CODEWITHSUNDEEP
pythoncsvamazon-s3botobuffering
inquiring minds
inquiring minds

Reputation: 1905

Can you upload to S3 using a stream rather than a local file?

I need to create a CSV and upload it to an S3 bucket. Since I'm creating the file on the fly, it would be better if I could write it directly to S3 bucket as it is being created rather than writing the whole file locally, and then uploading the file at the end.

Is there a way to do this? My project is in Python and I'm fairly new to the language. Here is what I tried so far:

import csv
import csv
import io
import boto
from boto.s3.key import Key


conn = boto.connect_s3()
bucket = conn.get_bucket('dev-vs')
k = Key(bucket)
k.key = 'foo/foobar'

fieldnames = ['first_name', 'last_name']
writer = csv.DictWriter(io.StringIO(), fieldnames=fieldnames)
k.set_contents_from_stream(writer.writeheader())

I received this error: BotoClientError: s3 does not support chunked transfer

UPDATE: I found a way to write directly to S3, but I can't find a way to clear the buffer without actually deleting the lines I already wrote. So, for example:

conn = boto.connect_s3()
bucket = conn.get_bucket('dev-vs')
k = Key(bucket)
k.key = 'foo/foobar'

testDict = [{
    "fieldA": "8",
    "fieldB": None,
    "fieldC": "888888888888"},
    {
    "fieldA": "9",
    "fieldB": None,
    "fieldC": "99999999999"}]

f = io.StringIO()
fieldnames = ['fieldA', 'fieldB', 'fieldC']
writer = csv.DictWriter(f, fieldnames=fieldnames)
writer.writeheader()
k.set_contents_from_string(f.getvalue())

for row in testDict:
    writer.writerow(row)
    k.set_contents_from_string(f.getvalue())

f.close()

Writes 3 lines to the file, however I'm unable to release memory to write a big file. If I add:

f.seek(0)
f.truncate(0)

to the loop, then only the last line of the file is written. Is there any way to release resources without deleting lines from the file?

Upvotes: 81

Views: 84362

Answers (8)

Mihir
Mihir

Reputation: 105

To upload a stream to s3 You can use Boto3 Session

r = requests.get(download_url, stream=True)
session = boto3.Session(aws_access_key_id=S3_ACCESS_KEY, aws_secret_access_key=S3_SECRET_KEY)
s3 = session.resource("s3")
bucket = s3.Bucket(UPLOAD_BUCKET_NAME)
bucket.upload_fileobj(r.raw, key)

This code can be used to call a URL which force downloads a file to get it as a stream and then upload it to s3.

Upvotes: 1

Philip Couling
Philip Couling

Reputation: 14883

There's a well supported library for doing just this:

pip install s3fs

s3fs is really trivial to use:

import s3fs

s3fs.S3FileSystem(anon=False)

with s3.open('mybucket/new-file', 'wb') as f:
    f.write(2*2**20 * b'a')
    f.write(2*2**20 * b'a')

Incidentally there's also something built into boto3 (backed by the AWS API) called MultiPartUpload.

This isn't factored as a python stream which might be an advantage for some people. Instead you can start an upload and send parts one at a time.

Upvotes: 0

Scott
Scott

Reputation: 1688

Here is a complete example using boto3

import boto3
import io

session = boto3.Session(
    aws_access_key_id="...",
    aws_secret_access_key="..."
)

s3 = session.resource("s3")

buff = io.BytesIO()

buff.write("test1\n".encode())
buff.write("test2\n".encode())

s3.Object(bucket, keypath).put(Body=buff.getvalue())

Upvotes: -1

El Ruso
El Ruso

Reputation: 15861

According to docs it's possible

s3.Object('mybucket', 'hello.txt').put(Body=open('/tmp/hello.txt', 'rb'))

so we can use StringIO in ordinary way

Update: smart_open lib from @inquiring minds answer is better solution

Upvotes: 3

Sean Saúl Astrakhan
Sean Saúl Astrakhan

Reputation: 155

We were trying to upload file contents to s3 when it came through as an InMemoryUploadedFile object in a Django request. We ended up doing the following because we didn't want to save the file locally. Hope it helps:

@action(detail=False, methods=['post'])
def upload_document(self, request):
     document = request.data.get('image').file
     s3.upload_fileobj(document, BUCKET_NAME, 
                                 DESIRED_NAME_OF_FILE_IN_S3, 
                                 ExtraArgs={"ServerSideEncryption": "aws:kms"})

Upvotes: 2

Mass Dot Net
Mass Dot Net

Reputation: 2259

There's an interesting code solution mentioned in a GitHub smart_open issue (#82) that I've been meaning to try out. Copy-pasting here for posterity... looks like boto3 is required:

csv_data = io.BytesIO()
writer = csv.writer(csv_data)
writer.writerows(my_data)

gz_stream = io.BytesIO()
with gzip.GzipFile(fileobj=gz_stream, mode="w") as gz:
    gz.write(csv_data.getvalue())
gz_stream.seek(0)

s3 = boto3.client('s3')
s3.upload_fileobj(gz_stream, bucket_name, key)

This specific example is streaming to a compressed S3 key/file, but it seems like the general approach -- using the boto3 S3 client's upload_fileobj() method in conjunction with a target stream, not a file -- should work.

Upvotes: 0

Sam
Sam

Reputation: 6132

To write a string to an S3 object, use:

s3.Object('my_bucket', 'my_file.txt').put('Hello there')

So convert the stream to string and you're there.

Upvotes: -4

inquiring minds
inquiring minds

Reputation: 1905

I did find a solution to my question, which I will post here in case anyone else is interested. I decided to do this as parts in a multipart upload. You can't stream to S3. There is also a package available that changes your streaming file over to a multipart upload which I used: Smart Open.

import smart_open
import io
import csv

testDict = [{
    "fieldA": "8",
    "fieldB": None,
    "fieldC": "888888888888"},
    {
    "fieldA": "9",
    "fieldB": None,
    "fieldC": "99999999999"}]

fieldnames = ['fieldA', 'fieldB', 'fieldC']
f = io.StringIO()
with smart_open.smart_open('s3://dev-test/bar/foo.csv', 'wb') as fout:
    writer = csv.DictWriter(f, fieldnames=fieldnames)
    writer.writeheader()
    fout.write(f.getvalue())

    for row in testDict:
        f.seek(0)
        f.truncate(0)
        writer.writerow(row)
        fout.write(f.getvalue())

f.close()

Upvotes: 58

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