为什么追加到文本文件时最后一行重复？

Question

当我将最后一行附加到文本文件中时，我的代码正在复制它

下面是一个输入文件示例

[headline - https://www.rfa.org/cantonese/news/us-pompeo-06012020072305.html]
This
some-text-here

[date - https://www.rfa.org/cantonese/news/us-pompeo-06012020072305.html]
https://www.rfa.org/cantonese/news/us-pompeo-06012020072305.html/US-Pompeo.mp3

[headline - https://www.rfa.org/cantonese/news/htm/tw-uk-06012020113435.html]
Is
some-text-here

[date - https://www.rfa.org/cantonese/news/htm/tw-uk-06012020113435.html]
https://www.rfa.org/cantonese/news/htm/tw-uk-06012020113435.html/tw-su.mp3

[headline - https://www.rfa.org/cantonese/news/wang-06012020103828.html]
Test
some-text-here

[date - https://www.rfa.org/cantonese/news/wang-06012020103828.html]
https://www.rfa.org/cantonese/news/wang-06012020103828.html/wang.mp3

[headline - https://www.rfa.org/cantonese/news/us-wang-06012020135251.html]
TEST
some-text-here

[headline - https://www.rfa.org/cantonese/news/htm/hk-chan-06012020073718.html]
TEST
some-text-here

[headline - https://www.rfa.org/cantonese/news/ear/ear-state-06012020035108.html]
TEST
some-text-here

[date - https://www.rfa.org/cantonese/news/ear/ear-state-06012020035108.html]
https://www.rfa.org/cantonese/news/ear/ear-state-06012020035108.html/EarState.mp3

[headline - https://www.rfa.org/cantonese/news/htm/hk-innocent-06012020114634.html]
TEST
some-text-here

但是，出于某种原因，输出文件总是附加最后一行两次。我为ear-state-06012020035108.txt得到这个

TEST
some-text-here
some-text-here

您可以看到这里的一些文本正在被复制。我只是想把所有的文本都放到一个文本文件中。然而，出于某种原因，它只在底部添加最后一行两次

这是我的密码

import pandas as pd
import os
import re
import requests

def tabulate_headlines(text="", filename="", verbose=0):
    """Tabulates the information from either a text string (text) or from the
    text read from a file (filename) and returns a dataframe.

    Example:
        # Case: from text
        df = tabulate_headlines(text=s, filename="", verbose=1)
        # Case: from a file
        df = tabulate_headlines(text="", filename="input.txt", verbose=1)
    """

    ## Read text from input file
    if not text and (filename is not None):
        with open(filename, "r") as f:
            text = f.read()
    if text is not None:
        ## Define regex patterns for
        #  - headline-text and corresponding source-id
        #  - headline_url
        #  - date_url
        #  - mp3_url
        #  - source_id from (headline, date and mp3)
        headline_text_pat = r"\n?\[headline - https://.*/(.*?)\.html\]\n((.*\n)+?)\n"
        headline_pat = r".*\[headline - (https://.*?\.html?)[,\]]"
        date_pat = r".*\[date - (https://.*?\.html?)[,\]]"
        mp3_pat = r".*\n(https://.*?\.html/.*?\.mp3)\s*\n"
        source_id_pat = r"https://.*/(.*?)\.html" # headline, date
        source_id_pat_mp3 = r"https://.*/(.*?).html/.*?\.mp3" # mp3

        ## Compile regex-patterns for speed
        headline_text_pat = re.compile(headline_text_pat)
        headline_pat = re.compile(headline_pat)
        date_pat = re.compile(date_pat)
        mp3_pat = re.compile(mp3_pat)
        source_id_pat = re.compile(source_id_pat)
        source_id_pat_mp3 = re.compile(source_id_pat_mp3)

        ## Extract headlines (texts)
        #  and store in a pandas.Series object: headlines
        headline_data = headline_text_pat.findall(text + '\n[')
        headline_texts = []
        source_ids = []
        for headline in headline_data:
            source_id, headline_text = headline[0], ''.join(headline[1:]).strip()
            headline_texts.append(headline_text)
            source_ids.append(source_id)
        # Save as a pandas.Series object: headlines
        headlines = pd.Series(data=headline_texts, index=source_ids)

        ## Extract the urls (for headline, date, mp3)
        headline_urls = headline_pat.findall(text)
        date_urls = date_pat.findall(text)
        mp3_urls = mp3_pat.findall(text)

        ## Make temporary dataframes
        df_headline = pd.DataFrame({'headline_url': headline_urls})
        df_date = pd.DataFrame({'date_url': date_urls})
        df_mp3 = pd.DataFrame({'mp3_url': mp3_urls})

