以下是对具有 10^6 行和 10 列 (n=50) 的约 200 MB CSV 文件的三种建议解决方案的比较。
对于较大和较小的文件(10 MB 到 8 GB),该比率大致相同。
cp:shutil:csv_reader 1:10:55
即使用内置的 cp 函数比使用 Python 的 csv 模块快大约 55 倍。
电脑:
- 普通硬盘
- Python 3.5.2 64 位
- Ubuntu 16.04
- i7-3770
import csv
import random
import shutil
import time
import subprocess
rows = 1 * 10**3
cols = 10
repeats = 50
shell_script = '/tmp/csv.sh'
input_csv = '/tmp/temp.csv'
output_csv = '/tmp/huge_output.csv'
col_titles = ['titles_' + str(i) for i in range(cols)]
with open(shell_script, 'w') as f:
f.write("#!/bin/bash\necho '{0}' > {1}\ncat {2} >> {1}".format(','.join(col_titles), output_csv, input_csv))
with open(shell_script, 'w') as f:
f.write("echo '{0}' > {1}\ncat {2} >> {1}".format(','.join(col_titles), output_csv, input_csv))
subprocess.call(['chmod', '+x', shell_script])
run_times = dict([
('csv_writer', list()),
('external', list()),
('shutil', list())
])
def random_csv():
with open(input_csv, 'w') as csvfile:
csv_writer = csv.writer(csvfile, delimiter=',')
for i in range(rows):
csv_writer.writerow([str(random.random()) for i in range(cols)])
with open(output_csv, 'w'):
pass
for r in range(repeats):
random_csv()
#http://stackoverflow.com/a/41982368/2776376
start_time = time.time()
with open(input_csv) as fr, open(output_csv, "w", newline='') as fw:
cr = csv.reader(fr)
cw = csv.writer(fw)
cw.writerow(col_titles)
cw.writerows(cr)
run_times['csv_writer'].append(time.time() - start_time)
random_csv()
#http://stackoverflow.com/a/41982383/2776376
start_time = time.time()
subprocess.call(['bash', shell_script])
run_times['external'].append(time.time() - start_time)
random_csv()
#http://stackoverflow.com/a/41982383/2776376
start_time = time.time()
with open('header.txt', 'w') as header_file:
header_file.write(','.join(col_titles))
with open(output_csv, 'w') as new_file:
with open('header.txt', 'r') as header_file, open(input_csv, 'r') as main_file:
shutil.copyfileobj(header_file, new_file)
shutil.copyfileobj(main_file, new_file)
run_times['shutil'].append(time.time() - start_time)
print('#'*20)
for key in run_times:
print('{0}: {1:.2f} seconds'.format(key, run_times[key][-1]))
print('#'*20)
print('Averages')
for key in run_times:
print('{0}: {1:.2f} seconds'.format(key, sum(run_times[key])/len(run_times[key])))
如果您真的想在 Python 中执行此操作,可以先创建头文件,然后通过 shutil.copyfileobj 将其与您的第二个文件合并。
import shutil
with open('header.txt', 'w') as header_file:
header_file.write('col1;col2;col3')
with open('new_file.csv', 'w') as new_file:
with open('header.txt', 'r') as header_file, open('main.csv', 'r') as main_file:
shutil.copyfileobj(header_file, new_file)
shutil.copyfileobj(main_file, new_file)