Fixed Breaking Datetime change
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@@ -17,7 +17,7 @@
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import utils.pretty as ct
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import utils.pretty as ct
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#Standard Libary Imports:
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#Standard Libary Imports:
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from datetime import datetime
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import datetime
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import json
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import json
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import os
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import os
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import re
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import re
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@@ -198,22 +198,21 @@ def findAllAgents(url):
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def findAgents(url, device_input_str):
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def findAgents(url, device_input_str):
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os.makedirs("device_search", exist_ok=True)
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os.makedirs("device_search", exist_ok=True)
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# Step 1: Get the DataFrame from your function
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df = findAllAgents(url)
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df = findAllAgents(url)
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# Step 2: Parse the input string into device names (newline-separated only)
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#Parse the input string into device names (newline-separated only)
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device_names = device_input_str.strip().split('\n')
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device_names = device_input_str.strip().split('\n')
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device_names = [name.strip() for name in device_names if name.strip()]
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device_names = [name.strip() for name in device_names if name.strip()]
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# Step 3: Build a regex pattern for case-insensitive matching
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#Build a regex pattern for case-insensitive matching
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pattern = '|'.join([re.escape(name) for name in device_names])
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pattern = '|'.join([re.escape(name) for name in device_names])
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regex = re.compile(pattern, re.IGNORECASE)
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regex = re.compile(pattern, re.IGNORECASE)
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# Step 4: Filter the DataFrame using regex
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#Filter the DataFrame using regex
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matched_df = df[df['hostname'].apply(lambda x: bool(regex.search(str(x))))]
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matched_df = df[df['hostname'].apply(lambda x: bool(regex.search(str(x))))]
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# Step 5: Export to CSV with timestamp
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#Export to CSV with timestamp
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timestamp = datetime.now().strftime("%Y-%m-%d_%H-%M-%S")
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timestamp = datetime.datetime.now().strftime("%Y-%m-%d_%H-%M-%S")
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filename = f"agentsearch_{timestamp}.csv"
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filename = f"agentsearch_{timestamp}.csv"
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matched_df.to_csv(f"device_search\\{filename}", index=False)
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matched_df.to_csv(f"device_search\\{filename}", index=False)
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