您可能希望使用经过时间验证的xPDF和派生工具来提取文本，因为pyPDF2在文本提取方面似乎仍然存在各种问题。

长的答案是，文本如何在PDF中编码有很多变化，它可能需要解码PDF字符串本身，然后可能需要与CMAP映射，然后可能需要分析单词和字母之间的距离等。

如果PDF被损坏(即显示正确的文本，但复制时产生垃圾)，并且您确实需要提取文本，那么您可能需要考虑将PDF转换为图像(使用ImageMagik)，然后使用Tesseract使用OCR从图像中获取文本。

我在这里找到了一个解决方案PDFLayoutTextStripper

这很好，因为它可以保持原始PDF的布局。

它是用Java编写的，但我已经添加了一个网关来支持Python。

示例代码:

from py4j.java_gateway import JavaGateway

gw = JavaGateway()
result = gw.entry_point.strip('samples/bus.pdf')

# result is a dict of {
#   'success': 'true' or 'false',
#   'payload': pdf file content if 'success' is 'true'
#   'error': error message if 'success' is 'false'
# }

print result['payload']

示例输出PDFLayoutTextStripper:

你可以在这里看到更多细节Stripper with Python

我正在添加代码来实现这一点: 这对我来说很好:

# This works in python 3
# required python packages
# tabula-py==1.0.0
# PyPDF2==1.26.0
# Pillow==4.0.0
# pdfminer.six==20170720

import os
import shutil
import warnings
from io import StringIO

import requests
import tabula
from PIL import Image
from PyPDF2 import PdfFileWriter, PdfFileReader
from pdfminer.converter import TextConverter
from pdfminer.layout import LAParams
from pdfminer.pdfinterp import PDFResourceManager, PDFPageInterpreter
from pdfminer.pdfpage import PDFPage

warnings.filterwarnings("ignore")


def download_file(url):
    local_filename = url.split('/')[-1]
    local_filename = local_filename.replace("%20", "_")
    r = requests.get(url, stream=True)
    print(r)
    with open(local_filename, 'wb') as f:
        shutil.copyfileobj(r.raw, f)

    return local_filename


class PDFExtractor():
    def __init__(self, url):
        self.url = url

    # Downloading File in local
    def break_pdf(self, filename, start_page=-1, end_page=-1):
        pdf_reader = PdfFileReader(open(filename, "rb"))
        # Reading each pdf one by one
        total_pages = pdf_reader.numPages
        if start_page == -1:
            start_page = 0
        elif start_page < 1 or start_page > total_pages:
            return "Start Page Selection Is Wrong"
        else:
            start_page = start_page - 1

        if end_page == -1:
            end_page = total_pages
        elif end_page < 1 or end_page > total_pages - 1:
            return "End Page Selection Is Wrong"
        else:
            end_page = end_page

        for i in range(start_page, end_page):
            output = PdfFileWriter()
            output.addPage(pdf_reader.getPage(i))
            with open(str(i + 1) + "_" + filename, "wb") as outputStream:
                output.write(outputStream)

    def extract_text_algo_1(self, file):
        pdf_reader = PdfFileReader(open(file, 'rb'))
        # creating a page object
        pageObj = pdf_reader.getPage(0)

        # extracting extract_text from page
        text = pageObj.extractText()
        text = text.replace("\n", "").replace("\t", "")
        return text

    def extract_text_algo_2(self, file):
        pdfResourceManager = PDFResourceManager()
        retstr = StringIO()
        la_params = LAParams()
        device = TextConverter(pdfResourceManager, retstr, codec='utf-8', laparams=la_params)
        fp = open(file, 'rb')
        interpreter = PDFPageInterpreter(pdfResourceManager, device)
        password = ""
        max_pages = 0
        caching = True
        page_num = set()

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

        text = retstr.getvalue()
        text = text.replace("\t", "").replace("\n", "")

        fp.close()
        device.close()
        retstr.close()
        return text

    def extract_text(self, file):
        text1 = self.extract_text_algo_1(file)
        text2 = self.extract_text_algo_2(file)

        if len(text2) > len(str(text1)):
            return text2
        else:
            return text1

    def extarct_table(self, file):

