About This Project
HypePlot is a comprehensive tool for tracking keyword trends across multiple platforms and timeframes. It combines 12 powerful data sources to give you a complete picture of topic evolution:
Flexible Time Bucketing: Analyze data at yearly, monthly, quarterly, or custom intervals (e.g., every 10 days).
📚 Showcase Examples
Artificial Intelligence
Data from scholar sources
Fhir
Data from scholar sources
Pandas
Data from scholar sources
🚀 Use It Yourself
Want to analyze your own topics? Install and run HypePlot locally:
# Clone the repository
git clone https://github.com/quotentiroler/HypePlot
cd HypePlot
# Install dependencies (requires Python 3.12+ and uv)
pip install uv
uv sync
# Run with different sources and time buckets
uv run hype "FHIR" 2024 2025 plot --source github --bucket monthly
uv run hype "python" 2023 2025 plot --source github,arxiv --bucket quarterly
uv run hype "covid" 2020 2024 plot --source patents,news --bucket yearly
# Custom buckets (10-day periods)
uv run hype "AI" 2025 2025 plot --source github --bucket days:10
Available Sources
github- Repository counts and metricsarxiv- Research preprintsreddit- Discussion posts via Pushshiftyoutube- Video contentscholar- Academic publicationstrends- Google search interestnews- News articles (NewsAPI)twitter- Mentions (requires API access)patents- USPTO patentspackages- PyPI download statsjobs- Job postings (Adzuna)grants- NSF research grants and funding
Time Bucket Options
--bucket yearly- Annual aggregation (1 year)--bucket quarterly- Quarterly periods (3 months)--bucket monthly- Monthly periods--bucket days:N- Custom N-day periods
✨ Features
🔍 12 Data Sources
Comprehensive coverage across platforms
📅 Flexible Bucketing
Yearly, monthly, quarterly, or custom intervals
📈 Interactive Plots
Built with Plotly for rich interactivity
💾 CSV Export
All data exported for further analysis
🐍 Modern Python
Built with uv, type hints, async-ready
🤖 Automation Ready
GitHub Actions for scheduled updates