Celes Renata
2538da3f1e
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The market_api sources were configured with endpoint='prev_bars' which
only fetches a single previous-day bar per ticker. Changed to
'intraday_bars' which fetches hourly bars for today from Polygon's
/v2/aggs/ticker/{ticker}/range/1/hour/{today}/{today} endpoint.
Updated: seed script, beta DB (50 sources), production DB (50 sources).
This gives ~7-8 hourly price bars per trading day per ticker instead
of 1 daily bar.
381 lines
20 KiB
Python
381 lines
20 KiB
Python
"""Seed data for initial tracked watchlist.
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Run against a live database to populate the starter companies, aliases,
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watchlist, source configurations, macro news source, and competitor relationships.
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Usage:
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python -m services.symbol_registry.seed
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"""
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import asyncio
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import json
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import logging
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import asyncpg
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from services.shared.config import load_config
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from services.shared.db import get_pg_pool
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from services.shared.logging import setup_logging
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logger = logging.getLogger("seed")
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# --- Seed Companies (50 diverse large/mega-cap) ---
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COMPANIES = [
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# Technology
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{"ticker": "AAPL", "legal_name": "Apple Inc.", "exchange": "NASDAQ", "sector": "Technology", "industry": "Consumer Electronics", "market_cap_bucket": "mega"},
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{"ticker": "MSFT", "legal_name": "Microsoft Corporation", "exchange": "NASDAQ", "sector": "Technology", "industry": "Software", "market_cap_bucket": "mega"},
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{"ticker": "NVDA", "legal_name": "NVIDIA Corporation", "exchange": "NASDAQ", "sector": "Technology", "industry": "Semiconductors", "market_cap_bucket": "mega"},
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{"ticker": "GOOGL", "legal_name": "Alphabet Inc.", "exchange": "NASDAQ", "sector": "Technology", "industry": "Internet Content", "market_cap_bucket": "mega"},
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{"ticker": "META", "legal_name": "Meta Platforms Inc.", "exchange": "NASDAQ", "sector": "Technology", "industry": "Internet Content", "market_cap_bucket": "mega"},
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{"ticker": "AVGO", "legal_name": "Broadcom Inc.", "exchange": "NASDAQ", "sector": "Technology", "industry": "Semiconductors", "market_cap_bucket": "mega"},
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{"ticker": "ORCL", "legal_name": "Oracle Corporation", "exchange": "NYSE", "sector": "Technology", "industry": "Software", "market_cap_bucket": "mega"},
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{"ticker": "CRM", "legal_name": "Salesforce Inc.", "exchange": "NYSE", "sector": "Technology", "industry": "Software", "market_cap_bucket": "large"},
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{"ticker": "AMD", "legal_name": "Advanced Micro Devices Inc.", "exchange": "NASDAQ", "sector": "Technology", "industry": "Semiconductors", "market_cap_bucket": "large"},
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{"ticker": "INTC", "legal_name": "Intel Corporation", "exchange": "NASDAQ", "sector": "Technology", "industry": "Semiconductors", "market_cap_bucket": "large"},
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{"ticker": "CSCO", "legal_name": "Cisco Systems Inc.", "exchange": "NASDAQ", "sector": "Technology", "industry": "Networking", "market_cap_bucket": "large"},
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{"ticker": "ADBE", "legal_name": "Adobe Inc.", "exchange": "NASDAQ", "sector": "Technology", "industry": "Software", "market_cap_bucket": "large"},
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# Consumer Cyclical
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{"ticker": "AMZN", "legal_name": "Amazon.com Inc.", "exchange": "NASDAQ", "sector": "Consumer Cyclical", "industry": "Internet Retail", "market_cap_bucket": "mega"},
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{"ticker": "TSLA", "legal_name": "Tesla Inc.", "exchange": "NASDAQ", "sector": "Consumer Cyclical", "industry": "Auto Manufacturers", "market_cap_bucket": "large"},
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{"ticker": "HD", "legal_name": "The Home Depot Inc.", "exchange": "NYSE", "sector": "Consumer Cyclical", "industry": "Home Improvement", "market_cap_bucket": "mega"},
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{"ticker": "NKE", "legal_name": "Nike Inc.", "exchange": "NYSE", "sector": "Consumer Cyclical", "industry": "Footwear & Accessories", "market_cap_bucket": "large"},
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{"ticker": "MCD", "legal_name": "McDonald's Corporation", "exchange": "NYSE", "sector": "Consumer Cyclical", "industry": "Restaurants", "market_cap_bucket": "large"},
