is probably bad practice... Modify the original clingo docstrings so that
# when I generate the autodoc with clingo being mocked it installs a reference
# to the original clingo docs.
#
# UPDATE: I'm confused what the autodoc mocking is doing (or not doing). I'm
# sure I had it working but now seems to be failing. Adding more hacks :(
# ------------------------------------------------------------------------------

Control.__doc__ += OControl.__doc__
Control.assign_external.__doc__ += OControl.assign_external.__doc__
Control.release_external.__doc__ += OControl.release_external.__doc__
Control.solve.__doc__ += OControl.solve.__doc__
Model.__doc__ += OModel.__doc__
Model.contains.__doc__ += OModel.contains.__doc__
SolveHandle.__doc__ += OSolveHandle.__doc__

#------------------------------------------------------------------------------
# main
#------------------------------------------------------------------------------
if __name__ == "__main__":
    raise RuntimeError('Cannot run modules')
A plugin replacement for the ``clingo`` modules that wraps the key clingo objects to integrate Clorm ``Predicate`` and ``FactBase`` interfaces. See the `Clingo API <https://potassco.org/clingo/python-api/current/clingo.html#Model>`_ for more details. # TODO: For clorm v2.0 the raise_on_empty parameter in Model.facts() should be #       moved to the second parameter position. # I want to replace the original clingo - re-exporting everything in clingo # except replacing the class overides with my version: _class_overides = [ # 'Control', 'Model', 'SolveHandle' ]. The following seems to work but I'm not # sure if this is bad. #------------------------------------------------------------------------------ # Reference to the original clingo objects so that when we replace them our # references point to the originals. #------------------------------------------------------------------------------ # ------------------------------------------------------------------------------ # Helper function to smartly build a unifier if only a list of predicates have # been provided. # ------------------------------------------------------------------------------ # ------------------------------------------------------------------------------ # Helper function to test that an attribute exists and corresponds to a function. # ------------------------------------------------------------------------------ # ------------------------------------------------------------------------------ # Wrap clingo.Model and override some functions # ------------------------------------------------------------------------------ #class Model(OModel, metaclass=WrapperMetaClass): Provides access to a model during a solve call.      Objects mustn't be created manually. Instead they are returned by     ``clorm.clingo.Control.solve`` callbacks.      Behaves like ``clingo.Model`` but offers better integration with clorm facts     and fact bases. #------------------------------------------------------------------------------ # Return the underlying model object #------------------------------------------------------------------------------ Returns the underlying clingo.Model object. #------------------------------------------------------------------------------ # A new function to return a list of facts - similar to symbols #------------------------------------------------------------------------------ Returns a FactBase containing the facts in the model that unify with the         SymbolPredicateUnifier.          This function provides a wrapper around the ``clingo.Model.symbols``         functions, but instead of returning a list of symbols it returns a         FactBase containing the facts represented as ``clorm.Predicate``         sub-class instances.          Args:            unifier(list | SymbolPredicateUnifier): used to unify and instantiate               FactBase (Default: passed via the constructor if specified in the               `clorm.clingo.Control` object)            atoms: select all atoms in the model (Default: False)            terms: select all terms displayed with #show statements (Default: False)            shown: select all atoms and terms (Default: False)            raise_on_empty: raise a ValueError if the resulting FactBase is empty                            (Default: False) #------------------------------------------------------------------------------ # Overide contains #------------------------------------------------------------------------------ Return whether the fact or symbol is contained in the model. Extends         ``clingo.Model.contains`` to allow for clorm facts as well as a clingo         symbols. # ------------------------------------------------------------------------------ # Wrap clingo.SolveHandle and override some functions # ------------------------------------------------------------------------------ #class SolveHandle(OSolveHandle, metaclass=WrapperMetaClass): Handle for solve calls.      Objects mustn't be created manually. Instead they are returned by     ``clorm.clingo.Control.solve``.      Behaves like ``clingo.SolveHandle`` but iterates over ``clorm.clingo.Model``     objects. #------------------------------------------------------------------------------ # Return the underlying solvehandle object #------------------------------------------------------------------------------ Access the underlying clingo.SolveHandle object. #------------------------------------------------------------------------------ # Overrides #------------------------------------------------------------------------------ # ------------------------------------------------------------------------------ # Wrap clingo.Control and override some functions # ------------------------------------------------------------------------------ # ------------------------------------------------------------------------------ # Helper functions to expand the assumptions list as part of a solve() call. The # assumptions list is a list of argument-boolean pairs where the argument can be # be a clingo symbol, or clorm predicate instance, or a collection of clingo # symbols or clorm predicates. This needs to be expanded into a list of # symbol-bool pairs. # ------------------------------------------------------------------------------ # Now returned a list of raw assumptions combining pos and neg # ------------------------------------------------------------------------------ # Control class # ------------------------------------------------------------------------------ #class Control(OControl, metaclass=WrapperMetaClass): Control object for the grounding/solving process.      