Develop Reference

How to get object from MinIO response?

I am using python API to save and download model from MinIO. This is a MinIO installed on my server. The data is in binary format.
a = 'Hello world!'
a = pickle.dumps(a)
client.put_object(
bucket_name='my_bucket',
object_name='my_object',
data=io.BytesIO(a),
length=len(a)
)
I can see object saved through command line :
mc cat origin/my_bucket/my_object
Hello world!
However, when i try to get it through Python API :
response = client.get_object(
bucket_name = 'my_bucket',
object_name= 'my_object'
)
response is a urllib3.response.HTTPResponse object here.
I am trying to read it as :
response.read()
b''
I get a blank binary string. How can I read this object? It won't be possible for me to know its length at the time of reading it.
and here is response.__dict__ :
{'headers': HTTPHeaderDict({'Accept-Ranges': 'bytes', 'Content-Length': '27', 'Content-Security-Policy': 'block-all-mixed-content', 'Content-Type': 'application/octet-stream', 'ETag': '"75687-1"', 'Last-Modified': 'Fri, 16 Jul 2021 14:47:35 GMT', 'Server': 'MinIO/DEENT.T', 'Vary': 'Origin', 'X-Amz-Request-Id': '16924CCA35CD', 'X-Xss-Protection': '1; mode=block', 'Date': 'Fri, 16 Jul 2021 14:47:36 GMT'}), 'status': 200, 'version': 11, 'reason': 'OK', 'strict': 0, 'decode_content': True, 'retries': Retry(total=5, connect=None, read=None, redirect=None, status=None), 'enforce_content_length': False, 'auto_close': True, '_decoder': None, '_body': None, '_fp': <http.client.HTTPResponse object at 01e50>, '_original_response': <http.client.HTTPResponse object at 0x7e50>, '_fp_bytes_read': 0, 'msg': None, '_request_url': None, '_pool': <urllib3.connectionpool.HTTPConnectionPool object at 0x790>, '_connection': None, 'chunked': False, 'chunk_left': None, 'length_remaining': 27}

Try with response.data.decode()

The response is a urllib3.response.HTTPResponse object.
See urllib3 Documentation:
Backwards-compatible with http.client.HTTPResponse but the response body is loaded and decoded on-demand when the data property is accessed.
Specifically, you should read the answer like this:
response.data # len(response.data)
Or, if you want to stream the object, you have examples on the minio-py repository: examples/get_objects.

Why does Cloud Tasks gives "Deadline Exceeded" error after 60s?

I'm using google-cloud-tasks==2.2.0 with Flask Gunicorn. This is how I send a task to a queue:
def send_task(payload, queue, uri, *args):
url = f'https://www.mywebsite.com/{uri}'
payload = json.dumps(payload)
payload = payload.encode()
parent = client.queue_path(project=project, location=location, queue=queue)
service_account_email = 'myaccount.com'
# Construct the request body.
td = '1800s'
duration = duration_pb2.Duration()
time = duration.FromJsonString(td)
now = datetime.utcnow() + timedelta(seconds=10)
ts = timestamp_pb2.Timestamp()
now = ts.FromDatetime(now)
task = {
'http_request': { # Specify the type of request.
'http_method': tasks_v2beta3.HttpMethod.POST,
'url': url,
'body': payload, # Convert dictionary to string
'headers': { # Add custom header
'Content-Type': 'application/json'
},
'oidc_token': {'service_account_email': service_account_email}
}
}
task['schedule_time'] = now
task['dispatch_deadline'] = time
response = client.create_task(request={"parent": parent, "task": task}, timeout=30.0)
I use dispatch_deadline which is supposed to support 30 minutes timeout, using this API reference.
But no matter how I try, my task fails after 60 seconds with 504 DEADLINE_EXCEEDED error.
Honestly, is this something necessary I'm missing here, or is it a bug?

aws python lambda: reading csv file (iterator should return strings)

