如何将python中的for循环的输出写入csv格式的文件？

Question

下面是python脚本，它标识在不同文件列表中是否找到了某些单词。

experiment=open('potentiation.txt')
lines=experiment.read().splitlines()
receptors=['crystal_1.txt', 'modeller_1.txt', 'moe_1.txt',
           'nci5_modeller0000_1.txt', 'nci5_modeller0001_1.txt',
           'nci5_modeller0002_1.txt', 'nci5_modeller0003_1.txt',
           'nci5_modeller0004_1.txt', 'nci5_modeller0005_1.txt',
           'nci5_modeller0006_1.txt', 'nci5_modeller0007_1.txt',
           'nci5_modeller0008_1.txt', 'nci5_modeller0009_1.txt',
           'nci5_modeller0010_1.txt', 'nci5_modeller0011_1.txt',
           'nci5_moe0000_1.txt', 'nci5_moe0001_1.txt', 'nci5_moe0002_1.txt',
           'nci5_moe0003_1.txt', 'nci5_moe0004_1.txt', 'nci5_moe0005_1.txt',
           'nci5_moe0006_1.txt', 'nci5_moe0007_1.txt', 'nci5_moe0008_1.txt',
           'nci5_moe0009_1.txt', 'nci5_moe0010_1.txt', 'nci5_moe0011_1.txt',
           'nci5_moe0012_1.txt', 'nci5_moe0013_1.txt', 'nci5_moe0014_1.txt']

for ligand in lines:
    for protein in receptors:
        file1=open(protein,"r")
        read1=file1.read()
        find_hit=read1.find(ligand)
        if find_hit == -1:
            print ligand,protein,"Not Found"
        else:
            print ligand,protein, "Found"

下面是此代码输出的一个示例：

345647 nci5_moe0012_1.txt Not Found
345647 nci5_moe0013_1.txt Not Found
345647 nci5_moe0014_1.txt Found

我的问题是如何获取输出并将其格式化为如下示例所示的csv文件？

Ligand  nci5_moe0012_1. nci5_moe_0013_1   nci5_moe_0014
345647  Not Found        Not Found        Found

Answer 1

我认为这样的操作(假设您的输出文件是制表符分隔的)：

import csv
import os

receptors = ['crystal_1', 'modeller_1', 'moe_1',
             'nci5_modeller0000_1', 'nci5_modeller0001_1',
             'nci5_modeller0002_1', 'nci5_modeller0003_1',
             'nci5_modeller0004_1', 'nci5_modeller0005_1',
             'nci5_modeller0006_1', 'nci5_modeller0007_1',
             'nci5_modeller0008_1', 'nci5_modeller0009_1',
             'nci5_modeller0010_1', 'nci5_modeller0011_1',
             'nci5_moe0000_1', 'nci5_moe0001_1', 'nci5_moe0002_1',
             'nci5_moe0003_1', 'nci5_moe0004_1', 'nci5_moe0005_1',
             'nci5_moe0006_1', 'nci5_moe0007_1', 'nci5_moe0008_1',
             'nci5_moe0009_1', 'nci5_moe0010_1', 'nci5_moe0011_1',
             'nci5_moe0012_1', 'nci5_moe0013_1', 'nci5_moe0014_1']

with open('potentiation.txt', 'rt') as experiment, \
     open('output.csv', 'wb') as outfile:
    csv_writer = csv.writer(outfile, delimiter='\t')
    csv_writer.writerow(['Ligand'] + receptors)  # header row
    for ligand in (line.rstrip() for line in experiment):
        row = [ligand]
        for protein in receptors:
            with open(protein+'.txt', "rt") as file1:
                found = ['Found', 'Not Found'][file1.read().find(ligand) == -1]
                row.append(found)
        csv_writer.writerow(row)

print('output.csv file written')

更新

正如我在一条评论中所说，只要只读一次蛋白质文件，就可以更快地完成这一任务。为了能够做到这一点，并以你想要的方式格式化输出，检查每个文件中每个配体的结果需要存储在一个数据结构中，当每个文件被读取，然后被多次检查时，每一个配体都需要存储在一个数据结构中，最后被写出来，一次又一次地完成。一份简单的清单足以满足这一目的，并已在下面的实施中使用.

交换的方法是使用更多的内存，而不是一遍又一遍地阅读和重读蛋白质文件。由于磁盘IO通常是计算机上最慢的东西之一，所以只要代码复杂度稍微增加，就有可能获得很大的性能增益。

下面是显示这个替代版本的代码：

import csv
import os

receptors = ['crystal_1', 'modeller_1', 'moe_1',
             'nci5_modeller0000_1', 'nci5_modeller0001_1',
             'nci5_modeller0002_1', 'nci5_modeller0003_1',
             'nci5_modeller0004_1', 'nci5_modeller0005_1',
             'nci5_modeller0006_1', 'nci5_modeller0007_1',
             'nci5_modeller0008_1', 'nci5_modeller0009_1',
             'nci5_modeller0010_1', 'nci5_modeller0011_1',
             'nci5_moe0000_1', 'nci5_moe0001_1', 'nci5_moe0002_1',
             'nci5_moe0003_1', 'nci5_moe0004_1', 'nci5_moe0005_1',
             'nci5_moe0006_1', 'nci5_moe0007_1', 'nci5_moe0008_1',
             'nci5_moe0009_1', 'nci5_moe0010_1', 'nci5_moe0011_1',
             'nci5_moe0012_1', 'nci5_moe0013_1', 'nci5_moe0014_1']

# initialize list of lists holding each ligand and its presence in each receptor
with open('potentiation.txt') as experiment:
    ligands = [[ligand] for ligand in (line.rstrip() for line in experiment)]

for protein in receptors:
    with open(protein + '.txt') as protein_file:
        protein_file_data = protein_file.read()
        for row in ligands:
            # determine if this ligand (row[0]) appears in protein data
            row.append('Found' if row[0] in protein_file_data else 'Not Found')

with open('output.csv', 'wb') as outfile:
    csv_writer = csv.writer(outfile, delimiter='\t')
    csv_writer.writerow(['Ligand'] + receptors)  # header row
    csv_writer.writerows(ligands)

print('output.csv file written')

Answer 2

在将“蛋白质”和“配体”的值添加到适当的列表(在0索引中)之后，可以将结果保存在列表中(一个列表用于配体，一个用于蛋白质)。在很容易保存文本文件之后。

为了保存您，请打开一个文件，以便在字符串中写入和转换列表：

my_string = " ".join(map(str, lst))

然后保存my_string (并对每个列表执行此操作)