Session

Python's memory story is not often told. We hear it uses reference counting and that's about the end of it. But there is so much more going on. There is also a GC backing up reference counting, why? Instagram turned theirs off and got faster, how? Python classes can be memory hogs. But there is an escape hatch that is almost always available to us which uses much less memory and is faster computationally. Yet, almost no one opens it. You might want to.
 
Join Michael Kennedy from Talk Python Training and look at how Python memory works and design patterns for functions and classes making Python more efficient (memory-wise) and get a solid speed boost as a side benefit.