Reputation: 881
I am trying to write and save a CSV file to a specific folder in s3 (exist). this is my code:
from io import BytesIO
import pandas as pd
import boto3
s3 = boto3.resource('s3')
d = {'col1': [1, 2], 'col2': [3, 4]}
df = pd.DataFrame(data=d)
csv_buffer = BytesIO()
bucket = 'bucketName/folder/'
filename = "test3.csv"
df.to_csv(csv_buffer)
content = csv_buffer.getvalue()
def to_s3(bucket,filename,content):
s3.Object(bucket,filename).put(Body=content)
to_s3(bucket,filename,content)
this is the error that I get:
Invalid bucket name "bucketName/folder/": Bucket name must match the regex "^[a-zA-Z0-9.\-_]{1,255}$"
I also tried :
bucket = bucketName/folder
and:
bucket = bucketName
key = folder/
s3.Object(bucket,key,filename).put(Body=content)
Any suggestions?
Upvotes: 6
Views: 35941
Reputation: 49
This works for me.
import os
import pandas as pd
import boto3
from io import StringIO
from dotenv import load_dotenv
load_dotenv("/path/to/.env", override=True)
def df_to_s3(df, bucket, key):
# Create a session
session = boto3.session.Session(profile_name=os.environ.get("AWS_SECRETS_PROFILE_NAME"))
aws_s3_client = session.client(
service_name="s3",
region_name=os.environ.get("AWS_SECRETS_REGION_NAME"),
)
# Create a CSV string from the DataFrame
csv_buffer = StringIO()
df.to_csv(csv_buffer, index=False)
# Put the CSV string to S3
aws_s3_client.put_object(
Body=csv_buffer.getvalue(),
Bucket=bucket,
Key=key
)
print(f'Successfully put DataFrame to {bucket}/{key}')
df = pd.DataFrame({'A': [1, 2, 3], 'B': [4, 5, 6]})
df_to_s3(df, 'bucketName/folder/', 'test3.csv')
Upvotes: 0
Reputation: 887
This should work:
bucket = bucketName
key = f"{folder}/{filename}"
csv_buffer=StringIO()
df.to_csv(csv_buffer)
content = csv_buffer.getvalue()
s3.put_object(Bucket=bucket, Body=content,Key=key)
AWS bucket names are not allowed to have slashes ("/"), which should be part of Key. AWS uses slashes to show "virtual" folders in the dashboard. Since csv is a text file I'm using StringIO instead of BytesIO
Upvotes: 2
Reputation: 91
Saving into s3 buckets can be also done with upload_file
with an existing .csv file:
import boto3
s3 = boto3.resource('s3')
bucket = 'bucket_name'
filename = 'file_name.csv'
s3.meta.client.upload_file(Filename = filename, Bucket= bucket, Key = filename)
Upvotes: 9
Reputation: 82755
This should work
def to_s3(bucket,filename, content):
client = boto3.client('s3')
k = "folder/subfolder"+filename
client.put_object(Bucket=bucket, Key=k, Body=content)
Upvotes: 3