PyPDF2读取带数字签名PDF报IndexError，求跳过签名字段方案

问题 #

我是Python和PyPDF2新手，正在尝试提取PDF表单中的所有字段并存入DataFrame，最终要批量处理数千份同结构的PDF表单。代码在无数字签名的PDF上运行正常，但读取带数字签名的PDF时触发IndexError。由于不需要签名字段，希望跳过该字段但不知如何实现。

原代码 #

import os
import PyPDF2 as pypdf
import pandas as pd

directory = 'files'

for filename in os.listdir(directory):
    f = os.path.join(directory, filename)
    if os.path.isfile(f):
        print(f)
        pdf=pypdf.PdfFileReader(f, strict= False)
        print(pdf)
        #information = pdf.getFormTextFields()
        information = pdf.getFields()
        print(information)
        output = pd.DataFrame([information])
        df = pd.concat([df, output], ignore_index=True)

错误信息 #

Traceback (most recent call last):
  File "/workspace/app.py", line 77, in <module>
    information = pdf.getFields()
  File "/app/.heroku/python/lib/python3.7/site-packages/PyPDF2/_reader.py", line 526, in getFields
    return self.get_fields(tree, retval, fileobj)
  File "/app/.heroku/python/lib/python3.7/site-packages/PyPDF2/_reader.py", line 510, in get_fields
    self._build_field(field, retval, fileobj, field_attributes)
  File "/app/.heroku/python/lib/python3.7/site-packages/PyPDF2/_reader.py", line 535, in _build_field
    self._check_kids(field, retval, fileobj)
  File "/app/.heroku/python/lib/python3.7/site-packages/PyPDF2/_reader.py", line 555, in _check_kids
    self.get_fields(kid.get_object(), retval, fileobj)
  File "/app/.heroku/python/lib/python3.7/site-packages/PyPDF2/_reader.py", line 499, in get_fields
    self._check_kids(tree, retval, fileobj)
  File "/app/.heroku/python/lib/python3.7/site-packages/PyPDF2/_reader.py", line 555, in _check_kids
    self.get_fields(kid.get_object(), retval, fileobj)
  File "/app/.heroku/python/lib/python3.7/site-packages/PyPDF2/_reader.py", line 503, in get_fields
    self._build_field(tree, retval, fileobj, field_attributes)
  File "/app/.heroku/python/lib/python3.7/site-packages/PyPDF2/_reader.py", line 547, in _build_field
    retval[key] = Field(field)
  File "/app/.heroku/python/lib/python3.7/site-packages/PyPDF2/generic.py", line 1626, in __init__
    self[NameObject(attr)] = data[attr]
  File "/app/.heroku/python/lib/python3.7/site-packages/PyPDF2/generic.py", line 679, in __getitem__
    return dict.__getitem__(self, key).get_object()
  File "/app/.heroku/python/lib/python3.7/site-packages/PyPDF2/generic.py", line 251, in get_object
    obj = self.pdf.get_object(self)
  File "/app/.heroku/python/lib/python3.7/site-packages/PyPDF2/_reader.py", line 1167, in get_object
    retval, indirect_reference.idnum, indirect_reference.generation
  File "/app/.heroku/python/lib/python3.7/site-packages/PyPDF2/_encryption.py", line 741, in decrypt_object
    return cf.decrypt_object(obj)
  File "/app/.heroku/python/lib/python3.7/site-packages/PyPDF2/_encryption.py", line 182, in decrypt_object
    obj[dictkey] = self.decrypt_object(value)
  File "/app/.heroku/python/lib/python3.7/site-packages/PyPDF2/_encryption.py", line 185, in decrypt_object
    obj[i] = self.decrypt_object(obj[i])
  File "/app/.heroku/python/lib/python3.7/site-packages/PyPDF2/_encryption.py", line 182, in decrypt_object
    obj[dictkey] = self.decrypt_object(value)
  File "/app/.heroku/python/lib/python3.7/site-packages/PyPDF2/_encryption.py", line 176, in decrypt_object
    data = self.strCrypt.decrypt(obj.original_bytes)
  File "/app/.heroku/python/lib/python3.7/site-packages/PyPDF2/_encryption.py", line 88, in decrypt
    return d[: -d[-1]]
IndexError: index out of range

解决方案 #

方法1：捕获异常+过滤签名字段 #

用try-except包裹字段读取操作，遇到IndexError时降级到纯文本字段读取；读取成功后手动过滤掉类型为/Sig的签名字段：

import os
import PyPDF2 as pypdf
import pandas as pd

directory = 'files'
df = pd.DataFrame()  # 初始化空DataFrame，避免未定义报错

for filename in os.listdir(directory):
    f = os.path.join(directory, filename)
    # 只处理PDF文件，避免非PDF干扰
    if os.path.isfile(f) and f.lower().endswith('.pdf'):
        print(f"Processing: {f}")
        pdf = pypdf.PdfFileReader(f, strict=False)
        information = {}
        try:
            # 尝试读取所有字段
            information = pdf.getFields()
            # 过滤签名字段：签名字段的类型标识为'/Sig'
            information = {k: v for k, v in information.items() if v.get('/FT') != '/Sig'}
        except IndexError:
            # 读取失败时，改用getFormTextFields()提取纯文本字段
            print(f"Error reading {f}, falling back to text fields only")
            information = pdf.getFormTextFields()
        # 将有效字段加入DataFrame
        if information:
            output = pd.DataFrame([information])
            df = pd.concat([df, output], ignore_index=True)

# 保存结果到CSV
df.to_csv('pdf_form_fields.csv', index=False)

方法2：手动遍历表单结构跳过签名字段 #

直接遍历PDF的AcroForm结构，从根源跳过签名字段，避免触发读取异常：

import os
import PyPDF2 as pypdf
import pandas as pd
from PyPDF2.generic import NameObject

directory = 'files'
df = pd.DataFrame()

for filename in os.listdir(directory):
    f = os.path.join(directory, filename)
    if os.path.isfile(f) and f.lower().endswith('.pdf'):
        print(f"Processing: {f}")
        pdf = pypdf.PdfFileReader(f, strict=False)
        information = {}
        acro_form = pdf.getAcroForm()
        if acro_form is not None:
            # 递归遍历所有字段节点
            def traverse_fields(node, field_dict):
                if '/Kids' in node:
                    for kid in node['/Kids']:
                        traverse_fields(kid.get_object(), field_dict)
                elif '/FT' in node:
                    # 跳过类型为'/Sig'的签名字段
                    if node['/FT'] != NameObject('/Sig'):
                        # 处理字段名称和值
                        field_name = node.get('/T', '')
                        if isinstance(field_name, bytes):
                            field_name = field_name.decode('utf-8')
                        field_value = node.get('/V')
                        if field_value is not None:
                            if isinstance(field_value, bytes):
                                field_value = field_value.decode('utf-8')
                            else:
                                field_value = str(field_value)
                            field_dict[field_name] = field_value
            traverse_fields(acro_form, information)
        # 加入DataFrame
        if information:
            output = pd.DataFrame([information])
            df = pd.concat([df, output], ignore_index=True)

df.to_csv('pdf_form_fields.csv', index=False)

关键说明 #

• 签名字段的标准类型标识为/Sig，通过判断字段的/FT属性即可过滤。
• 方法1实现简单，优先保证兼容性，适合大多数场景。
• 方法2直接操作PDF底层结构，避免读取签名字段时触发异常，适合报错频繁的批量处理场景。

内容的提问来源于stack exchange，提问作者ItzGravy314