The document summarizes a presentation on SQLAlchemy by Roger Barnes at the PyCon conference in June 2013, highlighting its features as a Python SQL toolkit and object-relational mapper. It compares SQLAlchemy with Django's ORM, noting that while both have their merits, SQLAlchemy is more flexible and suitable for a broader range of applications. The presentation also outlines the core structure and functionality of SQLAlchemy, including session management and mapping between domain objects and database rows.

1. SyPy June 2013
● Introduction to SQLAlchemy - Roger Barnes
● Using Robot Framework for testing,
communication and world domination - Dylan Jay
● Configuration management with Salt Stack -
Daniel Bryan
● + lightning talks
● Pub

3. SyPy June 2013
Next SyPy - Aug 1, 2013
http://bit.ly/11kHTmB

4. Introduction to
SQLAlchemy
Roger Barnes
SyPy June 2013
roger@mindsocket.com.au @mindsocket

5. About Me
15 years software development
4 years Python/Django
4 months SQLAlchemy

6. SQLAlchemy is...
Python SQL toolkit
&
Object Relational Mapper

7. About SQLAlchemy
● Full featured
● Mature, robust, documented, maintained
● Flexible
– Use what you need
– Extend when you need
– Database oriented
– Doesn't dictate schema design
– ...

8. Enterprise!

9. DB support
● SQLite
● Postgresql
● MySQL
● Oracle
● MS-SQL
● Firebird
● Sybase
● ...

10. Python support
cPython 2.5+
cPython 3+
Jython 2.5+
Pypy 1.5+

11. Compared with Django ORM?
● Both are good
● Key philosophical design difference
Django → Web applications
SQLAlchemy → Database applications

12. Compared with Django ORM?
● Django ORM
– easier to learn
– less flexible
– well suited for most web apps
– comes with a free admin app

13. Compared with Django ORM?
● SQLAlchemy
– harder to learn (but only a little)
– massively flexible
– suited to a wider range of
applications, especially those that
benefit from the power of an
RDBMS

14. Project Structure
SQLAlchemy is like an onion...
… or a cake

15. Structure

16. Core
● Abstraction over Python's DBAPI
● SQL language via generative
Python expressions

17. Core
● Good for DB performance
– bulk operations
– complex queries
– fine-tuning
– connection/tx management

18. Core
● Schema
– Managed by a Metadata object
– Declare tables, columns and
other attributes
– Closely aligned with Data
Definition Language

19. Core
● SQL Expressions
– INSERT, UPDATE, DELETE
– SELECT, joins, grouping
– Functions, expressions, operators
● Connection pooling
● Backend DB dialects

20. Demo

21. ORMs in General
● Simple case – translate between a
domain object and a table row
● More complex – arbitrary rows
mapped to an object
● Handle relationships

22. ORMs in General
● Query in terms of objects
● Represent class inheritance
● Data validation

23. SQLAlchemy ORM
● Layer on top of core
● Session based
● Session manages object state

24. SQLAlchemy ORM
● 2 ways to use
– Classical Mapping
● Define table
● Define object
● Configure mapper
– Modern - Declarative
● Shorthand combining table metadata and
class mapping
● Similar to Django ORM

25. Demo

26. Questions?
● Other resources
– SQLAlchemy - http://sqlalchemy.org/
– Longer (better) introduction -
http://bit.ly/13UQXVV
● Contact
roger@mindsocket.com.au
@mindsocket