Rememberme is a handy tool for memory problems in Python.
Project description
Remember Me
RememberMe is a handy tool for memory problems in Python. It computes the total memory usage of Python objects.
RememberMe is a replacement for sys.getsizeof
sys.getsizeof
is almost confusing in Python:
import sys a = [1, 2, 3] b = [a, a, a] print(sys.getsizeof(a) == sys.getsizeof(b)) # Can you believe the result is `True`?
While rememberme
gives you a clear idea how large an object is.
from rememberme import memory a = [1, 2, 3] b = [a, a, a] print(memory(a)) # 172 bytes! print(memory(b)) # 260 bytes!
Installation
pip install rememberme
More features
Check out memory usage in the current frame:
from rememberme import memory def foo(): a = [1, 2, 3] b = [a, a, a] print memory() foo() # 260 bytes. Note `a` is included in `b`.
Check out top memory consumers:
from rememberme import top def foo(): a = [1, 2, 3] b = [a, a, a] mem_top = top() # with no args, check current frame print(mem_top[0]) # `b` and its memory usage print(mem_top[1]) # `a` and its memory usage
Even pretty print the result!
from rememberme import mem_print def foo(): a = [1, 2, 3] b = [a, a, a] mem_print(b) foo()
Output:
┌int (28.0B)
┌list (172.0B)┼int (28.0B)
│ └int (28.0B)
│ ┌int (28.0B)
list (260.0B)┼list (172.0B)┼int (28.0B)
│ └int (28.0B)
│ ┌int (28.0B)
└list (172.0B)┼int (28.0B)
└int (28.0B)
Known issues and limitations
- For better performance (and making better sense), the global dict, as well as modules, are not included in the memory usage of any objects.
- We essentially relies on
tp_traverse
to traverse the object graph. For C extensions, memory usage might be underestimated under various circumstances. For the most commonnumpy.ndarray
, a specific procedure is defined to probe the memory usage correctly, but no correctness is guaranteed for other C extensions, which may have undetectable momery leaks within themselves.
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