python garbage collection example

for manual recycling: Based on time. Periodically call garbage collection. Event-based. Call garbage collection in an event. For example, when a user disconnects from the server or knows that the application is going to a standstill. Recommended behaviorWh

Transfer from http://www.cnblogs.com/kaituorensheng/p/4449457.htmlIn Python, in order to solve the problem of memory leaks, object reference counts are used, and automatic garbage collection is implemented based on reference counting.　　memory leaks: also known as "storage leaks." A dynamically opened space with dynamic storage allocation functions is not released

references A with the B any of them, their reference count is 1 , but clearly should be recycled, examples:A = {} # A has a reference of 1the reference to B = {} # b is 1a[' B ' = b # b 's reference is increased by 1, andb is quoted as 2B[' a '] = a # A 's reference is increased by 1,a reference is 2The reference to Del a # A is minus 1,a 's reference is 1the reference to Del B # B is minus 1, and the reference for B is 1 .In this example , the D

accessed tagged, and then sweep the memory space, all unmarked objects released. 3, sub-generational technology The whole idea of generational recycling is that all memory blocks in the system are divided into different sets according to their survival time, each set becomes a "generation", and the garbage collection frequency decreases with the increase of the survival time of "generation",

Overview: Garbage collection is primarily done by reference counting, which means that when an object is not referenced by another object, it frees up memory. But there will be some circular reference objects, through the above method, there is no way to clear out. So, Python has another mechanism to solve this problem, that is, mark-erase. Mark-Clear: The main p

--python garbage collection mechanism#python GC module (garbagecollection)--garbage collection module #The main use of reference counting to track recycling garbage;1. Reference

A2 reference counts are 2, even if del A1,del A2, their reference count is 1, So we're still going to stay in memory and not be recycled. When we go through the second cycle, we will continue to create a copy of A1 and A2 in memory, constantly looping and discovering the larger the memory used by the program until the overflow crashes ." "Explore the garbage collection mechanism of ruby and PythonBoth Ruby

list, which can be gc.get_count() obtained.For example (488,3,0) , 488 it refers to the last generation of garbage checks, the number of Python allocated memory minus the number of freed memory, and the memory allocation, not the increase in the reference count . For example:Application Avoid circular references in projects Introduction of GC module

, and then sweep the memory space, all unmarked objects released.3 Generational TechnologyThe whole idea of generational recycling is that all memory blocks in the system are divided into different sets according to their survival time, each set becomes a "generation", and the garbage collection frequency decreases with the increase of the survival time of "generation", and the survival time is usually meas

are run for 10 minutes, and the following table summarizes the results of the three large gaps:Pause the effective working duration of the heap GC algorithm-Xmx12g-XX: + UseConcMarkSweepGC 89.8% 560 MS-Xmx12g-XX: + UseParallelGC 91.5% 1,104 MS-Xmx8g-XX: + UseConcMarkSweepGC 66.3% 1,610 MSIn the experiment, set different GC algorithms and different heap sizes, run the same code, and then measure the duration and throughput of the garbage

There are three main Python garbage collection mechanisms, the first is to use reference counting to track and recycle garbage, in order to solve the loopReferring to the problem, the use of the tag-clear method, the tag-purge method brings additional operations to the total memory in the system actuallyThe total numbe

Reference count Python's default garbage collection mechanism is reference counting, and each object maintains a ob_ref field. Its advantage is that the mechanism is simple, when the new reference point to the object, the reference count plus 1, when an object's reference is destroyed minus 1, once the object's reference count is 0, the object is immediately reclaimed, the memory will be freed. The disadva

Reference count Python's default garbage collection mechanism is reference counting, and each object maintains a ob_ref field. Its advantage is that the mechanism is simple, when the new reference point to the object, the reference count plus 1, when an object's reference is destroyed minus 1, once the object's reference count is 0, the object is immediately reclaimed, the memory will be freed. The disadvan

Reference count python The default garbage collection mechanism is reference count, and each object maintains a ob_ref field. Its advantage is that the mechanism is simple, and when a new reference points to the object, the reference count reference countPython's default garbage co