        # Read pdf into DataFrame
        try:
            df = tabula.read_pdf(file, output_format="csv")
        except:
            print("Error Reading Table")
            return

        print("\nPrinting Table Content: \n", df)
        print("\nDone Printing Table Content\n")

    def tiff_header_for_CCITT(self, width, height, img_size, CCITT_group=4):
        tiff_header_struct = '<' + '2s' + 'h' + 'l' + 'h' + 'hhll' * 8 + 'h'
        return struct.pack(tiff_header_struct,
                           b'II',  # Byte order indication: Little indian
                           42,  # Version number (always 42)
                           8,  # Offset to first IFD
                           8,  # Number of tags in IFD
                           256, 4, 1, width,  # ImageWidth, LONG, 1, width
                           257, 4, 1, height,  # ImageLength, LONG, 1, lenght
                           258, 3, 1, 1,  # BitsPerSample, SHORT, 1, 1
                           259, 3, 1, CCITT_group,  # Compression, SHORT, 1, 4 = CCITT Group 4 fax encoding
                           262, 3, 1, 0,  # Threshholding, SHORT, 1, 0 = WhiteIsZero
                           273, 4, 1, struct.calcsize(tiff_header_struct),  # StripOffsets, LONG, 1, len of header
                           278, 4, 1, height,  # RowsPerStrip, LONG, 1, lenght
                           279, 4, 1, img_size,  # StripByteCounts, LONG, 1, size of extract_image
                           0  # last IFD
                           )

    def extract_image(self, filename):
        number = 1
        pdf_reader = PdfFileReader(open(filename, 'rb'))

        for i in range(0, pdf_reader.numPages):

            page = pdf_reader.getPage(i)

            try:
                xObject = page['/Resources']['/XObject'].getObject()
            except:
                print("No XObject Found")
                return

            for obj in xObject:

                try:

                    if xObject[obj]['/Subtype'] == '/Image':
                        size = (xObject[obj]['/Width'], xObject[obj]['/Height'])
                        data = xObject[obj]._data
                        if xObject[obj]['/ColorSpace'] == '/DeviceRGB':
                            mode = "RGB"
                        else:
                            mode = "P"

                        image_name = filename.split(".")[0] + str(number)

                        print(xObject[obj]['/Filter'])

                        if xObject[obj]['/Filter'] == '/FlateDecode':
                            data = xObject[obj].getData()
                            img = Image.frombytes(mode, size, data)
                            img.save(image_name + "_Flate.png")
                            # save_to_s3(imagename + "_Flate.png")
                            print("Image_Saved")

                            number += 1
                        elif xObject[obj]['/Filter'] == '/DCTDecode':
                            img = open(image_name + "_DCT.jpg", "wb")
                            img.write(data)
                            # save_to_s3(imagename + "_DCT.jpg")
                            img.close()
                            number += 1
                        elif xObject[obj]['/Filter'] == '/JPXDecode':
                            img = open(image_name + "_JPX.jp2", "wb")
                            img.write(data)
                            # save_to_s3(imagename + "_JPX.jp2")
                            img.close()
                            number += 1
                        elif xObject[obj]['/Filter'] == '/CCITTFaxDecode':
                            if xObject[obj]['/DecodeParms']['/K'] == -1:
                                CCITT_group = 4
                            else:
                                CCITT_group = 3
                            width = xObject[obj]['/Width']
                            height = xObject[obj]['/Height']
                            data = xObject[obj]._data  # sorry, getData() does not work for CCITTFaxDecode
                            img_size = len(data)
                            tiff_header = self.tiff_header_for_CCITT(width, height, img_size, CCITT_group)
                            img_name = image_name + '_CCITT.tiff'
                            with open(img_name, 'wb') as img_file:
                                img_file.write(tiff_header + data)

                            # save_to_s3(img_name)
                            number += 1
                except:
                    continue

        return number

    def read_pages(self, start_page=-1, end_page=-1):

