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"$type": "site.standard.document",
"bskyPostRef": {
"cid": "bafyreiewzx3vhczsipg4zhexgo33roow376wvykhsssv3ph42gzw3djqs4",
"uri": "at://did:plc:pgryn3ephfd2xgft23qokfzt/app.bsky.feed.post/3miwvs36d2kq2"
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"path": "/t/can-any-run-see-if-this-pi-based-reconstruction-and-archival-protocol-works/175057#post_1",
"publishedAt": "2026-04-07T17:31:30.000Z",
"site": "https://discuss.huggingface.co",
"textContent": "#!/usr/bin/env python3\n“”\"\nPi-RAP: Pi-based Reconstruction & Archival Protocol\nComplete File System with Error Correction, Encryption, Compression\nInspired by “No Way Out” (1987) reconstruction scene\n\nFeatures:\n\n * Pi-based sector distribution\n * Reed-Solomon error correction\n * Pi stream cipher encryption\n * Zlib compression\n * Network distribution simulation\n * Checksum verification\n * Progress tracking\n“”\"\n\n\n\nimport os\nimport sys\nimport zlib\nimport hashlib\nimport random\nimport struct\nimport json\nimport time\nfrom pathlib import Path\nfrom datetime import datetime\nfrom typing import Dict, List, Tuple, Optional\nimport math\n\n# Try to import reedsolo for advanced error correction\n\ntry:\nimport reedsolo\nREED_SOLOMON_AVAILABLE = True\nexcept ImportError:\nREED_SOLOMON_AVAILABLE = False\nprint(“Note: Install ‘reedsolo’ for advanced error correction: pip install reedsolo”)\n\nclass PiDigitGenerator:\n“”“Generate Pi digits using spigot algorithm”“”\n\n\n def __init__(self):\n self.digits = self._calculate_pi_digits(10000)\n\n def _calculate_pi_digits(self, n_digits: int) -> str:\n \"\"\"Calculate Pi digits using spigot algorithm\"\"\"\n if n_digits < 100:\n # Use pre-calculated for small requests\n pi_str = \"14159265358979323846264338327950288419716939937510\"\n pi_str += \"58209749445923078164062862089986280348253421170679\"\n return pi_str[:n_digits]\n\n # Spigot algorithm for more digits\n pi_digits = []\n arr = [2] * (n_digits * 10 // 3)\n carry = 0\n\n for i in range(n_digits):\n sum_val = 0\n for j in range(len(arr) - 1, -1, -1):\n num = arr[j] * 10 + carry\n if j == 0:\n pi_digits.append(str(num // (2 * j + 1)))\n carry = num % (2 * j + 1)\n else:\n arr[j] = num % (2 * j + 1)\n sum_val = num // (2 * j + 1)\n carry = sum_val * (j)\n\n if len(pi_digits) >= n_digits:\n break\n\n result = ''.join(pi_digits[:n_digits])\n return result if result else \"14159265358979323846264338327950288419716939937510\"\n\n def get_digit(self, position: int) -> int:\n \"\"\"Get Pi digit at specific position (0-indexed)\"\"\"\n if position < len(self.digits):\n return int(self.digits[position])\n return int(self.digits[position % len(self.digits)])\n\n def get_digits(self, start: int, length: int) -> str:\n \"\"\"Get a sequence of Pi digits\"\"\"\n result = \"\"\n for i in range(length):\n result += str(self.get_digit(start + i))\n return result\n\n\nclass PiStreamCipher:\n“”“Encryption using Pi digits as stream cipher key”“”\n\n\n def __init__(self, pi_gen: PiDigitGenerator, seed: int = 0):\n self.pi_gen = pi_gen\n self.seed = seed\n\n def _generate_keystream(self, length: int) -> bytes:\n \"\"\"Generate keystream from Pi digits\"\"\"\n keystream = bytearray()\n position = self.seed\n\n # Generate enough bytes\n while len(keystream) < length:\n # Get multiple Pi digits and combine them\n digits = self.pi_gen.get_digits(position, 4)\n byte_val = int(digits) % 256\n keystream.append(byte_val)\n position += 4\n\n return bytes(keystream[:length])\n\n def encrypt(self, data: bytes) -> bytes:\n \"\"\"Encrypt data using XOR with Pi keystream\"\"\"\n keystream = self._generate_keystream(len(data))\n encrypted = bytes(a ^ b for a, b in zip(data, keystream))\n return encrypted\n\n def decrypt(self, data: bytes) -> bytes:\n \"\"\"Decrypt data (same as encrypt for XOR cipher)\"\"\"\n return self.encrypt(data)\n\n\nclass ReedSolomonCodec:\n“”“Error correction using Reed-Solomon codes”“”\n\n\n def __init__(self, nsym: int = 10):\n \"\"\"\n nsym: number of error correction symbols\n More symbols = more error correction but larger overhead\n \"\"\"\n self.nsym = nsym\n self.rs = None\n\n if REED_SOLOMON_AVAILABLE:\n try:\n self.rs = reedsolo.RSCodec(nsym)\n except:\n self.rs = None\n\n def encode(self, data: bytes) -> bytes:\n \"\"\"Add error correction codes\"\"\"\n if self.rs:\n return self.rs.encode(data)\n else:\n # Simple parity fallback\n parity = bytes([sum(data) % 256])\n return data + parity * self.nsym\n\n def decode(self, data: bytes) -> bytes:\n \"\"\"Remove error correction and correct errors\"\"\"\n if self.rs:\n try:\n return self.rs.decode(data)[0]\n except:\n return data[:len(data) - self.nsym]\n else:\n # Simple parity fallback\n return data[:-self.nsym] if self.nsym > 0 else data\n\n\nclass NetworkDistributor:\n“”“Simulate network distribution across multiple nodes”“”\n\n\n def __init__(self, num_nodes: int = 5):\n self.num_nodes = num_nodes\n self.nodes = {f\"node_{i}\": {} for i in range(num_nodes)}\n\n def distribute(self, sectors: Dict[str, dict]) -> Dict[str, Dict]:\n \"\"\"Distribute sectors across network nodes\"\"\"\n distribution = {}\n\n for sector_id, sector_data in sectors.items():\n # Use Pi digit to determine primary and backup nodes\n sector_num = int(sector_id.split('_')[-1].replace('.dat', ''))\n pi_digit = sector_num % 10\n\n primary_node = f\"node_{pi_digit % self.num_nodes}\"\n backup_node = f\"node_{(pi_digit + 1) % self.num_nodes}\"\n\n # Store on primary node\n self.nodes[primary_node][sector_id] = {\n 'data': sector_data['data'],\n 'type': 'primary'\n }\n\n # Store backup on secondary node\n self.nodes[backup_node][sector_id] = {\n 'data': sector_data['data'],\n 'type': 'backup'\n }\n\n distribution[sector_id] = {\n 'primary': primary_node,\n 'backup': backup_node\n }\n\n return distribution\n\n def simulate_node_failure(self, failed_node: str) -> int:\n \"\"\"Simulate a node going offline\"\"\"\n if failed_node in self.nodes:\n lost_sectors = len(self.nodes[failed_node])\n self.nodes[failed_node] = {}\n return lost_sectors\n return 0\n\n def recover_from_backup(self, lost_sectors: List[str]) -> Dict[str, dict]:\n \"\"\"Recover lost sectors from backup nodes\"\"\"\n recovered = {}\n\n for sector_id in lost_sectors:\n for node_name, node_data in self.nodes.items():\n if sector_id in node_data:\n if node_data[sector_id]['type'] == 'backup':\n # Promote backup to primary\n node_data[sector_id]['type'] = 'primary'\n recovered[sector_id] = node_data[sector_id]['data']\n break\n\n return recovered\n\n def get_all_sectors(self) -> Dict[str, dict]:\n \"\"\"Get all sectors from all nodes\"\"\"\n all_sectors = {}\n for node_name, node_data in self.nodes.items():\n for sector_id, sector_info in node_data.items():\n if sector_info['type'] == 'primary':\n all_sectors[sector_id] = {\n 'data': sector_info['data'],\n 'node': node_name\n }\n return all_sectors\n\n\nclass PiRAPFileSystem:\n“”“Main Pi-RAP File System”“”\n\n\n def __init__(self, config: dict = None):\n self.config = config or {\n 'sector_size': 50000, # bits\n 'compression': True,\n 'encryption': True,\n 'error_correction': True,\n 'encryption_seed': 0,\n 'network_nodes': 5,\n 'redundancy_level': 2,\n 'verbose': True\n }\n\n # Initialize components\n self.pi_gen = PiDigitGenerator()\n self.cipher = PiStreamCipher(self.pi_gen, self.config.get('encryption_seed', 