PDF 处理技能：提取、合并与文档自动化 - Openclaw Skills

什么是 PDF 处理工具包？

此技能为您的 AI 代理环境提供了一套强大的工具，用于处理任何与 PDF 相关的任务。通过集成 pypdf 和 pdfplumber 等库，此 Openclaw Skills 条目能够实现精确的文本提取、布局保持和复杂的表格解析。它专为需要大规模自动化文档处理的开发人员设计，无论是使用 reportlab 从头开始创建报告，还是使用 qpdf 解密安全文件。该资源是基于 Openclaw Skills 环境管理文档生命周期的权威指南。

下载入口:https://github.com/openclaw/skills/tree/main/skills/awspace/pdf

安装与下载

1. ClawHub CLI

从源直接安装技能的最快方式。

npx clawhub@latest install pdf

2. 手动安装

将技能文件夹复制到以下位置之一

全局模式 ~/.openclaw/skills/ 工作区 <project>/skills/

优先级：工作区 > 本地 > 内置

3. 提示词安装

将此提示词复制到 OpenClaw 即可自动安装。

请帮我使用 Clawhub 安装 pdf。如果尚未安装 Clawhub，请先安装（npm i -g clawhub）。

PDF 处理工具包 应用场景

• 自动将财务报表中的表格数据提取到 Excel 中。
• 通过编程将多个文档片段合并为一个内聚的 PDF。
• 对扫描文档执行 OCR，使其可搜索和可索引。
• 生成具有自定义样式和多页布局的动态业务报告。
• 通过密码加密和自定义水印保护敏感文档。

PDF 处理工具包 工作原理

1. 根据任务选择合适的工具，例如用于表格提取的 pdfplumber 或用于文档创建的 reportlab。
2. 将源 PDF 文件加载到环境中或调用相关的 CLI 实用程序（如 qpdf）。
3. 执行特定的转换或提取逻辑，例如旋转页面或合并元数据。
4. 通过 Pandas DataFrames 等结构处理提取的数据，或将最终的二进制文件写入磁盘。
5. 将生成的资产集成到更广泛的 Openclaw Skills 工作流程中，以实现端到端自动化。

PDF 处理工具包 配置指南

要开始使用这些 Openclaw Skills，请安装必要的 Python 依赖项：

pip install pypdf pdfplumber reportlab pytesseract pdf2image

对于基于 CLI 的操作，请确保存在所需的系统软件包：

sudo apt-get install poppler-utils qpdf

PDF 处理工具包 数据架构与分类体系

该技能通过各种面向对象的结构和文件输出组织数据：

组件	数据类型	描述
元数据	字典	包含标题、作者、主题和创建者字段。
提取的文本	字符串	原始文本内容，可选择保留原始布局。
表格	列表嵌套列表	为转换为 CSV 或 Excel 而构建的表格数据。
页面对象	对象	可用于旋转或合并的单个 PDF 页面。
图像	JPEG/PNG	从文档层提取的栅格化资产。

name: pdf
description: Comprehensive PDF manipulation toolkit for extracting text and tables, creating new PDFs, merging/splitting documents, and handling forms. When Claude needs to fill in a PDF form or programmatically process, generate, or analyze PDF documents at scale.
license: Proprietary. LICENSE.txt has complete terms

PDF Processing Guide

Overview

This guide covers essential PDF processing operations using Python libraries and command-line tools. For advanced features, JavaScript libraries, and detailed examples, see reference.md. If you need to fill out a PDF form, read forms.md and follow its instructions.

Quick Start

from pypdf import PdfReader, PdfWriter

# Read a PDF
reader = PdfReader("document.pdf")
print(f"Pages: {len(reader.pages)}")

# Extract text
text = ""
for page in reader.pages:
    text += page.extract_text()

Python Libraries

pypdf - Basic Operations

Merge PDFs

from pypdf import PdfWriter, PdfReader

writer = PdfWriter()
for pdf_file in ["doc1.pdf", "doc2.pdf", "doc3.pdf"]:
    reader = PdfReader(pdf_file)
    for page in reader.pages:
        writer.add_page(page)

with open("merged.pdf", "wb") as output:
    writer.write(output)

Split PDF

reader = PdfReader("input.pdf")
for i, page in enumerate(reader.pages):
    writer = PdfWriter()
    writer.add_page(page)
    with open(f"page_{i+1}.pdf", "wb") as output:
        writer.write(output)

Extract Metadata

reader = PdfReader("document.pdf")
meta = reader.metadata
print(f"Title: {meta.title}")
print(f"Author: {meta.author}")
print(f"Subject: {meta.subject}")
print(f"Creator: {meta.creator}")