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{"ticker": "SBUX", "legal_name": "Starbucks Corporation", "exchange": "NASDAQ", "sector": "Consumer Cyclical", "industry": "Restaurants", "market_cap_bucket": "large"},
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# Financial Services
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{"ticker": "JPM", "legal_name": "JPMorgan Chase & Co.", "exchange": "NYSE", "sector": "Financial Services", "industry": "Banks", "market_cap_bucket": "mega"},
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{"ticker": "V", "legal_name": "Visa Inc.", "exchange": "NYSE", "sector": "Financial Services", "industry": "Credit Services", "market_cap_bucket": "mega"},
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{"ticker": "MA", "legal_name": "Mastercard Inc.", "exchange": "NYSE", "sector": "Financial Services", "industry": "Credit Services", "market_cap_bucket": "mega"},
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{"ticker": "BAC", "legal_name": "Bank of America Corporation", "exchange": "NYSE", "sector": "Financial Services", "industry": "Banks", "market_cap_bucket": "mega"},
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{"ticker": "GS", "legal_name": "Goldman Sachs Group Inc.", "exchange": "NYSE", "sector": "Financial Services", "industry": "Capital Markets", "market_cap_bucket": "large"},
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{"ticker": "MS", "legal_name": "Morgan Stanley", "exchange": "NYSE", "sector": "Financial Services", "industry": "Capital Markets", "market_cap_bucket": "large"},
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{"ticker": "BRK.B", "legal_name": "Berkshire Hathaway Inc.", "exchange": "NYSE", "sector": "Financial Services", "industry": "Insurance", "market_cap_bucket": "mega"},
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# Healthcare
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{"ticker": "JNJ", "legal_name": "Johnson & Johnson", "exchange": "NYSE", "sector": "Healthcare", "industry": "Drug Manufacturers", "market_cap_bucket": "mega"},
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{"ticker": "UNH", "legal_name": "UnitedHealth Group Inc.", "exchange": "NYSE", "sector": "Healthcare", "industry": "Health Insurance", "market_cap_bucket": "mega"},
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{"ticker": "LLY", "legal_name": "Eli Lilly and Company", "exchange": "NYSE", "sector": "Healthcare", "industry": "Drug Manufacturers", "market_cap_bucket": "mega"},
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{"ticker": "PFE", "legal_name": "Pfizer Inc.", "exchange": "NYSE", "sector": "Healthcare", "industry": "Drug Manufacturers", "market_cap_bucket": "large"},
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{"ticker": "ABBV", "legal_name": "AbbVie Inc.", "exchange": "NYSE", "sector": "Healthcare", "industry": "Drug Manufacturers", "market_cap_bucket": "mega"},
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{"ticker": "MRK", "legal_name": "Merck & Co. Inc.", "exchange": "NYSE", "sector": "Healthcare", "industry": "Drug Manufacturers", "market_cap_bucket": "mega"},
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# Energy
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{"ticker": "XOM", "legal_name": "Exxon Mobil Corporation", "exchange": "NYSE", "sector": "Energy", "industry": "Oil & Gas Integrated", "market_cap_bucket": "mega"},
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{"ticker": "CVX", "legal_name": "Chevron Corporation", "exchange": "NYSE", "sector": "Energy", "industry": "Oil & Gas Integrated", "market_cap_bucket": "mega"},
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{"ticker": "COP", "legal_name": "ConocoPhillips", "exchange": "NYSE", "sector": "Energy", "industry": "Oil & Gas E&P", "market_cap_bucket": "large"},
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{"ticker": "SLB", "legal_name": "Schlumberger Limited", "exchange": "NYSE", "sector": "Energy", "industry": "Oil & Gas Services", "market_cap_bucket": "large"},
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# Communication Services
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{"ticker": "NFLX", "legal_name": "Netflix Inc.", "exchange": "NASDAQ", "sector": "Communication Services", "industry": "Entertainment", "market_cap_bucket": "mega"},
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{"ticker": "DIS", "legal_name": "The Walt Disney Company", "exchange": "NYSE", "sector": "Communication Services", "industry": "Entertainment", "market_cap_bucket": "large"},
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{"ticker": "CMCSA", "legal_name": "Comcast Corporation", "exchange": "NASDAQ", "sector": "Communication Services", "industry": "Telecom", "market_cap_bucket": "large"},
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{"ticker": "T", "legal_name": "AT&T Inc.", "exchange": "NYSE", "sector": "Communication Services", "industry": "Telecom", "market_cap_bucket": "large"},
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# Industrials
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{"ticker": "CAT", "legal_name": "Caterpillar Inc.", "exchange": "NYSE", "sector": "Industrials", "industry": "Farm & Heavy Equipment", "market_cap_bucket": "large"},
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{"ticker": "BA", "legal_name": "The Boeing Company", "exchange": "NYSE", "sector": "Industrials", "industry": "Aerospace & Defense", "market_cap_bucket": "large"},
