ppget 0.1.9

A simple CLI tool to download PubMed articles without the complexity of EDirect

ppget

A simple CLI tool to easily download PubMed articles

日本語版README | English

ppget is a command-line tool for searching and downloading literature data from PubMed. It focuses on being easy to run immediately: no multi-step pipelines, just one command that delivers CSV/JSON plus metadata.

✨ Features

• 🚀 No installation required - Run instantly with uvx
• 📝 CSV/JSON support - Easy to use in spreadsheets or programs
• 🔍 Flexible search - Full support for PubMed search syntax (AND, OR, MeSH, etc.)
• 📊 Automatic metadata - Automatically records search queries and timestamps
• 🎯 Simple API - Clear and intuitive options

🚀 Quick Start

Run without installation (Recommended)

If you have uv installed, you can run it instantly without installation:

# Basic usage
uvx ppget "machine learning AND medicine"

# Specify number of results
uvx ppget "COVID-19 vaccine" -l 50

# Save as JSON
uvx ppget "cancer immunotherapy" -f json

Install and use

For frequent use, you can install it:

# Install with pip
pip install ppget

# Install with uv
uv tool install ppget

# Run
ppget "your search query"

📖 Usage

Basic usage

# Simple search (CSV format by default, up to 100 results)
ppget "diabetes treatment"

# Example output:
# Searching PubMed...
# Query: 'diabetes treatment'
# Max results: 100
# ✓ Found 100 articles
# ✓ Saved 100 articles to pubmed_20251018_143022.csv
# ✓ Metadata saved to pubmed_20251018_143022.meta.txt

Options

ppget [query] [options]

Required:
  query                 Search query (wrap in quotes only when the query contains spaces or shell-special characters)

Options:
  -l, --limit          Maximum number of results (default: 100)
  -o, --output         Output file or directory
  -f, --format         Output format: csv or json (default: csv)
  -e, --email          Email address (for API rate limit relaxation)
  -q, --quiet          Suppress progress messages (errors only)
  -v, --version        Show version and exit
  -h, --help           Show help message

Advanced usage

1. Change number of results

# Retrieve up to 200 results
ppget "machine learning healthcare" -l 200

2. Specify output format

# Save as JSON
ppget "spine surgery" -f json

# Default is CSV (can be opened in Excel)
ppget "orthopedics" -f csv

3. Specify filename

# Specify file path directly
ppget "cancer research" -o results/cancer_papers.csv

# Specify directory (filename is auto-generated)
ppget "neuroscience" -o ./data/

# Extension determines format
ppget "cardiology" -o heart_disease.json

4. Specify email address (recommended for heavy usage)

NCBI requests a contact email for tools that access the E-utilities API. Providing one helps them reach you about issues and may reduce rate-limiting for larger batches:

ppget "genomics" -e [e-mail] -l 500

5. Use PubMed search syntax

# AND search
ppget "machine learning AND radiology"

# OR search
ppget "COVID-19 OR SARS-CoV-2"

# MeSH term search
ppget "Diabetes Mellitus[MeSH] AND Drug Therapy[MeSH]"

# Filter by year
ppget "cancer immunotherapy AND 2024[PDAT]"

# Search by author
ppget "Smith J[Author]"

# Complex search
ppget "(machine learning OR deep learning) AND (radiology OR imaging) AND 2023:2024[PDAT]"

📁 Output Format

CSV format (default)

Easy to open in spreadsheets. A metadata file (.meta.txt) is also generated.

pubmed_20251018_143022.csv          # Article data
pubmed_20251018_143022.meta.txt     # Search metadata

CSV columns:

• pubmed_id - PubMed ID
• pubmed_link - Direct link to the PubMed article page
• title - Title
• abstract - Abstract
• journal - Journal name
• publication_date - Publication date
• doi - DOI
• authors - Author list (semicolon-separated)
• keywords - Keywords (semicolon-separated)

JSON format

Easy to process programmatically.

[
  {
    "pubmed_id": "12345678",
    "title": "...",
    "abstract": "...",
    ...
  }
]

Metadata file (.meta.txt):

Query: machine learning
Search Date: 2025-10-18 14:30:22
Retrieved Results: 100
Data File: pubmed_20251018_143022.json

ℹ️ Tips

• Quotes around the query are optional when it is a single token (e.g. ppget diabetes). Use quotes when the query contains spaces, parentheses, logical operators, or shell-special characters.
• Add -e [e-mail] if you plan to run many requests or large limits. It identifies your tool to NCBI and can keep you within their published rate limits (default 3 req/sec without email, up to 10 req/sec with email & api key).

💡 Use Cases

Collecting research papers

# Collect latest papers on a specific topic
ppget "CRISPR gene editing" -l 100 -o crispr_papers.csv

# Run multiple searches at once
ppget "diabetes treatment 2024[PDAT]" -o diabetes_2024.csv
ppget "cancer immunotherapy 2024[PDAT]" -o cancer_2024.csv

For data analysis

# Retrieve in JSON format and analyze with Python
ppget "artificial intelligence healthcare" -f json -l 500 -o ai_health.json

# Example Python code to read
import json
with open('ai_health.json') as f:
    data = json.load(f)
    # Analysis...

Literature review

# Retrieve in CSV and manage in Excel
ppget "systematic review AND meta-analysis" -l 200 -o reviews.csv

# → Open in Excel and review titles and abstracts

🤝 Contributing

Bug reports and feature requests are welcome at Issues.

📄 License

MIT License - See LICENSE for details.

🙏 Acknowledgments

This tool uses pymed-paperscraper.

---

Start searching PubMed easily and quickly!

uvx ppget "your research topic"