dr_scaffold VS LocalStack

For crud there’s a few good libraries out there, one of them I created a month ago for scaffolding REST APIs with Django, which you can find at https://github.com/Abdenasser/dr_scaffold

Hey :hand: my name is Abdenasser I'm the creator of this little django scaffold generator https://github.com/Abdenasser/dr_scaffold and today I'm gonna show you how to use it to create ready to use and fully functional REST apis with django only using the command line, let's get started.

You won't struggle anymore if you use Django and https://github.com/Abdenasser/dr_scaffold

github repo: dr_scaffold

save time creating django apis with this cool django package, and support the repository by dropping a star ⭐

Hey ✋ my name is Abdenasser I'm the creator of this little django scaffold generator https://github.com/Abdenasser/dr_scaffold and today I'm gonna show you how to use it to create ready to use and fully functional REST apis with django only using the command line, let's get started.

Later you can use any S3 compatible storage because the code I write will still work, but for testing purposes on my local machine, I will use LocalStack:

Acesse o site da LocalStack e faça login.

To give this a slightly different spin:

--> "The best optimization is simply not spinning things up."

At least for local development and testing, as made possible by LocalStack (https://localstack.cloud), among other local testing solutions and emulators.

We've seen so many teams fall into the trap of "someone forgot to shut down dev resource X for a week and now we've racked up a $$$ bill on AWS".

What is everyone's strategy to avoid this kind of situation? Tools like `aws-nuke` (https://github.com/rebuy-de/aws-nuke) are awesome (!) to clean up unused resources, but frankly they should not be necessary in the first place.

(For others who hadn't heard of it: localstack is

LocalStack Website

O Localstack: https://localstack.cloud/, é um recurso que possibilita simular diversos recursos AWS (dynamoDB, s3, iam, cognito, ses), dentro da sua máquina, utilizando o docker.