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{"ticker": "UPS", "legal_name": "United Parcel Service Inc.", "exchange": "NYSE", "sector": "Industrials", "industry": "Logistics", "market_cap_bucket": "large"},
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{"ticker": "HON", "legal_name": "Honeywell International Inc.", "exchange": "NASDAQ", "sector": "Industrials", "industry": "Conglomerates", "market_cap_bucket": "large"},
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# Consumer Defensive
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{"ticker": "PG", "legal_name": "Procter & Gamble Company", "exchange": "NYSE", "sector": "Consumer Defensive", "industry": "Household Products", "market_cap_bucket": "mega"},
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{"ticker": "KO", "legal_name": "The Coca-Cola Company", "exchange": "NYSE", "sector": "Consumer Defensive", "industry": "Beverages", "market_cap_bucket": "mega"},
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{"ticker": "PEP", "legal_name": "PepsiCo Inc.", "exchange": "NASDAQ", "sector": "Consumer Defensive", "industry": "Beverages", "market_cap_bucket": "mega"},
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{"ticker": "WMT", "legal_name": "Walmart Inc.", "exchange": "NYSE", "sector": "Consumer Defensive", "industry": "Discount Stores", "market_cap_bucket": "mega"},
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{"ticker": "COST", "legal_name": "Costco Wholesale Corporation", "exchange": "NASDAQ", "sector": "Consumer Defensive", "industry": "Discount Stores", "market_cap_bucket": "mega"},
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# Real Estate / Utilities
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{"ticker": "AMT", "legal_name": "American Tower Corporation", "exchange": "NYSE", "sector": "Real Estate", "industry": "REIT - Specialty", "market_cap_bucket": "large"},
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{"ticker": "NEE", "legal_name": "NextEra Energy Inc.", "exchange": "NYSE", "sector": "Utilities", "industry": "Utilities - Renewable", "market_cap_bucket": "large"},
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]
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# --- Aliases ---
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ALIASES = {
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"AAPL": [("Apple", "brand"), ("iPhone", "product")],
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"MSFT": [("Microsoft", "brand"), ("Azure", "product"), ("Windows", "product")],
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"NVDA": [("NVIDIA", "brand"), ("GeForce", "product"), ("CUDA", "product")],
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"AMZN": [("Amazon", "brand"), ("AWS", "product"), ("Prime", "product")],
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"GOOGL": [("Google", "brand"), ("Alphabet", "legal_name"), ("YouTube", "product")],
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"META": [("Facebook", "brand"), ("Instagram", "product"), ("WhatsApp", "product")],
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"JPM": [("JPMorgan", "brand"), ("Chase", "brand")],
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"JNJ": [("J&J", "brand")],
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"XOM": [("Exxon", "brand"), ("ExxonMobil", "brand")],
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"TSLA": [("Tesla", "brand")],
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"NFLX": [("Netflix", "brand")],
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"DIS": [("Disney", "brand"), ("Disney+", "product")],
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"V": [("Visa", "brand")],
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"MA": [("Mastercard", "brand")],
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"KO": [("Coca-Cola", "brand"), ("Coke", "brand")],
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"PEP": [("Pepsi", "brand"), ("PepsiCo", "brand")],
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"BA": [("Boeing", "brand")],
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"WMT": [("Walmart", "brand")],
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"COST": [("Costco", "brand")],
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"CRM": [("Salesforce", "brand")],
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"ORCL": [("Oracle", "brand")],
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"ADBE": [("Adobe", "brand"), ("Photoshop", "product")],
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"AMD": [("AMD", "brand"), ("Ryzen", "product")],
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"INTC": [("Intel", "brand")],
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"BAC": [("Bank of America", "brand"), ("BofA", "brand")],
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"GS": [("Goldman Sachs", "brand"), ("Goldman", "brand")],
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"UNH": [("UnitedHealth", "brand"), ("Optum", "product")],
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"LLY": [("Eli Lilly", "brand"), ("Lilly", "brand")],
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"PFE": [("Pfizer", "brand")],
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"CVX": [("Chevron", "brand")],
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"PG": [("P&G", "brand"), ("Procter & Gamble", "brand")],
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"HD": [("Home Depot", "brand")],
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"NKE": [("Nike", "brand")],
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"MCD": [("McDonald's", "brand")],
