{"id":45915,"date":"2023-07-05T17:09:03","date_gmt":"2023-11-26T22:27:59","guid":{"rendered":"https:\/\/www.silicloud.com\/zh\/blog\/45915-2\/"},"modified":"2024-04-30T12:08:18","modified_gmt":"2024-04-30T04:08:18","slug":"45915-2","status":"publish","type":"post","link":"https:\/\/www.silicloud.com\/zh\/blog\/45915-2\/","title":{"rendered":""},"content":{"rendered":"

\u306f\u3058\u3081\u306b<\/h1>\n

Jupyter\u30ce\u30fc\u30c8\u30d6\u30c3\u30af\u306f\u30c7\u30fc\u30bf\u5206\u6790\u3084\u79d1\u5b66\u7814\u7a76\u3067\u5e83\u304f\u4f7f\u308f\u308c\u3066\u3044\u307e\u3059\u304c\u3001\u5927\u898f\u6a21\u306a\u30d7\u30ed\u30b8\u30a7\u30af\u30c8\u3067\u306f\u3001\u591a\u6570\u306e\u30ce\u30fc\u30c8\u30d6\u30c3\u30af\u3092\u52b9\u7387\u7684\u306b\u5b9f\u884c\u30fb\u7ba1\u7406\u3059\u308b\u3053\u3068\u304c\u8ab2\u984c\u3068\u306a\u308a\u307e\u3059\u3002\u3053\u306e\u8a18\u4e8b\u3067\u306f\u3001Jupyter\u30ce\u30fc\u30c8\u30d6\u30c3\u30af\u3092\u52b9\u7387\u7684\u306b\u5b9f\u884c\u3057\u3001\u305d\u306e\u7d50\u679c\u3092\u6574\u7406\u3059\u308b\u305f\u3081\u306ePython\u30b9\u30af\u30ea\u30d7\u30c8execute.py\u3068execute_jupyter_notebook_by_papermill.py\u3092\u7d39\u4ecb\u3057\u307e\u3059\u3002Papermill\u30e9\u30a4\u30d6\u30e9\u30ea\u3092\u4f7f\u7528\u3059\u308b\u3053\u3068\u3067\u3001Jupyter\u30ce\u30fc\u30c8\u30d6\u30c3\u30af\u306b\u5f15\u6570\u3092\u4e0e\u3048\u3066\u5b9f\u884c\u3059\u308b\u3053\u3068\u304c\u53ef\u80fd\u3068\u306a\u308a\u307e\u3057\u305f\u3002\u307e\u305f\u3001\u8907\u6570\u306eJupyter\u30ce\u30fc\u30c8\u30d6\u30c3\u30af\u3092\u4e26\u5217\u5b9f\u884c\u3059\u308b\u95a2\u6570\u3082\u5b9f\u88c5\u3057\u307e\u3057\u305f\u3002<\/p>\n

\uff08\u30b9\u30af\u30ea\u30d7\u30c8\u672c\u4f53\u306f \u3053\u3061\u3089)<\/p>\n

\u306a\u304a\u3001\u672c\u8a18\u4e8b\u306e\u5185\u5bb9\u306f\u3001ChatGPT4\u3068\u306e\u5171\u540c\u4f5c\u696d\u306b\u3088\u308a\u4f5c\u6210\u3055\u308c\u307e\u3057\u305f\u3002 \u4e0b\u8a18\u306e\u6587\u7ae0\u306f\u3001ChatGPT4\u306b\u3088\u308a\u751f\u6210\u3055\u308c\u305f\u539f\u7a3f\u306b\u7b46\u8005\u304c\u82e5\u5e72\u306e\u624b\u76f4\u3057\u3092\u52a0\u3048\u308b\u3053\u3068\u3067\u4f5c\u6210\u3055\u308c\u307e\u3057\u305f\u3002<\/p>\n