Rotate Pages

reader = PdfReader("input.pdf")
writer = PdfWriter()

page = reader.pages[0]
page.rotate(90)  # Rotate 90 degrees clockwise
writer.add_page(page)

with open("rotated.pdf", "wb") as output:
    writer.write(output)

pdfplumber - Text and Table Extraction

Extract Text with Layout

import pdfplumber

with pdfplumber.open("document.pdf") as pdf:
    for page in pdf.pages:
        text = page.extract_text()
        print(text)

Extract Tables

with pdfplumber.open("document.pdf") as pdf:
    for i, page in enumerate(pdf.pages):
        tables = page.extract_tables()
        for j, table in enumerate(tables):
            print(f"Table {j+1} on page {i+1}:")
            for row in table:
                print(row)

Advanced Table Extraction

import pandas as pd

with pdfplumber.open("document.pdf") as pdf:
    all_tables = []
    for page in pdf.pages:
        tables = page.extract_tables()
        for table in tables:
            if table:  # Check if table is not empty
                df = pd.DataFrame(table[1:], columns=table[0])
                all_tables.append(df)

# Combine all tables
if all_tables:
    combined_df = pd.concat(all_tables, ignore_index=True)
    combined_df.to_excel("extracted_tables.xlsx", index=False)

reportlab - Create PDFs

Basic PDF Creation

from reportlab.lib.pagesizes import letter
from reportlab.pdfgen import canvas

c = canvas.Canvas("hello.pdf", pagesize=letter)
width, height = letter

# Add text
c.drawString(100, height - 100, "Hello World!")
c.drawString(100, height - 120, "This is a PDF created with reportlab")

# Add a line
c.line(100, height - 140, 400, height - 140)

# Save
c.save()

Create PDF with Multiple Pages

from reportlab.lib.pagesizes import letter
from reportlab.platypus import SimpleDocTemplate, Paragraph, Spacer, PageBreak
from reportlab.lib.styles import getSampleStyleSheet

doc = SimpleDocTemplate("report.pdf", pagesize=letter)
styles = getSampleStyleSheet()
story = []

# Add content
title = Paragraph("Report Title", styles['Title'])
story.append(title)
story.append(Spacer(1, 12))

body = Paragraph("This is the body of the report. " * 20, styles['Normal'])
story.append(body)
story.append(PageBreak())

# Page 2
story.append(Paragraph("Page 2", styles['Heading1']))
story.append(Paragraph("Content for page 2", styles['Normal']))

# Build PDF
doc.build(story)

Command-Line Tools

pdftotext (poppler-utils)

# Extract text
pdftotext input.pdf output.txt

# Extract text preserving layout
pdftotext -layout input.pdf output.txt

# Extract specific pages
pdftotext -f 1 -l 5 input.pdf output.txt  # Pages 1-5

qpdf

# Merge PDFs
qpdf --empty --pages file1.pdf file2.pdf -- merged.pdf

# Split pages
qpdf input.pdf --pages . 1-5 -- pages1-5.pdf
qpdf input.pdf --pages . 6-10 -- pages6-10.pdf

# Rotate pages
qpdf input.pdf output.pdf --rotate=+90:1  # Rotate page 1 by 90 degrees

# Remove password
qpdf --password=mypassword --decrypt encrypted.pdf decrypted.pdf

pdftk (if available)

# Merge
pdftk file1.pdf file2.pdf cat output merged.pdf

# Split
pdftk input.pdf burst

# Rotate
pdftk input.pdf rotate 1east output rotated.pdf

Common Tasks

Extract Text from Scanned PDFs

# Requires: pip install pytesseract pdf2image
import pytesseract
from pdf2image import convert_from_path

# Convert PDF to images
images = convert_from_path('scanned.pdf')

# OCR each page
text = ""
for i, image in enumerate(images):
    text += f"Page {i+1}:
"
    text += pytesseract.image_to_string(image)
    text += "

"

print(text)

Add Watermark

from pypdf import PdfReader, PdfWriter

# Create watermark (or load existing)
watermark = PdfReader("watermark.pdf").pages[0]

# Apply to all pages
reader = PdfReader("document.pdf")
writer = PdfWriter()

for page in reader.pages:
    page.merge_page(watermark)
    writer.add_page(page)

with open("watermarked.pdf", "wb") as output:
    writer.write(output)

Extract Images

# Using pdfimages (poppler-utils)
pdfimages -j input.pdf output_prefix

# This extracts all images as output_prefix-000.jpg, output_prefix-001.jpg, etc.

Password Protection

from pypdf import PdfReader, PdfWriter

reader = PdfReader("input.pdf")
writer = PdfWriter()

for page in reader.pages:
    writer.add_page(page)

# Add password
writer.encrypt("userpassword", "ownerpassword")

with open("encrypted.pdf", "wb") as output:
    writer.write(output)

Quick Reference

Next Steps

• For advanced pypdfium2 usage, see reference.md
• For JavaScript libraries (pdf-lib), see reference.md
• If you need to fill out a PDF form, follow the instructions in forms.md
• For troubleshooting guides, see reference.md