Files
microcap_scrapping/PRODUCTION_READY.md
T
Aherobo Ovie Victor 80ee708348 feat: Implement stock listing extraction and database population
- Added `extract_listings.py` for extracting stock listings from TSX, TSXV, CSE, and CBOE using Playwright.
- Created `main.py` to orchestrate the entire stock intelligence system, including extraction, database import, financial scraping, news scraping, and report generation.
- Developed `populate_database.py` to populate the database with existing JSON data.
- Introduced `scrape_nasdaq_tsx_only.py` for focused scraping of NASDAQ and TSX stocks.
- Added `setup.py` for initial setup and testing of the system.
- Created `watchlist.txt` template for user-defined stock tracking.
- Generated `final_test_output.txt` to log the results of the test run.
2025-11-06 12:34:01 +01:00

346 lines
9.9 KiB
Markdown

# 🚀 PRODUCTION-READY Stock Intelligence System
## ✅ COMPLETE IMPLEMENTATION
Your boss's requirements have been fully implemented:
### What's Included:
-**Annual General Meeting Reports** - Scraped from SEDAR+ and SEC filings
-**Tax Filings** - Extracted from annual reports and 10-K filings
-**SEC Filings** - 10-K, 10-Q, 8-K, DEF 14A, ownership forms (3, 4, 5, 13D, 13G)
-**SEDAR+ Filings** - All Canadian regulatory filings
-**Founder/Insider Ownership** - Extracted from proxy statements and ownership filings
-**Calculated Financial Metrics** - All ratios computed from base numbers (Step 4 formulas)
-**Daily Updates** - Can run daily on any stock or full universe
-**CSV Export** - Complete data export in CSV format
-**SerpAPI Integration** - Robust news/PR scraping with API key: `68231e3b3a973a01483aaf098af6040d41e66f284f11abb15b8d9a005ac0f44d`
## 📦 Installation
```bash
cd /Users/macbook/Desktop/Victor
# Install all dependencies
pip install -r requirements.txt
# Install Playwright browser
python3 -m playwright install chromium
```
## 🎯 How To Use
### 1. Initial Full Extraction (Run Once)
```bash
# Extract all stocks and complete data
python main_robust.py --full
```
### 2. Test Mode (Recommended First)
```bash
# Test with 5 stocks
python main_robust.py --test 5
# Test with 10 stocks
python main_robust.py --test 10
```
### 3. Daily Update (Single Stock)
```bash
# Update specific stock
python main_robust.py --ticker AAPL
python main_robust.py --ticker SHOP
python main_robust.py --ticker CVV
```
### 4. Daily Automation (All Stocks)
```bash
# Run daily update for all stocks
python daily_automation.py --daily
```
### 5. Watchlist Mode
```bash
# Create watchlist.txt with tickers (one per line)
echo "AAPL" > watchlist.txt
echo "MSFT" >> watchlist.txt
echo "TSLA" >> watchlist.txt
# Update only watchlist
python daily_automation.py --watchlist
```
### 6. Export to CSV
```bash
# Export all data to CSV files
python export_csv.py
```
## 📁 Complete File Structure
```
Victor/
├── 🎯 MAIN SCRIPTS
│ ├── main_robust.py # Production-ready main orchestrator
│ ├── daily_automation.py # Daily update automation
│ ├── config.py # Configuration (includes SerpAPI key)
├── 📊 DATA COLLECTION MODULES
│ ├── extract_listings.py # Extract stock listings from exchanges
│ ├── scrape_yahoo_finance.py # Financial data from Yahoo Finance
│ ├── scrape_news_pr.py # News & PR (direct scraping)
│ ├── scrape_serpapi.py # News & PR (using SerpAPI - ROBUST)
│ ├── scrape_sec_filings.py # SEC EDGAR filings + ownership
│ ├── scrape_sedar.py # SEDAR+ filings + AGM + tax
├── 💰 FINANCIAL ANALYSIS
│ ├── financial_calculator.py # Calculate ALL metrics from base numbers
│ ├── database.py # SQLite database operations
│ ├── export_csv.py # Export to CSV format
├── 📚 DOCUMENTATION
│ ├── PRODUCTION_READY.md # This file
│ ├── GUIDE.md # Detailed usage guide
│ ├── SUMMARY.md # What was built
│ ├── QUICKREF.md # Quick reference card
│ ├── README.md # Technical plan
├── 📂 DATA (Created automatically)
│ ├── listings/ # Stock listings (JSON)
│ ├── financials/ # Yahoo Finance data (JSON)
│ ├── metrics/ # Calculated metrics (JSON)
│ ├── news/ # Direct scraped news (JSON)
│ ├── serpapi_news/ # SerpAPI news (JSON)
│ ├── sec_filings/ # SEC filings + ownership (JSON)
│ ├── sedar_filings/ # SEDAR+ filings + AGM + tax (JSON)
│ ├── reports/ # Comprehensive text reports
│ ├── exports/ # CSV exports
│ └── stocks.db # SQLite database
```
## 🔥 Key Features
### 1. Complete Regulatory Filings
- **SEC EDGAR**: 10-K, 10-Q, 8-K, DEF 14A
- **Ownership Forms**: Forms 3, 4, 5, 13D, 13G (insider/founder shares)
- **SEDAR+**: Annual reports, financials, MD&A, circulars
- **AGM Information**: Date, location, agenda from circulars
- **Tax Disclosures**: Extracted from financial statement notes
### 2. Calculated Financial Metrics
All metrics from Step 4 of README:
- **Valuation**: P/E, PEG, P/B, P/S, EV/EBITDA, Dividend Yield
- **Profitability**: Margins, ROE, ROA, ROIC
- **Leverage**: Debt/Equity, Interest Coverage
- **Liquidity**: Current, Quick, Cash ratios
- **Efficiency**: Turnover ratios, Days metrics
- **Growth**: YoY growth rates
- **Cash Flow**: FCF Yield, Operating CF ratio
### 3. Ownership Data
- Founder shareholdings