execute.py\u306e\u6982\u8981<\/h1>\n

\u3053\u306e\u30b9\u30af\u30ea\u30d7\u30c8\u306f\u3001\u7279\u5b9a\u306e\u30e2\u30c7\u30eb\u3068\u89e3\u6790\u6642\u9593\u306b\u57fa\u3065\u3044\u3066\u8907\u6570\u306eJupyter\u30ce\u30fc\u30c8\u30d6\u30c3\u30af\u3092\u5b9f\u884c\u3059\u308b\u6a5f\u80fd\u3092\u63d0\u4f9b\u3057\u307e\u3059\u3002\u30d1\u30e9\u30e1\u30fc\u30bf\u306e\u8f9e\u66f8\u3092\u4f5c\u6210\u3057\u3001\u305d\u308c\u3092parallel_execute\u95a2\u6570\u306b\u6e21\u3057\u3066\u3001\u6307\u5b9a\u3055\u308c\u305f\u30ce\u30fc\u30c8\u30d6\u30c3\u30af\u3092\u5b9f\u884c\u3057\u307e\u3059\u3002\u307e\u305f\u3001\u5fc5\u8981\u306b\u5fdc\u3058\u3066\u30d5\u30a1\u30a4\u30eb\u306e\u4e0a\u66f8\u304d\u78ba\u8a8d\u3082\u884c\u3044\u307e\u3059\u3002<\/p>\n

execute_jupyter_notebook_by_papermill.py\u306e\u6982\u8981<\/h1>\n

\u3053\u306e\u30b9\u30af\u30ea\u30d7\u30c8\u306f\u3001\u6307\u5b9a\u3055\u308c\u305f\u30d1\u30e9\u30e1\u30fc\u30bf\u3092\u4f7f\u7528\u3057\u3066Jupyter\u30ce\u30fc\u30c8\u30d6\u30c3\u30af\u3092\u5b9f\u884c\u3059\u308bexecute_notebook\u95a2\u6570\u3068\u3001\u3053\u308c\u3092\u4e26\u5217\u306b\u5b9f\u884c\u3059\u308bparallel_execute\u95a2\u6570\u3092\u542b\u3093\u3067\u3044\u307e\u3059\u3002\u307e\u305f\u3001\u5b9f\u884c\u3055\u308c\u305f\u30ce\u30fc\u30c8\u30d6\u30c3\u30af\u306e\u60c5\u5831\u3092README.md\u30d5\u30a1\u30a4\u30eb\u306b\u81ea\u52d5\u7684\u306b\u8ffd\u52a0\u3059\u308bappend_to_readme\u95a2\u6570\u3082\u63d0\u4f9b\u3057\u307e\u3059\u3002<\/p>\n

\u30b9\u30af\u30ea\u30d7\u30c8\u306e\u4f7f\u7528\u65b9\u6cd5<\/h1>\n

execute.py: \u30ea\u30dd\u30b8\u30c8\u30ea\u306e\u30d1\u30b9\u3092\u8a2d\u5b9a\u3057\u3001\u5b9f\u884c\u3057\u305f\u3044\u30ce\u30fc\u30c8\u30d6\u30c3\u30af\u306e\u540d\u524d\u3001\u30e2\u30c7\u30eb\u3001\u89e3\u6790\u6642\u9593\u3092\u6307\u5b9a\u3057\u3066\u5b9f\u884c\u3057\u307e\u3059\u3002<\/p>\n

execute_jupyter_notebook_by_papermill.py: \u4e26\u5217\u5b9f\u884c\u306e\u6700\u5927\u30ef\u30fc\u30ab\u30fc\u6570\u3092\u8a2d\u5b9a\u3057\u3001\u5404\u30ce\u30fc\u30c8\u30d6\u30c3\u30af\u306b\u6e21\u3059\u30d1\u30e9\u30e1\u30fc\u30bf\u306e\u8f9e\u66f8\u3092\u4f5c\u6210\u3057\u307e\u3059\u3002\u4e0a\u66f8\u304d\u78ba\u8a8d\u6a5f\u80fd\u3082\u542b\u307e\u308c\u3066\u3044\u307e\u3059\u3002<\/p>\n

\u95a2\u6570\u306e\u8a73\u7d30<\/h1>\n

\u4ee5\u4e0b\u306b\u3001\u8a18\u4e8b\u3067\u7d39\u4ecb\u3059\u308b\u4e3b\u8981\u306a\u95a2\u6570\u306e\u8a73\u7d30\u3092\u8a18\u8f09\u3057\u307e\u3059\u3002<\/p>\n