I'm getting this message when I'm trying to test my python 3.8 lambda function:
Logs are:
soc-connect
contacts.csv
{'ResponseMetadata': {'RequestId': '9D7D7F0C5CB79984', 'HostId': 'wOd6HvIm+BpLOMKF2beRvqLiW0NQt5mK/kzjCjYxQ2kHQZY0MRCtGs3l/rqo4o0r4xAPuV1QpGM=', 'HTTPStatusCode': 200, 'HTTPHeaders': {'x-amz-id-2': 'wOd6HvIm+BpLOMKF2beRvqLiW0NQt5mK/kzjCjYxQ2kHQZY0MRCtGs3l/rqo4o0r4xAPuV1QpGM=', 'x-amz-request-id': '9D7D7F0C5CB79984', 'date': 'Thu, 26 Mar 2020 11:21:35 GMT', 'last-modified': 'Tue, 24 Mar 2020 16:07:30 GMT', 'etag': '"8a3785e750475af3ca25fa7eab159dab"', 'accept-ranges': 'bytes', 'content-type': 'text/csv', 'content-length': '52522', 'server': 'AmazonS3'}, 'RetryAttempts': 0}, 'AcceptRanges': 'bytes', 'LastModified': datetime.datetime(2020, 3, 24, 16, 7, 30, tzinfo=tzutc()), 'ContentLength': 52522, 'ETag': '"8a3785e750475af3ca25fa7eab159dab"', 'ContentType': 'text/csv', 'Metadata': {}, 'Body': <botocore.response.StreamingBody object at 0x7f858dc1e6d0>}
1153
<_csv.reader object at 0x7f858ea76970>
[ERROR] Error: iterator should return strings, not bytes (did you open the file in text mode?)
The code snippet is:
import boto3
import csv
def digest_csv(bucket_name, key_name):
# Let's use Amazon S3
s3 = boto3.client('s3');
print(bucket_name)
print(key_name)
s3_object = s3.get_object(Bucket=bucket_name, Key=key_name)
print(s3_object)
# read the contents of the file and split it into a list of lines
lines = s3_object['Body'].read().splitlines(True)
print(len(lines))
contacts = csv.reader(lines, delimiter=';')
print(contacts)
# now iterate over those contacts
for contact in contacts:
# here you get a sequence of dicts
# do whatever you want with each line here
print('-*-'.join(contact))
I think the problem is on csv.reader.
I'm setting first parameter an array of lines... Should it be modified?
Any ideas?

Instead of using the csv.reader the following worked for me (adjusted for your delimiter and variables):
for line in lines:
contact = ''.join(line.decode().split(';'))
print(contact)

Boto3 Cloudtrail returns no events for a resource

I am trying to get events like (runinstances,createtags & terminateinstances) from cloudtrail for a instance id through boto3, below is my code
import boto3
cloudtrail = boto3.client('cloudtrail')
instance_id = 'i-0002e660b987688'
starttime = '2020-04-01'
endtime = '2020-04-03'
try:
response = cloudtrail.lookup_events(
LookupAttributes=[
{
'AttributeKey': 'ResourceName',
'AttributeValue': instance_id
},
],
StartTime=starttime,
EndTime=endtime,
MaxResults=50
)
except Exception as e:
print(e)
raise(e)
print(response)
I am not getting any events , where as from AWS console I can see all those events for the time period specified above.
{u'Events': [], 'ResponseMetadata': {'RetryAttempts': 0,
'HTTPStatusCode': 200, 'RequestId': '658e4873-b0d1-453c',
'HTTPHeaders': {'x-amzn-requestid': '658e4873-b0d1-453', 'date': 'Fri,
03 Apr 2020 03:53:57 GMT', 'content-length': '13', 'content-type':
'application/x-amz-json-1.1'}}}

Seems like removing endtime worked for me , not sure why though.
I can able to get the desired events now.
try:
response = cloudtrail.lookup_events(
LookupAttributes=[
{
'AttributeKey': 'ResourceName',
'AttributeValue': instance_id
},
],
StartTime=starttime,
#EndTime=endtime,
MaxResults=50
)
except Exception as e:
print(e)
raise(e)
print(response)