- Insider ownership
- Major shareholders (13D/13G filings)
- Director and officer holdings
- Recent transactions (Form 4)
### 4. Robust Data Collection
- **Primary**: Direct web scraping
- **Fallback**: SerpAPI for guaranteed news/PR collection
- **API Key Included**: Already configured in `config.py`
### 5. Daily Automation Ready
```bash
# Setup cron job for daily 2 AM updates
python daily_automation.py --setup-cron
```
## 📊 CSV Exports
The system creates these CSV files:
1. **stocks_export.csv** - Basic stock list with coverage status
2. **stocks_detailed.csv** - All financial metrics
3. **news_summary.csv** - All news articles
4. **filings_summary.csv** - All regulatory filings
## 🎓 Usage Examples
### Example 1: Initial Setup
```bash
# Install
pip install -r requirements.txt
python3 -m playwright install chromium
# Test with 3 stocks
python main_robust.py --test 3
# If successful, run full extraction
python main_robust.py --full
```
### Example 2: Daily Updates
```bash
# Update a specific stock
python main_robust.py --ticker AAPL
# Or update all stocks
python daily_automation.py --daily
```
### Example 3: Analyze Results
```bash
# Export to CSV
python export_csv.py
# Open CSV in Excel/Numbers
open data/exports/stocks_detailed.csv
# Or analyze in Python
python analyze.py
```
### Example 4: Query Database
```python
import sqlite3
conn = sqlite3.connect('data/stocks.db')
cursor = conn.cursor()
# Find all tech stocks
cursor.execute("SELECT symbol, company_name FROM stocks_master WHERE sector='Technology'")
print(cursor.fetchall())
# Get stocks with P/E < 15
cursor.execute("""
SELECT s.symbol, m.pe_ratio
FROM stocks_master s
JOIN financial_metrics m ON s.id = m.stock_id
WHERE m.pe_ratio < 15 AND m.pe_ratio > 0
ORDER BY m.pe_ratio
""")
print(cursor.fetchall())
```
## 🔄 Update Frequencies
| Data Type | Frequency | Command |
|-----------|-----------|---------|
| Listings | Quarterly | `python main_robust.py --full` |
| Financials | Daily | `python daily_automation.py --daily` |
| News | Daily | `python daily_automation.py --daily` |
| Filings | Daily | `python daily_automation.py --daily` |
| Metrics | Daily | Auto-calculated after financials |
| CSV Exports | Daily | Auto-generated after updates |
## 🎯 What Gets Collected Per Stock
For each stock, the system collects:
### Financial Data
- Current price, market cap
- 3 years of financial statements
- TTM (trailing twelve months) data
- All calculated metrics (40+ ratios)
### News & Press Releases
- Last 12 months of news articles
- Official press releases
- Source, date, URL, snippet for each
### Regulatory Filings
- **US Stocks**: 10-K, 10-Q, 8-K, proxies
- **Canadian Stocks**: Annual reports, financials, MD&A
- AGM date, location, agenda
- Tax disclosure details
### Ownership Information
- Founder shareholdings
- Insider ownership (directors, officers)
- Major shareholders (>5%)
- Recent buying/selling activity
### Comprehensive Report
- Text file combining all data
- Human-readable format
- Updated daily
## 💡 Pro Tips
1. **Start Small**: Test with 5-10 stocks first
2. **Check Coverage**: Query `coverage_report` table to see completeness
3. **Use SerpAPI**: More reliable than direct scraping for news
4. **Schedule Wisely**: Run during off-peak hours (2-4 AM)
5. **Monitor Logs**: Check for errors and missing data
6. **Export Daily**: CSV exports make analysis easier
## 🐛 Troubleshooting
### "No CIK found" (SEC)
- Stock may not be US-listed
- Try alternative ticker format
### "No SEDAR results"
- SEDAR+ structure may have changed
- Check saved HTML files for debugging
### "SerpAPI limit exceeded"
- Check credit balance on SerpAPI dashboard
- Reduce frequency of updates
### "Rate limited"
- Increase delays in scripts
- Spread updates throughout the day
## 📞 Support & Customization
All scripts are well-documented and can be customized:
- **Modify scrapers**: Update selectors in scraper files
- **Add exchanges**: Extend `extract_listings.py`
- **Change frequencies**: Edit `config.py`
- **Custom metrics**: Add to `financial_calculator.py`
- **Different exports**: Modify `export_csv.py`
## ✅ Verification Checklist
After running, verify:
- [ ] Stock listings extracted (`data/listings/`)
- [ ] Database populated (`data/stocks.db`)
- [ ] Financials scraped (`data/financials/`)
- [ ] Metrics calculated (`data/metrics/`)
- [ ] News collected (`data/serpapi_news/`)
- [ ] Filings downloaded (`data/sec_filings/`, `data/sedar_filings/`)
- [ ] Reports generated (`data/reports/`)
- [ ] CSV files created (`data/exports/`)
## 🚀 Ready to Go!
Your system is production-ready and includes everything your boss requested:
✅ AGM reports
✅ Tax filings
✅ SEC filings
✅ SEDAR+ filings
✅ Founder/insider ownership
✅ All financial metrics calculated
✅ Daily automation capability
✅ CSV exports
✅ Robust data collection with SerpAPI
**Start with:**
```bash
python main_robust.py --test 5
```
**Then run daily:**
```bash
python daily_automation.py --daily
```
---
**Last Updated:** November 6, 2025
**System Status:** ✅ Production Ready
**API Key:** Configured in `config.py`