我更新了我的问题：我有一个XML文件，其中包含几个标题。但是，这些标题是法语，而不是英语，像这样：

<entity name="MissionTemplate">
  <string name="code" required="true" title="Bond Restitution Date"/>
  <string name="description" namecolumn="true" title="Description"/>

我想用英语翻译每个标题。为了使它，我有一个翻译的CSV文件，我必须使用它来翻译XML文件。这个CSV文件不在最终的应用程序中，只是在我的计算机本地，它只是用来获得正确的翻译。下面是一个示例：

Table;Champ;Anglais;Français

"HeaderTable8011405";"Code";"Code";"Code"

"HeaderTable8011405";"Activity_Type";"Auction,Mission";"Vente,Mission"

"HeaderTable8011405";"Activity_Type";"Activity Type";"Type activité"
...

我还有另一个CSV翻译的文件，其中包含英语单词和法语单词之间的对应关系。它在最终应用程序中。因此，当用户更改语言时，此文件用于翻译应用程序。下面是该文件的示例：

"key","message","comment","context"
"Code","Code",,
"Auction,Mission","Vente,Mission",, 
"Activity Type","Type activité",,
...

我必须在XML文件中获得法语标题，并在本地CSV文件（第一个CSV翻译的文件）中搜索它。如果有法语标题，我就复制英语翻译，并替换XML文件中的法语翻译。最后，我必须在第二个CSV翻译文件（用于在英语和法语之间切换的文件）中添加一个新行，第一列是英语单词，第二列是法语单词。总结一下，有3个文件：一个XML文件（包含几个标题），一个CSV本地文件，其中包含良好的翻译（不在我的应用程序中，只是用来获得正确的英语翻译），另一个CSV文件，其中包含英语和法语单词之间的对应关系（它在应用程序中使用两种语言之间的切换：英文和法文）。
我可以手工制作这个以前的任务，因为它是如此繁琐和耗时.
所以，我试着创建一个Python程序来代替我完成这个任务。代码如下：

from bs4 import BeautifulSoup
import pandas as pd
import csv

xml_file = input("Give here the name of the XML file which you want translate : ")
translations_file = input("Give here the name of the translation's file : ")
final_translations_file = input("Give here the name of the final translation's file : ")

# Reading the data inside the xml
# file to a variable under the name
# data
with open('MissionTemplate_model.xml', 'r') as f:
    data = f.read()

# Passing the stored data inside
# the beautifulsoup parser, storing
# the returned object
data = BeautifulSoup(data, "xml")

# Title list
title_list = []

# Get each title in the XML file
for element in data.find_all():
    if 'title' in element.attrs:
        title_content = element['title']
        title_list.append(title_content)

# Check if the title is translated
missing_translations = []
translation_list= pd.read_csv(translations_file,delimiter=';')
translation_fr_list = translation_list.Français
translation_en_list = translation_list.Anglais
header = ['key', 'message', 'comment', 'context']
additional_data = []
for each_title in title_list:
    found = False
    lineNb = 0
    for each_translation in translation_fr_list:
        # It's all right
        if each_title == each_translation: 
            found = True
            translation_en = translation_en_list[lineNb]
            translation_fr = each_translation
            for element in data.find_all():
                if 'title' in element.attrs and element['title'] == translation_fr:
                    # Set the title in the XML file
                    element['title'] = translation_en
                    # Add couple of translation in the additional data's list
                    additional_data.append([translation_en,translation_fr,None,None])
            continue
        lineNb = lineNb + 1
    # Else
    if found == False:
        missing_translations.append(each_title)
# Load the CSV file using pandas
df = pd.read_csv(final_translations_file)
# Create a DataFrame from additional_data
additional_df = pd.DataFrame(additional_data, columns=header)
# Add the news datas at the end of the existing DataFrame
updated_df = pd.concat([df, additional_df], ignore_index=True)
# Save the updated DataFrame in the CSV file 
updated_df = updated_df.applymap(lambda x: ' '.join(x.strip().split()) if isinstance(x, str) else x)
updated_df.to_csv(final_translations_file, index=False, quoting=csv.QUOTE_NONE, escapechar=' ')




# Load the CSV file using pandas
df = pd.read_csv(final_translations_file, sep=',', skipinitialspace=True)

# Function to check if a string begins and ends by double quotes
def has_quotes(s):
    return s.startswith('"') and s.endswith('"')

# Explore the lines of the DataFrame
for index, row in df.iterrows():
    # Check if the two first columns doesn't already have double quotes
    if not has_quotes(row[0]) and not has_quotes(row[1]):
        # Modify this line
        df.iloc[index, :2] = '"' + df.iloc[index, :2] + '"'

# Save the modified DataFrame as new csv file 
df.to_csv(final_translations_file, index=False, quoting=csv.QUOTE_NONE, escapechar=' ')

# Open again the file in read/write mode
with open(final_translations_file, "r+") as f:
    # Read the current content of the file

    content = f.read()

    # Find the first line's position (up to the first occurence of \n)
    first_line_end = content.find("\n") + 1

    # Extract the first line and check if it contains double quotes
    first_line = content[:first_line_end]
    if not has_quotes(first_line):
        modified_first_line = '"' + '","'.join(first_line.strip().split(",")) + '"\n'

        # Replace the first line by the modified 
        f.seek(0)
        f.write(modified_first_line)
        f.write(content[first_line_end:])




# Replace the content of the XML original XML file by the modified content
modified_xml_file = data.prettify()
with open(xml_file, 'w') as f:
    f.write(modified_xml_file)

# Write the missing translations in a file
with open('missing_translations.txt','w') as f:
    missing_translations.insert(0,xml_file+":\n") # Add the name of the file at the begining of the missing translations's list
    missing_translations_string = '\n'.join(missing_translations) # Tranform the list to string
    f.write(missing_translations_string)

没关系，但在第二个CSV文件（应用程序内部使用的CSV文件）中的每个单词之间存在不需要的空格，例如：

"key","message","comment","context"
"Code","Code",,
"Auction,    Mission","Vente,    Mission",, 
"Activity    Type","Type    activité",,

我尝试了很多解决方案，在使用split（）函数创建文件后删除每个空格，但它不起作用...
你能帮帮我吗？
谢谢你，谢谢！