pdf-processing-pro
/pdf-processing-pro
Production-ready PDF processing with forms, tables, OCR, validation, and batch operations. Use when working with complex PDF workflows in production environments, processing large volumes of PDFs, or requiring robust error handling and validation.
- Author
- davila7 ↗
- Repository
- claude-code-templates ↗
- Licence
- MIT
- Last repository change
- 25.10.2026
Assessment and security
- Files in this package
- 5
- Scripts
- 1
- HTML comments
- 0
- URLs in SKILL.md
- 0
No signals detected. Repository changed on 25.10.2026, without references to retired models or APIs.
MIT, open: use and modify while retaining author attribution.
- 1 scripts in this package. Review them before installing, as Claude may execute them.
Scripts: scripts/analyze_form.py
What it does and when to use it
Production-ready PDF processing with forms, tables, OCR, validation, and batch operations. Use when working with complex PDF workflows in production environments, processing large volumes of PDFs, or requiring robust error handling and validation.
Original author description
Production-ready PDF processing with forms, tables, OCR, validation, and batch operations. Use when working with complex PDF workflows in production environments, processing large volumes of PDFs, or requiring robust error handling and validation.
How it works
- Quick start
- Features
- Advanced topics
- Included scripts
- Common workflows
- Error handling
- Dependencies
- Performance tips
- Best practices
- Troubleshooting
SKILL.md preview
---
name: pdf-processing-pro
description: Production-ready PDF processing with forms, tables, OCR, validation, and batch operations. Use when working with complex PDF workflows in production environments, processing large volumes of PDFs, or requiring robust error handling and validation.
---
# PDF Processing Pro
Production-ready PDF processing toolkit with pre-built scripts, comprehensive error handling, and support for complex workflows.
## Quick start
### Extract text from PDF
```python
import pdfplumber
with pdfplumber.open("document.pdf") as pdf:
text = pdf.pages[0].extract_text()
print(text)
```
### Analyze PDF form (using included script)
```bash
python scripts/analyze_form.py input.pdf --output fields.json
# Returns: JSON with all form fields, types, and positions
```
### Fill PDF form with validation
```bash
python scripts/fill_form.py input.pdf data.json output.pdf
# Validates all fields before filling, includes error reporting
```
### Extract tables from PDF
```bash
python scripts/extract_tables.py report.pdf --output tables.csv
# Extracts all tables with automatic column detection
```
## Features
### ✅ Production-ready scripts
All scripts include:
- **Error handling**: Graceful failures with detailed error messages
- **Validation**: Input validation and type checking
- **Logging**: Configurable logging with timestamps
- **Type hints**: Full type annotations for IDE support
- **CLI interface**: `--help` flag for all scripts
- **Exit codes**: Proper exit codes for automation
### ✅ Comprehensive workflows
- **PDF Forms**: Complete form processing pipeline
- **Table Extraction**: Advanced table detection and extraction
- **OCR Processing**: Scanned PDF text extraction
- **Batch Operations**: Process multiple PDFs efficiently
- **Validation**: Pre and post-processing validation
## Advanced topics
### PDF Form Processing
For complete form workflows including:
- Field analysis and detection
- Dynamic form filling
- Validation rules
- Multi-page forms
- Checkbox and radio button handling
See [FORMS.md](FORMS.md)
### Table Extraction
For complex table extraction:
- Multi-page tables
- Merged cells
- Nested tables
- Custom table detection
- Export to CSV/Excel
See [TABLES.md](TABLES.md)
### OCR Processing
For scanned PDFs and image-based documents:
- Tesseract integration
- Language support
- Image preprocessing
- Confidence scoring
- Batch OCR
See [OCR.md](OCR.md)
## Included scripts
### Form processing
**analyze_form.py** - Extract form field information
```bash
python scripts/analyze_form.py input.pdf [--output fields.json] [--verbose]
```
**fill_form.py** - Fill PDF forms with data
```bash
python scripts/fill_form.py input.pdf data.json output.pdf [--validate]
```
**validate_form.py** - Validate form data before filling
```bash
python scripts/validate_form.py data.json schema.json
```
### Table extraction
**extract_tables.py** - Extract tables to CSV/Excel
```bash