Behaves like ``clingo.Control`` but with modifications to deal with Clorm     facts and fact bases.      Adds an additional parameter ``unifier`` to specify how any generated clingo     models will be unified with the clorm Predicate definitions. The unifier can     be specified as a list of predicates or as a SymbolPredicateUnifier object.      An existing ``clingo.Control`` object can be passed using the ``control_``     parameter. # Do we need to build a clingo.Control object or use an existing one. If # using existing one make sure the wrapped object has at least the # ground and solve functions. #------------------------------------------------------------------------------ # Return the underlying control object #------------------------------------------------------------------------------ Returns the underlying clingo.Control object. #------------------------------------------------------------------------------ # Make the unifier a property with a getter and setter #------------------------------------------------------------------------------ Get/set the unifier.          Unifier can be specified as a SymbolPredicateUnifier or a collection of         Predicates. Always returns a SymbolPredicateUnifier (or None). #------------------------------------------------------------------------------ # A new function to add facts from a factbase or a list of facts #------------------------------------------------------------------------------ Add facts to the control object. Note: facts must be added before grounding.             This function can take an arbitrary collection containing a mixture            of ``clorm.Predicate`` and ``clingo.Symbol`` objects. A            ``clorm.FactBase`` is also a valid collection but it can only contain            ``clorm.Predicate`` instances.          Args:           facts: a collection of ``clorm.Predicate`` or ``clingo.Symbol`` objects #------------------------------------------------------------------------------ # Overide assign_external to deal with Predicate object and a Clingo Symbol #------------------------------------------------------------------------------ Assign a truth value to an external fact (or collection of facts)          A fact can be a raw clingo.Symbol object, a clorm.Predicate instance, or         a program literal (an int). If the external is a collection then the         truth value is assigned to all elements in the collection.          This function extends ``clingo.Control.release_external``. #------------------------------------------------------------------------------ # Overide release_external to deal with Predicate object and a Clingo Symbol #------------------------------------------------------------------------------ Release an external fact (or collection of facts)          A fact can be a raw clingo.Symbol object, a clorm.Predicate instance, or         a program literal (an int). If the external is a collection then the         truth value is assigned to all elements in the collection.          This function extends ``clingo.Control.release_external``. #--------------------------------------------------------------------------- # Overide solve and if necessary replace on_model with a wrapper that # returns a clorm.Model object. Also because of the issue with using the # keyword "async" as a parameter in Python 3.7 (which forced clingo 5.3.1+ # to switch to using "async_") we have to use a complicated way to work out # function parameters. At some point will drop support for older clingo and # can simplify this function. # --------------------------------------------------------------------------- Run the clingo solver.          This function extends ``clingo.Control.solve()`` in two ways:          1) The ``assumptions`` argument is generalised so that in the list of         argument-boolean pairs the argument can be be a clingo symbol, or clorm         predicate instance, or a collection of clingo symbols or clorm         predicates.          2) It produces either a ``clorm.clingo.SolveHandle`` wrapper object or a         ``clorm.clingo.Model`` wrapper objects as appropriate (depending on the         ``yield_``, ``async_``, and ``on_model`` parameters). # Build the list of valid arguments; using the correct "async" or # "async_" parameter based on the clingo version.  Note: "async" is a # keyword for Python 3.7+. # translate all positional arguments into keyword arguments. # generate a new assumptions list if necesary # generate a new on_model function if necessary # Call the wrapped solve function and handle the return value # appropriately #------------------------------------------------------------------------------ # This is probably bad practice... Modify the original clingo docstrings so that # when I generate the autodoc with clingo being mocked it installs a reference # to the original clingo docs. # # UPDATE: I'm confused what the autodoc mocking is doing (or not doing). I'm # sure I had it working but now seems to be failing. Adding more hacks :( # ------------------------------------------------------------------------------ #------------------------------------------------------------------------------ # main #------------------------------------------------------------------------------