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.. $Id$
..
.. Copyright Š 2007 Bruce Frederiksen
..
.. Permission is hereby granted, free of charge, to any person obtaining a copy
.. of this software and associated documentation files (the "Software"), to deal
.. in the Software without restriction, including without limitation the rights
.. to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
.. copies of the Software, and to permit persons to whom the Software is
.. furnished to do so, subject to the following conditions:
..
.. The above copyright notice and this permission notice shall be included in
.. all copies or substantial portions of the Software.
..
.. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
.. IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
.. FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
.. AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
.. LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
.. OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
.. THE SOFTWARE.
restindex
crumb: Using Pyke
page-description:
How your python program uses pyke.
/description
format: rest
encoding: utf8
output-encoding: utf8
include: yes
/restindex
===================================
Using Pyke
===================================
This describes how to use pyke from within your python program.
Initializing Pyke
===============================
There are two steps to initializing a pyke engine:
pyke.engine(paths = ('.',), gen_dir = '.', gen_root_dir = 'compiled_krb', load_fc = True, load_bc = True)
The pyke inference engine is offered
as a class so that you can instantiate multiple copies of it with different
rule bases to accomplish different tasks.
Once you have a pyke.engine object; generally, all of
the functions that you need are provided directly by this object:
>>> import pyke
>>> my_engine = pyke.engine('examples')
This expects either a single directory or a sequence of directories as
the ``paths`` argument.
It recursively walks each directory looking for `.krb files`_.
Each `.krb file`_ that it finds is compiled, if out of date, and then
the resulting python modules imported (depending on ``load_fc`` and
``load_bc``).
This causes all of the `rule bases`_ to be loaded and made ready to
*activate* (see below).
All generated python files are placed in a mirror directory structure
under the *gen_root_dir* directory in *gen_dir*. Thus, by default,
this mirrored directory structure would be rooted under the
"./compiled_krb" directory. You probably want to add ``compiled_krb`` to
your subversion ``global-ignores`` option. *Gen_dir*, *gen_root_dir*
and the mirrored directory structure will be created automatically if
any of them do not already exist.
If you change some of the .krb files, you can create a new engine
object to compile and reload the generated python modules without
restarting your program. But note that you'll need to rerun your
``add_universal_fact`` calls.
*some_engine*.add_universal_fact(kb_name, fact_name, arguments)
The ``add_universal_fact`` function is called once per fact_. These facts_
are never deleted and apply to all *cases*.
>>> my_engine.add_universal_fact('family', 'son_of', ('bruce', 'thomas', 'norma'))
Multiple facts with the same name are allowed.
>>> my_engine.add_universal_fact('family', 'son_of', ('david', 'bruce', 'marilyn'))
But duplicate facts (with the same arguments) are silently ignored.
>>> my_engine.add_universal_fact('family', 'son_of', ('david', 'bruce', 'marilyn'))
>>> my_engine.get_kb('family').dump_universal_facts()
son_of('bruce', 'thomas', 'norma')
son_of('david', 'bruce', 'marilyn')
These facts are accessed as *kb_name.fact_name(arguments)* within the
.krb files.
Setting up Each Case
===========================
Pyke is designed to be run multiple times for multiple *cases*. In
general each case has its own set of starting facts_ and may use different
`rule bases`_, depending on the situation.
Three functions initialize each case:
*some_engine*.reset()
The ``reset`` function is called once to delete all of the `case specific
facts`_ from the last run. It also deactivates all `rule bases`_.
*some_engine*.assert_(kb_name, fact_name, arguments)
Call ``assert_`` (or the equivalent, ``add_case_specific_fact``,
see `Other Functions`_, below) for each starting fact_ for this case.
Like universal facts, you may have multiple facts with the same name so
long as they have different arguments.
>>> my_engine.assert_('family', 'daughter_of', ('marilyn', 'arthur', 'kathleen'))
>>> my_engine.assert_('family', 'daughter_of', ('sue', 'arthur', 'kathleen'))
>>> my_engine.assert_('family', 'daughter_of', ('sue', 'arthur', 'kathleen'))
Duplicates with universal facts are also ignored.
