import boto3

# Create an S3 client
s3 = boto3.client('s3')

# Set the name of the S3 bucket and the file key
bucket_name = 'my-bucket'
file_key = 'path/to/file.txt'

# Use the S3 client to get the object
response = s3.get_object(Bucket=bucket_name, Key=file_key)

# Extract the file content from the response
file_content = response['Body'].read()

# Print the file content
print(file_content)

import boto3

# Create an S3 client
s3 = boto3.client('s3')

# Set the name of the S3 bucket and the folder prefix
bucket_name = 'my-bucket'
folder_prefix = 'path/to/folder/'

# Use the S3 client to list the objects in the bucket
result = s3.list_objects_v2(Bucket=bucket_name, Prefix=folder_prefix)

# Extract the list of files from the response
files = [content['Key'] for content in result.get('Contents', [])]

# Print the list of files
print(files)

import logging
 
from botocore.exceptions import ClientError
import boto3
 
 
def create_bucket(bucket_name, region=None):
    """Create an S3 bucket in a specified region
    If a region is not specified, the bucket is created in the S3 default
    region (us-east-1).
    :param bucket_name: Bucket to create
    :param region: String region to create bucket in, e.g., 'us-west-2'
    :return: True if bucket created, else False
    """
 
    # Create bucket
    try:
        if region is None:
            s3_client = boto3.client('s3')
            s3_client.create_bucket(Bucket=bucket_name)
        else:
            s3_client = boto3.client('s3', region_name=region)
            location = {'LocationConstraint': region}
            s3_client.create_bucket(Bucket=bucket_name,
                                    CreateBucketConfiguration=location)
    except ClientError as e:
        logging.error(e)
        return False
    return True

import boto3
import pandas as pd
from sagemaker import get_execution_role

role = get_execution_role()
bucket='my-bucket'
data_key = 'train.csv'
data_location = 's3://{}/{}'.format(bucket, data_key)

pd.read_csv(data_location)