使用project-lib将csv文件保存到云对象存储的步骤如下:
- 导入所需的库和模块:from project_lib import Project
import pandas as pd
- 创建一个Project对象,并获取云对象存储的访问凭证:project = Project(None, 'xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx', 'p-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx')
cos_credentials = project.get_storage_metadata()['properties']['storage']['cos']其中,'xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx'是项目ID,'p-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx'是项目访问凭证。
- 使用pandas库读取csv文件:df = pd.read_csv('path/to/your/csv/file.csv')请确保将'path/to/your/csv/file.csv'替换为实际的csv文件路径。
- 将数据保存到云对象存储:from ibm_botocore.client import Config
import ibm_boto3
cos = ibm_boto3.client('s3',
ibm_api_key_id=cos_credentials['apikey'],
ibm_service_instance_id=cos_credentials['resource_instance_id'],
ibm_auth_endpoint=cos_credentials['iam_url'],
config=Config(signature_version='oauth'),
endpoint_url=cos_credentials['endpoints'])
bucket_name = 'your-bucket-name'
file_name = 'your-file-name.csv'
cos.upload_file(Filename='path/to/your/csv/file.csv', Bucket=bucket_name, Key=file_name)请将'your-bucket-name'替换为实际的存储桶名称,'your-file-name.csv'替换为实际的文件名。
- 完整代码示例:from project_lib import Project
import pandas as pd
from ibm_botocore.client import Config
import ibm_boto3
# 创建Project对象并获取云对象存储的访问凭证
project = Project(None, 'xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx', 'p-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx')
cos_credentials = project.get_storage_metadata()['properties']['storage']['cos']
# 读取csv文件
df = pd.read_csv('path/to/your/csv/file.csv')
# 保存数据到云对象存储
cos = ibm_boto3.client('s3',
ibm_api_key_id=cos_credentials['apikey'],
ibm_service_instance_id=cos_credentials['resource_instance_id'],
ibm_auth_endpoint=cos_credentials['iam_url'],
config=Config(signature_version='oauth'),
endpoint_url=cos_credentials['endpoints'])
bucket_name = 'your-bucket-name'
file_name = 'your-file-name.csv'
cos.upload_file(Filename='path/to/your/csv/file.csv', Bucket=bucket_name, Key=file_name)
这样,你就可以使用project-lib将csv文件保存到云对象存储了。