如何提取文本文件中多次出现指定词汇后的3000字符或300词？

Got it, let's walk through how to pull the text following each occurrence of Accounting Principles—capped at either 3000 characters or 300 words, whichever comes first. Here are two reliable methods:

1. Python Script (Automated, Scalable) #

This is the best option if you're working with longer texts or need to repeat this task. The script will find every hit and extract the desired text automatically:

def extract_post_keyword_text(input_text, keyword, max_chars=3000, max_words=300):
    extracted_sections = []
    current_pos = 0
    
    while True:
        # Locate the next occurrence of the keyword
        keyword_pos = input_text.find(keyword, current_pos)
        if keyword_pos == -1:
            break  # No more occurrences to find
        
        # Start extracting right after the keyword ends
        start_extract = keyword_pos + len(keyword)
        # First grab up to 3000 characters
        char_limit_text = input_text[start_extract : start_extract + max_chars]
        
        # Now trim to 300 words if that's shorter
        word_list = char_limit_text.split()
        word_limit_text = ' '.join(word_list[:max_words])
        
        # Add the section to results (include context for clarity)
        extracted_sections.append(f"""
### Occurrence at index {keyword_pos}:
> **{keyword}** {word_limit_text}
        """)
        
        # Move the search position forward to avoid reprocessing the same text
        current_pos = start_extract
    
    return extracted_sections

# Your input text
source_text = """Accounting Principles. Negative Pledge Clauses . Clauses Restricting Subsidiary Distributions . Lines of Business......Accounting Principles: is defined in the definition of IFRS. Administrative Agent: SVB......In the event that any Accounting Principles (as defined below) shall occur and such change results......"""

# Run the extraction
results = extract_post_keyword_text(source_text, "Accounting Principles")

# Print or save the output
for section in results:
    print(section.strip())

What this script does: #

• Loops through every instance of Accounting Principles in your text.
• For each hit, it first extracts up to 3000 characters starting right after the keyword.
• Then it splits that text into words and caps it at 300 words (so you don't end up with partial words or overly long sections if 300 words is shorter than 3000 characters).
• Outputs each section with a clear label showing where the occurrence was found in the original text.

2. Manual Method (Quick, No Code Needed) #

If you just need a one-off extraction, use a text editor like VS Code, Sublime Text, or even Notepad++:

• Use the Find All function (press Ctrl+Shift+F on Windows/Linux, Cmd+Shift+F on Mac) and search for Accounting Principles.
• For each result in the find panel, click to jump to that position in the text.
• Place your cursor right after the keyword, then:
  • To count characters: Watch the character counter in your editor's status bar while selecting text until you hit 3000.
  • To count words: Hold Ctrl (or Cmd) and click repeatedly to select individual words until you reach 300, then copy the selection.

Either method will get you the text you need. The script is great for consistency or larger datasets, while the manual approach works for quick checks.

内容的提问来源于stack exchange，提问作者WUTONG