Components:
Alfred: The main utility cleanup program.
Sub-Watchdogs: Perform specific maintenance tasks.
ISL (Independent Security Layer): Monitors and manages Alfred, provides two-way communication with one-way control, and includes machine learning for error and cleanup analysis.
Secondary Watchdog: Monitors Alfred, restores previous versions, interacts with ISL, and applies machine learning insights.
import os
import tempfile
import shutil
import numpy as np
from datetime import datetime
from sklearn.ensemble import RandomForestClassifier
class Alfred:
def init(self):
self.registry_cleaner = RegistryCleaner()
self.shortcut_fixer = ShortcutFixer()
self.track_eraser = TrackEraser()
self.temp_file_cleaner = TempFileCleaner()
self.startup_boot_analyzer = StartupBootAnalyzer()
self.disk_data_repair = DiskDataRepair()
self.log = []
def run_all_tasks(self):
self.log.append(f"Run started at: {datetime.now()}")
self.registry_cleaner.clean()
self.shortcut_fixer.fix()
self.track_eraser.erase()
self.temp_file_cleaner.clean()
self.startup_boot_analyzer.analyze()
self.diskdatarepair.repair()
self.log.append(f"Run completed at: {datetime.now()}")
def audit_log(self):
return "\n".join(self.log)
class RegistryCleaner:
def clean(self):
print("Cleaning registry...")
class ShortcutFixer:
def fix(self):
print("Fixing shortcuts...")
class TrackEraser:
def erase(self):
print("Erasing tracks...")
class TempFileCleaner:
def clean(self):
print("Cleaning temporary files...")
temp_dir = tempfile.gettempdir()
try:
shutil.rmtree(temp_dir)
os.makedirs(temp_dir)
except Exception as e:
print(f"Error cleaning temp files: {e}")
class StartupBootAnalyzer:
def analyze(self):
print("Analyzing startup and boot processes...")
class DiskDataRepair:
def repair(self):
print("Repairing disk and data...")
class SecondaryWatchdog:
def init(self, alfred):
self.alfred = alfred
self.previous_state = None
def monitor(self):
print("Monitoring Alfred...")
Logic to monitor Alfred
def restore(self):
print("Restoring Alfred to previous state...")
features = self._extract_features_from_logs(logs)
prediction = self.model.predict([features])
self._handle_prediction(prediction)
def extractfeatures_from_logs(self, logs):
Placeholder: convert log text to numerical features
return np.random.rand(10) # Example features
def handleprediction(self, prediction):
if prediction == 1: # Assume 1 indicates an issue
print("Issue detected, updating Alfred...")
self.secondary_watchdog.update()
def update_model(self):
print("Updating model with new data...")
if self.data and self.labels:
self.model.fit(self.data, self.labels)
def audit_log(self):
return "\n".join(self.log)
def control_alfred(self):
print("ISL controlling Alfred...")
Logic for ISL to control Alfred
if name == "main":
alfred = Alfred()
isl = ISL(alfred)
alfred.run_all_tasks()
isl.monitor()
isl.analyze_logs()
print(alfred.audit_log())
print(isl.audit_log())
Components: Alfred: The main utility cleanup program. Sub-Watchdogs: Perform specific maintenance tasks. ISL (Independent Security Layer): Monitors and manages Alfred, provides two-way communication with one-way control, and includes machine learning for error and cleanup analysis. Secondary Watchdog: Monitors Alfred, restores previous versions, interacts with ISL, and applies machine learning insights.
import os import tempfile import shutil import numpy as np from datetime import datetime from sklearn.ensemble import RandomForestClassifier class Alfred: def init(self): self.registry_cleaner = RegistryCleaner() self.shortcut_fixer = ShortcutFixer() self.track_eraser = TrackEraser() self.temp_file_cleaner = TempFileCleaner() self.startup_boot_analyzer = StartupBootAnalyzer() self.disk_data_repair = DiskDataRepair() self.log = [] def run_all_tasks(self): self.log.append(f"Run started at: {datetime.now()}") self.registry_cleaner.clean() self.shortcut_fixer.fix() self.track_eraser.erase() self.temp_file_cleaner.clean() self.startup_boot_analyzer.analyze() self.diskdatarepair.repair() self.log.append(f"Run completed at: {datetime.now()}") def audit_log(self): return "\n".join(self.log) class RegistryCleaner: def clean(self): print("Cleaning registry...") class ShortcutFixer: def fix(self): print("Fixing shortcuts...") class TrackEraser: def erase(self): print("Erasing tracks...") class TempFileCleaner: def clean(self): print("Cleaning temporary files...") temp_dir = tempfile.gettempdir() try: shutil.rmtree(temp_dir) os.makedirs(temp_dir) except Exception as e: print(f"Error cleaning temp files: {e}") class StartupBootAnalyzer: def analyze(self): print("Analyzing startup and boot processes...") class DiskDataRepair: def repair(self): print("Repairing disk and data...") class SecondaryWatchdog: def init(self, alfred): self.alfred = alfred self.previous_state = None def monitor(self): print("Monitoring Alfred...")
Logic to monitor Alfred
def restore(self): print("Restoring Alfred to previous state...")
Logic to restore Alfred
def analyze(self): print("Analyzing Alfred's behavior...")
Logic to analyze Alfred
def update(self): print("Updating Alfred...")
Logic to update Alfred
class ISL: def init(self, alfred): self.alfred = alfred self.secondary_watchdog = SecondaryWatchdog(alfred) self.log = [] self.model = RandomForestClassifier() self.data = [] self.labels = [] def monitor(self): self.log.append(f"ISL monitoring started at: {datetime.now()}") self.secondary_watchdog.monitor() self.log.append(f"ISL monitoring completed at: {datetime.now()}") def analyze_logs(self): logs = self.alfred.audit_log() print(f"Analyzing logs: {logs}")
Placeholder: convert logs to features
features = self._extract_features_from_logs(logs) prediction = self.model.predict([features]) self._handle_prediction(prediction) def extractfeatures_from_logs(self, logs):
Placeholder: convert log text to numerical features
return np.random.rand(10) # Example features def handleprediction(self, prediction): if prediction == 1: # Assume 1 indicates an issue print("Issue detected, updating Alfred...") self.secondary_watchdog.update() def update_model(self): print("Updating model with new data...") if self.data and self.labels: self.model.fit(self.data, self.labels) def audit_log(self): return "\n".join(self.log) def control_alfred(self): print("ISL controlling Alfred...")
Logic for ISL to control Alfred
if name == "main": alfred = Alfred() isl = ISL(alfred) alfred.run_all_tasks() isl.monitor() isl.analyze_logs() print(alfred.audit_log()) print(isl.audit_log())