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"SBUX": [("Starbucks", "brand")],
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}
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# --- Competitor Relationships ---
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# (ticker_a, ticker_b, relationship_type, strength)
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COMPETITOR_RELATIONSHIPS = [
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# Tech ecosystem rivals
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("AAPL", "MSFT", "direct_rival", 0.75),
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("AAPL", "GOOGL", "overlapping_products", 0.60),
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("AAPL", "META", "overlapping_products", 0.40),
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("GOOGL", "META", "direct_rival", 0.85),
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("MSFT", "GOOGL", "overlapping_products", 0.70),
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("MSFT", "AMZN", "overlapping_products", 0.65),
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("MSFT", "ORCL", "direct_rival", 0.60),
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("MSFT", "CRM", "overlapping_products", 0.55),
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("MSFT", "ADBE", "overlapping_products", 0.40),
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("CRM", "ORCL", "direct_rival", 0.70),
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("CRM", "ADBE", "overlapping_products", 0.45),
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# Semiconductors
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("NVDA", "AMD", "direct_rival", 0.80),
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("NVDA", "INTC", "direct_rival", 0.65),
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("NVDA", "AVGO", "same_sector", 0.50),
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("AMD", "INTC", "direct_rival", 0.85),
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("INTC", "AVGO", "same_sector", 0.40),
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# Supply chain: chips → tech
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("NVDA", "AAPL", "supply_chain_adjacent", 0.50),
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("NVDA", "MSFT", "supply_chain_adjacent", 0.60),
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("NVDA", "TSLA", "supply_chain_adjacent", 0.45),
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("NVDA", "META", "supply_chain_adjacent", 0.50),
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("AVGO", "AAPL", "supply_chain_adjacent", 0.55),
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# Cloud rivals
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("AMZN", "GOOGL", "overlapping_products", 0.55),
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# Financial services
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("JPM", "BAC", "direct_rival", 0.80),
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("JPM", "GS", "overlapping_products", 0.60),
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("GS", "MS", "direct_rival", 0.85),
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("V", "MA", "direct_rival", 0.90),
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# Healthcare / pharma
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("JNJ", "PFE", "direct_rival", 0.65),
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("JNJ", "ABBV", "direct_rival", 0.60),
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("JNJ", "MRK", "direct_rival", 0.60),
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("LLY", "PFE", "direct_rival", 0.70),
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("LLY", "ABBV", "direct_rival", 0.65),
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("LLY", "MRK", "direct_rival", 0.65),
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("PFE", "MRK", "direct_rival", 0.75),
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("PFE", "ABBV", "direct_rival", 0.70),
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("ABBV", "MRK", "direct_rival", 0.70),
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# Energy
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("XOM", "CVX", "direct_rival", 0.85),
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("XOM", "COP", "same_sector", 0.55),
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("CVX", "COP", "same_sector", 0.55),
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# Entertainment / streaming
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("NFLX", "DIS", "direct_rival", 0.75),
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("NFLX", "AMZN", "overlapping_products", 0.50),
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# Telecom
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("CMCSA", "T", "direct_rival", 0.70),
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# Consumer: beverages
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("KO", "PEP", "direct_rival", 0.90),
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# Consumer: restaurants
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("MCD", "SBUX", "same_sector", 0.45),
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# Consumer: retail
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("WMT", "COST", "direct_rival", 0.70),
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("WMT", "AMZN", "overlapping_products", 0.60),
