5 Python Scripts to Automate PDF Tasks

A collection of standalone Python scripts for common PDF automation tasks.

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Scripts

Script	What it does
pdf_merge_split.py	Merge multiple PDFs into one, or split a PDF by page range or chunk size
pdf_extractor.py	Extract text and tables from PDFs into text files and Excel/CSV
pdf_stamper.py	Add watermarks, stamps, or page numbers to PDFs in batch
pdf_redactor.py	Permanently redact text matching patterns from PDF files
pdf_inventory.py	Scan a folder of PDFs and export a metadata inventory

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Dependencies

Script	Packages
pdf_merge_split.py	pypdf
pdf_extractor.py	pypdf, pdfplumber, pandas, openpyxl
pdf_stamper.py	pypdf, reportlab
pdf_redactor.py	pymupdf
pdf_inventory.py	pypdf, pdfplumber, pandas, openpyxl

Install all at once

pip install pypdf pdfplumber pymupdf reportlab pandas openpyxl

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Quick Start

1. pdf_merge_split.py

Merge a folder of PDFs into one file, or split a PDF into parts.

# Merge all PDFs in a folder (sorted alphabetically)
python pdf_merge_split.py merge --input ./reports --output merged.pdf

# Merge in a specific order defined in a text file
python pdf_merge_split.py merge --input ./chapters --output book.pdf --order order.txt

# Split every 10 pages
python pdf_merge_split.py split --input large_report.pdf --output-dir ./splits --every 10

# Split by specific page ranges
python pdf_merge_split.py split --input report.pdf --output-dir ./splits --ranges "1-5,6-20,21-"

# Split before specific page numbers
python pdf_merge_split.py split --input report.pdf --output-dir ./splits --on-pages 10 25 40

order.txt format (merge mode): One filename per line in the desired order.

--ranges format: Comma-separated ranges. Use - as the end of a range to mean "to the last page" (e.g. 21-).

Output: Single merged PDF, or numbered split files in the output directory.

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2. pdf_extractor.py

Extract text and tables from PDFs into usable output files.

# Extract both text and tables from a single file
python pdf_extractor.py --input report.pdf

# Extract tables only, write to CSV
python pdf_extractor.py --input report.pdf --mode tables --table-format csv

# Process an entire folder, output as markdown and Excel
python pdf_extractor.py --input ./pdfs --mode both --text-format md --table-format xlsx

# Extract text only
python pdf_extractor.py --input statement.pdf --mode text --output-dir ./text_output

--mode options: text | tables | both

Output:

• Text → {filename}_text.txt or .md per file
• Tables → {filename}_tables.xlsx (one sheet per table) or individual CSVs
• _summary.csv listing pages, tables found, and any extraction warnings per file

Note: Scanned PDFs (image-only) will not yield extractable text. The summary flags these.

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3. pdf_stamper.py

Add a watermark, stamp, or page numbers to one or more PDFs.

# Diagonal watermark (default)
python pdf_stamper.py --input report.pdf --text "CONFIDENTIAL"

# Full folder, custom opacity and angle
python pdf_stamper.py --input ./pdfs --text "DRAFT" --angle 45 --opacity 0.12

# Horizontal stamp at the top
python pdf_stamper.py --input contract.pdf --mode stamp \
    --text "APPROVED" --position top-center --angle 0

# Add page numbers at the bottom
python pdf_stamper.py --input report.pdf --mode page-numbers \
    --position bottom-center --page-num-fmt "Page {n} of {total}"

--mode options: watermark | stamp | page-numbers

--position options: center, top-left, top-center, top-right, bottom-left, bottom-center, bottom-right

Output: One output PDF per input file, named {original}_watermark.pdf / _stamp.pdf / _page-numbers.pdf. Originals are never modified.

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4. pdf_redactor.py

Permanently remove sensitive text from PDFs using pattern matching.

# Redact specific strings
python pdf_redactor.py --input document.pdf --patterns "John Smith" "Project Alpha"

# Redact using regex patterns
python pdf_redactor.py --input document.pdf --patterns "ACC-\d{6}" "REF:\s?\d+"

# Redact using built-in categories
python pdf_redactor.py --input document.pdf --categories email phone

# Combine patterns and categories
python pdf_redactor.py --input ./pdfs --patterns "CONFIDENTIAL-\d+" --categories email ssn

# Match whole words only
python pdf_redactor.py --input document.pdf --patterns "Smith" --whole-word

Built-in --categories: email, phone, ssn, credit, postcode, date

Output: {filename}_redacted.pdf per input file. A _redaction_log.csv lists every redaction made (page, pattern, matched text — recorded before redaction).

⚠️ Always verify the output before distributing. Test on a copy before processing originals.

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5. pdf_inventory.py

Generate a metadata inventory of a folder of PDF files.

# Basic inventory
python pdf_inventory.py --input ./documents

# Custom output and deeper text sampling
python pdf_inventory.py --input ./documents --output my_inventory.xlsx --sample-pages 5

# Include subdirectories
python pdf_inventory.py --input ./archive --recursive

Output columns: filename, path, size_kb, pages, encrypted, scanned, title, author, creator, producer, created, modified, pdf_version, error

Row colors in Excel:

• Yellow = scanned/image PDF (no extractable text)
• Red = encrypted file that could not be opened
• Blue alternating = standard files