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Use Markdown readme instead or RST to use native mermaid diagrams
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README.md

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# django-s3file
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A lightweight file upload input for Django and Amazon S3.
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Django-S3File allows you to upload files directly AWS S3 effectively
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bypassing your application server. This allows you to avoid long running
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requests from large file uploads. This is particularly helpful for if
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you run your service on AWS Lambda or Heroku where you have a hard
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request limit.
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[![PyPi
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Version](https://img.shields.io/pypi/v/django-s3file.svg)](https://pypi.python.org/pypi/django-s3file/)
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[![Test
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Coverage](https://codecov.io/gh/codingjoe/django-s3file/branch/master/graph/badge.svg)](https://codecov.io/gh/codingjoe/django-s3file)
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[![GitHub
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license](https://img.shields.io/badge/license-MIT-blue.svg)](https://raw.githubusercontent.com/codingjoe/django-s3file/master/LICENSE)
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## Features
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- lightweight: less 200 lines
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- no JavaScript or Python dependencies (no jQuery)
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- easy integration
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- works just like the built-in
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- extendable JavaScript API
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## For the Nerds
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```mermaid
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sequenceDiagram
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autonumber
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actor Browser
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Browser->>S3: POST large file
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activate S3
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S3->>Browser: RESPONSE AWS S3 key
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Browser->>Middleware: POST AWS S3 key
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activate Middleware
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Middleware->>S3: GET AWS S3 key
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S3->>Middleware: RESPONSE large file promise
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deactivate S3
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Middleware->>Django: request incl. large file promise
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deactivate Middleware
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activate Django
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opt only if files is procssed by Django
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Django-->>S3: GET large file
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activate S3
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S3-->>Django: RESPONSE large file
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deactivate S3
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end
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Django->>Browser: RESPONSE success
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deactivate Django
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```
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In a nutshell, we can bypass Django completely and have AWS handle
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the upload or any processing. Of course, if you want to do something
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with your file in Django, you can do so, just like before, with the
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added advantage, that your file is served from within your datacenter.
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## Installation
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Make sure you have [Amazon S3
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storage](http://django-storages.readthedocs.io/en/latest/backends/amazon-S3.html)
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setup correctly.
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Just install S3file using `pip`.
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```bash
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pip install django-s3file
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# or
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pipenv install django-s3file
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```
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Add the S3File app and middleware in your settings:
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```python
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# settings.py
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INSTALLED_APPS = (
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'...',
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's3file',
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'...',
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)
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MIDDLEWARE = (
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'...',
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's3file.middleware.S3FileMiddleware',
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'...',
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)
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```
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## Usage
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S3File automatically replaces Django's `ClearableFileInput` widget, you
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do not need to alter your code at all.
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The `ClearableFileInput` widget is only than automatically replaced when
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the `DEFAULT_FILE_STORAGE` setting is set to `django-storages`'
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`S3Boto3Storage` or the dummy `FileSystemStorage` is enabled.
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### Setting up the AWS S3 bucket
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#### Upload folder
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S3File uploads to a single folder. Files are later moved by Django when
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they are saved to the `upload_to` location.
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It is recommended to [setup
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expiration](http://docs.aws.amazon.com/AmazonS3/latest/dev/intro-lifecycle-rules.html)
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for that folder, to ensure that old and unused file uploads don't add up
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and produce costs.
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The default folder name is: `tmp/s3file` You can change it by changing
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the `S3FILE_UPLOAD_PATH` setting.
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#### CORS policy
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You will need to allow `POST` from all origins. Just add the following
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to your CORS policy.
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```json
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[
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{
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"AllowedHeaders": [
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"*"
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],
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"AllowedMethods": [
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"POST"
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],
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"AllowedOrigins": [
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"*"
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],
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"ExposeHeaders": [],
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"MaxAgeSeconds": 3000
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}
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]
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```
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### Progress Bar
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S3File does emit progress signals that can be used to display some kind
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of progress bar. Signals named `progress` are emitted for both each
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individual file input as well as for the form as a whole.
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The progress signal carries the following details:
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```javascript
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console.log(event.detail)
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{
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progress: 0.4725307607171312 // total upload progress of either a form or single input
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loaded: 1048576 // total upload progress of either a form or single input
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total: 2219064 // total bytes to upload
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currentFile: File {…} // file object
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currentFileName: "text.txt" // file name of the file currently uploaded
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currentFileProgress: 0.47227834703299176 // upload progress of that file
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originalEvent: ProgressEvent {…} // the original XHR onprogress event
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}
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```
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The following example implements a Boostrap progress bar for upload
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progress of an entire form.
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```html
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<div class="progress">
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<div class="progress-bar" role="progressbar" style="width: 0%;" aria-valuenow="0" aria-valuemin="0" aria-valuemax="100">0%</div>
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</div>
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```
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```javascript
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(function () {
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var form = document.getElementsByTagName('form')[0]
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var progressBar = document.getElementsByClassName('progress-bar')[0]
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form.addEventListener('progress', function (event) {
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// event.detail.progress is a value between 0 and 1
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var percent = Math.round(event.detail.progress * 100)
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progressBar.setAttribute('style', 'width:' + percent + '%')
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progressBar.setAttribute('aria-valuenow', percent)
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progressBar.innerText = percent + '%'
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})
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})()
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```
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### Using S3File in development
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Using S3File in development can be helpful especially if you want to use
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the progress signals described above. Therefore, S3File comes with a AWS
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S3 dummy backend. It behaves similar to the real S3 storage backend. It
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is automatically enabled, if the `DEFAULT_FILE_STORAGE` setting is set
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to `FileSystemStorage`.
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To prevent users from accidentally using the `FileSystemStorage` and the
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insecure S3 dummy backend in production, there is also an additional
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deployment check that will error if you run Django\'s deployment check
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suite:
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```shell
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python manage.py check --deploy
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```
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We recommend always running the deployment check suite as part of your
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deployment pipeline.
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### Uploading multiple files
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Django does have limited support for [uploading multiple
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files](https://docs.djangoproject.com/en/stable/topics/http/file-uploads/#uploading-multiple-files).
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S3File fully supports this feature. The custom middleware makes ensure
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that files are accessible via `request.FILES`, even though they have
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been uploaded to AWS S3 directly and not to your Django application
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server.
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### Using optimized S3Boto3Storage
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Since `S3Boto3Storage` supports storing data from any other fileobj, it
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uses a generalized `_save` function. This leads to the frontend
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uploading the file to S3 and then copying it byte-by-byte to perform a
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move operation just to rename the uploaded object. For large files this
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leads to additional loading times for the user.
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That\'s why S3File provides an optimized version of this method at
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`storages_optimized.S3OptimizedUploadStorage`. It uses the more
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efficient `copy` method from S3, given that we know that we only copy
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from one S3 location to another.
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```python
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from s3file.storages_optimized import S3OptimizedUploadStorage
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class MyStorage(S3OptimizedUploadStorage): # Subclass and use like any other storage
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default_acl = 'private'
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```

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