Getting Started with SQLAlchemy
This is a self-paced GK Digital Learning product. GK Digital learning products are created by world-class production and instructional design teams to deliver an experience that feels more like a classroom than traditional e-learning with hands-on activities for real-world results. In addition to high quality video content and hands-on labs you will have access to subject matter experts to ask questions for feedback and support.
One of the biggest productivity boosts you can add to your data-driven application is to use a high-level framework to access your database. SQLAlchemy is the most flexible and highly popular ORM (Object Relational Mapper) in Python. Once you take this course, you'll be able to write efficient and reliable code whether you're working on a web application or other data driven application.
This course begins with an overview of ORMs and SQLAlchemy. Then we move on to the most commonly used features of SQLAlchemy, the ORM. You'll learn how to map classes to the database and even generate the database from your in-memory models. Finally, we'll round out the course with a look at a lower-level layer of SQLAlchemy that provides greater flexibility than the ORM (at the cost of more work on your side).
This online learning event is comprised of Articles to read, Labs to participate in, Videos to watch and all the time you have access to Mentors that will help you better understand this ORM within Python. We estimate that the learning event will take you around 3 ½hrs to complete.
Pre-RequisitesA basic command of the Python language and standard library.
- Introduction to ORMs and SQLAlchemy - 33 minutes 9 Activities: Article (1) | Lab (1) | Video (7)
SQLAlchemy ORM - 1 hours 29 minutes 14 Activities: Article (1) | Lab (1) | Video (12)
SQLAlchemy Core - 1 hours 23 minutes 13 Activities: Article (1) | Lab (1) | Video (11)
- Data access techniques
- Use SQLAlchemy to access your DB
- What an ORM is and why you should use it
- Map classes to the database
- Generate the database from your in-memory models
- Use the more flexible SQLAlchemy core layer