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Testing Parallel Text Segmentation Performance in jieba

This test suite evaluates the parallel processing capabilities of the Jieba Chinese text segmentation library. It measures performance and throughput by processing text files in parallel mode while tracking execution time and segmentation accuracy.

Test Coverage Overview

The test coverage focuses on Jieba’s parallel processing functionality for Chinese text segmentation.

Tests parallel mode enablement and performance
Measures processing speed in bytes per second
Validates text segmentation output accuracy
Handles file I/O operations and content processing

Implementation Analysis

The testing approach implements a straightforward performance benchmark for parallel text processing.

Utilizes system time measurements for performance metrics
Implements file handling for input and output validation
Employs Jieba’s parallel processing mode via enable_parallel()
Calculates and reports processing speed metrics

Technical Details

Python standard libraries: sys, time
Jieba segmentation library
Command line argument handling for file input
File I/O operations for content reading and result logging
Performance timing mechanisms

Best Practices Demonstrated

The test implements essential performance testing practices for text processing applications.

Clear separation of setup, execution, and reporting phases
Proper resource handling for file operations
Performance metric calculation and logging
Modular test structure with focused functionality

fxsjy/jieba

test/parallel/test_file.py

            
import sys
import time
sys.path.append("../../")
import jieba

jieba.enable_parallel()

url = sys.argv[1]
content = open(url,"rb").read()
t1 = time.time()
words = "/ ".join(jieba.cut(content))

t2 = time.time()
tm_cost = t2-t1

log_f = open("1.log","wb")
log_f.write(words.encode('utf-8'))

print('speed %s bytes/second' % (len(content)/tm_cost))