I am implementing a feature in a new project and I was wondering what was the optimal solution to it. The feature itself consists of sub functionality as follows: starting a process, stop a process, and checking if the process is running...all these done in a non-blocking way with django. I am trying to avoid stuff like RabbitMQ, etc. I was thinking maybe of using threading or cron.
EDIT: these functionality need to be triggered from a view.
Any comments or suggestions are the most welcomed. Thanks.
You can surely use celery with the database backend instead of RabbitMQ. Personally, for simple tasks I tend to just write a custom mangement command launched from cron, that gets its input from some database table (i.e. Django model) which is populated by Django view(s).
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HEROKU gives me H12 error on transferring the file to an API from my Django application (Understood it's a long running process and there is some memory/worker tradeoff I guess so). I am on one single hobby Dyno right now.
The function just runs smoothly for around 50MB file. The file itself is coming from a different source ( requests python package )
The idea is to build a file transfer utility using Django app on HEROKU. The file will not gets stored in my app side. Its just getting from point A and sending to point B.
Went through multiple discussions along with the standard HEROKU documentations, however I am struggling in between in some concepts:
Will this problem be solved by background tasks really? (If YES, I am finding explanation of the process than the direct way to do it such that I can optimize my flow)
As mentioned in standard docs, they recommend background tasks using RQ package for python, I am using Postgre SQL at moment. Will I need to install and manage Redis Database as well for this. Is this even related to Database?
Some recommend using extra Worker other than the WEB worker we have by default. How does this relate to my problem?
Some say to add multiple workers, not sure how this solve it. Let's say today it starts working for large files using background tasks, what if the load of users at same time increases. How this will impact my solution and how should I plan the mitigation plan around the risks.
If someone here has a strong understanding with respect to the architecture, I am here to listen your experiences and thoughts. Also, let me know if there is other way than HEROKU from a solution standpoint which will make this more easy for me.
Have you looked at using celery to run this as a background task?
This is a very standard way of dealing with requests which take a large time to complete.
Will this problem be solved by background tasks really? ( If YES, I am finding explanation of the process than the direct way to do it such that I can optimise my flow )
Yes it can be solved by background tasks. If you are using something like Celery which has direct support for django, you will be running another instance of your Django application but with a different startup command for Celery. It then keeps reading for new tasks to execute and reads the task name from the redis queue (or rabbitmq - whichever you use as the broker) and then executes that task and updates the status back to redis (or the broker you use).
You can also use flower along with celery so that you have a dashboard to see how many tasks are being executed and what are their statuses etc.
As mentioned in standard docs, they recommend background tasks using RQ package for python, I am using Postgre SQL at moment. Will I need to install and manage Redis Database as well for this. Is this even related to Database?
To use background task with Celery you will need to set up some sort of message broker like Redis or RabbitMQ
Some recommend using extra Worker other than the WEB worker we have by default. How does this relate to my problem?
I dont think that would help for your use case
Some say to add multiple workers, not sure how this solve it. Let's say today it starts working for large files using background tasks, what if the load of users at same time increases. How this will impact my solution and how should I plan the mitigation plan around the risks.
When you use celery, you will have to start few workers for that Celery instance, these workers are the ones who execute your background tasks. Celery documentation will help you with exact count calculation of these workers based on your instance CPU and memory etc.
If someone here has a strong understanding with respect to the architecture, I am here to listen your experiences and thoughts. Also, let me know if there is other way than HEROKU from a solution standpoint which will make this more easy for me.
I have worked on few projects where we used Celery with background tasks to upload large files. It has worked well for our use cases.
Here is my final take on this after full evaluation, trials and earlier recommendations made here, thanks #arun.
HEROKU needs a web worker to deliver the website runtime which hold 512MB of memory, operations your perform if are below this limits should be fine.
Beyond that let's say you have scenarios like mentioned above where a large file is coming from one source api and going into another target api with Django app, you will have to:
First, you will have to run the file upload function as a background process since it will take time more than 30 seconds to respond which HEROKU expects to return. If not H12 Error is waiting for you. Solution to this is implementing Django Background tasks, Celery worked in my case. So here Celery is your same Django app functionality running as a background handler which needs its own app Dyno ( The Worker ) This can be scaled as needed in future.
To make your Django WSGI ( Frontend App ) talk to the Celery ( Background App), you need a message broker in between which can be HEROKU Redis, RabbitMQ, etc.