1. run_notebooks\u95a2\u6570\uff08execute.py\u5185\uff09<\/h2>\n

\u76ee\u7684: \u8907\u6570\u306e\u30e2\u30c7\u30eb\u3068\u89e3\u6790\u6642\u9593\u306b\u57fa\u3065\u3044\u3066\u3001\u6307\u5b9a\u3055\u308c\u305fJupyter\u30ce\u30fc\u30c8\u30d6\u30c3\u30af\u3092\u5b9f\u884c\u3057\u307e\u3059\u3002\u3053\u306e\u95a2\u6570\u3060\u3051\u30b9\u30af\u30ea\u30d7\u30c8\u304c\u5206\u304b\u308c\u3066\u3044\u308b\u306e\u306f\u3001Jupyter\u30ce\u30fc\u30c8\u30d6\u30c3\u30af\u306b\u4e0e\u3048\u308b\u5f15\u6570\u304c\u5897\u3048\u305f\u5834\u5408\u306b\u3001run_notebooks\u95a2\u6570\u3092\u4fee\u6b63\u3059\u308b\u5fc5\u8981\u304c\u3042\u308b\u304b\u3089\u3067\u3059\u3002<\/p>\n

\u6a5f\u80fd: \u30e2\u30c7\u30eb\u3068\u89e3\u6790\u6642\u9593\u306e\u7d44\u307f\u5408\u308f\u305b\u3054\u3068\u306b\u30d1\u30e9\u30e1\u30fc\u30bf\u8f9e\u66f8\u3092\u4f5c\u6210\u3057\u3001parallel_execute\u95a2\u6570\u3092\u547c\u3073\u51fa\u3057\u3066\u30ce\u30fc\u30c8\u30d6\u30c3\u30af\u3092\u5b9f\u884c\u3057\u307e\u3059\u3002<\/p>\n

\u30d1\u30e9\u30e1\u30fc\u30bf:<\/p>\n

notebook_name: \u5b9f\u884c\u3059\u308b\u30ce\u30fc\u30c8\u30d6\u30c3\u30af\u306e\u540d\u524d\u3002<\/p>\n

models: \u5b9f\u884c\u3059\u308b\u30e2\u30c7\u30eb\u306e\u30ea\u30b9\u30c8\u3002<\/p>\n

analysis_times: \u89e3\u6790\u6642\u9593\uff08\u30aa\u30d7\u30b7\u30e7\u30f3\uff09\u3002\u6307\u5b9a\u3055\u308c\u3066\u3044\u306a\u3044\u5834\u5408\u3001\u30e2\u30c7\u30eb\u306e\u307f\u3067\u5b9f\u884c\u3055\u308c\u307e\u3059\u3002<\/p>\n

check_overwrite: \u65e2\u5b58\u306e\u30d5\u30a1\u30a4\u30eb\u3092\u4e0a\u66f8\u304d\u3059\u308b\u304b\u3069\u3046\u304b\u306e\u78ba\u8a8d\u3092\u884c\u3046\u304b\u3069\u3046\u304b\uff08\u30d6\u30fc\u30eb\u5024\uff09\u3002<\/p>\n

2. execute_notebook\u95a2\u6570\uff08execute_jupyter_notebook_by_papermill.py\u5185\uff09<\/h2>\n

\u76ee\u7684: \u6307\u5b9a\u3055\u308c\u305f\u30d1\u30e9\u30e1\u30fc\u30bf\u3092\u4f7f\u7528\u3057\u3066\u5358\u4e00\u306eJupyter\u30ce\u30fc\u30c8\u30d6\u30c3\u30af\u3092\u5b9f\u884c\u3057\u3001\u7d50\u679c\u3092\u6307\u5b9a\u3057\u305f\u540d\u524d\u306e\u30d5\u30a1\u30a4\u30eb\u306b\u4fdd\u5b58\u3057\u307e\u3059\u3002\u3053\u308c\u306b\u3088\u308a\u3001\u5b9f\u884c\u3059\u308b\u30ce\u30fc\u30c8\u30d6\u30c3\u30af\u3068\u7d50\u679c\u3092\u4fdd\u5b58\u3059\u308b\u30ce\u30fc\u30c8\u30d6\u30c3\u30af\u306e\u540d\u524d\u3092\u72ec\u7acb\u3057\u3066\u6307\u5b9a\u3067\u304d\u3001\u3088\u308a\u67d4\u8edf\u306a\u30d5\u30a1\u30a4\u30eb\u7ba1\u7406\u304c\u53ef\u80fd\u306b\u306a\u308a\u307e\u3059\u3002<\/p>\n

