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data-transport/transport/cloud/s3.py

139 lines
4.2 KiB
Python

"""
Data Transport - 1.0
Steve L. Nyemba, The Phi Technology LLC
This file is a wrapper around s3 bucket provided by AWS for reading and writing content
TODO:
- Address limitations that will properly read csv if it is stored with content type text/csv
"""
from datetime import datetime
import boto3
# from boto.s3.connection import S3Connection, OrdinaryCallingFormat
import numpy as np
import botocore
from smart_open import smart_open
import sys
import json
from io import StringIO
import pandas as pd
import json
class s3 :
"""
@TODO: Implement a search function for a file given a bucket??
"""
__template__={"access_key":None,"secret_key":None,"bucket":None,"file":None,"region":None}
def __init__(self,**args) :
"""
This function will extract a file or set of files from s3 bucket provided
@param access_key
@param secret_key
@param path location of the file
@param filter filename or filtering elements
"""
try:
self._client = boto3.client('s3',aws_access_key_id=args['access_key'],aws_secret_access_key=args['secret_key'],region_name=args['region'])
self._bucket_name = args['bucket']
self._file_name = args['file']
self._region = args['region']
except Exception as e :
print (e)
pass
def has(self,**_args):
_found = None
try:
if 'file' in _args and 'bucket' in _args:
_found = self.meta(**_args)
elif 'bucket' in _args and not 'file' in _args:
_found = self._client.list_objects(Bucket=_args['bucket'])
elif 'file' in _args and not 'bucket' in _args :
_found = self.meta(bucket=self._bucket_name,file = _args['file'])
except Exception as e:
_found = None
pass
return type(_found) == dict
def meta(self,**args):
"""
This function will return information either about the file in a given bucket
:name name of the bucket
"""
_bucket = self._bucket_name if 'bucket' not in args else args['bucket']
_file = self._file_name if 'file' not in args else args['file']
_data = self._client.get_object(Bucket=_bucket,Key=_file)
return _data['ResponseMetadata']
def close(self):
self._client.close()
class Reader(s3) :
"""
Because s3 contains buckets and files, reading becomes a tricky proposition :
- list files if file is None
- stream content if file is Not None
@TODO: support read from all buckets, think about it
"""
def __init__(self,**_args) :
super().__init__(**_args)
def _stream(self,**_args):
"""
At this point we should stream a file from a given bucket
"""
_object = self._client.get_object(Bucket=_args['bucket'],Key=_args['file'])
_stream = None
try:
_stream = _object['Body'].read()
except Exception as e:
pass
if not _stream :
return None
if _object['ContentType'] in ['text/csv'] :
return pd.read_csv(StringIO(str(_stream).replace("\\n","\n").replace("\\r","").replace("\'","")))
else:
return _stream
def read(self,**args) :
_name = self._file_name if 'file' not in args else args['file']
_bucket = args['bucket'] if 'bucket' in args else self._bucket_name
return self._stream(bucket=_bucket,file=_name)
class Writer(s3) :
"""
"""
def __init__(self,**_args) :
super().__init__(**_args)
#
#
if not self.has(bucket=self._bucket_name) :
self.make_bucket(self._bucket_name)
def make_bucket(self,bucket_name):
"""
This function will create a folder in a bucket,It is best that the bucket is organized as a namespace
:name name of the folder
"""
self._client.create_bucket(Bucket=bucket_name,CreateBucketConfiguration={'LocationConstraint': self._region})
def write(self,_data,**_args):
"""
This function will write the data to the s3 bucket, files can be either csv, or json formatted files
"""
content = 'text/plain'
if type(_data) == pd.DataFrame :
_stream = _data.to_csv(index=False)
content = 'text/csv'
elif type(_data) == dict :
_stream = json.dumps(_data)
content = 'application/json'
else:
_stream = _data
file = StringIO(_stream)
bucket = self._bucket_name if 'bucket' not in _args else _args['bucket']
file_name = self._file_name if 'file' not in _args else _args['file']
self._client.put_object(Bucket=bucket, Key = file_name, Body=_stream,ContentType=content)
pass