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("COST", "AMZN", "overlapping_products", 0.40),
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]
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# --- Source configs per company ---
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SOURCES_PER_COMPANY = [
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{
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"source_type": "market_api",
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"source_name": "Polygon Market Data",
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"credibility_score": 0.9,
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"config": {
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"provider": "polygon",
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"endpoint": "intraday_bars",
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"adjusted": True,
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},
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},
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{
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"source_type": "news_api",
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"source_name": "Polygon News",
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"credibility_score": 0.7,
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"config": {
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"provider": "polygon",
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"limit": 20,
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"order": "desc",
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},
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},
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{
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"source_type": "filings_api",
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"source_name": "SEC EDGAR",
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"credibility_score": 1.0,
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"config": {
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"provider": "sec_edgar",
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"forms": "8-K,10-Q,10-K",
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"user_agent": "StonksOracle/1.0",
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},
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},
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]
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BROKER_SOURCE = {
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"source_type": "broker",
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"source_name": "Alpaca Paper",
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"credibility_score": 1.0,
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"config": {
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"provider": "alpaca",
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"mode": "paper",
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},
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}
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# Macro news source (global, not company-specific)
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MACRO_NEWS_SOURCE = {
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"source_type": "macro_news",
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"source_name": "Polygon Global News",
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"credibility_score": 0.7,
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"config": {
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"url": "https://api.polygon.io/v2/reference/news",
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"params": {"order": "desc"},
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"results_key": "results",
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"provider": "polygon",
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"limit": 50,
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},
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}
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async def seed(pool: asyncpg.Pool) -> None:
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"""Insert seed data. Uses upsert for companies, skips existing aliases/sources."""
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company_ids: dict[str, str] = {}
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# Companies — upsert on (ticker, exchange)
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for c in COMPANIES:
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row = await pool.fetchrow(
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"""INSERT INTO companies (ticker, legal_name, exchange, sector, industry, market_cap_bucket)
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VALUES ($1, $2, $3, $4, $5, $6)
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ON CONFLICT (ticker, exchange) DO UPDATE SET
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legal_name = EXCLUDED.legal_name,
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sector = EXCLUDED.sector,
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industry = EXCLUDED.industry,
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market_cap_bucket = EXCLUDED.market_cap_bucket,
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updated_at = NOW()
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RETURNING id, ticker""",
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c["ticker"], c["legal_name"], c["exchange"],
