【附代码】Jupyter 多进程调用 seaborn 并保留格式

Jupyter 多进程调用 seaborn 格式会和单进程使用不统一，本文将解决以上问题。

Jupyter 多进程的简单例子

Jupyter 中直接使用多进程可能会有诸多问题，推荐把 function 放在 .py文件里，然后在 Jupyter 中多进程调用。

文件目录

PythonProject
├─csdn_jupyter_multiprocessing
│    example_multiprocessing.ipynb
│    function.py

代码

# example_multiprocessing.ipynbfrom concurrent.futures import ProcessPoolExecutor
from tqdm import tqdm
from csdn_jupyter_multiprocessing.function import squareif __name__ == '__main__':with ProcessPoolExecutor(max_workers=2) as executor:results = list(tqdm(executor.map(square, [1, 2, 3, 4, 5]),total=5,desc="计算中",unit="任务"))print(results)

# function.pydef square(x):return x * x

运行结果

计算中: 100%|██████████| 5/5 [00:00<00:00, 92.59任务/s]
[1, 4, 9, 16, 25]

Jupyter 多进程调用 seaborn（保留格式）

核心思路是主进程中把 sns.axes_style() 传递到子进程。

文件目录

PythonProject
├─csdn_jupyter_multiprocessing
│    example_multiprocessing.ipynb
│    function.py

代码

# example_multiprocessing.ipynbfrom concurrent.futures import ProcessPoolExecutor
from tqdm import tqdm
from csdn_jupyter_multiprocessing.function import seaborn_example
import seaborn as snsif __name__ == '__main__':seaborn_style = sns.axes_style()with ProcessPoolExecutor(max_workers=2) as executor:list(tqdm(executor.map(seaborn_example, [('0.svg', seaborn_style), ('1.svg', seaborn_style)]),total=2,desc="计算中",unit="任务"))

# function.pyimport seaborn as sns
import matplotlib.pyplot as plt
import pandas as pd
import numpy as npdef seaborn_example(args):save_name, seaborn_style = argssns.set_style(seaborn_style)# 创建示例数据：模拟某产品每日销售额days = np.arange(1, 31)  # 1到30天sales = np.random.normal(loc=100, scale=15, size=30).cumsum() + 1000  # 模拟销售额趋势# 构建DataFramedata = pd.DataFrame({'Day': days,'Sales': sales})# 绘制基础线图sns.lineplot(data=data, x='Day', y='Sales')plt.savefig(save_name)plt.close()

运行结果

计算中: 100%|██████████| 2/2 [00:01<00:00,  1.66任务/s]