How to import a text file on AWS S3 into pandas without writing to disk

Question

I have a text file saved on S3 which is a tab delimited table. I want to load it into pandas but cannot save it first because I am running on a heroku server. Here is what I have so far.

import io import boto3 import os import pandas as pd  os.environ["AWS_ACCESS_KEY_ID"] = "xxxxxxxx" os.environ["AWS_SECRET_ACCESS_KEY"] = "xxxxxxxx"  s3_client = boto3.client('s3') response = s3_client.get_object(Bucket="my_bucket",Key="filename.txt") file = response["Body"]   pd.read_csv(file, header=14, delimiter="\t", low_memory=False) 

the error is

OSError: Expected file path name or file-like object, got <class 'bytes'> type 

How do I convert the response body into a format pandas will accept?

pd.read_csv(io.StringIO(file), header=14, delimiter="\t", low_memory=False)  returns  TypeError: initial_value must be str or None, not StreamingBody  pd.read_csv(io.BytesIO(file), header=14, delimiter="\t", low_memory=False)  returns  TypeError: 'StreamingBody' does not support the buffer interface 

UPDATE - Using the following worked

file = response["Body"].read() 

and

pd.read_csv(io.BytesIO(file), header=14, delimiter="\t", low_memory=False) 

Answer 1

pandas uses boto for read_csv, so you should be able to:

import boto data = pd.read_csv('s3://bucket....csv') 

If you need boto3 because you are on python3.4+, you can

import boto3 import io s3 = boto3.client('s3') obj = s3.get_object(Bucket='bucket', Key='key') df = pd.read_csv(io.BytesIO(obj['Body'].read())) 

Since version 0.20.1 pandas uses s3fs, see answer below.

Answer 2

Now pandas can handle S3 URLs. You could simply do:

import pandas as pd import s3fs  df = pd.read_csv('s3://bucket-name/file.csv') 

You need to install s3fs if you don't have it. pip install s3fs

Authentication

If your S3 bucket is private and requires authentication, you have two options:

1- Add access credentials to your ~/.aws/credentials config file

[default] aws_access_key_id=AKIAIOSFODNN7EXAMPLE aws_secret_access_key=wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY 

Or

2- Set the following environment variables with their proper values:

• aws_access_key_id
• aws_secret_access_key
• aws_session_token