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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=" ", 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=" ", low_memory=False)
returns
TypeError: initial_value must be str or None, not StreamingBody
pd.read_csv(io.BytesIO(file), header=14, delimiter=" ", 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=" ", low_memory=False)
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Warsaw | 2023-03-24
Simply put and clear. Thank you for sharing. How to import a text file on AWS S3 into pandas without writing to disk and other issues with StackOverflow was always my weak point 😁. Will get back tomorrow with feedback
California | 2023-03-24
Thanks for explaining! I was stuck with How to import a text file on AWS S3 into pandas without writing to disk for some hours, finally got it done 🤗. Checked yesterday, it works!
Boston | 2023-03-24
Thanks for explaining! I was stuck with How to import a text file on AWS S3 into pandas without writing to disk for some hours, finally got it done 🤗. Will get back tomorrow with feedback