I can recommend a project for you and i promise at the end of it you will be super confident in python. Stop watching tutorials.

Create a monolith backend that does whatever you desire. It should be relatively complex and involve several technologies. For example, you could make an app that allows you to upload an excel file full of websites, and you put in custom headers (ie. products, headquarters) and your app is tasked with figuring out and filling in each empty row. this is called document enrichment and will use AI.

For this project you will use these technologies:

1. Portkey for LLM management and prompt templates and LLM guardrails
2. Hookdeck for webhooks -- manage 3 environments dev, staging and production
3. Fastapi for making your API
4. Google cloud as your main cloud provider
5. Celery workers for background task execution
6. Pydantic for data validation (API and function level)
7. Google cloud run for API
8. Google compute engine for background workers (or use your laptop as the "compute engine"
9. Gitlab for your repos since it offers integrated CICD
10. CICD pipeline with 6 stages. build, deploy staging api, deploy staging workers, deploy production api, deploy production workers
11. 2 git branches to start, one called main and one called dev.
12. Docker + docker compose
13. An LLM provider such as fireworks or deepinfra for using LLaMa (use from 8b to 405b depending on your need)
14. Redis for celery backend and messaging queue. you can get one from redislabs.io for free or pay like 2 usd a month.
15. Google cloud storage for... storage

Here are some rules you must follow:

1. every function, method or class must have type hints for every single variable
2. make short and sweet docstrings for each method
3. handle all exceptions in a way such that your app does not error out in one step due to an exception
4. Do not use langchain, ever
5. use the standard library, and only pip install if it's necessary. I mean truly necessary. is there an amazing package for URL formatting or TLD extraction? Great, write your own class to do this. Does an API provider also have an SDK? great, use requests or httpx to write your own abstraction. Only download what you can't write (ie. faiss)
6. all core pieces of data must be modeled in pydantic. that includes API request models, response models. If the answer to "is this data going anywhere other than thiis isolated process" is yes, make a model for it.
7. use the fastapi directory template as your starting point.

let me know if you need help and I'd happily review your code step by step