>>> my_engine.assert_('family', 'son_of', ('bruce', 'thomas', 'norma'))
>>> my_engine.get_kb('family').dump_specific_facts()
daughter_of('marilyn', 'arthur', 'kathleen')
daughter_of('sue', 'arthur', 'kathleen')
>>> my_engine.get_kb('family').dump_universal_facts()
son_of('bruce', 'thomas', 'norma')
son_of('david', 'bruce', 'marilyn')
There is no difference within the .krb files of how universal facts
verses specific facts are used. The only difference between the two
types of facts is that the specific facts are deleted when a reset is
done.
>>> my_engine.reset()
>>> my_engine.get_kb('family').dump_specific_facts()
>>> my_engine.get_kb('family').dump_universal_facts()
son_of('bruce', 'thomas', 'norma')
son_of('david', 'bruce', 'marilyn')
*some_engine*.activate(\*rb_names)
Then call ``activate`` to activate the appropriate `rule bases`_. This
may be called more than once, if desired, or it can simply take multiple
arguments.
>>> my_engine.activate('bc_example')
Your pyke engine is now ready to prove goals for this case!
Proving Goals
======================
Two functions are provided that cover the easy cases. More general
functions are provided in `Other Functions`_, below.
*some_engine*.prove_1(kb_name, entity_name, fixed_args, num_returns)
``Kb_name`` may name either a fact_base_ or an activated
`rule base category`_. The ``entity_name`` is the fact_name for fact_bases,
or the name of the `backward chaining`_ goal for `rule bases`_.
The ``fixed_args`` are a tuple of python values. These form the first
group of arguments to the proof. ``Num_returns`` specifies the number of
additional `pattern variables`_ to be appended to the arguments for the
proof. The bindings of these pattern variables will be returned as the
answer for the proof. For example:
*some_engine*.prove_1(*some_rule_base_category*, *some_goal*, (1, 2, 3), 2)
Proves the goal:
*some_rule_base_category.some_goal* (1, 2, 3, $ans_0, $ans_1)
And will return the bindings for ``$ans_0`` and ``$ans_1`` produced by
the proof.
Returns the first proof found as a 2-tuple: a tuple of the bindings for
the ``num_returns`` pattern variables, and a plan_. The plan_ is ``None``
if no plan_ was generated; otherwise, it is a python function as
described below__.
.. __: #running-and-pickling-plans
>>> my_engine.prove_1('bc_example', 'child_parent', ('david', 'norma'), 3)
((('grand',), 'son', 'mother'), None)
Raises ``pyke.CanNotProve`` if no proof is found.
>>> my_engine.prove_1('bc_example', 'bogus', ('david', 'norma'), 3)
Traceback (most recent call last):
...
CanNotProve: Can not prove bc_example.bogus(david, norma, $ans_0, $ans_1, $ans_2)
*some_engine*.prove_n(kb_name, entity_name, fixed_args, num_returns)
This is a generator yielding 2-tuples, a tuple whose length == num_returns
and a plan_, for each possible proof. Like ``prove_1``, the plan_ is None
if no plan_ was generated.
>>> for ans in my_engine.prove_n('bc_example', 'child_parent', ('david',), 4):
... print ans
(('bruce', (), 'son', 'father'), None)
(('marilyn', (), 'son', 'mother'), None)
(('thomas', ('grand',), 'son', 'father'), None)
(('norma', ('grand',), 'son', 'mother'), None)
Running and Pickling Plans
----------------------------
Once you've obtained a plan_ from ``prove_1`` or ``prove_n``, you just call
it like a normal python function. The arguments required are simply those
specified, if any, in the `taking clause`_ of the rule_ proving the top-level
goal.