        # Downloading file locally
        downloaded_file = download_file(self.url)
        print(downloaded_file)

        # breaking PDF into number of pages in diff pdf files
        self.break_pdf(downloaded_file, start_page, end_page)

        # creating a pdf reader object
        pdf_reader = PdfFileReader(open(downloaded_file, 'rb'))

        # Reading each pdf one by one
        total_pages = pdf_reader.numPages

        if start_page == -1:
            start_page = 0
        elif start_page < 1 or start_page > total_pages:
            return "Start Page Selection Is Wrong"
        else:
            start_page = start_page - 1

        if end_page == -1:
            end_page = total_pages
        elif end_page < 1 or end_page > total_pages - 1:
            return "End Page Selection Is Wrong"
        else:
            end_page = end_page

        for i in range(start_page, end_page):
            # creating a page based filename
            file = str(i + 1) + "_" + downloaded_file

            print("\nStarting to Read Page: ", i + 1, "\n -----------===-------------")

            file_text = self.extract_text(file)
            print(file_text)
            self.extract_image(file)

            self.extarct_table(file)
            os.remove(file)
            print("Stopped Reading Page: ", i + 1, "\n -----------===-------------")

        os.remove(downloaded_file)


# I have tested on these 3 pdf files
# url = "http://s3.amazonaws.com/NLP_Project/Original_Documents/Healthcare-January-2017.pdf"
url = "http://s3.amazonaws.com/NLP_Project/Original_Documents/Sample_Test.pdf"
# url = "http://s3.amazonaws.com/NLP_Project/Original_Documents/Sazerac_FS_2017_06_30%20Annual.pdf"
# creating the instance of class
pdf_extractor = PDFExtractor(url)

# Getting desired data out
pdf_extractor.read_pages(15, 23)

下面的代码是Python 3中该问题的解决方案。在运行代码之前，请确保已在您的环境中安装了PyPDF2库。如果未安装，打开命令提示符，执行以下命令:

pip3 install PyPDF2

使用PyPDF2 <= 1.26.0的解决方案代码:

import PyPDF2
pdfFileObject = open('sample.pdf', 'rb')
pdfReader = PyPDF2.PdfFileReader(pdfFileObject)
count = pdfReader.numPages
for i in range(count):
    page = pdfReader.getPage(i)
    print(page.extractText())

Camelot似乎是在Python中从pdf中提取表的一个相当强大的解决方案。

乍一看，它似乎实现了几乎和CreekGeek建议的tabura -py包一样准确的提取，CreekGeek在可靠性方面已经超过了任何其他发布的解决方案，但它应该是更可配置的。此外，它有自己的精度指示器(results.parsing_report)，以及强大的调试功能。

Camelot和Tabula都将结果作为Pandas的dataframe提供，因此之后很容易调整表。

pip install camelot-py

(不要与卡梅洛特的包装混淆。)

import camelot

df_list = []
results = camelot.read_pdf("file.pdf", ...)
for table in results:
    print(table.parsing_report)
    df_list.append(results[0].df)

它还可以输出结果为CSV, JSON, HTML或Excel。

卡梅洛特的到来是以牺牲许多属地为代价的。

NB :由于我的输入非常复杂，有许多不同的表，我最终使用Camelot和Tabula，根据表，以达到最好的结果。

在2020年，上述解决方案并不适用于我正在使用的特定pdf。下面是诀窍。我用的是Windows 10和Python 3.8

测试pdf文件:https://drive.google.com/file/d/1aUfQAlvq5hA9kz2c9CyJADiY3KpY3-Vn/view?usp=sharing

#pip install pdfminer.six
import io

from pdfminer.pdfinterp import PDFResourceManager, PDFPageInterpreter
from pdfminer.converter import TextConverter
from pdfminer.layout import LAParams
from pdfminer.pdfpage import PDFPage


def convert_pdf_to_txt(path):
    '''Convert pdf content from a file path to text

    :path the file path
    '''
    rsrcmgr = PDFResourceManager()
    codec = 'utf-8'
    laparams = LAParams()

    with io.StringIO() as retstr:
        with TextConverter(rsrcmgr, retstr, codec=codec,
                           laparams=laparams) as device:
            with open(path, 'rb') as fp:
                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)

                return retstr.getvalue()


if __name__ == "__main__":
    print(convert_pdf_to_txt('C:\\Path\\To\\Test_PDF.pdf'))