AWS S3 image saving loses metadata

I am working with an AWS Lambda function written in python 2.7x which downloads, saves to /tmp , then uploads the image file back to bucket.
My image meta data starts out in original bucket with http headers like Content-Type= image/jpeg, and others.
After saving my image with PIL, all headers are gone and I am left with Content-Type = binary/octet-stream
From what I can tell, image.save is loosing the headers due to the way PIL works. How do I either preserve metadata or at least apply it to the new saved image?
I have seen post suggesting that this metadata is in exif but I tried to get exif info from original file and apply to saved file with no luck. I am not clear of it's in exif data anyway.
Partial code to give idea of what I am doing:
def resize_image(image_path):
with Image.open(image_path) as image:
image.save(upload_path, optimize=True)
def handler(event, context):
global upload_path
for record in event['Records']:
bucket = record['s3']['bucket']['name']
key = urllib.unquote_plus(event['Records'][0]['s3']['object']['key'].encode("utf8"))
download_path = '/tmp/{}{}'.format(uuid.uuid4(), file_name)
upload_path = '/tmp/resized-{}'.format(file_name)
s3_client.download_file(bucket, key, download_path)
resize_image(download_path)
s3_client.upload_file(upload_path, '{}resized'.format(bucket), key)
Thanks to Sergey, I changed to using get_object but response is missing Metadata:
response = s3_client.get_object(Bucket=bucket,Key=key)
response= {u'Body': , u'AcceptRanges': 'bytes', u'ContentType': 'image/jpeg', 'ResponseMetadata': {'HTTPStatusCode': 200, 'RetryAttempts': 0, 'HostId': 'au30hBMN37/ti0WCfDqlb3t9ehainumc9onVYWgu+CsrHtvG0u/zmgcOIvCCBKZgQrGoooZoW9o=', 'RequestId': '1A94D7F01914A787', 'HTTPHeaders': {'content-length': '84053', 'x-amz-id-2': 'au30hBMN37/ti0WCfDqlb3t9ehainumc9onVYWgu+CsrHtvG0u/zmgcOIvCCBKZgQrGoooZoW9o=', 'accept-ranges': 'bytes', 'expires': 'Sun, 01 Jan 2034 00:00:00 GMT', 'server': 'AmazonS3', 'last-modified': 'Fri, 23 Dec 2016 15:21:56 GMT', 'x-amz-request-id': '1A94D7F01914A787', 'etag': '"9ba59e5457da0dc40357f2b53715619d"', 'cache-control': 'max-age=2592000,public', 'date': 'Fri, 23 Dec 2016 15:21:58 GMT', 'content-type': 'image/jpeg'}}, u'LastModified': datetime.datetime(2016, 12, 23, 15, 21, 56, tzinfo=tzutc()), u'ContentLength': 84053, u'Expires': datetime.datetime(2034, 1, 1, 0, 0, tzinfo=tzutc()), u'ETag': '"9ba59e5457da0dc40357f2b53715619d"', u'CacheControl': 'max-age=2592000,public', u'Metadata': {}}
If I use:
metadata = response['ResponseMetadata']['HTTPHeaders']
metadata = {'content-length': '84053', 'x-amz-id-2': 'f5UAhWzx7lulo3cMVF8hdVRbHnhdnjHWRDl+LDFkYm9pubjL0A01L5yWjgDjWRE4TjRnjqDeA0U=', 'accept-ranges': 'bytes', 'expires': 'Sun, 01 Jan 2034 00:00:00 GMT', 'server': 'AmazonS3', 'last-modified': 'Fri, 23 Dec 2016 15:47:09 GMT', 'x-amz-request-id': '4C69DF8A58EF3380', 'etag': '"9ba59e5457da0dc40357f2b53715619d"', 'cache-control': 'max-age=2592000,public', 'date': 'Fri, 23 Dec 2016 15:47:10 GMT', 'content-type': 'image/jpeg'}
Saving with put_object
s3_client.put_object(Bucket=bucket+'resized',Key=key, Metadata=metadata, Body=downloadfile)
creates a whole lot of extra metadata in s3 including the fact that it does not save content-type as image/jpeg but rather as binary/octet-stream and it does create metadata x-amz-meta-content-type = image/jpeg

You are confusing S3 metadata, stored by AWS S3 along with an object, and EXIF metadata, stored inside the file itself.
download_file() doesn't get object attributes from S3. You should use get_object() instead: https://boto3.readthedocs.io/en/latest/reference/services/s3.html#S3.Client.get_object
Then you can use put_objects() with the same attributes to upload new file: https://boto3.readthedocs.io/en/latest/reference/services/s3.html#S3.Client.put_object

Content type information is not on the file you upload, it has to be guessed or extracted somehow. This is something you must do manually or using tools. With a fairly small dictionary you can guess most file types.
When you upload a file or object, you have the chance to specify its content type. Otherwise S3 defaults to application/octet-stream.
Using the boto3 python package for instance:
s3client.upload_file(
Filename=local_path,
Bucket=bucket,
Key=remote_path,
ExtraArgs={
"ContentType": "image/jpeg"
}
)