TimezoneFinder Initialization Performance Benchmark

System Status

Python Environment

Python Version: 3.14.2 (CPython)

NumPy Version: 2.3.5

Platform: Darwin arm64

Processor: arm

TimezoneFinder Configuration

C Implementation Available: False

Numba JIT Available: True

Performance Optimizations

✗ Using pure Python point-in-polygon implementation
✓ Numba JIT compilation enabled

Benchmark Configuration

Test Runs Per Configuration: 100

Algorithm Type: Class Initialization

Test Configurations: TimezoneFinder and TimezoneFinderL with file-based and in-memory modes

Initialization Performance Results

Configuration	Average Time (ms)	Average Time (s)
TimezoneFinder (File-Based)	216.9	0.217
TimezoneFinder (In-Memory)	225.0	0.225
TimezoneFinderL (File-Based)	212.8	0.213
TimezoneFinderL (In-Memory)	210.4	0.210

Performance Analysis

Fastest configuration: TimezoneFinderL (In-Memory) (210.4 ms)
Slowest configuration: TimezoneFinder (In-Memory) (225.0 ms)
Performance difference: 6% faster
File-based mode is 1% faster (214.9 ms vs 217.7 ms)

Note

Initialization times may vary based on system I/O performance, available memory, and background system activity. In-memory mode loads all data into RAM during initialization, while file-based mode opens files but defers data loading.