panda3d.core.MemoryUsage

from panda3d.core import MemoryUsage

class MemoryUsage

Bases: MemoryHook

This class is used strictly for debugging purposes, specifically for tracking memory leaks of reference-counted objects: it keeps a record of every such object currently allocated.

When compiled with NDEBUG set, this entire class does nothing and compiles to a stub.

Inheritance diagram

__init__(param0: MemoryUsage) → None

static isTracking() → bool

Returns true if the MemoryUsage object is currently tracking memory (e.g. track-memory-usage is configured #t).

static isCounting() → bool

Returns true if the MemoryUsage object is currently at least counting memory (e.g. this is a Windows debug build), even if it’s not fully tracking it.

static getCurrentCppSize() → size_t

Returns the total number of bytes of allocated memory consumed by C++ objects, not including the memory previously frozen.

Return type

size_t

static getTotalCppSize() → size_t

Returns the total number of bytes of allocated memory consumed by C++ objects, including the memory previously frozen.

Return type

size_t

static getPandaHeapSingleSize() → size_t

Returns the total number of bytes allocated from the heap from code within Panda, for individual objects.

Return type

size_t

static getPandaHeapArraySize() → size_t

Returns the total number of bytes allocated from the heap from code within Panda, for arrays.

Return type

size_t

static getPandaHeapOverhead() → size_t

Returns the extra bytes allocated from the system that are not immediately used for holding allocated objects. This can only be determined if ALTERNATIVE_MALLOC is enabled.

Return type

size_t

static getPandaMmapSize() → size_t

Returns the total number of bytes allocated from the virtual memory pool from code within Panda.

Return type

size_t

static getExternalSize() → size_t

Returns the total number of bytes of allocated memory in the heap that Panda didn’t seem to be responsible for. This includes a few bytes for very low-level objects (like ConfigVariables) that cannot use Panda memory tracking because they are so very low-level.

This also includes all of the memory that might have been allocated by a high-level interpreter, like Python.

This number is only available if Panda is able to hook into the actual heap callback.

Return type

size_t

static getTotalSize() → size_t

Returns the total size of allocated memory consumed by the process, as nearly as can be determined.

Return type

size_t

static getNumPointers() → int

Returns the number of pointers currently active.

static getPointers(result: MemoryUsagePointers) → None

Fills the indicated MemoryUsagePointers with the set of all pointers currently active.

static getPointersOfType(result: MemoryUsagePointers, type: TypeHandle) → None

Fills the indicated MemoryUsagePointers with the set of all pointers of the indicated type currently active.

static getPointersOfAge(result: MemoryUsagePointers, from: float, to: float) → None

Fills the indicated MemoryUsagePointers with the set of all pointers that were allocated within the range of the indicated number of seconds ago.

static getPointersWithZeroCount(result: MemoryUsagePointers) → None

Fills the indicated MemoryUsagePointers with the set of all currently active pointers (that is, pointers allocated since the last call to freeze(), and not yet freed) that have a zero reference count.

Generally, an undeleted pointer with a zero reference count means its reference count has never been incremented beyond zero (since once it has been incremented, the only way it can return to zero would free the pointer). This may include objects that are allocated statically or on the stack, which are never intended to be deleted. Or, it might represent a programmer or compiler error.

This function has the side-effect of incrementing each of their reference counts by one, thus preventing them from ever being freed–but since they hadn’t been freed anyway, probably no additional harm is done.

static freeze() → None

‘Freezes’ all pointers currently stored so that they are no longer reported; only newly allocate pointers from this point on will appear in future information requests. This makes it easier to differentiate between continuous leaks and one-time memory allocations.

static showCurrentTypes() → None

Shows the breakdown of types of all of the active pointers.

static showTrendTypes() → None

Shows the breakdown of types of all of the pointers allocated and freed since the last call to freeze().

static showCurrentAges() → None

Shows the breakdown of ages of all of the active pointers.

static showTrendAges() → None

Shows the breakdown of ages of all of the pointers allocated and freed since the last call to freeze().

property tracking

Returns true if the MemoryUsage object is currently tracking memory (e.g. track-memory-usage is configured #t).

Return type

bool

property counting

Returns true if the MemoryUsage object is currently at least counting memory (e.g. this is a Windows debug build), even if it’s not fully tracking it.

Return type

bool

property current_cpp_size

Returns the total number of bytes of allocated memory consumed by C++ objects, not including the memory previously frozen.

Return type

size_t

property total_cpp_size

Returns the total number of bytes of allocated memory consumed by C++ objects, including the memory previously frozen.

Return type

size_t

property panda_heap_single_size

Returns the total number of bytes allocated from the heap from code within Panda, for individual objects.

Return type

size_t

property panda_heap_array_size

Returns the total number of bytes allocated from the heap from code within Panda, for arrays.

Return type

size_t

property panda_heap_overhead

Returns the extra bytes allocated from the system that are not immediately used for holding allocated objects. This can only be determined if ALTERNATIVE_MALLOC is enabled.

Return type

size_t

property panda_mmap_size

Returns the total number of bytes allocated from the virtual memory pool from code within Panda.

Return type

size_t

property external_size

Returns the total number of bytes of allocated memory in the heap that Panda didn’t seem to be responsible for. This includes a few bytes for very low-level objects (like ConfigVariables) that cannot use Panda memory tracking because they are so very low-level.

This also includes all of the memory that might have been allocated by a high-level interpreter, like Python.

This number is only available if Panda is able to hook into the actual heap callback.

Return type

size_t

property total_size

Returns the total size of allocated memory consumed by the process, as nearly as can be determined.

Return type

size_t