Create epmd.py
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epmd.py
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class EmergentProgrammer:
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def __init__(self):
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self.action_primitives = ['map', 'filter', 'reduce', 'transform', 'compose']
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self.discovered_actions = set()
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self.fractal_scales = {} # scale_level: {actions, dependencies}
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def discover_from_conditions(self, conditions, parameters, scale_level=0):
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"""Discover new programming actions from conditions and parameters"""
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discovered = []
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# Analyze parameter patterns for action discovery
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param_patterns = self._analyze_parameter_patterns(parameters)
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condition_structure = self._analyze_condition_structure(conditions)
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# Generate new actions based on patterns
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for pattern in param_patterns:
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new_action = self._synthesize_action(pattern, condition_structure)
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if new_action and self._validate_action(new_action, scale_level):
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discovered.append(new_action)
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self.discovered_actions.add(new_action)
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# Update fractal scale registry
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self._update_fractal_scale(scale_level, discovered, parameters)
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return discovered
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def _synthesize_action(self, pattern, conditions):
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"""Synthesize new action from patterns and conditions"""
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# Pattern-based action generation
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if pattern.get('type') == 'iterative':
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return f"cascade_{pattern.get('domain')}"
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elif pattern.get('type') == 'transformative':
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return f"resonate_{conditions.get('context', 'general')}"
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elif pattern.get('type') == 'emergent':
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return f"fractalize_{pattern.get('complexity')}"
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return None
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def _validate_action(self, action, scale_level):
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"""Validate action maintains fractal resonance"""
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# Check scale consistency (EFL Axiom)
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curvature = self._compute_action_curvature(action, scale_level)
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return abs(curvature) < 0.1 # Maintain flat emergence
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