You may call the plan_ function any number of times. You may even pickle
the plan_ for later use. But the plans_ are constructed out of
`functools.partial`_ functions, so you need to register this with copy_reg_
before pickling the plan_:
>>> import copy_reg
>>> import functools
>>> copy_reg.pickle(functools.partial,
... lambda p: (functools.partial, (p.func,) + p.args))
No special code is required to unpickle a plan_. Also, the program that
unpickles the plan_ does not have to import any pyke modules to be able
to run the plan_. Just unpickle and call it.
Other Functions
========================
There are a few more functions that may be useful in special situations.
The first two of these provide more general access to the fact_ lookup and
goal proof mechanisms. The catch is that you must first convert **all**
arguments into patterns_ and create a *context* for these patterns_. This is
discussed below_.
*some_engine*.lookup(kb_name, entity_name, pattern_context, patterns)
This is a generator that binds patterns_ to successive facts_. Yields None
for each successful match.
*some_engine*.prove(kb_name, entity_name, pattern_context, patterns)
A generator that binds patterns_ to successive proofs. Yields a
*prototype_plan* or ``None`` for each successful match. To turn the
prototype_plan into a python function, use *prototype_plan*.create_plan().
This returns the plan_ function.
The remaining functions are:
*some_engine*.add_case_specific_fact(kb_name, fact_name, args)
This is an alternate to the ``assert_`` function.
*some_engine*.get_kb(kb_name)
Finds and returns the `knowledge base`_ by the name ``kb_name``. Raises
KeyError if not found. Note that for `rule bases`_, this returns the
active `rule base`_ where ``kb_name`` is the `rule base category`_ name.
Thus, not all `rule bases`_ are accessible through this call.
*some_engine*.get_rb(rb_name)
Finds and returns the `rule base`_ by the name ``rb_name``. Raises
KeyError if not found. This works for any `rule base`_, whether it is
active or not.
Creating Your Own Patterns
----------------------------------
You'll need two more pyke modules to create your own patterns_ and contexts:
>>> from pyke import pattern, contexts
There are four kinds of patterns_:
pattern.pattern_literal(data)
This matches the ``data`` provided.
pattern.pattern_tuple((elements), rest_var = None)
This matches a tuple. ``Elements`` must each be a pattern and must
match the first *n* elements of the tuple. ``Rest_var`` must be a
variable (or anonymous). It will match the rest of the tuple and is
always bound to a (possibly empty) tuple.
contexts.variable(name)
This will match anything the first time it is encountered. But then
must match the first value each additional time it is encountered.
Calling the constructor twice with the same name produces the same
variable and must match the same value in all of the places that it is
used.
contexts.anonymous()
This will match anything each time it is encountered.
Calling the constructor many times is not a problem.
Finally, to create a *pattern context*, you need:
contexts.simple_context()
You'll need to save this context to lookup your variable values after each
proof is yielded. This is done by either:
| *some_context*.lookup_data(*variable_name*)
| *some_variable*.as_data(*some_context*)
.. _backward chaining: overview/rules/backward_chaining.html
.. _below: `Creating Your Own Patterns`_
.. _case specific facts:
overview/knowledge_bases/fact_bases.html#case-specific-facts
.. _copy_reg: http://docs.python.org/lib/module-copyreg.html
.. _fact: overview/knowledge_bases/fact_bases.html#facts
.. _fact_base: overview/knowledge_bases/fact_bases.html
.. _facts: fact_
.. _functools.partial: http://docs.python.org/lib/module-functools.html
.. _knowledge base: overview/knowledge_bases/index.html
.. _.krb file: krb_syntax/index.html
.. _.krb files: `.krb file`_
.. _pattern: krb_syntax/pattern.html
.. _pattern variables: krb_syntax/pattern.html#pattern-variable
.. _patterns: pattern_
.. _plan: overview/plans.html
.. _plans: plan_
.. _rule: overview/rules/index.html
.. _rules: rule_
.. _rule base: overview/knowledge_bases/rule_bases.html
.. _rule base category:
overview/knowledge_bases/rule_bases.html#rule-base-categories
.. _rule bases: `rule base`_
.. _taking clause: krb_syntax/bc_rule.html#taking-clause