0))\n self.rs_codec = ReedSolomonCodec(nsym=10 if self.config.get('error_correction') else 0)\n self.network = NetworkDistributor(self.config.get('network_nodes', 5))\n\n self.byte_sector_size = self.config.get('sector_size', 50000) // 8\n self.storage_map = {}\n self.file_metadata = {}\n self.distribution_map = {}\n\n # Statistics\n self.stats = {\n 'original_size': 0,\n 'compressed_size': 0,\n 'encrypted_size': 0,\n 'total_sectors': 0,\n 'compression_ratio': 0,\n 'processing_time': 0\n }\n\n def log(self, message: str, level: str = \"INFO\"):\n \"\"\"Log message with timestamp\"\"\"\n if self.config.get('verbose', True):\n timestamp = datetime.now().strftime(\"%H:%M:%S\")\n print(f\"[{timestamp}] [{level}] {message}\")\n\n def progress_bar(self, current: int, total: int, prefix: str = \"\", length: int = 40):\n \"\"\"Display progress bar\"\"\"\n if not self.config.get('verbose', True):\n return\n\n percent = 100 * (current / total) if total > 0 else 0\n filled = int(length * current // total)\n bar = '█' * filled + '░' * (length - filled)\n sys.stdout.write(f'\\r{prefix} |{bar}| {percent:.1f}% ({current}/{total})')\n sys.stdout.flush()\n if current >= total:\n print()\n\n def calculate_checksum(self, data: bytes) -> str:\n \"\"\"Calculate SHA-256 checksum\"\"\"\n return hashlib.sha256(data).hexdigest()\n\n def compress_data(self, data: bytes) -> bytes:\n \"\"\"Compress data using zlib\"\"\"\n if not self.config.get('compression', True):\n return data\n\n compressed = zlib.compress(data, level=9)\n compression_ratio = len(compressed) / len(data) if len(data) > 0 else 1\n self.stats['compression_ratio'] = compression_ratio\n return compressed\n\n def decompress_data(self, data: bytes) -> bytes:\n \"\"\"Decompress data\"\"\"\n if not self.config.get('compression', True):\n return data\n\n try:\n return zlib.decompress(data)\n except:\n return data\n\n def read_file(self, filepath: str) -> Tuple[bytes, str]:\n \"\"\"Read file and calculate checksum\"\"\"\n self.log(f\"Reading file: {filepath}\")\n\n with open(filepath, 'rb') as f:\n data = f.read()\n\n checksum = self.calculate_checksum(data)\n file_size = len(data)\n\n self.stats['original_size'] = file_size\n\n self.log(f\"File size: {file_size:,} bytes ({file_size*8:,} bits)\")\n self.log(f\"SHA-256: {checksum[:32]}...\")\n\n return data, checksum\n\n def create_sectors(self, data: bytes, filename: str) -> List[bytes]:\n \"\"\"Break data into sectors\"\"\"\n self.log(f\"Creating sectors ({self.byte_sector_size:,} bytes each)...\")\n\n # Pad data if needed\n original_len = len(data)\n if len(data) % self.byte_sector_size != 0:\n padding_len = self.byte_sector_size - (len(data) % self.byte_sector_size)\n data = data + b'\\x00' * padding_len\n\n # Split into sectors\n sectors = []\n total_sectors = len(data) // self.byte_sector_size\n\n for i in range(total_sectors):\n start = i * self.byte_sector_size\n end = start + self.byte_sector_size\n sector_data = data[start:end]\n sectors.append(sector_data)\n\n if self.config.get('verbose', True):\n self.progress_bar(i + 1, total_sectors, \"Sectorizing\")\n\n self.stats['total_sectors'] = len(sectors)\n\n # Store metadata\n self.file_metadata = {\n 'filename': filename,\n 'original_size': original_len,\n 'padded_size': len(data),\n 'num_sectors': len(sectors),\n 'sector_size': self.byte_sector_size,\n 'timestamp': datetime.now().isoformat(),\n 'config': self.config\n }\n\n self.log(f\"✓ Created {len(sectors)} sectors\")\n\n return sectors\n\n def encrypt_and_encode_sectors(self, sectors: List[bytes]) -> Dict[str, dict]:\n \"\"\"Encrypt sectors and add error correction\"\"\"\n self.log(\"Encrypting and adding error correction...