Earnings Transcripts

Automated earnings call transcript fetcher using API Ninjas, running on GitHub Actions.

This repository automatically fetches earnings call transcripts for S&P 100 companies and stores them as JSON files. The fetcher runs daily via GitHub Actions and commits new transcripts to this repository.

API Ninjas - Free tier covers S&P 100 companies (top 100 US stocks by market cap).

Includes: Apple, Microsoft, Amazon, Google, Meta, Tesla, Nvidia, JPMorgan, and 90+ more major companies.

1. Sign up at api-ninjas.com/register
2. Copy your API key from the dashboard

1. Go to your repository Settings
2. Navigate to Secrets and variables → Actions
3. Click "New repository secret"
4. Name: API_NINJAS_KEY
5. Value: Your API key

1. Go to Settings → Actions → General
2. Under "Workflow permissions", select "Read and write permissions"
3. Save

The workflow runs daily at 6 AM UTC and fetches the latest transcript for each S&P 100 company.

1. Go to Actions tab
2. Select "Fetch Earnings Transcripts"
3. Click "Run workflow"
4. Options:
   • tickers: Comma-separated list (e.g., AAPL,MSFT,GOOGL) or leave empty for all
   • latest_only: true for latest only, false for all available

# Clone
git clone https://github.com/YOUR_USERNAME/earnings-transcripts.git
cd earnings-transcripts
# Setup
python -m venv venv
source venv/bin/activate
pip install -r requirements.txt
# Run (set your API key)
export API_NINJAS_KEY="your_api_key_here"
python scrape_transcripts.py
# Or fetch specific tickers
TICKERS="AAPL,MSFT" python scrape_transcripts.py

Files are saved as {TICKER}_{YEAR}_Q{QUARTER}.json:

{
 "ticker": "AAPL",
 "year": 2024,
 "quarter": 4,
 "date": "2024年10月31日",
 "transcript": "...",
 "participants": [...],
 "fetched_at": "2024年11月01日T06:00:00",
 "source": "api-ninjas"
}

A daily-updated calendar of upcoming S&P 500 earnings calls.

• View the Calendar — human-readable Markdown
• JSON Data — machine-readable structured data

Data source: Yahoo Finance via yfinance. Updated daily at 8 AM UTC by GitHub Actions.

# Run locally
python scripts/update_earnings_calendar.py
# Test with a few tickers
python scripts/update_earnings_calendar.py --limit 10
# Refresh S&P 500 list from Wikipedia
python scripts/update_earnings_calendar.py --update-tickers

MIT