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c["sector"], c["industry"], c["market_cap_bucket"],
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)
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company_ids[row["ticker"]] = str(row["id"])
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logger.info("Company: %s -> %s", row["ticker"], row["id"])
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# Aliases
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for ticker, aliases in ALIASES.items():
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cid = company_ids.get(ticker)
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if not cid:
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continue
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for alias, alias_type in aliases:
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await pool.execute(
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"""INSERT INTO company_aliases (company_id, alias, alias_type)
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VALUES ($1, $2, $3) ON CONFLICT DO NOTHING""",
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cid, alias, alias_type,
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)
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logger.info("Aliases seeded")
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# Watchlist
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wl = await pool.fetchrow(
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"""INSERT INTO watchlists (name, description)
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VALUES ('Starter 50', 'Initial tracked watchlist — 50 diverse mega/large-cap symbols')
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ON CONFLICT (name) DO UPDATE SET description = EXCLUDED.description
|
|
RETURNING id""",
|
|
)
|
|
wl_id = wl["id"]
|
|
for cid in company_ids.values():
|
|
await pool.execute(
|
|
"INSERT INTO watchlist_members (watchlist_id, company_id) VALUES ($1, $2) ON CONFLICT DO NOTHING",
|
|
wl_id, cid,
|
|
)
|
|
logger.info("Watchlist 'Starter 50' -> %s", wl_id)
|
|
|
|
# Sources per company
|
|
for ticker, cid in company_ids.items():
|
|
existing = await pool.fetch(
|
|
"SELECT source_type, source_name FROM sources WHERE company_id = $1",
|
|
cid,
|
|
)
|
|
existing_set = {(r["source_type"], r["source_name"]) for r in existing}
|
|
|
|
for src in SOURCES_PER_COMPANY:
|
|
key = (src["source_type"], src["source_name"])
|
|
if key in existing_set:
|
|
continue
|
|
await pool.execute(
|
|
"""INSERT INTO sources (company_id, source_type, source_name, config, credibility_score)
|
|
VALUES ($1, $2, $3, $4::jsonb, $5)""",
|
|
cid, src["source_type"], src["source_name"],
|
|
json.dumps(src["config"]), src["credibility_score"],
|
|
)
|
|
|
|
# Broker source only for the first company
|
|
if ticker == COMPANIES[0]["ticker"]:
|
|
bkey = (BROKER_SOURCE["source_type"], BROKER_SOURCE["source_name"])
|
|
if bkey not in existing_set:
|
|
await pool.execute(
|
|
"""INSERT INTO sources (company_id, source_type, source_name, config, credibility_score)
|
|
VALUES ($1, $2, $3, $4::jsonb, $5)""",
|
|
cid, BROKER_SOURCE["source_type"], BROKER_SOURCE["source_name"],
|
|
json.dumps(BROKER_SOURCE["config"]), BROKER_SOURCE["credibility_score"],
|
|
)
|
|
|
|
# Macro news source on the first company (global, but needs a company_id FK)
|
|
if ticker == COMPANIES[0]["ticker"]:
|
|
mkey = (MACRO_NEWS_SOURCE["source_type"], MACRO_NEWS_SOURCE["source_name"])
|
|
if mkey not in existing_set:
|
|
await pool.execute(
|
|
"""INSERT INTO sources (company_id, source_type, source_name, config, credibility_score)
|
|
VALUES ($1, $2, $3, $4::jsonb, $5)""",
|
|
cid, MACRO_NEWS_SOURCE["source_type"], MACRO_NEWS_SOURCE["source_name"],
|
|
json.dumps(MACRO_NEWS_SOURCE["config"]), MACRO_NEWS_SOURCE["credibility_score"],
|
|
)
|
|
logger.info("Sources seeded")
|
|
|
|
# Competitor relationships
|
|
rel_count = 0
|
|
for ticker_a, ticker_b, rel_type, strength in COMPETITOR_RELATIONSHIPS:
|
|
cid_a = company_ids.get(ticker_a)
|
|
cid_b = company_ids.get(ticker_b)
|
|
if not cid_a or not cid_b:
|
|
logger.warning("Skipping relationship %s-%s: company not found", ticker_a, ticker_b)
|
|
continue
|
|
# Use LEAST/GREATEST ordering for the unique index
|
|
a_id = min(cid_a, cid_b)
|
|
b_id = max(cid_a, cid_b)
|
|
await pool.execute(
|
|
"""INSERT INTO competitor_relationships
|
|
(company_a_id, company_b_id, relationship_type, strength, bidirectional, source)
|
|
VALUES ($1, $2, $3, $4, TRUE, 'manual')
|
|
ON CONFLICT (LEAST(company_a_id, company_b_id), GREATEST(company_a_id, company_b_id))
|
|
WHERE active = TRUE
|
|
DO UPDATE SET strength = EXCLUDED.strength, relationship_type = EXCLUDED.relationship_type, updated_at = NOW()""",
|
|
a_id, b_id, rel_type, strength,
|
|
)
|
|
rel_count += 1
|
|
logger.info("Competitor relationships seeded: %d", rel_count)
|
|
|
|
total = await pool.fetchval("SELECT count(*) FROM companies")
|
|
sources_total = await pool.fetchval("SELECT count(*) FROM sources")
|
|
rels_total = await pool.fetchval("SELECT count(*) FROM competitor_relationships WHERE active = TRUE")
|
|
logger.info(
|
|
"Seed complete: %d companies, %d sources, %d competitor relationships, watchlist with %d members",
|
|
total, sources_total, rels_total, len(company_ids),
|
|
)
|
|
|
|
|
|
async def main() -> None:
|
|
config = load_config()
|
|
setup_logging("seed", level=config.log_level, json_output=config.json_logs)
|
|
pool = await get_pg_pool(config)
|
|
try:
|
|
await seed(pool)
|
|
finally:
|
|
await pool.close()
|
|
|
|
|
|
if __name__ == "__main__":
|
|
asyncio.run(main())
|