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Separate blackboard per python version
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‎README.md

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| Pattern | Description |
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|:-------:| ----------- |
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| [blackboard](patterns/other/blackboard.py) | architectural model, assemble different sub-system knowledge to build a solution, AI approach - non gang of four pattern |
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| [blackboard](patterns/other/blackboard__py3.py) | architectural model, assemble different sub-system knowledge to build a solution, AI approach - non gang of four pattern |
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| [graph_search](patterns/other/graph_search.py) | graphing algorithms - non gang of four pattern |
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| [hsm](patterns/other/hsm/hsm.py) | hierarchical state machine - non gang of four pattern |
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‎patterns/other/blackboard.py renamed to ‎patterns/other/blackboard__py2.py

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‎patterns/other/blackboard__py3.py

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#!/usr/bin/env python
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# -*- coding: utf-8 -*-
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"""
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@author: Eugene Duboviy <eugene.dubovoy@gmail.com> | github.com/duboviy
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In Blackboard pattern several specialised sub-systems (knowledge sources)
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assemble their knowledge to build a possibly partial or approximate solution.
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In this way, the sub-systems work together to solve the problem,
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where the solution is the sum of its parts.
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https://en.wikipedia.org/wiki/Blackboard_system
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"""
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import abc
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import random
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class Blackboard(object):
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def __init__(self):
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self.experts = []
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self.common_state = {
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'problems': 0,
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'suggestions': 0,
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'contributions': [],
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'progress': 0, # percentage, if 100 -> task is finished
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}
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def add_expert(self, expert):
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self.experts.append(expert)
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class Controller(object):
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def __init__(self, blackboard):
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self.blackboard = blackboard
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def run_loop(self):
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while self.blackboard.common_state['progress'] < 100:
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for expert in self.blackboard.experts:
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if expert.is_eager_to_contribute:
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expert.contribute()
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return self.blackboard.common_state['contributions']
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class AbstractExpert(metaclass=abc.ABCMeta):
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def __init__(self, blackboard):
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self.blackboard = blackboard
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@property
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@abc.abstractmethod
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def is_eager_to_contribute(self):
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raise NotImplementedError('Must provide implementation in subclass.')
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@abc.abstractmethod
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def contribute(self):
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raise NotImplementedError('Must provide implementation in subclass.')
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class Student(AbstractExpert):
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@property
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def is_eager_to_contribute(self):
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return True
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def contribute(self):
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self.blackboard.common_state['problems'] += random.randint(1, 10)
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self.blackboard.common_state['suggestions'] += random.randint(1, 10)
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self.blackboard.common_state['contributions'] += [self.__class__.__name__]
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self.blackboard.common_state['progress'] += random.randint(1, 2)
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class Scientist(AbstractExpert):
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@property
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def is_eager_to_contribute(self):
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return random.randint(0, 1)
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def contribute(self):
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self.blackboard.common_state['problems'] += random.randint(10, 20)
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self.blackboard.common_state['suggestions'] += random.randint(10, 20)
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self.blackboard.common_state['contributions'] += [self.__class__.__name__]
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self.blackboard.common_state['progress'] += random.randint(10, 30)
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class Professor(AbstractExpert):
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@property
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def is_eager_to_contribute(self):
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return True if self.blackboard.common_state['problems'] > 100 else False
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def contribute(self):
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self.blackboard.common_state['problems'] += random.randint(1, 2)
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self.blackboard.common_state['suggestions'] += random.randint(10, 20)
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self.blackboard.common_state['contributions'] += [self.__class__.__name__]
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self.blackboard.common_state['progress'] += random.randint(10, 100)
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if __name__ == '__main__':
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blackboard = Blackboard()
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blackboard.add_expert(Student(blackboard))
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blackboard.add_expert(Scientist(blackboard))
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blackboard.add_expert(Professor(blackboard))
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c = Controller(blackboard)
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contributions = c.run_loop()
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from pprint import pprint
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pprint(contributions)
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### OUTPUT ###
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# ['Student',
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# 'Student',
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# 'Scientist',
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# 'Student',
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# 'Scientist',
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# 'Student',
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# 'Scientist',
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# 'Student',
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# 'Scientist',
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# 'Student',
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# 'Scientist',
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# 'Professor']

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