\")\n\n encrypted_sectors = {}\n total = len(sectors)\n\n for idx, sector in enumerate(sectors):\n # Encrypt\n if self.config.get('encryption', True):\n encrypted = self.cipher.encrypt(sector)\n else:\n encrypted = sector\n\n # Add error correction\n if self.config.get('error_correction', True):\n encoded = self.rs_codec.encode(encrypted)\n else:\n encoded = encrypted\n\n # Determine storage location using Pi\n pi_digit = self.pi_gen.get_digit(idx)\n disk_id = f\"Disk_{pi_digit}\"\n sector_address = f\"{disk_id}/sector_{idx:06d}.dat\"\n\n encrypted_sectors[sector_address] = {\n 'data': encoded,\n 'original_index': idx,\n 'pi_digit': pi_digit,\n 'disk_id': disk_id,\n 'size': len(encoded)\n }\n\n if self.config.get('verbose', True):\n self.progress_bar(idx + 1, total, \"Encrypting\")\n\n self.log(f\"✓ Encoded {len(encrypted_sectors)} sectors\")\n\n return encrypted_sectors\n\n def scatter_sectors(self, sectors: Dict[str, dict]):\n \"\"\"Distribute sectors across network\"\"\"\n self.log(f\"Distributing across {self.config.get('network_nodes', 5)} nodes...\")\n\n # Network distribution\n self.distribution_map = self.network.distribute(sectors)\n\n # Also store locally\n self.storage_map = sectors\n\n self.log(f\"✓ Distributed to {len(self.distribution_map)} locations\")\n\n # Show distribution stats\n node_counts = {}\n for sector_id, dist_info in self.distribution_map.items():\n primary = dist_info['primary']\n node_counts[primary] = node_counts.get(primary, 0) + 1\n\n self.log(\"Distribution across nodes:\")\n for node, count in sorted(node_counts.items()):\n self.log(f\" {node}: {count} sectors\")\n\n def simulate_data_loss(self, loss_percentage: float = 10) -> Tuple[Dict, List]:\n \"\"\"Simulate data loss for testing recovery\"\"\"\n self.log(f\"⚠️ Simulating {loss_percentage}% data loss...\")\n\n all_sectors = self.network.get_all_sectors()\n total_sectors = len(all_sectors)\n num_lost = int(total_sectors * loss_percentage / 100)\n\n # Randomly select sectors to lose\n lost_keys = random.sample(list(all_sectors.keys()), num_lost)\n\n # Remove from network\n for sector_id in lost_keys:\n for node_name in self.network.nodes:\n if sector_id in self.network.nodes[node_name]:\n del self.network.nodes[node_name][sector_id]\n\n remaining = self.network.get_all_sectors()\n\n self.log(f\" Lost: {len(lost_keys)} sectors\")\n self.log(f\" Remaining: {len(remaining)} sectors\")\n\n return remaining, lost_keys\n\n def recover_and_reconstruct(self, available_sectors: Dict = None) -> bytes:\n \"\"\"Recover from backups and reconstruct file\"\"\"\n self.log(\"🔨 Recovering and reconstructing...\")\n\n if available_sectors is None:\n available_sectors = self.network.get_all_sectors()\n\n # Check for missing sectors\n total_expected = self.file_metadata.get('num_sectors', 0)\n available_count = len(available_sectors)\n missing_count = total_expected - available_count\n\n if missing_count > 0:\n self.log(f\" Missing {missing_count} sectors, attempting recovery...\")\n\n # Try to recover from backups\n all_sectors = {}\n for node_name, node_data in self.network.nodes.items():\n for sector_id, sector_info in node_data.items():\n if sector_id not in all_sectors:\n all_sectors[sector_id] = sector_info\n\n available_sectors = all_sectors\n\n # Sort sectors by index\n sorted_sectors = sorted(\n available_sectors.items(),\n key=lambda x: x[1].get('original_index', 0)\n )\n\n # Reconstruct data\n reconstructed_data = b''\n\n for sector_id, sector_info in sorted_sectors:\n sector_data = sector_info['data']\n\n # Remove error correction\n if self.config.get('error_correction', True):\n decoded = self.rs_codec.decode(sector_data)\n else:\n decoded = sector_data\n\n # Decrypt\n if self.config.get('encryption', True):\n decrypted = self.cipher.decrypt(decoded)\n else:\n decrypted = decoded\n\n reconstructed_data += decrypted\n\n # Remove padding\n original_size = self.file_metadata.get('original_size', len(reconstructed_data))\n reconstructed_data = reconstructed_data[:original_size]\n\n self.log(f\"✓ Reconstructed {len(reconstructed_data):,} bytes\")\n\n return reconstructed_data\n\n def verify_integrity(self, data: bytes, original_checksum: str) -> bool:\n \"\"\"Verify reconstructed data matches original\"\"\"\n self.log(\"✅ Verifying integrity...\")\n\n reconstructed_checksum = self.calculate_checksum(data)\n\n self.log(f\" Original: {original_checksum}\")\n self.log(f\" Reconstructed: {reconstructed_checksum}\")\n\n if reconstructed_checksum == original_checksum:\n self.log(\"🎉 SUCCESS! Checksum MATCH!\")\n return True\n else:\n self.log(\"❌ FAILURE! Checksum mismatch!\")\n return False\n\n def save_file(self, data: bytes, output_path: str):\n \"\"\"Save reconstructed file\"\"\"\n self.log(f\"💾 Saving to: {output_path}\")\n\n with open(output_path, 'wb') as f:\n f.write(data)\n\n file_size = os.path.getsize(output_path)\n self.log(f\"✓ Saved {file_size:,} bytes\")\n\n def process_file(self, input_path: str, output_path: str = None,\n simulate_loss: float = 0) -> bool:\n \"\"\"Complete pipeline: Read → Process → Scatter → Recover → Verify\"\"\"\n\n start_time = time.time()\n\n if output_path is None:\n output_path = \"reconstructed_\" + os.path.basename(input_path)\n\n print(\"\\n\" + \"=\"*70)\n print(\"🥧 Pi-RAP FILE SYSTEM v2.0 - COMPLETE EDITION\")\n print(\"=\"*70)\n print(f\"Input: {input_path}\")\n print(f\"Output: {output_path}\")\n print(f\"Config: Compression={self.config.get('compression')}, \" +\n f\"Encryption={self.config.get('encryption')}, \" +\n f\"Error Correction={self.config.get('error_correction')}\")\n print(\"=\"*70)\n\n try:\n # Step 1: Read file\n original_data, checksum = self.read_file(input_path)\n\n # Step 2: Compress\n if self.config.get('compression', True):\n self.log(\"Compressing data...\")\n compressed_data = self.compress_data(original_data)\n self.stats['compressed_size'] = len(compressed_data)\n self.log(f\"✓ Compressed: {len(original_data):,} → {len(compressed_data):,} bytes \" +\n f\"({self.stats['compression_ratio']*100:.1f}%)\")\n else:\n compressed_data = original_data\n\n # Step 3: Create sectors\n sectors = self.create_sectors(compressed_data, input_path)\n\n # Step 4: Encrypt and encode\n encrypted_sectors = self.encrypt_and_encode_sectors(sectors)\n self.stats['encrypted_size'] = sum(s['size'] for s in encrypted_sectors.values())\n\n # Step 5: Scatter across network\n self.scatter_sectors(encrypted_sectors)\n\n # Step 6: Simulate data loss (optional)\n if simulate_loss > 0:\n available_sectors, lost = self.simulate_data_loss(simulate_loss)\n else:\n available_sectors = self.network.get_all_sectors()\n\n # Step 7: Recover and reconstruct\n reconstructed_compressed = self.recover_and_reconstruct(available_sectors)\n\n # Step 8: Decompress\n if self.config.get('compression', True):\n self.log(\"Decompressing...