On this post you could have a small idea how SQLAlchemy works. However, all my study on SQLAlchemy basics was due to a problem I was having that took me a lot of time to figure it out. Since the problem was more complex and didn’t actually fit on the last post, I decided to create a new one dedicated to it, so here it is :)
I’ve been working with Project Jupyter since December of last year and it has been a wonderful experience. The last couple of days I struggled with the SQLAlchemy library that JupyterHub works on its internals. Since I studied this library and had to scratch some Stack Overflow questions to find some answers, I created this post to help digesting some of my doubts and findings.
I started working with MongoDB for fun and for some side projects in the last year. The main idea of using MongoDB is its flexibility. The pymongo library is really nice for getting some information, but on a project more complex, we may need something a little more intense. A nice alternative is the MongoEngine library, which is an Object-Document Mapper (ODM), which treats MongoDB documents as a kind of ORM.