Breverdbidder Zonewise Everest Supabase Operations

Everest Supabase Operations

Connection

Project: mocerqjnksmhcjzxrewo.supabase.co Region: us-east-1

from supabase import create_client

SUPABASE_URL = "https://mocerqjnksmhcjzxrewo.supabase.co"
SUPABASE_KEY = os.environ["SUPABASE_KEY"]  # Service role key

supabase = create_client(SUPABASE_URL, SUPABASE_KEY)

Key Tables

BidDeed.AI Tables

ZoneWise Tables

Life OS Tables

Shared Tables

Query Patterns

Safe Query Building

from scripts.query_builder import QueryBuilder

qb = QueryBuilder("historical_auctions")

# Select with filters
result = qb.select(
    columns=["case_number", "judgment_amount", "sale_price"],
    filters={"zip_code": "32937", "year": 2025},
    order_by="auction_date",
    limit=100
).execute()

Insert with Validation

from scripts.query_builder import safe_insert

# Validates against schema before insert
result = safe_insert(
    table="multi_county_auctions",
    data={
        "case_number": "05-2024-CA-012345",
        "parcel_id": "12345678",
        "judgment_amount": 150000,
        "auction_date": "2026-01-21"
    }
)

Upsert Pattern

result = supabase.table("multi_county_auctions").upsert(
    data,
   
).execute()

Checkpoint Management

Save Checkpoint

from scripts.checkpoint_manager import save_checkpoint

save_checkpoint(
    conversation_id="conv_123",
    state={
        "current_task": "foreclosure_analysis",
        "properties_processed": 15,
        "pending_properties": ["12345678", "87654321"],
        "context_summary": "Analyzing Dec 3 auction..."
    },
    token_count=150000
)

Load Checkpoint

from scripts.checkpoint_manager import load_checkpoint

checkpoint = load_checkpoint(conversation_id="conv_123")
if checkpoint:
    state = checkpoint["state"]
    # Resume from saved state

Auto-Checkpoint Trigger

TOKEN_THRESHOLD = 150000  # 75% of 200K limit

def check_checkpoint_needed(current_tokens: int) -> bool:
    return current_tokens >= TOKEN_THRESHOLD

Insights Logging

Log Insight

from scripts.insights_logger import log_insight

log_insight(
    category="ml_prediction",
    message="Third-party probability: 72%",
    data={
        "parcel_id": "12345678",
        "probability": 0.72,
        "confidence": "high"
    },
    level="info"
)

Log Categories

• pipeline: Scraper/workflow events
• ml_prediction: Model predictions
• decision: BID/REVIEW/SKIP decisions
• error: Errors and failures
• performance: Timing and metrics
• audit: Security/compliance events

Query Insights

# Get recent errors
errors = supabase.table("insights")\
    .select("*")\
    .eq("level", "error")\
    .gte("created_at", "2026-01-20")\
    .execute()

Table Schemas

historical_auctions

CREATE TABLE historical_auctions (
    id SERIAL PRIMARY KEY,
    case_number TEXT UNIQUE NOT NULL,
    parcel_id TEXT,
    address TEXT,
    zip_code TEXT,
    judgment_amount NUMERIC,
    opening_bid NUMERIC,
    sale_price NUMERIC,
    sold_to_third_party BOOLEAN,
    plaintiff TEXT,
    plaintiff_category TEXT,
    auction_date DATE,
    property_type TEXT,
    assessed_value NUMERIC,
    bedrooms INT,
    bathrooms NUMERIC,
    building_sf INT,
    lot_sf INT,
    year_built INT,
    created_at TIMESTAMPTZ DEFAULT NOW()
);

claude_context_checkpoints

CREATE TABLE claude_context_checkpoints (
    id SERIAL PRIMARY KEY,
    conversation_id TEXT NOT NULL,
    state JSONB NOT NULL,
    token_count INT,
    created_at TIMESTAMPTZ DEFAULT NOW(),
    expires_at TIMESTAMPTZ DEFAULT (NOW() + INTERVAL '7 days')
);

CREATE INDEX idx_checkpoints_conv ON claude_context_checkpoints(conversation_id);

insights

CREATE TABLE insights (
    id SERIAL PRIMARY KEY,
    category TEXT NOT NULL,
    level TEXT DEFAULT 'info',
    message TEXT NOT NULL,
    data JSONB,
    created_at TIMESTAMPTZ DEFAULT NOW()
);

CREATE INDEX idx_insights_category ON insights(category);
CREATE INDEX idx_insights_created ON insights(created_at DESC);

RLS Policies

Service Role (Full Access)

-- Used by backend/scripts
CREATE POLICY "Service role full access" ON historical_auctions
    FOR ALL USING (auth.role() = 'service_role');

Anon Role (Read Only)

-- Used by public API
CREATE POLICY "Anon read access" ON districts
    FOR SELECT USING (true);

Error Recovery

Retry Pattern

from scripts.query_builder import with_retry

@with_retry(max_attempts=3, backoff=2.0)
async def fetch_with_retry(table: str, filters: dict):
    return supabase.table(table).select("*").match(filters).execute()

Connection Recovery

from scripts.connection_manager import get_client

# Auto-reconnects on failure
client = get_client()  # Cached, reconnects if stale

Migrations

Run Migration

# Using Supabase CLI
supabase db push

# Or direct SQL
psql $DATABASE_URL -f migrations/001_add_column.sql

Migration Naming

migrations/
├── 001_initial_schema.sql
├── 002_add_ml_features.sql
├── 003_add_checkpoints.sql
└── 004_add_indexes.sql

Performance Tips

1. Use indexes for filtered columns
2. Limit results - never SELECT * without LIMIT
3. Use RPC for complex queries
4. Batch inserts - use upsert with arrays
5. Cache lookups - districts change rarely

Integration

• BidDeed.AI: Historical data, predictions, reports
• ZoneWise: District data, MCP logs
• Life OS: Task tracking, tax records
• Claude Sessions: Context checkpoints

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