Cyclic GC issues

A mystery to be debugged soon:

import pandas as pd
import numpy as np

arr = np.random.randn(100000, 5)

def leak():
    for i in xrange(10000):
        df = pd.DataFrame(arr.copy())
        result = df.xs(1000)
        # result = df.ix[5000]

if __name__ == '__main__':
    leak()

[alanjds]

For the record, we (+@sbneto) are using this in preduction for a bit of time, and is doing very good:

# monkeypatches.py

# Solving memory leak problem in pandas
# https://github.com/pandas-dev/pandas/issues/2659#issuecomment-12021083
import pandas as pd
from ctypes import cdll, CDLL
try:
    cdll.LoadLibrary("libc.so.6")
    libc = CDLL("libc.so.6")
    libc.malloc_trim(0)
except (OSError, AttributeError):
    libc = None

__old_del = getattr(pd.DataFrame, '__del__', None)

def __new_del(self):
    if __old_del:
        __old_del(self)
    libc.malloc_trim(0)

if libc:
    print('Applying monkeypatch for pd.DataFrame.__del__', file=sys.stderr)
    pd.DataFrame.__del__ = __new_del
else:
    print('Skipping monkeypatch for pd.DataFrame.__del__: libc or malloc_trim() not found', file=sys.stderr)

[wesm]

Ok, this is, in a word, f*cked up. If I add gc.collect to that for loop it stops leaking memory:

import pandas as pd
import numpy as np
import gc

arr = np.random.randn(100000, 5)

def leak():
    pd.util.testing.set_trace()
    for i in xrange(10000):
        df = pd.DataFrame(arr.copy())
        result = df.xs(1000)
        gc.collect()
        # result = df.ix[5000]

if __name__ == '__main__':
    leak()

There are objects here that only get garbage collected when the cyclic GC runs. What’s the solution here, break cycle explicitly in __del__ so the Python memory allocator stops screwing us?