使用pandas创建缓冲区时出现内存泄漏？

Question

我正在使用熊猫做环形缓冲区,但内存使用量不断增长.我究竟做错了什么？

这是代码(从问题的第一篇文章稍微编辑):

import pandas as pd
import numpy as np
import resource


tempdata = np.zeros((10000,3))
tdf = pd.DataFrame(data=tempdata, columns = ['a', 'b', 'c'])

i = 0
while True:
    i += 1
    littledf = pd.DataFrame(np.random.rand(1000, 3), columns = ['a', 'b', 'c'])
    tdf = pd.concat([tdf[1000:], littledf], ignore_index = True)
    del littledf
    currentmemory = resource.getrusage(resource.RUSAGE_SELF).ru_maxrss
    if i% 1000 == 0:
        print 'total memory:%d kb' % (int(currentmemory)/1000)

这就是我得到的:

total memory:37945 kb
total memory:38137 kb
total memory:38137 kb
total memory:38768 kb
total memory:38768 kb
total memory:38776 kb
total memory:38834 kb
total memory:38838 kb
total memory:38838 kb
total memory:38850 kb
total memory:38854 kb
total memory:38871 kb
total memory:38871 kb
total memory:38973 kb
total memory:38977 kb
total memory:38989 kb
total memory:38989 kb
total memory:38989 kb
total memory:39399 kb
total memory:39497 kb
total memory:39587 kb
total memory:39587 kb
total memory:39591 kb
total memory:39604 kb
total memory:39604 kb
total memory:39608 kb
total memory:39608 kb
total memory:39608 kb
total memory:39608 kb
total memory:39608 kb
total memory:39608 kb
total memory:39612 kb

不确定它是否与此相关:

https://github.com/pydata/pandas/issues/2659

使用Anaconda Python在MacBook Air上测试

Answer 1

为什么不直接更新DataFrame，而不是使用concat呢？ 将确定您写入每个更新的 1000 行槽。i % 10

i = 0
while True:
    i += 1
    tdf.iloc[1000*(i % 10):1000+1000*(i % 10)] = np.random.rand(1000, 3)
    currentmemory = resource.getrusage(resource.RUSAGE_SELF).ru_maxrss
    if i% 1000 == 0:
        print 'total memory:%d kb' % (int(currentmemory)/1000)