Now, I have realized the uploading process is like that:
1. Generate the HTTP request object, and set the value to request.FILE by using uploadhandler.
2. In the views.py, the instance of FieldFile which is the mirror of FileField will call the storage.save() to upload file.
So, as you see, django always use the cache or disk to pass the data, if your file is too large, it will cost too much time.
And the design I want to figure this problem is to custom an uploadhandler which will call storage.save() by using input raw data. The only question is how can I modify the actions of FileField?
Thanks for any help.
you can use this package
Add direct uploads to AWS S3 functionality with a progress bar to file input fields.
https://github.com/bradleyg/django-s3direct
You can use one of the following packages
https://github.com/cloudinary/pycloudinary
http://django-storages.readthedocs.io/en/latest/backends/amazon-S3.html
Related
I have a general understanding question. I am building a flutter app that relies on a content library containing text files, latex equations, images, pdfs, videos etc.
The content lies on an aws amplify backend. Depending on the navigation of the user in the app, the corresponding data is fetched and displayed.
I am not sure about the correct way of fetching the data. The current method (which works) is that the data is stored in an S3 bucket. When data is requested, the data is downloaded to a temporary directory and then opened and processed in the app. This is actually not slow, but I feel that it is not the way it should be done.
When data is downloaded a file transfer notification pops up, which bothers me because it is shown all the time. Also I would like to read the data directly with something like a get request, without downloading the file first (specially for text files, which I would like to read directly into a String). But here I don't know how it works, because I don't see that you can save data in a file system with the other amplify services like data store or the rest api. Also, the S3 bucket is an intuitive way of storing data that is easy to use for the content creators of my company, for me it seems that the S3 bucket is the way to go. However with S3 I have only figured out the download method to fetch data.
Could someone give me a hint on what is the correct approach for this use case? Thank you very much!
I am developing an application with Django, AWS S3 and hosted on Heroku.
At one point users have to upload multiple large files, totaling around 150MB each time.
I have tried various approaches.
1st attempt: directly call the save method of the Django form:
Result: the request takes more than 30 seconds and returns a timeout.
2nd attempt: temporarily save the file to a Heroku directory and read it from Celery task.
Result: Cannot save because it throws FileNotFoundError: [Errno 2] No such file or directory on production.
3rd attempt: pass the uploaded files (in memory files) to a celery task but the bytes cannot be serialized and passed to the task neither with json or with pickle.
Could anyone help me please?
Thanks advance.
Another approach can be like that
Expose an APIs to generate presigned URL for Frontend (Steps are here).
Upload files by using that URL from the frontend in async way. That will offload your computation at Backend.
After successful upload, you will get an URL of file location. Now save the S3 URL along with other fields data to Django model.
You can upload more than 150MB file size by this method. Your system will be scalable.
So I have added s3 support to one of my Django projects. (storages and boto3)
I have a model that has a file field with zip-archive with images in it.
At some point I need to access this zip-archive and parse it to create instances of another model with those images from archive. It looks something like this:
I access archive data with zipfile
Get image from it
Put this image to django File object
Add this file object to model field
Save model
I works perfectly fine without s3, however with it I get UnsupportedOperation: seek error.
My guess is that boto3/storages does not support uploading files to s3 from memory files. Is it the case? If so, how to fix id/ avoid this in this kind of situation?
I want to do the following: a user in a browser types some text and after he presses a 'Save' button, the text should be saved in a file (for example: content.txt) in a folder (for example: /username_text) on the root of an S3 bucket.
Also, I want the user to be able, when he visits the same page, load the content from S3 and continue working on the file. Then, if he/she is done, save the file to S3 again.
Probably important to mention, but I plan on using NodeJS for my back-end...
My question now is: What is the best way to set this storing-and-retrieving thing up? Do I create an API gateway + Lambda function to GET and POST files through that? Or do I for example use the aws-sdk in Node to directly push and pull files from S3? Or is there a better way to do this?
I looked at the following two guides:
Using AWS S3 Buckets in a NodeJS App – Codebase – Medium
Image Upload and Retrieval from S3 Using AWS API Gateway and Lambda
Welcome to StackOverflow!
I think you are worrying too much about the not-so-important stuff. S3 is nothing but a storage system. You could have decided to store the content of these files on DynamoDB, RDS, etc. What would you do if you stored its contents on these real databases? You'd fetch for data and display it to the user, wouldn't you?