Second, the problems doesn't gets solved here even though you have a new Worker dedicated for the Celery app, the memory limits will still apply as its also a Dyno with its own memory.
To overcome this, your Python requests module should download the file in stream instead of direct downloading complete file in a single memory buffer. Iterate and load the stream data in chunks and send the file chunks to target endpoint.
Even chunk size plays here an important role. I will not put exact number here since it depends on various factors:
Should not be too small, else it will take more time to transfer.
Should not be too big to be handled by either of the source/target endpoint servers.
I have a Django backend for my project using Postgres as a DB. Apart from it, I have a systemd service running and inserting a new row in a specific table in the DB. I would need to detect the moment in which a new row is inserted in the table to run a callback function, which is defined in Django. The service takes different times to complete. I would also like to make it efficient. I thought of these options:
I used to use celery in the project but don't anymore. It is kind of set up already, so I thought one option would be a PeriodicTask that checks if something has been addedd. I dislike periodic tasks, though, and it is not quite precise (there could be a gap between the time the service finishes and the time the task runs). So EASY but UGLY
If it were possible, I would like to use a Postgres TRIGGER to insert my callback task in the Celery queue. On paper, that sounds fast and clean. I have NO CLUE how to add something to the Celery task queue though. So CLEAN and EFFICIENT but DIFFICULT
I thought of implementing a separate service which listens to NOTIFY from Postgres, also using TRIGGER. It would then cURL the backend to start the callback function. This seems clunky. So MEH
If it seems like I do not know much of this, you are absolutely correct. I am learning as I go, but this is a must have feature for me. Any help would be much appreciated.
You could add a django management command and call it after your current execution on your service.
Just to add an example:
[Unit]
...
[Service]
...
ExecStart=java -jar file.jar && /.../python /.../manage.py <management_command>
[Install]
...
I'm building web app using django. I need to use lots of multithreading. Here I have to add features to start or stop specific thread, I didn't know what to use to achieve this. Here can I use django celery?, but i also need to implement to stop that task. Any suggestion would be appreciated. Eg:
In my admin I have a form allowing to upload a file to fill the DB.
Parsing and filling the DB take a long time, so I'd like to do it asynchronously.
As recommended by several SO users I tried to install python-celery, but I can't manage to do it (I'm on Webfaction).
Is there any simple, easy-to-install alternative?
If webfaction supports cron jobs you can create your own pseudo broker. You could save your long running tasks to the db and in a 'tasks' table, this would allow you to return a response to the user instantaneously. Then there could be a cron that goes through very frequently and looks for uncompleteled tasks and processes them.
I believe this is what django mailer does
https://github.com/jtauber/django-mailer/
https://stackoverflow.com/a/1419640/594589
Try Gearman along with it's python client library
It's very easy to setup and run gearman. Try few examples.
How to make Django execute something automatically at a particular time.?
For example, my django application has to ftp upload to remote servers at pre defined times. The ftp server addresses, usernames, passwords, time, day and frequency has been defined in a django model.
I want to run a file upload automatically based on the values stored in the model.
One way to do is to write a python script and add it to the crontab. This script runs every minute and keeps an eye on the time values defined in the model.
Other thing that I can roughly think of is maybe django signals. I'm not sure if they can handle this issue. Is there a way to generate signals at predefined times (Haven't read indepth about them yet).
Just for the record - there is also celery which allows to schedule messages for the future dispatch. It's, however, a different beast than cron, as it requires/uses RabbitMQ and is meant for message queues.
I have been thinking about this recently and have found django-cron which seems as though it would do what you want.
Edit: Also if you are not specifically looking for Django based solution, I have recently used scheduler.py, which is a small single file script which works well and is simple to use.
I've had really good experiences with django-chronograph.
You need to set one crontab task: to call the chronograph python management command, which then runs other custom management commands, based on an admin-tweakable schedule
The problem you're describing is best solved using cron, not Django directly. Since it seems that you need to store data about your ftp uploads in your database (using Django to access it for logs or graphs or whatever), you can make a python script that uses Django which runs via cron.
James Bennett wrote a great article on how to do this which you can read in full here: http://www.b-list.org/weblog/2007/sep/22/standalone-django-scripts/
The main gist of it is that, you can write standalone django scripts that cron can launch and run periodically, and these scripts can fully utilize your Django database, models, and anything else they want to. This gives you the flexibility to run whatever code you need and populate your database, while not trying to make Django do something it wasn't meant to do (Django is a web framework, and is event-driven, not time-driven).
Best of luck!