我正在嘗試使用Python API將文件從筆記本本身內的Datalab實例上傳到我的Google存儲桶，但我無法弄清楚。Google在其文檔中提供的代碼示例似乎不適用于Datalab。我目前正在使用gsutil命令，但想了解如何在使用Python API時執行此操作。文件目錄（我想上傳位于檢查點文件夾中的python文件）：!ls -R.:checkpoints README.md tpot_model.ipynb./checkpoints:pipeline_2020.02.29_00-22-17.py pipeline_2020.02.29_06-33-25.pypipeline_2020.02.29_00-58-04.py pipeline_2020.02.29_07-13-35.pypipeline_2020.02.29_02-00-52.py pipeline_2020.02.29_08-45-23.pypipeline_2020.02.29_02-31-57.py pipeline_2020.02.29_09-16-41.pypipeline_2020.02.29_03-02-51.py pipeline_2020.02.29_11-13-00.pypipeline_2020.02.29_05-01-17.py當前代碼：import google.datalab.storage as storagefrom pathlib import Pathbucket = storage.Bucket('machine_learning_data_bucket')for file in Path('').rglob('*.py'): # API CODE GOES HERE當前工作解決方案：!gsutil cp checkpoints/*.py gs://machine_learning_data_bucket
1 回答
藍山帝景
TA貢獻1843條經驗 獲得超7個贊
這是為我工作的代碼：
from google.cloud import storage
from pathlib import Path
storage_client = storage.Client()
bucket = storage_client.bucket('bucket')
for file in Path('/home/jupyter/folder').rglob('*.py'):
blob = bucket.blob(file.name)
blob.upload_from_filename(str(file))
print("File {} uploaded to {}.".format(file.name,bucket.name))
輸出：
File file1.py uploaded to bucket.
File file2.py uploaded to bucket.
File file3.py uploaded to bucket.
編輯
或者，您可以使用：
import google.datalab.storage as storage
from pathlib import Path
bucket = storage.Bucket('bucket')
for file in Path('/home/jupyter/folder').rglob('*.py'):
blob = bucket.object(file.name)
blob.write_stream(file.read_text(), 'text/plain')
print("File {} uploaded to {}.".format(file.name,bucket.name))
輸出：
File file1.py uploaded to bucket.
File file2.py uploaded to bucket.
File file3.py uploaded to bucket.
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