Which specific scripts benefit from this skill?

This skill is specifically designed for financial trading environments, particularly scripts like monitor_dashboard.py and live_trader.py that utilize the get_symbol_signals() function.

Does this pattern handle lists of different lengths?

Yes, the implementation includes specific bounds checking (e.g., i < len(list)) to prevent IndexError crashes if some data fields like 'confidences' or 'gate_statuses' are partially missing.

How do I fix the ''list' object has no attribute 'get'' error?

This error occurs when the code assumes a data structure is a dictionary. This skill provides a pattern to extract the lists and use enumerate() to iterate by index instead of using .items() or .get().

Why use parallel lists instead of dictionaries in trading systems?

Parallel lists offer better performance during high-frequency signal generation loops, preserve strict processing order for display, and are more efficient for JSON serialization between the backend and the dashboard.

Trading Dashboard Parallel Lists Pattern

Name: Trading Dashboard Parallel Lists Pattern
Author: smith6jt-cop

bysmith6jt-cop

分析与监控

Standardizes the handling of trading signal data structured as parallel lists to prevent dashboard crashes and improve processing efficiency.

关于

This skill provides a robust implementation pattern for processing trading dashboard metrics when data is stored in parallel lists rather than dictionary keys. It resolves common runtime errors like "'list' object has no attribute 'get'" by implementing index-based iteration with safe bounds checking across symbol names, signal values, and gate statuses. It is essential for developers working on financial monitoring scripts who need to extract model metrics, process gate statuses, or retrieve individual symbol data from high-performance data structures optimized for JSON serialization.

主要功能

0 GitHub stars
Safe bounds checking for disparate list lengths
Standardized signal value processing (-1, 0, 1)
Gate status evaluation (READY, BLOCKED, HOLD)
Index-based parallel list iteration logic
High-performance symbol data retrieval by index

使用场景

Fixing 'attribute get' or 'items' errors in trading signal processing
Calculating aggregate model metrics from parallel list structures
Efficiently mapping trading symbols to their respective risk gate statuses

关于

主要功能

0 GitHub stars
Safe bounds checking for disparate list lengths
Standardized signal value processing (-1, 0, 1)
Gate status evaluation (READY, BLOCKED, HOLD)
Index-based parallel list iteration logic
High-performance symbol data retrieval by index

使用场景

Fixing 'attribute get' or 'items' errors in trading signal processing
Calculating aggregate model metrics from parallel list structures
Efficiently mapping trading symbols to their respective risk gate statuses