Finally the File I/O API in the Amazon.S3.IO namespace gives the ability to use filesystem semantics with S3. For easy uploads and downloads, there is TransferUtility, which is found in the Amazon.S3.Transfer namespace. content_type = res.get('ContentType', 'application/json')ĭata = res.read(). The low-level API found in the Amazon.S3 and Amazon.S3.Model namespaces provides complete coverage of the S3 APIs. Else, we just return the object data as plaintext. Step 1 Create a REST API Gateway with required resource & method. SAM Template to create RestApi with multipart enabled. Here we simply check the content type of the object, and if it's JSON then we load it and return the data as a Python list or dict type. So let’s go step by step on how to achieve this. """upload a file (usually a JSON file) to S3"""įile_name, bucket, key or file_name, )Ī similar snippet of code when I'm downloading a file from S3 (generally a JSON file). Upload a message into the created bucket as a text file. def upload(self, file_name, bucket, key=None, content_type='application/json'): Create a S3 bucket (a location for storing your data) in Amazon cloud. The self.client is a cached property which is equivalent to boto3.client('s3') in your code above only I have cached it for reusability, as it's a bit faster when making multiple requests to same bucket, like to read a uploaded file and then re-upload it. Here is a snippet of code I am using internally for uploading files (generally JSON) to S3.
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