After building, deploying and scaling a dozen on products with the Django + GraphQL + SPA (React) setup, we have come to understand what works and what does not. In this talk, I will share our findings on how to do the same. I will be using a simplified StackOverflow clone for demonstration. First, I will introduce Python-Graphene (and few other related libraries), the library that is used to build GraphQL endpoints. Then the talk will focus on how to structure your Django GraphQL project. Share the toolchain (a few management command scripts) that are handy to export your constants & GraphQL schemas to be used with your SPA. Integrating with an SPA (React for demo purpose) Auth, API calls. Then I will talk about how you go about deploying your API using 2 different strategies: 1. Docker compose / swarm (Vendor independent, non-production workloads) 2. AWS Fargate (Vendor dependant, production workloads, serverless containers) And a cost-effective and highly scale-able deployment strategy for your SPA (using AWS S3, CloudFront and ACM).

1. Build, deploy and scale:
Django, GraphQL and SPA
@dhilipsiva

2. @dhilipsiva
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Optimistic Nihilist
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Democratic Socialist
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I code for fun & profit
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I love Science, Python, FOSS & தமிழ்
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Dad of 2. Environmentalist. Story Teller.
Gamer.
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Jack of all trades & Master of none
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A volunteer for progressives

3. I have no idea what I am talking about 🤪

4. Credentials
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11+ years of professional experience in
python
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Built over 20 different products using
django alone
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Scaled more than 5 products to serve
millions of requests per second
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Built a Device Farm (iOS and Android)
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Involved in building a Bitcoin mining
farm with Rpi + ASIC (aws for miners)

5. Profession
VP of Engineering @ Reckonsys
Hitoshīkage @ Nitimis

6. Why GraphQL?
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Much more standardized than the
fragmented RESTful implementations
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Out-of-box live & browsable
documentation
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No back-and-forth communication
between API developer and SPA
developer
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Precise queries

7. Let’s look at our (buggy ) demo app
😬
https://stackopenflow.space
It is a very silly StackOverflow
clone

8. Stack
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Python
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Django
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Graphene
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Django-graphql-jwt
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Django-rules
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postgres
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JavaScript
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React
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Relay
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easy-peasy

9. Graphene
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Custom field defs
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Syncronous
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Mature
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Status Quo
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Fantastic Django
integration
Strawberry.rocks
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Dataclasses
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Asyncronous
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Not-so-mature
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Future (maybe)
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Very minimal
Django integration

10. Per-object perms
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Choose a rule based framework (like django-
rules) over a DB-based framework (guardian)
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Less DB calls = less latency
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No unnecessary migrations gue to change in
logic
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Easier to maintain

11. Why React?
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Plays really well with GraphQL (Facebook being
a big proponent of both React and GraphQL)
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Can build native applications with react-
native. So a front-end engineer can easily
scale-up as a mobile application developer.
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Second only to vue.js in terms of
community/popularity

12. Why Relay?
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Relay’s APIs are cleaner compared to
Apollo
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Hooks are 1st
class citizens
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Out of box caching support
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Backed by Facebook (just like GraphQL and
React) so React has excellent
integration.
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Relay-compiler is fantastic at catching
errors

13. Why easy-peasy?
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Hooks are 1st
class citizens
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Less boilerplate
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Pleasant APIs
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Ease of use

14. Project Layout
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All other django apps are placed
under the django root
“stackopenflow” app (the module that
contains settings.py, urls.py,
wsgi.py, etc)
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Therefore, all imports are
namespaced with “stackopenflow”

15. Typical Modules
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admin.py
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apps.py
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models.py
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tests.py
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views.py

16. Our Modules
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admin.py
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apps.py
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behaviours.py
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choices.py
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inputs.py
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models.py
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mutations.py
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queries.py
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tests.py
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types.py

17. Let’s walk through the source code
Django & React
https://github.com/djconeu2021/stackopenflow-api
https://github.com/djconeu2021/stackopenflow-app

18. bigga
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https://github.com/djconeu2021/bigga
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A docker-compose based deployment
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Can be configured to be used to
docker-swarm with minimal changes
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Handy for local development too
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Suitable for cheap, non-production
workloads
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Code walk through

19. AWS copilot
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https://aws.github.io/copilot-cli
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ECS on AWS Fargate (serverless containers)
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Very reliable & scaleable, but vendor dependent
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Easy auto scaling configuration
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Cheaper & faster than Lambda (serverless functions)
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But be sure set-up along with tools like Terraform

20. SPA Deployment
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S3 + CloudFront + ACM
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Cheaper than alternatives like Netlify
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Less latency
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Manual Setup:
https://github.com/reckonsys/bigga/blob/community/S3_FRONTEND_DEPLOYMENT.md
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Pyinvoke Script:
https://github.com/reckonsys/bigga/blob/community/tasks.py

21. Thank You
@dhilipsiva
dhilipsiva@pm.me
https://dhilipsiva.com
https://t.me/dhilipsiva