Python Tutorial: Diving into buckets

Key Takeaways

in the last lesson we learned about different EWS services in how to create our first bottle 3 client now let's dive into cloud storage with AWS s3 s3 lets us put any file in the cloud and make it accessible anywhere in the world through our URL managing cloud storage is a key component of data pipelines many services we will learn will depend on an object being uploaded to s3 the main components of s3 are buckets and objects buckets are like folders on our desktop objects are like files within those folders but there's a lot of power hidden underneath buckets have their own permissions policies they can be configured to act as folders for a static website they can generate logs about their own activity and write them to a different bucket the most important thing that buckets do they contain objects an object can be anything an image a video file CSV or a log file there are plenty of operations we can do with objects but for now let's focus on what we can do with buckets what can we do with buckets using pots of three we can create a bucket list buckets that we have in our account and we can delete a bucket we can only store objects in buckets so knowing how to work with buckets is a crucial component of s3 knowledge let's dive into some buckets let's start off by making a new bucket called GID requests we create a Botto three client that lets us interact with AWS s3 then we call the clients create bucket method passing the bucket name as the argument tada we have a shiny new bucket we can see it in the console as well keep in mind that bucket names have to be unique across all of us three otherwise we will get an error when trying to create one now that we can create a bucket let's get a list of all the buckets we have in s3 once again we create a Botto 3 s3 client then we call the list buckets method on the client when s3 responds it will give us some additional response metadata but it will include a dictionary under the buckets key let's get that dictionary and print it out we can see our new bucket name and the time that it was created now that we have this dictionary we can run it through a for loop and perform an operation on multiple buckets let's say we don't need the G ad requests bucket anymore let's delete it once again we create the Botto 3s3 client then we call the delete bucket method alas our bucket is gone if we try to delete it and it didn't exist we would have gotten an error it's nowhere to be found in the console either we will learn more operations on buckets as we get further in the course but we won't learn them all get in the habit of reading bottle three documentation for all the methods we can do on an Amazon Web service in this lesson we learned about how to work with a key component of s3 buckets we learned that buckets contain objects how to create buckets how to list buckets and how to delete buckets we also learned that there are more operations that we can read about in the bottom three docs now we're ready to dive into buckets let's