32 lines
1.0 KiB
Python
32 lines
1.0 KiB
Python
import json, hashlib
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class ListCompressor:
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def __init__(self):
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self.model = {}
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def save_model(self, file_name):
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with open(file_name, 'w') as f:
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json.dump(self.model, f)
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print(f"\nModel Is Saved In {file_name}")
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def load_model(self, model_data):
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if isinstance(model_data, str):
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with open(model_data, 'r') as f:
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model_data = json.load(f)
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self.model = model_data
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def train_model(self, label, data):
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if label not in self.model:
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self.model[label] = []
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for lst in data:
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self.model[label].append(hashlib.md5(''.join(map(str, lst)).encode()).hexdigest()[:8])
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def predict(self, new_list):
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for label, items in self.model.items():
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if label != 'word' and hashlib.md5(''.join(map(str, new_list)).encode()).hexdigest()[:8] in items:
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return True
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return False
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def get_label(self):
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return list(self.model.keys())[0]
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