\")\n reconstructed_data = self.decompress_data(reconstructed_compressed)\n else:\n reconstructed_data = reconstructed_compressed\n\n # Step 9: Verify\n success = self.verify_integrity(reconstructed_data, checksum)\n\n # Step 10: Save\n if success:\n self.save_file(reconstructed_data, output_path)\n\n # Calculate statistics\n self.stats['processing_time'] = time.time() - start_time\n\n # Print summary\n print(\"\\n\" + \"=\"*70)\n print(\"📊 PROCESSING SUMMARY\")\n print(\"=\"*70)\n print(f\"Original size: {self.stats['original_size']:,} bytes\")\n print(f\"Compressed size: {self.stats['compressed_size']:,} bytes\")\n print(f\"Total sectors: {self.stats['total_sectors']:,}\")\n print(f\"Compression ratio: {self.stats['compression_ratio']*100:.2f}%\")\n print(f\"Processing time: {self.stats['processing_time']:.3f} seconds\")\n if self.stats['processing_time'] > 0:\n throughput = self.stats['original_size'] / self.stats['processing_time'] / 1024 / 1024\n print(f\"Throughput: {throughput:.2f} MB/s\")\n print(\"=\"*70)\n\n if success:\n print(\"✅ PROCESSING COMPLETE - SUCCESS!\")\n else:\n print(\"❌ PROCESSING COMPLETE - FAILED!\")\n print(\"=\"*70 + \"\\n\")\n\n return success\n\n except Exception as e:\n self.log(f\"ERROR: {str(e)}\", \"ERROR\")\n import traceback\n traceback.print_exc()\n return False\n\n\ndef create_test_file(filepath: str, size_kb: int = 100):\n“”“Create a test file with random data”“”\nprint(f\"Creating test file: {filepath} ({size_kb} KB)\")\n\n\n # Create JPEG-like header\n data = bytearray()\n data.extend(b'\\xFF\\xD8\\xFF\\xE0\\x00\\x10JFIF') # JPEG header\n data.extend(b'\\x00' * (size_kb * 1024 - 20)) # Fill with zeros\n data.extend(b'\\xFF\\xD9') # JPEG footer\n\n with open(filepath, 'wb') as f:\n f.write(data)\n\n print(f\"✓ Test file created\")\n\n\ndef main():\n“”“Main entry point with CLI”“”\nimport argparse\n\n\n parser = argparse.ArgumentParser(\n description='Pi-RAP: Pi-based Reconstruction & Archival Protocol',\n formatter_class=argparse.RawDescriptionHelpFormatter,\n epilog=\"\"\"\n\n\nExamples:\npython pi_rap_complete.py -i myfile.jpg\npython pi_rap_complete.py -i myfile.jpg --loss 15\npython pi_rap_complete.py -i myfile.jpg --no-compression --no-encryption\npython pi_rap_complete.py --test\n“”\"\n)\n\n\n parser.add_argument('-i', '--input', help='Input file path')\n parser.add_argument('-o', '--output', help='Output file path')\n parser.add_argument('--loss', type=float, default=0,\n help='Simulate data loss percentage (0-100)')\n parser.add_argument('--sector-size', type=int, default=50000,\n help='Sector size in bits (default: 50000)')\n parser.add_argument('--nodes', type=int, default=5,\n help='Number of network nodes (default: 5)')\n parser.add_argument('--seed', type=int, default=0,\n help='Encryption seed (default: 0)')\n parser.add_argument('--no-compression', action='store_true',\n help='Disable compression')\n parser.add_argument('--no-encryption', action='store_true',\n help='Disable encryption')\n parser.add_argument('--no-error-correction', action='store_true',\n help='Disable error correction')\n parser.add_argument('--test', action='store_true',\n help='Run with test file')\n parser.add_argument('--quiet', action='store_true',\n help='Suppress verbose output')\n\n args = parser.parse_args()\n\n # Create configuration\n config = {\n 'sector_size': args.sector_size,\n 'compression': not args.no_compression,\n 'encryption': not args.no_encryption,\n 'error_correction': not args.no_error_correction,\n 'network_nodes': args.nodes,\n 'encryption_seed': args.seed,\n 'verbose': not args.quiet\n }\n\n # Initialize system\n pirap = PiRAPFileSystem(config)\n\n # Test mode\n if args.test:\n test_file = \"test_image.jpg\"\n create_test_file(test_file, size_kb=500)\n args.input = test_file\n if not args.output:\n args.output = \"recovered_test.jpg\"\n\n # Process file\n if args.input:\n success = pirap.process_file(\n input_path=args.input,\n output_path=args.output,\n simulate_loss=args.loss\n )\n sys.exit(0 if success else 1)\n else:\n parser.print_help()\n sys.exit(1)\n\n\nif **name** == “**main** ”:\nmain()",
"title": "Can any run see if this Pi-based Reconstruction and Archival Protocol Works?"
}