一个简单易用的Python性能跟踪和可视化工具
A simple performance tracking and visualization tool for Python applications
pip install tikTrack- 使用装饰器轻松跟踪函数执行时间 (Track function execution time easily with decorators)
- 自动生成性能报告和可视化图表 (Automatically generate performance reports and visualization charts)
- 支持多种输出格式：CSV报表和饼图 (Support for multiple output formats: CSV reports and pie charts)
- 程序退出时自动生成报告 (Automatically generate reports when the program exits)
- 聚合相同阶段的执行时间 (Aggregate execution times for the same stages)
- 支持中文字体显示 (Support for Chinese fonts in charts)
from tiktrack import timed_stage
@timed_stage("数据加载")
def load_data():
# 模拟数据加载过程
import time
time.sleep(1)
return "data"
@timed_stage("数据处理")
def process_data(data):
# 模拟数据处理过程
import time
time.sleep(0.5)
return f"processed {data}"
def main():
data = load_data()
processed_data = process_data(data)
print(processed_data)
if __name__ == "__main__":
main()
# 程序退出时会自动生成性能报告from tiktrack import timed_stage, set_default_output_dir
# 设置性能报告输出目录
set_default_output_dir("my_performance_reports")
@timed_stage("任务1")
def task1():
import time
time.sleep(0.8)
@timed_stage("任务2")
def task2():
import time
time.sleep(1.2)
def main():
task1()
task2()
if __name__ == "__main__":
main()from tiktrack import timed_stage, generate_performance_report
@timed_stage("任务A")
def task_a():
import time
time.sleep(0.5)
@timed_stage("任务B")
def task_b():
import time
time.sleep(0.7)
def main():
for i in range(3):
task_a()
task_b()
# 手动生成性能报告
generate_performance_report("custom_reports")
if __name__ == "__main__":
main()执行代码后，将生成以下文件：
performance_report.csv- 详细的每次函数调用性能数据performance_summary.csv- 按阶段聚合的性能摘要数据performance_chart.png- 性能分布饼图
欢迎贡献！请随时提交问题或拉取请求。 Contributions are welcome! Feel free to submit issues or pull requests.