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If my understanding is correct, in CPython objects will be deleted as soon as their reference count reaches zero. If you have reference cycles that become unreachable that logic will not work, but on occasion the interpreter will try to find them and delete them (and you can do this manually by calling gc.collect() ).
My question is, when do these interpreter-triggered cycle collection steps happen? What kind of events trigger them?
I am more interested in the CPython case, but would love to hear how this differs in PyPy or other python implementations.
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For each generation, the garbage collector module has a threshold number of objects. If the number of objects exceeds that threshold, the garbage collector will trigger a collection process. For any objects that survive that process, they're moved into an older generation.
Yes, Python garbage collector removes every object not referenced to. The feature is based on reference counting. However it can also deal with cyclic references. Of course when the process is terminated, all its resources are released.
Any time a reference count drops to zero, the object is immediately removed. 295 * deallocated immediately at that time. A full collection is triggered when the number of new objects is greater than 25% of the number of existing objects.
An object is eligible to be garbage collected if its reference variable is lost from the program during execution. Sometimes they are also called unreachable objects. What is reference of an object? The new operator dynamically allocates memory for an object and returns a reference to it.
Standard CPython's garbage collector has two components, the reference counting collector and the generational garbage collector, known as gc module. The reference counting algorithm is incredibly efficient and straightforward, but it cannot detect reference cycles. That is why Python has a supplemental algorithm called generational cyclic GC.
However, since it cannot be reached from inside Python and cannot possibly be used again, it is considered garbage. In the current version of Python, this list is never freed. Because reference cycles take computational work to discover, garbage collection must be a scheduled activity.
When the number of allocations minus the number of deallocations is greater than the threshold number, the garbage collector is run. One can inspect the threshold for new objects (objects in Python known as generation 0 objects) by importing the gc module and asking for garbage collection thresholds:
The garbage collector algorithm does not track all immutable types except for a tuple. Tuples and dictionaries containing only immutable objects can also be untracked depending on certain conditions. Thus, the reference counting technique handles all non-circular references.
The GC runs periodically based on the (delta between the) number of allocations and deallocations that have taken place since the last GC run.
See the gc.set_threshold() function:
In order to decide when to run, the collector keeps track of the number object allocations and deallocations since the last collection. When the number of allocations minus the number of deallocations exceeds threshold0, collection starts.
You can access the current counts with gc.get_count(); this returns a tuple of the 3 counts GC tracks (the other 2 are to determine when to run deeper scans).
The PyPy garbage collector operates entirely differently, as the GC process in PyPy is responsible for all deallocations, not just cyclic references. Moreover, the PyPy garbage collector is pluggable, meaning that how often it runs depends on what GC option you have picked. The default Minimark strategy doesn't even run at all when below a memory threshold, for example.
See the RPython toolchain Garbage Collector documentation for some details on their strategies, and the Minimark configuration options for more hints on what can be tweaked.
Ditto for Jython or IronPython; these implementations rely on the host runtime (Java and .NET) to handle garbage collection for them.
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