How to save S3 object to a file using boto3


I’m trying to do a “hello world” with new boto3 client for AWS.

The use-case I have is fairly simple: get object from S3 and save it to the file.

In boto 2.X I would do it like this:

import boto
key = boto.connect_s3().get_bucket('foo').get_key('foo')

In boto 3 . I can’t find a clean way to do the same thing, so I’m manually iterating over the “Streaming” object:

import boto3
key = boto3.resource('s3').Object('fooo', 'docker/my-image.tar.gz').get()
with open('/tmp/my-image.tar.gz', 'w') as f:
    chunk = key['Body'].read(1024*8)
    while chunk:
        chunk = key['Body'].read(1024*8)


import boto3
key = boto3.resource('s3').Object('fooo', 'docker/my-image.tar.gz').get()
with open('/tmp/my-image.tar.gz', 'w') as f:
    for chunk in iter(lambda: key['Body'].read(4096), b''):

And it works fine. I was wondering is there any “native” boto3 function that will do the same task?

Asked By: Vor



There is a customization that went into Boto3 recently which helps with this (among other things). It is currently exposed on the low-level S3 client, and can be used like this:

s3_client = boto3.client('s3')
open('hello.txt').write('Hello, world!')

# Upload the file to S3
s3_client.upload_file('hello.txt', 'MyBucket', 'hello-remote.txt')

# Download the file from S3
s3_client.download_file('MyBucket', 'hello-remote.txt', 'hello2.txt')

These functions will automatically handle reading/writing files as well as doing multipart uploads in parallel for large files.

Note that s3_client.download_file won’t create a directory. It can be created as pathlib.Path('/path/to/file.txt').parent.mkdir(parents=True, exist_ok=True).

Answered By: Daniel

boto3 now has a nicer interface than the client:

resource = boto3.resource('s3')
my_bucket = resource.Bucket('MyBucket')
my_bucket.download_file(key, local_filename)

This by itself isn’t tremendously better than the client in the accepted answer (although the docs say that it does a better job retrying uploads and downloads on failure) but considering that resources are generally more ergonomic (for example, the s3 bucket and object resources are nicer than the client methods) this does allow you to stay at the resource layer without having to drop down.

Resources generally can be created in the same way as clients, and they take all or most of the same arguments and just forward them to their internal clients.

Answered By: quodlibetor

For those of you who would like to simulate the set_contents_from_string like boto2 methods, you can try

import boto3
from cStringIO import StringIO

s3c = boto3.client('s3')
contents = 'My string to save to S3 object'
target_bucket = ''
target_file = 'data/hello.txt'
fake_handle = StringIO(contents)

# notice if you do it reads like a file handle
s3c.put_object(Bucket=target_bucket, Key=target_file,

For Python3:

In python3 both StringIO and cStringIO are gone. Use the StringIO import like:

from io import StringIO

To support both version:

   from StringIO import StringIO
except ImportError:
   from io import StringIO
Answered By: cgseller
# Preface: File is json with contents: {'name': 'Android', 'status': 'ERROR'}

import boto3
import io

s3 = boto3.resource('s3')

obj = s3.Object('my-bucket', 'key-to-file.json')
data = io.BytesIO()

# object is now a bytes string, Converting it to a dict:
new_dict = json.loads(data.getvalue().decode("utf-8"))

# Should print "Error"
Answered By: Lord Sumner

Note: I’m assuming you have configured authentication separately. Below code is to download the single object from the S3 bucket.

import boto3

#initiate s3 client 
s3 = boto3.resource('s3')

#Download object to the file    
s3.Bucket('mybucket').download_file('hello.txt', '/tmp/hello.txt')
Answered By: Tushar Niras

When you want to read a file with a different configuration than the default one, feel free to use either, destination) directly or the copy-pasted code:

def s3_download(source, destination,
    Copy a file from an S3 source to a local destination.

    source : str
        Path starting with s3://, e.g. 's3://bucket-name/key/'
    destination : str
    exists_strategy : {'raise', 'replace', 'abort'}
        What is done when the destination already exists?
    profile_name : str, optional
        AWS profile

        Botocore is not able to find your credentials. Either specify
        profile_name or add the environment variables AWS_ACCESS_KEY_ID,
    exists_strategies = ['raise', 'replace', 'abort']
    if exists_strategy not in exists_strategies:
        raise ValueError('exists_strategy '{}' is not in {}'
                         .format(exists_strategy, exists_strategies))
    session = boto3.Session(profile_name=profile_name)
    s3 = session.resource('s3')
    bucket_name, key = _s3_path_split(source)
    if os.path.isfile(destination):
        if exists_strategy is 'raise':
            raise RuntimeError('File '{}' already exists.'
        elif exists_strategy is 'abort':
    s3.Bucket(bucket_name).download_file(key, destination)

from collections import namedtuple

S3Path = namedtuple("S3Path", ["bucket_name", "key"])

def _s3_path_split(s3_path):
    Split an S3 path into bucket and key.

    s3_path : str

    splitted : (str, str)
        (bucket, key)

    >>> _s3_path_split('s3://my-bucket/foo/bar.jpg')
    S3Path(bucket_name='my-bucket', key='foo/bar.jpg')
    if not s3_path.startswith("s3://"):
        raise ValueError(
            "s3_path is expected to start with 's3://', " "but was {}"
    bucket_key = s3_path[len("s3://"):]
    bucket_name, key = bucket_key.split("/", 1)
    return S3Path(bucket_name, key)
Answered By: Martin Thoma

If you wish to download a version of a file, you need to use get_object.

import boto3

bucket = 'bucketName'
prefix = 'path/to/file/'
filename = 'fileName.ext'

s3c = boto3.client('s3')
s3r = boto3.resource('s3')

if __name__ == '__main__':
    for version in s3r.Bucket(bucket).object_versions.filter(Prefix=prefix + filename):
        file = version.get()
        version_id = file.get('VersionId')
        obj = s3c.get_object(
            Key=prefix + filename,
        with open(f"{filename}.{version_id}", 'wb') as f:
            for chunk in obj['Body'].iter_chunks(chunk_size=4096):


Answered By: Christian