Naturally, you need an instance variable a to hold the stack items in a Python list. Representing a stack with a Python list is a natural idea, but before reading further, it is worthwhile for you to think for a moment about how you would do so. Python List (Resizing Array) Implementation of a Stack The following API summarizes the operations: We also include a method to test whether the stack is empty. The last-in-first-out policy offered by a pushdown stack provides just the behavior that you expect.īy tradition, we name the stack insert operation push and the stack remove operation pop. You can always revisit the previous page by clicking the back button (remove it from a stack). You can keep clicking on hyperlinks to visit new pages. When you click a hyperlink, your browser displays the new page (and inserts it onto a stack). This policy is known as last-in first-out or LIFO.Ī pushdown stack (or just a stack) is a collection that is based on the last-in-first-out (LIFO) policy. The rule used for a stack is to always remove the item that has been in the collection the least amount of time. This policy is known as first-in-first-out or FIFO. But when we remove an item, which one do we choose? The rule used for a queue is to always remove the item that has been in the collection the most amount of time. When we insert an item, our intent is clear. Each is defined by two basic operations: insert a new item, and remove an item. Runs.append(executor.submit(purge_bucket, Bucket=bucket, S3Client=s3))įor run in _completed(runs):Įnd = s3.delete_bucket(Bucket=run.In this section, we introduce two closely-related data types for manipulating arbitrarily large collections of objects: the stack and the queue. Response = S3Client.list_objects_v2(Bucket=Bucket) Here's an example: cat file-of-keys | xargs -P8 -n1000 bash -c 'aws s3api delete-objects -bucket MY_BUCKET_NAME -delete "Objects=[$(printf "') I found I was able to get the most speed by deleting 1000 keys at a time using aws s3api delete-objects. Running parallel s3 rm -recursive with differing -include patterns is slightly faster but a lot of time is still spent waiting, as each process individually fetches the entire key list in order to locally perform the -include pattern matching. The excruciatingly slow option is s3 rm -recursive if you actually like waiting. But you can see Amazon's comments on request rate and performance here: And the s3 faq comments that bulk deleiton is the way to go if possible. So I'd avoid this scenario if possible.Įdit: I don't have the reputation to post more than 2 links. But both of these options needlessly complicate either your code (asynchronous code can be annoying) or your environment (you'd need a service/daemon/container/server to handle the queue. Or, you could offload the request to a queue. This would allow the deletion request to take up its own thread, and the rest of the code can execute without making a user wait. You can read a bit about how they'd work in general from this blog post or search for how to do it in the language of your choice. If not, you can look into asynchronous API calls. References to exact keys are supposed to be very quick, since S3 was designed to scale efficiently despite handling an extremely large amount of data. It also means the user will like more real time feedback about whether their file was deleted successfully or not. If so, you'll know the keys that you need to delete. Rather than initiating a task such as "purge all objects that refer to picture files" or "purge all files older than a certain date" (which I believe is easy to configure separately in S3). I'm assuming your use case involves end users specifying a number of specific files to delete at once. Just choose the method you're most comfortable with! AWS provides great information on this feature and its usage. You just need to know the objects' keys and create an HTTP request (or use an wrapper in your language of choice). Remember, each request is an HTTP (thus TCP) request. The S3 REST API can specify up to 1000 files to be deleted in a single request, which is must quicker than making individual requests. This method assumes you know the S3 object keys you want to remove (that is, it's not designed to handle something like a retention policy, files that are over a certain size, etc). AWS supports bulk deletion of up to 1000 objects per request using the S3 REST API and its various wrappers.
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