\u6a5f\u80fd: Papermill\u3092\u4f7f\u7528\u3057\u3066\u30ce\u30fc\u30c8\u30d6\u30c3\u30af\u3092\u5b9f\u884c\u3057\u3001\u5b9f\u884c\u5f8c\u306bappend_to_readme\u95a2\u6570\u3092\u547c\u3073\u51fa\u3057\u3066README.md\u306b\u5b9f\u884c\u60c5\u5831\u3092\u8a18\u9332\u3057\u307e\u3059\u3002<\/p>\n

\u30d1\u30e9\u30e1\u30fc\u30bf:<\/p>\n

notebook_name: \u5b9f\u884c\u3059\u308b\u30ce\u30fc\u30c8\u30d6\u30c3\u30af\u306e\u540d\u524d\u3002<\/p>\n

input_dir: \u5165\u529b\u30ce\u30fc\u30c8\u30d6\u30c3\u30af\u304c\u683c\u7d0d\u3055\u308c\u3066\u3044\u308b\u30c7\u30a3\u30ec\u30af\u30c8\u30ea\u3002<\/p>\n

output_dir: \u51fa\u529b\u30ce\u30fc\u30c8\u30d6\u30c3\u30af\u3092\u4fdd\u5b58\u3059\u308b\u30c7\u30a3\u30ec\u30af\u30c8\u30ea\u3002<\/p>\n

params: \u30ce\u30fc\u30c8\u30d6\u30c3\u30af\u306b\u6e21\u3059\u30d1\u30e9\u30e1\u30fc\u30bf\u306e\u8f9e\u66f8\u3002<\/p>\n

3. parallel_execute\u95a2\u6570\uff08execute_jupyter_notebook_by_papermill.py\u5185\uff09<\/h2>\n

\u76ee\u7684: \u8907\u6570\u306e\u30ce\u30fc\u30c8\u30d6\u30c3\u30af\u3092\u4e26\u5217\u306b\u5b9f\u884c\u3057\u307e\u3059\u3002<\/p>\n

\u6a5f\u80fd: \u5404\u30ce\u30fc\u30c8\u30d6\u30c3\u30af\u306e\u5b9f\u884c\u30bf\u30b9\u30af\u3092\u975e\u540c\u671f\u7684\u306b\u51e6\u7406\u3057\u3001\u5fc5\u8981\u306b\u5fdc\u3058\u3066\u30d5\u30a1\u30a4\u30eb\u306e\u4e0a\u66f8\u304d\u78ba\u8a8d\u3092\u884c\u3044\u307e\u3059\u3002<\/p>\n

\u30d1\u30e9\u30e1\u30fc\u30bf:<\/p>\n

notebook_name: \u5b9f\u884c\u3059\u308b\u30ce\u30fc\u30c8\u30d6\u30c3\u30af\u306e\u540d\u524d\u3002<\/p>\n

input_dir: \u5165\u529b\u30ce\u30fc\u30c8\u30d6\u30c3\u30af\u304c\u683c\u7d0d\u3055\u308c\u3066\u3044\u308b\u30c7\u30a3\u30ec\u30af\u30c8\u30ea\u3002<\/p>\n

output_dir: \u51fa\u529b\u30ce\u30fc\u30c8\u30d6\u30c3\u30af\u3092\u4fdd\u5b58\u3059\u308b\u30c7\u30a3\u30ec\u30af\u30c8\u30ea\u3002<\/p>\n

params_dict: \u5404\u30ce\u30fc\u30c8\u30d6\u30c3\u30af\u306b\u6e21\u3059\u30d1\u30e9\u30e1\u30fc\u30bf\u306e\u8f9e\u66f8\u3002<\/p>\n

max_workers: \u4e26\u5217\u5b9f\u884c\u306e\u6700\u5927\u30ef\u30fc\u30ab\u30fc\u6570\u3002<\/p>\n

check_overwrite: \u65e2\u5b58\u306e\u30d5\u30a1\u30a4\u30eb\u3092\u4e0a\u66f8\u304d\u3059\u308b\u304b\u3069\u3046\u304b\u306e\u78ba\u8a8d\u3092\u884c\u3046\u304b\u3069\u3046\u304b\uff08\u30d6\u30fc\u30eb\u5024\uff09\u3002<\/p>\n

4. append_to_readme\u95a2\u6570\uff08execute_jupyter_notebook_by_papermill.py\u5185\uff09<\/h2>\n

\u76ee\u7684: \u5b9f\u884c\u3055\u308c\u305f\u30ce\u30fc\u30c8\u30d6\u30c3\u30af\u306e\u60c5\u5831\u3092README.md\u30d5\u30a1\u30a4\u30eb\u306b\u8ffd\u8a18\u3057\u307e\u3059\u3002<\/p>\n

