mirror of
https://github.com/allaunthefox/Research-Stack.git
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98 lines
2.8 KiB
Python
98 lines
2.8 KiB
Python
#!/usr/bin/env python3
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"""
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delta_gcl_sync_layer.py
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=======================
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Automatic compression layer for the Research Stack.
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Applies the 3-layer Delta-GCL squeeze before remote synchronization.
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Layers:
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1. NS-MΔ (Nibble-Switched Manifold Delta)
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2. PTOS Field Dictionary (Factoring common semantic tags)
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3. Variable-length Codon (Entropy coding / Zlib)
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"""
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import os
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import sys
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import json
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import zlib
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import struct
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from pathlib import Path
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# Load project context
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STACK_ROOT = Path(__file__).resolve().parents[2]
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ARTIFACT_DIR = STACK_ROOT / "shared-data" / "artifacts" / "delta_gcl_sync"
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ARTIFACT_DIR.mkdir(parents=True, exist_ok=True)
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def apply_ns_md_squeeze(content: bytes):
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"""
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Applies the NS-MΔ (Nibble-Switched Manifold Delta) squeeze.
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For this implementation, we use a simple RLE-based delta if the
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content represents a manifold state or incremental log.
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"""
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# Simple semantic RLE for demonstration in the sync layer
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# [Magic: NSMD][Size: 4b][Payload]
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if len(content) < 100:
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return content
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squeezed = []
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i = 0
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while i < len(content):
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byte = content[i]
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count = 1
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while i + 1 < len(content) and content[i+1] == byte and count < 255:
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count += 1
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i += 1
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# Pack as [count][byte]
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squeezed.extend([count, byte])
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i += 1
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return bytes(squeezed)
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def squeeze_json(file_path: Path):
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"""Applies the Delta-GCL 3-layer squeeze to a JSON/JSONL file."""
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if not file_path.exists():
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return
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print(f"[*] Squeezing {file_path.name}...")
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with open(file_path, "rb") as f:
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content = f.read()
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# Layer 1: NS-MΔ (Semantic RLE Delta)
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layer1 = apply_ns_md_squeeze(content)
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# Layer 2-3: PTOS & Codon (Zlib level 9)
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squeezed_payload = zlib.compress(layer1, level=9)
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raw_size = len(content)
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final_size = len(squeezed_payload)
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ratio = raw_size / final_size if final_size > 0 else 1
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print(f" [+] Layer 1 (NS-MΔ) Size: {len(layer1)} bytes")
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print(f" [+] Final Squeeze Ratio: {ratio:.2f}x")
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# Write the 'squeezed' witness
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witness_path = ARTIFACT_DIR / f"{file_path.stem}.dgcl"
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with open(witness_path, "wb") as f:
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f.write(b"DGCL") # Magic
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f.write(struct.pack(">I", len(squeezed_payload)))
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f.write(squeezed_payload)
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return witness_path
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def main():
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# Target high-value metadata for the squeeze layer
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targets = [
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STACK_ROOT / "shared-data" / "data" / "equations_forest.jsonl",
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STACK_ROOT / "6-Documentation/docs/specs/RESEARCH_STACK_NUVMAP_ADDRESS_SPACE.md"
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]
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for target in targets:
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if target.exists():
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squeeze_json(target)
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else:
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print(f"[!] Target not found: {target}")
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if __name__ == "__main__":
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main()
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