Clingo Solver Integration

So for we have shown how to define predicates and fact bases, and perform queries over fact bases. However, we have not discussed in detail how these objects are integrated and interact with the Clingo ASP solver.

As detailed in Raw Clingo Symbols, at its most basic level a Clingo Symbol object can be extracted from a Clorm Predicate object using the raw property.

and conversely a Symbol object can be passed as the raw parameter in the Predicate constructor.

Wrapper classes

While extracting Symbol objects from Predicates is sufficient to use Clorm with the Clingo solver it is still not a particularly clean interface and can result in unnecessary boilerplate code. To avoid this the clorm.clingo module fully integrates Clorm objects into the Clingo API. It does this by providing wrapper classes around the key Clingo classes:

  • Control is the heart of the interface to the reasoner and determines when and how the reasoner is called. The Control.solve() function starts the solving process. Depending on the parameters it can operate in different modes; for example it can use a callback that is called with Model ojects and can also return a SolveHandle.

  • Model is the class that contains the facts (and other meta-data) associated with an ASP model. This class should not be instantiated explicitly and is instead passed within the Control.solve callback.

  • SolveHandle provides a mechanism to iterate over the models. Similarly to the Model class it should not be instantiated explicitly and is instead returned from the Control.solve() function.


Control is the main object for interacting with the ASP grounder and solver and provides a rich set of features. It allows an ASP program that is stored in a file to be loaded. It can then be grounded and solved and the generated models returned. It also allows for incremental solving, where a ground program can be extended and solved repeatedly, as well as both synchronous and asynchronous solving modes. These featuers are documented in the Clingo Control API so we only highlight the changes that Clorm introduces.

Clorm adds some new member functions as well as overloading some existing functions:

  • __init__(). Clorm adds an optional unifier parameter for specifying a default list of Predicate sub-classes (or a single SymbolPredicateUnifier object). This parameter is passed to any generated Model objects and is used during the unification process of converting raw symbols to Clorm facts. A second parameter control_ is introduced. This parameter is mutually exclusive with the standard parameters for clingo.Control. The control_ parameter allows an existing clingo.Control object to be passed to the wrapper and is a mechanism to allow Clorm to be used even when Python is embedded within Clingo. See the example embedded_quickstart.lp for more details, but the basics are that a Control object is passed to the embedded main function which is then wrapped in clorm.clingo.Control:

  • unifier. A property to get and set the unifier even after the clorm.clingo.Control object has been instantiated.


import clorm.clingo

def main(ctrl_):
    ctrl = clorm.clingo.Control(control_=ctrl_)

    # ...
  • add_facts(facts). A new function that adds facts to an ASP program. The input can be any collection of facts (such as a list, set, or clorm.FactBase). A fact can be either a clorm.Predicate or clingo.Symbol object. Note however that a clorm.FactBase can only contain clorm.Predicate instances. Warning: because the initial facts in an ASP program will affect the grounding, new facts should only be added to the program before grounding.

from clorm.clingo import Control

ctrl = Control()
  • solve(). This function provides a rich set of options for calling the solver and returning the results. These parameters are documented in the Clingo API. Clorm modifies this interface in three ways:

    • assumptions parameter. This parameter restricts the returned models to only those satisfying the given assumptions. This parameter must consist of a list of argument-boolean pairs. As well as clingo.Symbol objects the argument element is extended to allow clorm.Predicate instances or a collection of clingo symbols or clorm predicates. This makes it flexible so that, for example, a FactBase object can be specified as being either True or False in the model.

    • on_model callback parameter. Clorm modifies this interface so that a clorm.clingo.Model is pass to the callback function.

    • If the parameter yield_=True is specified then the return value of the function is a clorm.clingo.SolveHandle object. This object iterates over clorm.clingo.Model objects.

  • assign_external(external,truth). This function assigns a truth value to an external atom. This function has been overloaded so that the external parameter can also take a clorm.Predicate instance or a collection of external atoms (e.g., a FactBase), where the same truth value is assigned to all atoms in the collection.

  • release_external(external). This function releases an external atom so that it is permanently false. The function is overloaded so that the external parameter can also take a clorm.Predicate instance or a collection of extenal atoms.


The Clingo Model object encapsulates an ASP model and the associated meta-data. It is passed to the Clingo.solve(on_model=on_model) callback. Clorm wraps the Model class to provide a mechanism to extract Clorm facts from the model. The additional and modified functions are:

  • facts(self, unifier=None, atoms=False, terms=False, shown=False, raise_on_empty=True). returns a fact base object constructed from unifying against the raw Clingo symbols within the model.

    The unifier parameter takes a list of Predicate sub-classes or a single SymbolPredicateUnifier which defines the predicates to unify against. If no unifier parameter is provided then a unifier must have been passed to the clorm.clingo.Control object.

    The raise_on_empty parameter specifies that a ValueError will be raised if the returned fact base is empty. This can happen for two reasons: there were no selected elements in the model or there were elements from the model but none of them was able to unify with the fact base. This parameter is potentially useful for debugging purposes. While returning an empty fact base can be legimate outcomes for some applications, however in many cases this would indicate a problem; either in the ASP program or in the declaration of the predicates to unify against.

    Apart from the unifier and raise_on_empty parameters the remaining parameters are the same as for the Model.symbols() function.

  • contains(self,fact). Extends clingo.Model.contains() to allow for a clorm facts as well as a clingo symbols.


The Clingo SolveHandle object provides a mechanism for iterating over the models when the yield_=True option is specified in the Control.solve() function call. The various iterator functions are modified by Clorm, but its operations should be transparent to the user.


Clorm provides monkey patching of the Control class so that Clorm can be integrated into an existing code base with minimal effort.

from clorm import monkey; monkey.patch()
from clingo import Control


In general monkey patching should be avoided where possible.