pdf-large-reader
Memory-efficient PDF processing library for large files exceeding 100MB and 1000 pages
Best use case
pdf-large-reader is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Memory-efficient PDF processing library for large files exceeding 100MB and 1000 pages
Teams using pdf-large-reader should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/large-reader/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How pdf-large-reader Compares
| Feature / Agent | pdf-large-reader | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Memory-efficient PDF processing library for large files exceeding 100MB and 1000 pages
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# pdf-large-reader Skill
Memory-efficient PDF processing library for large files (100MB+, 1000+ pages).
## Repository
- **Location:** `/mnt/github/workspace-hub/pdf-large-reader`
- **GitHub:** https://github.com/vamseeachanta/pdf-large-reader
- **Coverage:** 93.58% (215 tests)
## Installation
```bash
cd /mnt/github/workspace-hub/pdf-large-reader
pip install -e .
```
## Quick Usage
### Python API
```python
from pdf_large_reader import process_large_pdf, extract_text_only
# Simple text extraction
text = extract_text_only("large_document.pdf")
# Full processing with options
result = process_large_pdf(
"document.pdf",
output_format="generator", # "generator", "list", or "text"
extract_images=True,
extract_tables=True
)
# Stream pages for memory efficiency
for page in result:
print(f"Page {page['page_num']}: {page['text'][:100]}...")
```
### CLI Tool
```bash
# Extract text
pdf-large-reader extract document.pdf
# Extract with options
pdf-large-reader extract document.pdf --output-format text --extract-images
# Get PDF info
pdf-large-reader info document.pdf
```
## Key Features
| Feature | Description |
|---------|-------------|
| **Streaming** | Generator output for memory efficiency |
| **Auto Strategy** | Intelligent chunk sizing based on file size |
| **Multi-format** | Text, images, tables, metadata extraction |
| **Progress** | Built-in progress callbacks |
| **AI Fallback** | Codex integration for complex extraction |
## Output Formats
### Generator (Streaming) - Default
```python
for page in process_large_pdf("doc.pdf", output_format="generator"):
# Process one page at a time - memory efficient
handle_page(page)
```
### List
```python
pages = process_large_pdf("doc.pdf", output_format="list")
# All pages in memory - use for smaller files
```
### Text
```python
text = process_large_pdf("doc.pdf", output_format="text")
# Plain text concatenation
```
## When to Use
- Processing PDFs > 50MB
- Batch processing many PDFs
- Extracting content from 100+ page documents
- Memory-constrained environments
- Streaming PDF content to other systems
## Integration Example
```python
from pdf_large_reader import process_large_pdf
from pathlib import Path
def process_pdf_directory(directory: str):
"""Process all PDFs in a directory efficiently."""
pdf_dir = Path(directory)
for pdf_file in pdf_dir.glob("*.pdf"):
print(f"Processing: {pdf_file.name}")
# Stream pages to avoid memory issues
for page in process_large_pdf(str(pdf_file)):
# Index, analyze, or store each page
yield {
"file": pdf_file.name,
"page": page["page_num"],
"text": page["text"],
"images": len(page.get("images", []))
}
```
## Error Handling
```python
from pdf_large_reader import process_large_pdf
from pdf_large_reader.exceptions import PDFProcessingError
try:
result = process_large_pdf("document.pdf")
except PDFProcessingError as e:
print(f"PDF processing failed: {e}")
except FileNotFoundError:
print("PDF file not found")
```
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- `file-org-standards` - Where to store extracted content
- `logging-standards` - Logging PDF processing operationsRelated Skills
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