如何使用 PDFMiner 更新的 API 在 Python 中從 PDF 檔案中提取文字？

Extracting Text from PDF Files with PDFMiner in Python

In the realm of document processing, PDF files hold a significant position. To extract valuable text data from these files, PDFMiner emerges as a powerful Python library, facilitating seamless text extraction. However, due to recent API updates, outdated examples and documentation pose obstacles for Python developers. This article aims to elucidate the updated approach to text extraction using PDFMiner in Python.

The updated API requires a different method of obtaining text from a PDF file. The code snippet below demonstrates the current approach:

<code class="python">from pdfminer.pdfinterp import PDFResourceManager, PDFPageInterpreter
from pdfminer.converter import TextConverter
from pdfminer.layout import LAParams
from pdfminer.pdfpage import PDFPage
from io import StringIO

def convert_pdf_to_txt(path):
    rsrcmgr = PDFResourceManager()
    retstr = StringIO()
    codec = 'utf-8'
    laparams = LAParams()
    device = TextConverter(rsrcmgr, retstr, codec=codec, laparams=laparams)
    fp = open(path, 'rb')
    interpreter = PDFPageInterpreter(rsrcmgr, device)
    password = ""
    maxpages = 0
    caching = True
    pagenos=set()

    for page in PDFPage.get_pages(fp, pagenos, maxpages=maxpages, password=password,caching=caching, check_extractable=True):
        interpreter.process_page(page)

    text = retstr.getvalue()

    fp.close()
    device.close()
    retstr.close()
    return text</code>

This optimized example effectively extracts text from a PDF file and returns it as a string variable. It is crucial to note that PDFMiner's structure has undergone revisions, making this code snippet indispensable for extracting text from PDF files with the latest version of the library.

As programming languages and libraries evolve over time, it becomes imperative to embrace the latest updates for optimal performance and functionality. This article provides a comprehensive solution to text extraction from PDF files, leveraging the updated API of PDFMiner in Python. By implementing the provided code snippet, developers can continue to harness PDFMiner's capabilities to effectively extract and process text data from PDF documents.

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