Python：文本文件替换多行中的不同字符串如何？

Question

基本任务：将 URL 请求转换为文本，并将其转储为文本文件（几乎是可用的 CSV）。

目标：干净的 CSV。在多行上，我试图替换多个（不同的）字符：

括号， 波浪号 (~), 每行末尾的额外逗号。

我找不到任何相对简单的示例来完成此操作。寻找可以逐行循环并替换的东西。

请注意：我预计此文件会随着时间的推移而变大，因此对内存不友好。

以下是创建文件的代码：

import urllib.request
with urllib.request.urlopen(URL1) as response:
    data = response.read()
decoded_data = data.decode(encoding='UTF-8')

str_data = str(decoded_data)
saveFile = open("test.txt",'w')
saveFile.write(str_data)
saveFile.close()

这是文件中的一个简化示例，第一行是字段名，第二行和第三行代表记录。

[["F1","F2","F3","F4","F5","F6"],

["string11","string12","string13","s~ring14","string15","string16"],

["string21","string22","s~ring23","string24","string25","string26"]]

Answer 1

如果要替换字符串开头或结尾的字符，请使用strip。如果要删除的字符具有任意位置，请改用replace，如下所示：line.replace("~","")。请注意，与strip 不同，您不能在一个replace 调用中指定多个字符，但可以将它们链接起来，如下所示：line.replace("~","").replace(",","").replace("[","")

只是一个可能对你有用的快速模型：

with open("text.txt", 'r') as f:
    with open("result.txt", 'w') as new_f:
        for line in f:
            new_line = line.strip(" [],\n\t\r").replace("~","")
            print(new_line)
            new_f.write(new_line+"\n")

因为我看到波浪号可以在任何地方，括号和逗号通常出现在末尾。我还在strip 中添加了“\n”、“\t”、“\r”和一个空格，因为这些字符可能（至少，“\n”肯定会出现在每一行的末尾）。

Answer 2

您可以使用简单的 for 循环来遍历文件。然后你可以替换每一行中的字符

file = open("text.txt", "r")
clean_txt = ""
for line in file:
    line = line.replace("~", "").replace("[","").replace("]","")
    line[len(line)-1] = "" #Replace the last character of the line.
file.close
w = open("text.txt", "w")
w.write(clean_txt)
w.close

Answer 3

#!/usr/bin/env python3

# Note, I used the print function as a way to visually confirm the code worked.
# the URL_call will yield a byte that has serialized data for a basic table (columns and rows, where first row are column names -- just like Excel or SQL)

URL_call = ("http://www.zzz.com/blabla.html")

# URLIB module & function: the request has to be first decoded from UTF-8
import urllib.request
with urllib.request.urlopen(URL_call) as response:
    URL_data = response.read()

URL_data_decoded = URL_data.decode(encoding='UTF-8')

# use json to convert decoded response into a python structure (from a JSON structure)
import json
URL_data_JSON = json.loads(URL_data_decoded)

# pandas will transition the python data structure from a "list-like" array to a table.
import pandas as pd
URL_data_panda = pd.DataFrame(URL_data_JSON)

# this will create the text (in this case a CSV) file
URL_data_panda.to_csv("test.csv")

# The file will need the first row removed (columns are indexed coming out of the panda)

#determine line count
num_lines = sum(1 for line in open("test.csv"))

print(num_lines)

# the zero position is assigned to the first row of text. Writing from the second row (indexed as 1) get the removal done.
lines = open("test.csv").readlines()
open("test2.csv","w").writelines(lines[1:(num_lines)])


# Changes the name of the first column from zero to a normalized name.

import fileinput

# Note, below you could setup a back-up file, in the file input, by adding an extra argument in the parens ("test2.csv", inplace=True, backup='.bak')
with fileinput.FileInput("test2.csv", inplace=True) as file:
    for line in file:
        print(line.replace("0,", "REC_NUM,"), end='')