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Have a look at this article Partition of a set of 418 objects Tracing python memory leaks also, note that the garbage collection module actually can have debug flags set

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Look at the set_debug function A doctorthread shows me these (shortened) results Additionally, look at this code by gnibbler for determining the types of objects that have been created after a call.

I don't have a code example, but i'm curious whether it's possible to write python code that results in essentially a memory leak.

To find out if there is a memory leak, we call the endpoint 'foo' multiple times and measure the memory usage before and after the api calls Also, we will take two tracemalloc snapshots Tracemalloc is a debug tool to trace memory blocks allocated by python. 1 memory profiling using tracemalloc tracemalloc is a package included in the python standard library

This will catch some uninitialized reads, some use after free, some buffer under/overflows, etc, but won't report leaks and won't touch memory that isn't allocated through python (when using glibc, the malloc_perturb_ and malloc_check_ environment variables might help there) see also Details of the available values 3.6 release notes with usage. I have a python program that runs a series of experiments, with no data intended to be stored from one test to another My code contains a memory leak which i am completely unable to find (i've look at the other threads on memory leaks).

To help others find the explanation

The cache may retain instance references, preventing garbage collection. Python memory profiler i've got a fairly complex (about 20,000) line python program which after some development has started consuming increasing amounts of memory when it r. Python itself is memory safe, if you stay away from native extensions It is also safe from memory leaks, except for a few edge cases.

I have a pretty big multithreading python project that apparently has a memory leak somewhere