This is what you need to do with S3! S3 is a smart choice on your scenario because your "file" can grow very big and S3 is a great place for storing files. However, apparently, you're not actually storing files (think of .pdf, .mp4, .mov, etc.), you're essentially only storing human-readable text.
So here's one approach on how to solve your problem:
FETCHING FILE CONTENT
User logs in
You fetch the user's personal information based on some token. You can store all the metadata in DynamoDB, where given a user_id, fetch all the "files" from this user. These "files" (metadata only) would be the bucket and key for the actual file on S3.
You use the getObject API from S3 to fetch the file based on your query and display the body of your file to your user in a RESTful way. Your response should look something like this:
{
"content": "some content"
}
SAVING FILE CONTENT
User logs in
The user writes anything in a form and submits it. In your Lambda function, you grab the content of this form and process it. This request should look something like this:
{
"file_id": "some-id",
"user_id": "some-id",
"content": "some-content"
}
If the file_id exists, update the content in S3. Otherwise, upload a new file in S3 and then create a new entry in DynamoDB. You'd then, of course, have to handle if the user submitting the changes actually owns the file, but if you're using UUIDs it shouldn't be too much of a problem, but still worth checking in case an ID is leaked somehow.
This way, you don't need to worry about uploading/downloading files as these are CPU intensive tasks, so you can keep your costs low as well as using very little RAM in your functions (128MB should be more than enough), after all, you're now only serving text. Not only this will simplify your way of designing it, but will also make things simpler both in API Gateway and in your code as you won't have to deal with binary types. The maximum you'll do is convert the buffer from S3 to a String when serving some content, but this should be completely fine.
EDIT
On your question regarding whether you should upload it from the browser or not, I suggest you take a look into this answer where I cover the pros/cons of doing it via API Gateway vs from the Browser.
Background
I'm doing fairly big file uploads on Django. File size is generally 10MB-100MB.
I'm on Heroku and I've been hitting the request timeout of 30 seconds.
The Beginning
In order to get around the limit, Heroku's recommendation is to upload from the browser DIRECTLY to S3.
Amazon documents this by showing you how to write an HTML form to perform the upload.
Since I'm on Django, rather than write the HTML by hand, I'm using django-uploadify-s3 (example). This provides me with an SWF object, wrapped in JS, that performs the actual upload.
This part is working fine! Hooray!
The Problem
The problem is in tying that data back to my Django model in a sane way.
Right now the data comes back as a simple URL string, pointing to the file's location.
However, I was previously using S3 Boto from django-storages to manage all of my files as FileFields, backed by the delightful S3BotoStorageFile.
To reiterate, S3 Boto is working great in isolation, Uploadify is working great in isolation, the problem is in putting the two together.
My understanding is that the only way to populate the FileField is by providing both the filename AND the file content. When you're uploading files from the browser to Django, this is no problem, as Django has the file content in a buffer and can do whatever it likes with it. However, when doing direct-to-S3 uploads like me, Django only receives the file name and URL, not the binary data, so I can't properly populate the FieldFile.
Cry For Help
Anyone know a graceful way to use S3Boto's FileField in conjunction with direct-to-S3 uploading?
Else, what's the best way to manage an S3 file just based on its URL? Including setting expiration, key id, etc.
Many thanks!
Use a URLField.
I had a similar issue where i want to store file to s3 either directly using FileField or i have an option for the user to input the url directly. So to circumvent that, i used 2 fields in my model, one for FileField and one for URLField. And in the template i could use 'or' to see which one exists and to use that like {{ instance.filefield or instance.url }}.
This is untested, but you should be able to use:
from django.core.files.storage import default_storage
f = default_storage.open('name_you_expect_in_s3', 'r')
#f is an instance of S3BotoStorageFile, and can be assigned to a field
obj, created = YourObject.objects.get_or_create(**stuff_you_know)
obj.s3file_field = f
obj.save()
I think this should set up the local pointer to s3 and save it, without over writing the content.
ETA: You should do this only after the upload completes on S3 and you know the key in s3.
Checkout django-filetransfers. Looks like it plays nice with django-storages.
I've never used django, so ymmv :) but why not just write a single byte to populate the content? That way, you can still use FieldFile.
I'm thinking that writing actual SQL may be the easiest solution here. Alternatively you could subclass S3BotoStorage, override the _save method and allow for an optional kwarg of filepath which sidesteps all the other saving stuff and just returns the cleaned_name.