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)
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.