用 boto3从 S3 bucket 读取文件内容

小开

最佳答案

boto3 offers a resource model that makes tasks like iterating through objects easier. Unfortunately, StreamingBody doesn't provide readline or readlines.

s3 = boto3.resource('s3')
bucket = s3.Bucket('test-bucket')
# Iterates through all the objects, doing the pagination for you. Each obj
# is an ObjectSummary, so it doesn't contain the body. You'll need to call
# get to get the whole body.
for obj in bucket.objects.all():
key = obj.key
body = obj.get()['Body'].read()

小开

When you want to read a file with a different configuration than the default one, feel free to use either mpu.aws.s3_read(s3path) directly or the copy-pasted code:

def s3_read(source, profile_name=None):
"""
Read a file from an S3 source.


Parameters
----------
source : str
Path starting with s3://, e.g. 's3://bucket-name/key/foo.bar'
profile_name : str, optional
AWS profile


Returns
-------
content : bytes


botocore.exceptions.NoCredentialsError
Botocore is not able to find your credentials. Either specify
profile_name or add the environment variables AWS_ACCESS_KEY_ID,
AWS_SECRET_ACCESS_KEY and AWS_SESSION_TOKEN.
See https://boto3.readthedocs.io/en/latest/guide/configuration.html
"""
session = boto3.Session(profile_name=profile_name)
s3 = session.client('s3')
bucket_name, key = mpu.aws._s3_path_split(source)
s3_object = s3.get_object(Bucket=bucket_name, Key=key)
body = s3_object['Body']
return body.read()

小开

You might consider the smart_open module, which supports iterators:

from smart_open import smart_open


# stream lines from an S3 object
for line in smart_open('s3://mybucket/mykey.txt', 'rb'):
print(line.decode('utf8'))

and context managers:

with smart_open('s3://mybucket/mykey.txt', 'rb') as s3_source:
for line in s3_source:
print(line.decode('utf8'))


s3_source.seek(0)  # seek to the beginning
b1000 = s3_source.read(1000)  # read 1000 bytes

Find smart_open at https://pypi.org/project/smart_open/

小开

If you already know the filename, you can use the boto3 builtin download_fileobj

import boto3


from io import BytesIO


session = boto3.Session()
s3_client = session.client("s3")


f = BytesIO()
s3_client.download_fileobj("bucket_name", "filename", f)
print(f.getvalue())

小开

Using the client instead of resource:

s3 = boto3.client('s3')
bucket='bucket_name'
result = s3.list_objects(Bucket = bucket, Prefix='/something/')
for o in result.get('Contents'):
data = s3.get_object(Bucket=bucket, Key=o.get('Key'))
contents = data['Body'].read()
print(contents.decode("utf-8"))

小开

the best way for me is this:

result = s3.list_objects(Bucket = s3_bucket, Prefix=s3_key)
for file in result.get('Contents'):
data = s3.get_object(Bucket=s3_bucket, Key=file.get('Key'))
contents = data['Body'].read()
#if Float types are not supported with dynamodb; use Decimal types instead
j = json.loads(contents, parse_float=Decimal)
for item in j:
timestamp = item['timestamp']


table.put_item(
Item={
'timestamp': timestamp
}
)

once you have the content you can run it through another loop to write it to a dynamodb table for instance ...

小开

import boto3

print("started")

s3 = boto3.resource('s3',region_name='region_name', aws_access_key_id='your_access_id', aws_secret_access_key='your access key')

obj = s3.Object('bucket_name','file_name')

data=obj.get()['Body'].read()

print(data)

小开

This is the correct and tested code to access the file contents using boto3 from the s3 bucket. It is working for me till the date of posting.

def get_file_contents(bucket, prefix):
s3 = boto3.resource('s3')
s3.meta.client.meta.events.register('choose-signer.s3.*', disable_signing)
bucket = s3.Bucket(bucket)
for obj in bucket.objects.filter(Prefix=prefix):
key = obj.key
body = obj.get()['Body'].read()
print(body)
return body


get_file_contents('coderbytechallengesandbox', '__cb__')

小开

An alternative to boto3 in this particular case is s3fs.

from s3fs import S3FileSystem
s3 = S3FileSystem()
bucket = 's3://your-bucket'


def read_file(key):
with s3.open(f'{s3_path}/{key}', 'r') as file:  # s3://bucket/file.txt
return file.readlines()


for obj in bucket.objects.all():
key = obj.key
lines = read_file(key)
...