Despite the temptation of buying new servers and adding CPU and RAM – you need to do what you can with the code first. I am exploring and cataloguing these methods to speed up Django QuerySets before server scaling.
The general idea is simple – use more QuerySet methods instead of Python methods to avoid evaluation.
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I needed to schedule 10 tasks that have these conditions
I tried a few options, and this one worked
ret = chain(task1.si(args).set(countdown=30*1), ..., task10.si(args).set(countdown=30*10)).apply_sync()Important note – the signature here is not .s() but .si() this way you don’t pass the result of task1 to task2. You set the countdown with set() and not inside the apply_sync().
It is simple but it took me some time to figure out.
I covered the basics in one of my articles on Video generation with Python, and today I want to write about different ways to assemble text on the image so it does not look too bland.
Read More »My previous version has flaws. It works well for opaque GIFs, but OpenCV is famous for not being good with transparent images. So instead of OpenCV I use imageio for GIF iteration and PIL for adding GIF frames to the static background.
The original algorithm left these artifacts, look at the cyan block on the intersection of GIF frame and a darker abstract part:
Initially, I aimed to make one big post, but I am splitting it up. This Part 1 is about how I made the frames to generate videos from.
I have been on and off doing this project for a few months. Many things did not work for me – from ffmpeg to sheer OpenCV/ffmpeg installation on Apple M1 systems – and I am not 100% sure what made it work to this day. I plan to put myself in a situation where I have to do it again, and I will make a guide then. However, right now, I can only say that this video tutorial on running native ffmpeg and this guide from OpenCV themselves are good places to start.
The last time I used OpenCV was in 2017 when I worked on my graduate work. Back then, I processed prerecorded videos with no need to worry about audio. So I had some background prior to this project, but I was in no way ready for the ride.
Buckle up!
Following Channels’ docs I encountered yet another error the solution to what was not obvious right off the bat.
Ditch Channels.
The End.
This was my original post in October 2020 and I stand by it. You can make your project work with Google Firebase - it handles signals well enough. Yes it is primarily used by mobile developers, but overall it is fine for web too. I spent trying to install Django Channels on my local Linux 18.04, and I kind of made it work, but then I had to deploy it... And as a professional backender you don't want to let people down. I decided to try Channels because my Python-related friends talked about it. But days into the trouble I asked my friend about a certain step and he asked me in return "oh so [you use it because] they fixed Channels since two years ago?". I as like ??????????????????. So that moment I ditched it. Too much time wasted, but I like the result I achieved with Firebase. What I am saying - Firebase is fast and universal. In a matter of days I managed to make and deploy an internal Customer Support chat service that connected mobile app users and a support from the web.</p> I will be writing a new series on Django + Firebase, and this post is pretty much a short introduction.
This error occured when I used ffmpeg to concatenate different videos that I generated:
ffmpeg -f concat -safe 0 -i list.txt -c copy final_video.avi -yBTW, if you want to run ffmpeg or any other command inside a python script (a very reasonable idea), use subprocess: command = "ffmpeg -f concat -safe 0 -i list.txt -c copy final_video.avi -y" subprocess.Popen(command.split(), stdout=subprocess.PIPE)
As a result – the videos got smashed together – some frames even never appeared.
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A bad solution (with Pillow) and a good solution (with OpenCV).
Contents:
Last year I wrote a guide for django-allauth, and now it’s time for DRF. I will be using drf-social-oauth2 for social authentication.
As far as I understood this is a collaboratory project, and it is currently maintained by Wagner De Lima.
You can find very useful materials here and there, but the purpose behind this tutorial is to help set up social authentication for your DRF-based API by following clear and easy steps. So that nobody suffers from the lack of base knowledge or the lack of time – been there, done that.
Table of contents:
1. Registering an app in Facebook and Google developer’s panels
2. Getting User Access Token from Facebook/Google
2.1 Facebook
2.2 Google
3. Installing drf-social-oauth2
3.1 settings.py
3.2 Facebook
3.3 Google
4. Creating a local app
5. Converting Token from Facebook/Google into a DRF Access token
6. Accessing things with this new Token
7. Refreshing Access Token
8. Changing Access Token Expiration
If you need to modify instance fields depending on the instance’s pk or id, hop on.
When you create an instance, before it is saved, you can’t have pk or id as it is not yet created.
def save(self, *args, **kwargs):
# self.pk == None
# self.id == None
super().save(*args, **kwargs)
# self.pk != None
# self.id != None If you have a property that somehow depends on the value of self.pk or self.id and you want to have it saved on creating, you have two options.
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Django Investigations 