Python代码运行太慢,我需要找到一种方法来为Python进程分配更多内存吗?

我在64位windows 10笔记本电脑上使用64位3.6.3 python,内存为12 Gig。

我有可以提取zip文件(tar.gz)的python代码。如果我使用代码,它需要很长的时间(约1.5小时),但如果我直接使用7zip解压,它需要不到5分钟的时间,所以我猜有什么东西阻碍了python的处理能力。

我正在尝试运行此代码 https://github.com/tensorflow/tensorflow/blob/master/tensorflow/examples/udacity/1_notmnist.ipynb

为了方便起见,以下是用于解压缩的特定命令。

import tarfile

tar = tarfile.open(filename)
sys.stdout.flush()
tar.extractall(data_root)
tar.close()

这是完整的代码。

from __future__ import print_function
import os
import sys
import tarfile
from six.moves.urllib.request import urlretrieve


# Config the matplotlib backend as plotting inline in IPython

url = 'https://commondatastorage.googleapis.com/books1000/'
last_percent_reported = None
data_root = '.'  # Change me to store data elsewhere


def download_progress_hook(count, blockSize, totalSize):
    """A hook to report the progress of a download. This is mostly intended for users with
    slow internet connections. Reports every 5% change in download progress.
    """
    global last_percent_reported
    percent = int(count * blockSize * 100 / totalSize)

    if last_percent_reported != percent:
        if percent % 5 == 0:
            sys.stdout.write("%s%%" % percent)
            sys.stdout.flush()
        else:
            sys.stdout.write(".")
            sys.stdout.flush()

        last_percent_reported = percent


def maybe_download(filename, expected_bytes, force=False):
    """Download a file if not present, and make sure it's the right size."""
    dest_filename = os.path.join(data_root, filename)
    if force or not os.path.exists(dest_filename):
        print('Attempting to download:', filename)
        filename, _ = urlretrieve(url + filename, dest_filename, reporthook=download_progress_hook)
        print('\nDownload Complete!')
    statinfo = os.stat(dest_filename)
    if statinfo.st_size == expected_bytes:
        print('Found and verified', dest_filename)
    else:
        raise Exception(
            'Failed to verify ' + dest_filename + '. Can you get to it with a browser?')
    return dest_filename


train_filename = maybe_download('notMNIST_large.tar.gz', 247336696)
test_filename = maybe_download('notMNIST_small.tar.gz', 8458043)

num_classes = 10

def maybe_extract(filename, force=False):
  root = os.path.splitext(os.path.splitext(filename)[0])[0]  # remove .tar.gz
  if os.path.isdir(root) and not force:
    # You may override by setting force=True.
    print('%s already present - Skipping extraction of %s.' % (root, filename))
  else:
    print('Extracting data for %s. This may take a while. Please wait.' % root)
    tar = tarfile.open(filename)
    sys.stdout.flush()
    tar.extractall(data_root)
    tar.close()
  data_folders = [
    os.path.join(root, d) for d in sorted(os.listdir(root))
    if os.path.isdir(os.path.join(root, d))]
  if len(data_folders) != num_classes:
    raise Exception(
      'Expected %d folders, one per class. Found %d instead.' % (
        num_classes, len(data_folders)))
  print(data_folders)
  return data_folders

train_folders = maybe_extract(train_filename)
test_folders = maybe_extract(test_filename)

我在64位windows 10笔记本电脑上使用64位3.6.3 python,内存为12 Gig。