Fix orchestration saga failure due to missing pandas dependency
Root cause analysis: - The orchestration saga was failing at the 'fetch_shared_data_snapshot' step - Lines 350-356 had a logic error: tried to import pandas in exception handler after pandas import already failed - This caused an uncaught exception that propagated up and failed the entire saga The fix: - Replaced pandas DataFrame placeholder with a simple dict for traffic_predictions - Since traffic predictions are marked as "not yet implemented", pandas is not needed yet - This eliminates the pandas dependency from the orchestrator service - When traffic predictions are implemented in Phase 5, the dict can be converted to DataFrame Impact: - Orchestration saga will no longer fail due to missing pandas - AI enhancement warning will still appear (requires separate fix to add pandas to requirements if needed) - Traffic predictions placeholder now uses empty dict instead of empty DataFrame
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@@ -344,16 +344,10 @@ class OrchestrationSaga:
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context['event_calendar'] = []
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# NEW: Placeholder for traffic predictions (Phase 5)
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try:
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# Note: Implement traffic forecasting in Phase 5
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# For now, initialize as empty DataFrame
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import pandas as pd
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context['traffic_predictions'] = pd.DataFrame()
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logger.info("Traffic predictions: not yet implemented, using empty DataFrame")
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except Exception as e:
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logger.warning(f"Could not fetch traffic predictions: {e}")
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import pandas as pd
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context['traffic_predictions'] = pd.DataFrame()
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# Note: Implement traffic forecasting in Phase 5
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# For now, initialize as empty dict (will be converted to DataFrame when implemented)
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context['traffic_predictions'] = {}
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logger.info("Traffic predictions: not yet implemented, using empty dict")
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logger.info(
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f"Shared data snapshot fetched successfully: "
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