Ich habe eine CSV mit zwei Spalten aus Bucket S3 gelesen und den Inhalt der Datei CSV in Pandas Dataframe eingefügt.
Beispiel:
config.json
{
"credential": {
"access_key":"xxxxxx",
"secret_key":"xxxxxx"
}
,
"s3":{
"bucket":"mybucket",
"key":"csv/user.csv"
}
}
cls_config.json
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import os
import json
class cls_config(object):
def __init__(self,filename):
self.filename = filename
def getConfig(self):
fileName = os.path.join(os.path.dirname(__file__), self.filename)
with open(fileName) as f:
config = json.load(f)
return config
cls_pandas.py
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import pandas as pd
import io
class cls_pandas(object):
def __init__(self):
pass
def read(self,stream):
df = pd.read_csv(io.StringIO(stream), sep = ",")
return df
cls_s3.py
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import boto3
import json
class cls_s3(object):
def __init__(self,access_key,secret_key):
self.s3 = boto3.client('s3', aws_access_key_id=access_key, aws_secret_access_key=secret_key)
def getObject(self,bucket,key):
read_file = self.s3.get_object(Bucket=bucket, Key=key)
body = read_file['Body'].read().decode('utf-8')
return body
test.py
#!/usr/bin/env python
# -*- coding: utf-8 -*-
from cls_config import *
from cls_s3 import *
from cls_pandas import *
class test(object):
def __init__(self):
self.conf = cls_config('config.json')
def process(self):
conf = self.conf.getConfig()
bucket = conf['s3']['bucket']
key = conf['s3']['key']
access_key = conf['credential']['access_key']
secret_key = conf['credential']['secret_key']
s3 = cls_s3(access_key,secret_key)
ob = s3.getObject(bucket,key)
pa = cls_pandas()
df = pa.read(ob)
print df
if __name__ == '__main__':
test = test()
test.process()
df.to_csv('s3://mybucket/dfs/somedf.csv')
. stackoverflow.com/a/56275519/908886 für weitere Informationen.