        ## Process temporary dataframes to
        df_headline['source_id'] = (df_headline['headline_url']
                                    .str.replace(source_id_pat, r"\1", regex=True))
        df_date['source_id'] = (df_date['date_url']
                                .str.replace(source_id_pat, r"\1", regex=True))
        df_mp3['source_id'] = (df_mp3['mp3_url']
                            .str.replace(source_id_pat_mp3, r"\1", regex=True))
        df_headline.set_index('source_id', inplace=True)
        df_date.set_index('source_id', inplace=True)
        df_mp3.set_index('source_id', inplace=True)

        ## Combine headlines, dates and mp3s together
        df = pd.concat([df_headline, df_date, df_mp3], axis=1)
        df['source_id'] = df.index
        df['headline_text'] = headlines
        df.reset_index(drop=True, inplace=True)
    else:
        df = None
    if verbose>0:
        print(df)
    return df


def download_mp3(url, filename='out.mp3', output_dir=''):
    if not filename.endswith('.mp3'):
        filename += '.mp3'
    r = requests.get(url, allow_redirects=True)
    # update filename (add path if applicable)
    filename = update_filename(filename=filename,
                               output_dir=output_dir)
    # write to mp3 file
    with open(filename, 'wb') as f:
        f.write(r.content)

def write_headline(text, filename='out.txt', output_dir=''):
    if not filename.endswith('.txt'):
        filename += '.txt'
    # update filename (add path if applicable)
    filename = update_filename(filename=filename,
                               output_dir=output_dir)
    # write to txt file
    with open(filename, 'w') as f:
        f.write(text)

def update_filename(filename, output_dir=''):
    if output_dir:
        output_dir = makedir(path=output_dir)
        filename = os.path.join(output_dir, filename)
    return filename

def makedir(path):
    path = os.path.abspath(path)
    if not os.path.exists(path):
        os.makedirs(path)
    return path

## Define output directory
OUTPUT_DIR_HEADLINES = 'output/headlines'
OUTPUT_DIR_AUDIO = 'output/audio'

## Extract data and tabulate as a pandas dataframe
df = tabulate_headlines(text="", filename="test.txt", verbose=1)

## Determine target rows
target_rows_headlines = ~df.headline_text.isna()
target_rows_mp3 = ~df.mp3_url.isna()

## Write headlines to .txt files
print('Total headlines: {}'.format(target_rows_headlines.sum()))
_ = (df
        .loc[target_rows_headlines, ["source_id", "headline_text"]]
        .apply(lambda row: write_headline(text = row['headline_text'],
                                          filename = row['source_id'],
                                          output_dir=OUTPUT_DIR_HEADLINES),
               axis=1))
print('Writing headlines to .txt files: COMPLETE')

## Save audio to .mp3 files
print('Total audio files: {}'.format(target_rows_mp3.sum()))
_ = (df
        .loc[target_rows_mp3, ["source_id", "mp3_url"]]
        .apply(lambda row: download_mp3(url = row['mp3_url'],
                                        filename = row['source_id'],
                                        output_dir=OUTPUT_DIR_AUDIO),
               axis=1))
print('Downloading audio to .mp3 files: COMPLETE')

Answer 1

问题在于你的正则表达式使得标题{}

如果对示例文件运行此正则表达式，您将看到捕获组1存储URl的结尾，组2捕获接下来的两行，组3捕获这两行中的最后一行

Match 1
Full match  0-99    
[headline - https://www.rfa.org/cantonese/news/us-pompeo-06012020072305.html]
This
some-text-here

Group 1.    47-71   
us-pompeo-06012020072305

Group 2.    78-98   
This
some-text-here

Group 3.    83-98   
some-text-here

因此，问题不在于在文本文件的最后一行追加多次，而在于源数据中

        for headline in headline_data:
            print("#", headline)

输出

# ('us-pompeo-06012020072305', 'This\nsome-text-here\n', 'some-text-here\n')
# ('tw-uk-06012020113435', 'Is\nsome-text-here\n', 'some-text-here\n')
# ('wang-06012020103828', 'Test\nsome-text-here\n', 'some-text-here\n')
# ('us-wang-06012020135251', 'TEST\nsome-text-here\n', 'some-text-here\n')
# ('hk-chan-06012020073718', 'TEST\nsome-text-here\n', 'some-text-here\n')
# ('ear-state-06012020035108', 'TEST\nsome-text-here\n', 'some-text-here\n')

因此，您可以看到，由于您的正则表达式，您的数据中实际上有两次“此处有一些文本”，因此您的append只执行您要求的操作，并将其追加，您需要查看您的正则表达式并将其更改为不再像这样拾取