Pandas is a Python library that is used mainly for Data Analysis and Machine Learning.
In this tutorial, we will look at how you can download a file stored in AWS S3 using Pandas.
AWS CLI provides two different commands to interact with AWS S3. These commands are:
s3command is easier to use but supports a limited set of functionality.
s3api, on the other hand, supports all of the functionality supported by AWS S3. This article covers the differences in more details.
In this tutorial, we will look at multiple use cases where you can use
s3apito download a file from S3.
AWS Boto3’s S3 API provides two methods that can be used to upload a file to an S3 bucket. These methods are:
In this article, we will look at the differences between these methods and when to use them.
AWS S3 supports the ability to tag objects. Each tag is a key-value pair. You can associate up to 10 tags with an object.
Some of the benefits of tagging objects in S3 are:
- Categorizing your storage
- Fine-grained access control: You can grant IAM user permissions to read-only objects with specific tags
- Fine-grained lifecycle management: You can specify a tag-based filter in a lifecycle rule.
s3apisupports Object Tagging via the
put-object-taggingcommand. However, this command only supports tagging one object at a time. In this article, we will look at how you can tag all objects within a S3 bucket.
AWS S3 Versioning allows you to keep multiple variants of an object in the same bucket. Versioning helps you recover from more easily from accidental deletes or overwrites.
By default, Versioning is disabled on buckets. In this article, we will look at how to enable and suspend versioning.