用python编写大字符串 [英] Writing huge strings in python

问题描述

我有一个很长的字符串，几乎有 1 兆字节长，我需要将其写入文本文件.常规

I have a very long string, almost a megabyte long, that I need to write to a text file. The regular

file = open("file.txt","w")
file.write(string)
file.close()

可以用，但是太慢了，有什么方法可以写得更快吗?

works but is too slow, is there a way I can write faster?

我正在尝试将数百万位数字写入文本文件该数字的顺序为 math.factorial(67867957)

I am trying to write a several million digit number to a text file the number is on the order of math.factorial(67867957)

这是在分析中显示的内容:

This is what shows on profiling:

    203 function calls (198 primitive calls) in 0.001 seconds

   Ordered by: standard name

   ncalls  tottime  percall  cumtime  percall filename:lineno(function)
        1    0.000    0.000    0.000    0.000 <string>:1(<module>)
        1    0.000    0.000    0.000    0.000 re.py:217(compile)
        1    0.000    0.000    0.000    0.000 re.py:273(_compile)
        1    0.000    0.000    0.000    0.000 sre_compile.py:172(_compile_charset)
        1    0.000    0.000    0.000    0.000 sre_compile.py:201(_optimize_charset)
        4    0.000    0.000    0.000    0.000 sre_compile.py:25(_identityfunction)
      3/1    0.000    0.000    0.000    0.000 sre_compile.py:33(_compile)
        1    0.000    0.000    0.000    0.000 sre_compile.py:341(_compile_info)
        2    0.000    0.000    0.000    0.000 sre_compile.py:442(isstring)
        1    0.000    0.000    0.000    0.000 sre_compile.py:445(_code)
        1    0.000    0.000    0.000    0.000 sre_compile.py:460(compile)
        5    0.000    0.000    0.000    0.000 sre_parse.py:126(__len__)
       12    0.000    0.000    0.000    0.000 sre_parse.py:130(__getitem__)
        7    0.000    0.000    0.000    0.000 sre_parse.py:138(append)
      3/1    0.000    0.000    0.000    0.000 sre_parse.py:140(getwidth)
        1    0.000    0.000    0.000    0.000 sre_parse.py:178(__init__)
       10    0.000    0.000    0.000    0.000 sre_parse.py:183(__next)
        2    0.000    0.000    0.000    0.000 sre_parse.py:202(match)
        8    0.000    0.000    0.000    0.000 sre_parse.py:208(get)
        1    0.000    0.000    0.000    0.000 sre_parse.py:351(_parse_sub)
        2    0.000    0.000    0.000    0.000 sre_parse.py:429(_parse)
        1    0.000    0.000    0.000    0.000 sre_parse.py:67(__init__)
        1    0.000    0.000    0.000    0.000 sre_parse.py:726(fix_flags)
        1    0.000    0.000    0.000    0.000 sre_parse.py:738(parse)
        3    0.000    0.000    0.000    0.000 sre_parse.py:90(__init__)
        1    0.000    0.000    0.000    0.000 {built-in method compile}
        1    0.001    0.001    0.001    0.001 {built-in method exec}
       17    0.000    0.000    0.000    0.000 {built-in method isinstance}
    39/38    0.000    0.000    0.000    0.000 {built-in method len}
        2    0.000    0.000    0.000    0.000 {built-in method max}
        8    0.000    0.000    0.000    0.000 {built-in method min}
        6    0.000    0.000    0.000    0.000 {built-in method ord}
       48    0.000    0.000    0.000    0.000 {method 'append' of 'list' objects}
        1    0.000    0.000    0.000    0.000 {method 'disable' of '_lsprof.Profiler' objects}
        5    0.000    0.000    0.000    0.000 {method 'find' of 'bytearray' objects}
        1    0.000    0.000    0.000    0.000 {method 'items' of 'dict' objects}

推荐答案

您的问题是 str(long) 对于 Python 中的大整数(数百万位)非常慢.它是 Python 中的二次运算(位数)，即，对于 ~1e8 位数，它可能需要 ~1e16 操作才能将整数转换为十进制字符串.

Your issue is that str(long) is very slow for large intergers (millions of digits) in Python. It is a quadratic operation (in number of digits) in Python i.e., for ~1e8 digits it may require ~1e16 operations to convert the integer to a decimal string.

写入一个 500MB 的文件应该不需要几个小时，例如:

Writing to a file 500MB should not take hours e.g.:

$ python3 -c 'open("file", "w").write("a"*500*1000000)'

几乎立即返回.ls -l file 确认文件已创建并且具有预期的大小.

returns almost immediately. ls -l file confirms that the file is created and it has the expected size.

计算math.factorial(67867957)(结果有~500M 位)可能需要几个小时，但使用pickle 保存它是即时的:

Calculating math.factorial(67867957) (the result has ~500M digits) may take several hours but saving it using pickle is instantaneous:

import math
import pickle

n = math.factorial(67867957) # takes a long time
with open("file.pickle", "wb") as file:
    pickle.dump(n, file) # very fast (comparatively)

使用 n = pickle.load(open('file.pickle', 'rb')) 重新加载它需要不到一秒钟的时间.

To load it back using n = pickle.load(open('file.pickle', 'rb')) takes less than a second.

str(n) 仍在我的机器上运行(50 小时后).

str(n) is still running (after 50 hours) on my machine.

要快速获得十进制表示，您可以使用 gmpy2:

To get the decimal representation fast, you could use gmpy2:

$ python -c'import gmpy2;open("file.gmpy2", "w").write(str(gmpy2.fac(67867957)))'

在我的机器上不到 10 分钟.

It takes less than 10 minutes on my machine.

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