\u6a5f\u80fd: \u5b9f\u884c\u3055\u308c\u305f\u30ce\u30fc\u30c8\u30d6\u30c3\u30af\u306e\u540d\u524d\u3001\u30d1\u30e9\u30e1\u30fc\u30bf\u3001\u51fa\u529b\u30d1\u30b9\u306a\u3069\u306e\u60c5\u5831\u3092\u30d5\u30a9\u30fc\u30de\u30c3\u30c8\u3057\u3066README.md\u306b\u8ffd\u52a0\u3057\u307e\u3059\u3002<\/p>\n

\u30d1\u30e9\u30e1\u30fc\u30bf:<\/p>\n

notebook_name: \u5b9f\u884c\u3055\u308c\u305f\u30ce\u30fc\u30c8\u30d6\u30c3\u30af\u306e\u540d\u524d\u3002<\/p>\n

params: \u30ce\u30fc\u30c8\u30d6\u30c3\u30af\u306b\u6e21\u3055\u308c\u305f\u30d1\u30e9\u30e1\u30fc\u30bf\u3002<\/p>\n

output_path: \u51fa\u529b\u3055\u308c\u305f\u30ce\u30fc\u30c8\u30d6\u30c3\u30af\u306e\u30d1\u30b9\u3002<\/p>\n

readme_path: README\u30d5\u30a1\u30a4\u30eb\u306e\u30d1\u30b9\u3002<\/p>\n

\u307e\u3068\u3081<\/h1>\n

\u3053\u308c\u3089\u306e\u95a2\u6570\u3092\u4f7f\u7528\u3059\u308b\u3053\u3068\u3067\u3001\u5927\u898f\u6a21\u306a\u30c7\u30fc\u30bf\u5206\u6790\u30d7\u30ed\u30b8\u30a7\u30af\u30c8\u306b\u304a\u3044\u3066\u3001Jupyter\u30ce\u30fc\u30c8\u30d6\u30c3\u30af\u306e\u5b9f\u884c\u3068\u7d50\u679c\u306e\u7ba1\u7406\u3092\u52b9\u7387\u7684\u306b\u884c\u3046\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002\u7279\u306b\u3001\u8907\u6570\u306e\u30ce\u30fc\u30c8\u30d6\u30c3\u30af\u3092\u4e26\u5217\u306b\u5b9f\u884c\u3059\u308b\u3053\u3068\u3067\u3001\u6642\u9593\u3092\u7bc0\u7d04\u3057\u3001\u30d7\u30ed\u30b8\u30a7\u30af\u30c8\u306e\u9032\u6357\u3092\u52a0\u901f\u3059\u308b\u3053\u3068\u304c\u53ef\u80fd\u3067\u3059\u3002\u307e\u305f\u3001README.md\u3078\u306e\u81ea\u52d5\u7684\u306a\u8a18\u9332\u306b\u3088\u308a\u3001\u5b9f\u884c\u3055\u308c\u305f\u30ce\u30fc\u30c8\u30d6\u30c3\u30af\u306e\u6982\u8981\u3092\u7c21\u5358\u306b\u78ba\u8a8d\u3067\u304d\u307e\u3059\u3002<\/p>\n

\u88dc\u8db3<\/h1>\n

\u30b9\u30af\u30ea\u30d7\u30c8\u306e\u4f7f\u7528\u306b\u306fPapermill\u30e9\u30a4\u30d6\u30e9\u30ea\u304c\u5fc5\u8981\u3067\u3059\u3002\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u306b\u3064\u3044\u3066\u306f\u3001Papermill\u516c\u5f0f\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u3092\u53c2\u7167\u3057\u3066\u304f\u3060\u3055\u3044\u3002<\/p>\n

