ai_performance_profiler
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| ai_performance_profiler [2025/05/29 03:20] – [Workflow] eagleeyenebula | ai_performance_profiler [2025/05/29 03:21] (current) – [Key Features] eagleeyenebula | ||
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| ===== Key Features ===== | ===== Key Features ===== | ||
| - | 1. **Execution Time Profiling | + | 1. **Execution Time Profiling **(profile_stage)**** |
| * Dynamically analyze the time spent by functions or code blocks. | * Dynamically analyze the time spent by functions or code blocks. | ||
| * Logs all execution times to a log file for a clear historical performance record. | * Logs all execution times to a log file for a clear historical performance record. | ||
| - | 2. **Caching | + | 2. **Caching **(cache_step)**** |
| * Built-in caching system to store computationally expensive function results. | * Built-in caching system to store computationally expensive function results. | ||
| * Uses **functools.lru_cache** with a configurable cache size for efficient memory utilization. | * Uses **functools.lru_cache** with a configurable cache size for efficient memory utilization. | ||
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| 1. **Initialization: | 1. **Initialization: | ||
| - | * Instantiate the PerformanceProfiler class. Optionally specify the log file's name. | + | * Instantiate the **PerformanceProfiler** class. Optionally specify the log file's name. |
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ai_performance_profiler.1748488802.txt.gz · Last modified: 2025/05/29 03:20 by eagleeyenebula