Python uses a combination of reference counting and cycle-detection to manage its memory and handle garbage collection.
1. Reference Counting: This is the primary memory management technique used by Python. Every object in Python has a count of references pointing to it. Once this count drops to zero, the object is no longer accessible and is marked for collection. Suppose an object is referenced by a variable or another object. In that case, its reference count goes up, and when the reference is deleted or reassigned, the reference count decreases. If the reference count reaches zero, the object’s memory gets deallocated.
1. Cycle Detection: Sometimes, there might be circular references, where a group of objects reference each other but are not referenced elsewhere. These objects are inaccessible but would not have a reference count of zero. In such scenarios, Python’s garbage collector comes into play with its cycle detector, which periodically checks for circular references and removes them. This cycle-detecting algorithm is known as the cyclic garbage collector.
The garbage collector can be controlled using the `gc` module. However, in most of the scenarios, we don’t have to worry about memory management as Python does it smartly for us. If you want the garbage collector to be more aggressive, you can tune it or manually run garbage collector at any point in time using `gc.collect()`. For most applications, however, the default settings will be more than sufficient.