\u30b9\u30af\u30ea\u30d7\u30c8<\/h1>\n
import<\/span> os<\/span>\r\nimport<\/span> datetime<\/span>\r\nimport<\/span> papermill<\/span> as<\/span> pm<\/span>\r\nfrom<\/span> concurrent.futures<\/span> import<\/span> ThreadPoolExecutor<\/span>\r\n\r\ndef<\/span> execute_notebook<\/span>(<\/span>notebook_name<\/span>,<\/span> input_dir<\/span>,<\/span> output_name<\/span>,<\/span> output_dir<\/span>,<\/span> params<\/span>):<\/span>\r\n    \"\"\"<\/span>\r\n    Execute a Jupyter notebook with specified parameters.\r\n\r\n    :param notebook_name: Name of the notebook to execute.\r\n    :param input_dir: Directory containing the input notebook.\r\n    :param output_name: Name for the output notebook.\r\n    :param output_dir: Directory to save the output notebook.\r\n    :param params: Dictionary of parameters to pass to the notebook.\r\n    <\/span>\"\"\"<\/span>\r\n    input_notebook<\/span> =<\/span> f<\/span>\"<\/span>{<\/span>input_dir<\/span>}<\/span>\/<\/span>{<\/span>notebook_name<\/span>}<\/span>.ipynb<\/span>\"<\/span>\r\n    output_notebook<\/span> =<\/span> f<\/span>\"<\/span>{<\/span>output_dir<\/span>}<\/span>\/<\/span>{<\/span>output_name<\/span>}<\/span>.ipynb<\/span>\"<\/span>\r\n\r\n    pm<\/span>.<\/span>execute_notebook<\/span>(<\/span>\r\n        input_notebook<\/span>,<\/span>\r\n        output_notebook<\/span>,<\/span>\r\n        parameters<\/span>=<\/span>params<\/span>\r\n    )<\/span>\r\n\r\n    if<\/span> notebook_name<\/span>:<\/span>\r\n            append_to_readme<\/span>(<\/span>output_name<\/span>,<\/span> params<\/span>,<\/span> \r\n                             output_path<\/span>=<\/span>f<\/span>\"<\/span>.\/<\/span>{<\/span>output_name<\/span>}<\/span>.ipynb<\/span>\"<\/span>,<\/span> \r\n                             readme_path<\/span>=<\/span>f<\/span>\"<\/span>{<\/span>output_dir<\/span>}<\/span>\/README.md<\/span>\"<\/span>)<\/span>\r\n\r\n\r\ndef<\/span> parallel_execute<\/span>(<\/span>notebook_name<\/span>,<\/span> input_dir<\/span>,<\/span> output_dir<\/span>,<\/span> params_dict<\/span>,<\/span> max_workers<\/span>=<\/span>4<\/span>,<\/span> check_overwrite<\/span>=<\/span>True<\/span>):<\/span>\r\n    \"\"\"<\/span>\r\n    Execute notebooks in parallel based on the provided parameters dictionary.\r\n\r\n    :param notebook_name: Name of the notebook to execute.\r\n    :param input_dir: Directory containing the input notebooks.\r\n    :param output_dir: Directory to save the output notebooks.\r\n    :param params_dict: Dictionary of parameters for each execution.\r\n    :param max_workers: Maximum number of parallel workers.\r\n    <\/span>\"\"\"<\/span>\r\n    with<\/span> ThreadPoolExecutor<\/span>(<\/span>max_workers<\/span>=<\/span>max_workers<\/span>)<\/span> as<\/span> executor<\/span>:<\/span>\r\n        futures<\/span> =<\/span> []<\/span>\r\n\r\n        for<\/span> key<\/span>,<\/span> params<\/span> in<\/span> params_dict<\/span>.<\/span>items<\/span>():<\/span>\r\n            output_name<\/span> =<\/span> f<\/span>\"<\/span>{<\/span>notebook_name<\/span>}<\/span>_<\/span>{<\/span>key<\/span>}<\/span>\"<\/span>\r\n            output_path<\/span> =<\/span> f<\/span>\"<\/span>{<\/span>output_dir<\/span>}<\/span>\/<\/span>{<\/span>output_name<\/span>}<\/span>.ipynb<\/span>\"<\/span>\r\n            \r\n            if<\/span> os<\/span>.<\/span>path<\/span>.