python scripts/extract_tables.py input.pdf [--output tables.csv] [--format csv|excel]
```
### Text extraction
**extract_text.py** - Extract text with formatting preservation
```bash
python scripts/extract_text.py input.pdf [--output text.txt] [--preserve-formatting]
```
### Utilities
**merge_pdfs.py** - Merge multiple PDFs
```bash
python scripts/merge_pdfs.py file1.pdf file2.pdf file3.pdf --output merged.pdf
```
**split_pdf.py** - Split PDF into individual pages
```bash
python scripts/split_pdf.py input.pdf --output-dir pages/
```
**validate_pdf.py** - Validate PDF integrity
```bash
python scripts/validate_pdf.py input.pdf
```
## Common workflows
### Workflow 1: Process form submissions
```bash
# 1. Analyze form structure
python scripts/analyze_form.py template.pdf --output schema.json
# 2. Validate submission data
python scripts/validate_form.py submission.json schema.json
# 3. Fill form
python scripts/fill_form.py template.pdf submission.json completed.pdf
# 4. Validate output
python scripts/validate_pdf.py completed.pdf
```
### Workflow 2: Extract data from reports
```bash
# 1. Extract tables
python scripts/extract_tables.py monthly_report.pdf --output data.csv
# 2. Extract text for analysis
python scripts/extract_text.py monthly_report.pdf --output report.txt
```
### Workflow 3: Batch processing
```python
import glob
from pathlib import Path
import subprocess
# Process all PDFs in directory
for pdf_file in glob.glob("invoices/*.pdf"):
output_file = Path("processed") / Path(pdf_file).name
result = subprocess.run([
"python", "scripts/extract_text.py",
pdf_file,
"--output", str(output_file)
], capture_output=True)
if result.returncode == 0:
print(f"✓ Processed: {pdf_file}")
else:
print(f"✗ Failed: {pdf_file} - {result.stderr}")
```
## Error handling
All scripts follow consistent error patterns:
```python
# Exit codes
# 0 - Success
# 1 - File not found
# 2 - Invalid input
# 3 - Processing error
# 4 - Validation error
# Example usage in automation
result = subprocess.run(["python", "scripts/fill_form.py", ...])
if result.returncode == 0:
print("Success")
elif result.returncode == 4:
print("Validation failed - check input data")
else:
print(f"Error occurred: {result.returncode}")
```
## Dependencies
All scripts require:
```bash
pip install pdfplumber pypdf pillow pytesseract pandas
```
Optional for OCR:
```bash
# Install tesseract-ocr system package
# macOS: brew install tesseract
# Ubuntu: apt-get install tesseract-ocr
# Windows: Download from GitHub releases
```
## Performance tips
- **Use batch processing** for multiple PDFs
- **Enable multiprocessing** with `--parallel` flag (where supported)
- **Cache extracted data** to avoid re-processing
- **Validate inputs early** to fail fast
- **Use streaming** for large PDFs (>50MB)
## Best practices
1. **Always validate inputs** before processing
2. **Use try-except** in custom scripts
3. **Log all operations** for debugging
4. **Test with sample PDFs** before production
5. **Set timeouts** for long-running operations
6. **Check exit codes** in automation
7. **Backup originals** before modification
## Troubleshooting
### Common issues
**"Module not found" errors**:
```bash
pip install -r requirements.txt
```
**Tesseract not found**:
```bash
# Install tesseract system package (see Dependencies)
```
**Memory errors with large PDFs**:
```python
# Process page by page instead of loading entire PDF
with pdfplumber.open("large.pdf") as pdf:
for page in pdf.pages:
text = page.extract_text()
# Process page immediately
```
**Permission errors**:
```bash
chmod +x scripts/*.py
```
## Getting help
All scripts support `--help`:
```bash
python scripts/analyze_form.py --help
python scripts/extract_tables.py --help
```
For detailed documentation on specific topics, see:
- [FORMS.md](FORMS.md) - Complete form processing guide
- [TABLES.md](TABLES.md) - Advanced table extraction
- [OCR.md](OCR.md) - Scanned PDF processing
Files in this package (5)
- FORMS.md 14 KB
- OCR.md 3 KB
- SKILL.md 7 KB
- TABLES.md 15 KB
- scripts/analyze_form.py 8 KB
Versions
| Repository | Score | Licence |
|---|---|---|
| This page · davila7/claude-code-templates | 100 | MIT |
| henkisdabro/wookstar-claude-plugins | 100 | MIT |
Identical content appears in 5 other GitHub folders. We show one copy with the highest score.
Database snapshot: 13.11.2026 · package version cdcf4d9977e2 (SHA-256 digest of the entire package)
Downloads in the last 30 days: 1 · ranking
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