我正在尝试从 DSX Python 笔记本将 pandas 数据帧作为 CSV 写入 Bluemix 对象存储。 我首先将数据帧保存到"本地"CSV 文件。 然后,我有一个例程,尝试将文件写入对象存储。 我收到 413 响应 - 对象太大。 该文件只有大约 3MB。 这是我的代码,基于我在这里找到的 JSON 示例:http://datascience.ibm.com/blog/working-with-object-storage-in-data-science-experience-python-edition/
import requests
def put_file(credentials, local_file_name):
"""This function writes file content to Object Storage V3 """
url1 = ''.join(['https://identity.open.softlayer.com', '/v3/auth/tokens'])
data = {'auth': {'identity': {'methods': ['password'],
'password': {'user': {'name': credentials['name'],'domain': {'id': credentials['domain']},
'password': credentials['password']}}}}}
headers = {'Content-Type': 'text/csv'}
with open(local_file_name, 'rb') as f:
resp1 = requests.post(url=url1, data=f, headers=headers)
return resp1
任何帮助或指示都非常感谢。
本教程中的这段代码片段对我来说效果很好(对于 12 MB 的文件(。
from io import BytesIO
import requests
import json
import pandas as pd
def put_file(credentials, local_file_name):
"""This functions returns a StringIO object containing
the file content from Bluemix Object Storage V3."""
f = open(local_file_name,'r')
my_data = f.read()
url1 = ''.join(['https://identity.open.softlayer.com', '/v3/auth/tokens'])
data = {'auth': {'identity': {'methods': ['password'],
'password': {'user': {'name': credentials['username'],'domain': {'id': credentials['domain_id']},
'password': credentials['password']}}}}}
headers1 = {'Content-Type': 'application/csv'}
resp1 = requests.post(url=url1, data=json.dumps(data), headers=headers1)
resp1_body = resp1.json()
for e1 in resp1_body['token']['catalog']:
if(e1['type']=='object-store'):
for e2 in e1['endpoints']:
if(e2['interface']=='public'and e2['region']=='dallas'):
url2 = ''.join([e2['url'],'/', credentials['container'], '/', local_file_name])
s_subject_token = resp1.headers['x-subject-token']
headers2 = {'X-Auth-Token': s_subject_token, 'accept': 'application/json'}
resp2 = requests.put(url=url2, headers=headers2, data = my_data )
print resp2
我使用以下命令创建了一个随机熊猫数据帧:
df = pd.DataFrame(np.random.randint(0,100,size=(1000000, 4)), columns=list('ABCD'))
保存到csv
df.to_csv('myPandasData_1000000.csv',index=False)
然后将其放入对象存储
put_file(credentials_1,'myPandasData_1000000.csv')
您可以通过单击对象存储中任何对象的insert to code -> Insert credentials
来获取credentials_1
对象。