<\/span>exists<\/span>(<\/span>output_path<\/span>)<\/span> and<\/span> check_overwrite<\/span>:<\/span>\r\n                response<\/span> =<\/span> input<\/span>(<\/span>f<\/span>\"<\/span>{<\/span>output_path<\/span>}<\/span> already exists. Overwrite? (y\/n): <\/span>\"<\/span>)<\/span>\r\n                if<\/span> response<\/span>.<\/span>lower<\/span>()<\/span> !=<\/span> '<\/span>y<\/span>'<\/span>:<\/span>\r\n                    print<\/span>(<\/span>f<\/span>\"<\/span>Skipping <\/span>{<\/span>output_path<\/span>}<\/span>\"<\/span>)<\/span>\r\n                    continue<\/span>\r\n\r\n            print<\/span>(<\/span>f<\/span>\"<\/span>Executing <\/span>{<\/span>notebook_name<\/span>}<\/span>.ipynb for <\/span>{<\/span>key<\/span>}<\/span>\"<\/span>)<\/span>\r\n            future<\/span> =<\/span> executor<\/span>.<\/span>submit<\/span>(<\/span>execute_notebook<\/span>,<\/span> notebook_name<\/span>,<\/span> input_dir<\/span>,<\/span> \r\n                                     output_name<\/span>,<\/span> output_dir<\/span>,<\/span> params<\/span>)<\/span>\r\n            futures<\/span>.<\/span>append<\/span>(<\/span>future<\/span>)<\/span>\r\n\r\n        for<\/span> future<\/span> in<\/span> futures<\/span>:<\/span>\r\n            future<\/span>.<\/span>result<\/span>()<\/span>\r\n\r\ndef<\/span> append_to_readme<\/span>(<\/span>notebook_name<\/span>,<\/span> params<\/span>,<\/span> output_path<\/span>,<\/span> readme_path<\/span>=<\/span>\"<\/span>README.md<\/span>\"<\/span>):<\/span>\r\n    \"\"\"<\/span>\r\n    Append executed notebook information to a README.md file.\r\n\r\n    :param notebook_name: Name of the executed notebook.\r\n    :param params: Parameters passed to the notebook.\r\n    :param output_path: Path to the output notebook.\r\n    :param readme_path: Path to the README file.\r\n    <\/span>\"\"\"<\/span>\r\n    with<\/span> open<\/span>(<\/span>readme_path<\/span>,<\/span> \"<\/span>a<\/span>\"<\/span>)<\/span> as<\/span> file<\/span>:<\/span>\r\n        timestamp<\/span> =<\/span> datetime<\/span>.<\/span>datetime<\/span>.<\/span>now<\/span>().<\/span>strftime<\/span>(<\/span>\"<\/span>%Y-%m-%d %H:%M:%S<\/span>\"<\/span>)<\/span>\r\n        file<\/span>.<\/span>write<\/span>(<\/span>f<\/span>\"<\/span>## <\/span>{<\/span>timestamp<\/span>}<\/span> - <\/span>{<\/span>notebook_name<\/span>}<\/span>.ipynb <\/span>\\n<\/span>\"<\/span>)<\/span>\r\n        file<\/span>.<\/span>write<\/span>(<\/span>f<\/span>\"<\/span>### Parameters<\/span>\\n<\/span>\"<\/span>)<\/span>\r\n        for<\/span> key<\/span>,<\/span> value<\/span> in<\/span> params<\/span>.<\/span>items<\/span>():<\/span>\r\n            file<\/span>.<\/span>write<\/span>(<\/span>f<\/span>\"<\/span>- **<\/span>{<\/span>key<\/span>}<\/span>**: <\/span>{<\/span>value<\/span>}<\/span>\\n<\/span>\"<\/span>)<\/span>\r\n        file<\/span>.<\/span>write<\/span>(<\/span>f<\/span>\"<\/span>### Output Notebook<\/span>\\n<\/span>\"<\/span>)<\/span>\r\n        file<\/span>.<\/span>write<\/span>(<\/span>f<\/span>\"<\/span>- [Link](<\/span>{<\/span>output_path<\/span>}<\/span>)<\/span>\\n\\n<\/span>\"<\/span>)<\/span>\r\n<\/code><\/pre>\n
from<\/span> execute_jupyter_notebook_by_papermill<\/span> import<\/span> parallel_execute<\/span>\r\n\r\n# Repository and directories setup\r\n<\/span>path_for_repo<\/span> =<\/span> \"<\/span>path_to_your_working_directory<\/span>\"<\/span>\r\nparent_dir<\/span> =<\/span> f<\/span>\"<\/span>{<\/span>path_for_repo<\/span>}<\/span>\/notebooks<\/span>\"<\/span>\r\nexploratory_dir<\/span> =<\/span> f<\/span>\"<\/span>{<\/span>parent_dir<\/span>}<\/span>\/exploratory<\/span>\"<\/span>\r\nreport_dir<\/span> =<\/span> f<\/span>\"<\/span>{<\/span>parent_dir<\/span>}<\/span>\/report<\/span>\"<\/span>\r\n\r\n\r\n# Function to run notebooks for given models and analysis times\r\n<\/span>def<\/span> run_notebooks<\/span>(<\/span>notebook_name<\/span>,<\/span> models<\/span>,<\/span> analysis_times<\/span>=<\/span>None<\/span>,<\/span> check_overwrite<\/span>=<\/span>True<\/span>):<\/span>\r\n    params_dict<\/span> =<\/span> {}<\/span>\r\n    if<\/span> analysis_times<\/span>:<\/span>\r\n        for<\/span> model<\/span> in<\/span> models<\/span>:<\/span>\r\n            for<\/span> analysis_time<\/span> in<\/span> analysis_times<\/span>:<\/span>\r\n                params_dict<\/span>[<\/span>f<\/span>\"<\/span>{<\/span>model<\/span>}<\/span>_<\/span>{<\/span>analysis_time<\/span>}<\/span>\"<\/span>]<\/span> =<\/span> {<\/span>\r\n                    \"<\/span>model<\/span>\"<\/span>:<\/span> model<\/span>,<\/span>\r\n                    \"<\/span>analysis_time<\/span>\"<\/span>:<\/span> analysis_time<\/span>\r\n                }<\/span>\r\n    else<\/span>:<\/span>\r\n        for<\/span> model<\/span> in<\/span> models<\/span>:<\/span>\r\n            params_dict<\/span>[<\/span>model<\/span>]<\/span> =<\/span> {<\/span>\"<\/span>model<\/span>\"<\/span>:<\/span> model<\/span>}<\/span>\r\n\r\n    parallel_execute<\/span>(<\/span>notebook_name<\/span>,<\/span> exploratory_dir<\/span>,<\/span> report_dir<\/span>,<\/span> params_dict<\/span>,<\/span> check_overwrite<\/span>=<\/span>check_overwrite<\/span>)<\/span>\r\n\r\n# Models and Analysis Times\r\n<\/span>models<\/span> =<\/span> [<\/span>\"<\/span>model1<\/span>\"<\/span>,<\/span> \"<\/span>model2<\/span>\"<\/span>]<\/span>\r\nanalysis_times<\/span> =<\/span> [<\/span>\"<\/span>annual<\/span>\"<\/span>,<\/span> \"<\/span>seasonal<\/span>\"<\/span>]<\/span>\r\n\r\n# Executing Notebooks\r\n<\/span>run_notebooks<\/span>(<\/span>\"<\/span>notebook1<\/span>\"<\/span>,<\/span> models<\/span>,<\/span> analysis_times<\/span>,<\/span> check_overwrite<\/span>=<\/span>False<\/span>)<\/span>\r\nrun_notebooks<\/span>(<\/span>\"<\/span>notebook2<\/span>\"<\/span>,<\/span> models<\/span>,<\/span> check_overwrite<\/span>=<\/span>True<\/span>)<\/span>\r\n<\/code><\/pre>\n","protected":false},"excerpt":{"rendered":"
\u306f\u3058\u3081\u306b Jupyter\u30ce\u30fc\u30c8\u30d6\u30c3\u30af\u306f\u30c7\u30fc\u30bf\u5206\u6790\u3084\u79d1\u5b66\u7814\u7a76\u3067\u5e83\u304f\u4f7f\u308f\u308c\u3066\u3044\u307e\u3059\u304c\u3001\u5927\u898f\u6a21\u306a\u30d7\u30ed\u30b8\u30a7\u30af\u30c8\u3067\u306f\u3001\u591a […]<\/p>\n","protected":false},"author":8,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-45915","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"yoast_head":"\n- Blog - Silicon Cloud<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.silicloud.com\/zh\/blog\/45915-2\/\" \/>\n<meta property=\"og:locale\" content=\"zh_CN\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:description\" content=\"\u306f\u3058\u3081\u306b Jupyter\u30ce\u30fc\u30c8\u30d6\u30c3\u30af\u306f\u30c7\u30fc\u30bf\u5206\u6790\u3084\u79d1\u5b66\u7814\u7a76\u3067\u5e83\u304f\u4f7f\u308f\u308c\u3066\u3044\u307e\u3059\u304c\u3001\u5927\u898f\u6a21\u306a\u30d7\u30ed\u30b8\u30a7\u30af\u30c8\u3067\u306f\u3001\u591a […]\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.silicloud.com\/zh\/blog\/45915-2\/\" \/>\n<meta property=\"og:site_name\" content=\"Blog - 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