7d702e9cbd
- Add db.py PostgreSQL abstraction layer (connection, upsert, table mgmt) - Replace sqlite3 with psycopg2 in: live_candle_fetcher, resampler, data_fetcher, fetch_history, import_csv, indicators, base_strategy - Sanitize table names (colons -> underscores) for PostgreSQL compat - Replace INSERT OR REPLACE with ON CONFLICT upserts - Replace pandas to_sql() with batch upsert_candles() - Add scripts: resampler_loop, gap_detector, backup_runner, cron_scheduler - Add migrate_sqlite_to_pg.py for one-time data migration - Add Dockerfile, docker-compose.yml, supervisord.conf - Add postgres/postgresql.conf tuned for 4GB RAM (Synology DS1513+) - Add .dockerignore, .env.docker.example, secrets template - Update requirements.txt (psycopg2-binary), .gitignore - Add MIGRATION_PLAN.md with full plan and todo list
133 lines
4.0 KiB
Python
133 lines
4.0 KiB
Python
"""
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PostgreSQL database abstraction layer for the Hyperliquid trading toolkit.
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Provides a thin wrapper around psycopg2 to centralize database operations,
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handle table name sanitization, and abstract SQL dialect differences
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from the SQLite-based codebase.
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"""
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import os
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import psycopg2
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from psycopg2.extras import execute_values
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PG_CONN_STR = os.environ.get(
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"PG_CONN_STR",
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"postgresql://hyper:hyper@localhost:5432/hyper"
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)
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def get_connection():
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"""Return a new psycopg2 connection to the PostgreSQL database."""
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return psycopg2.connect(PG_CONN_STR)
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def sanitize_table_name(coin, timeframe):
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"""
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Sanitize a coin/timeframe pair into a PostgreSQL-safe table name.
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Replaces colons with underscores (e.g., 'xyz:BRENTOIL' -> 'xyz_BRENTOIL')
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to ensure compatibility with PostgreSQL identifier rules.
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"""
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return f"{coin.replace(':', '_')}_{timeframe}"
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def create_candle_table(conn, table_name):
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"""
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Create a candle table if it does not already exist.
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Schema matches the original SQLite layout:
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datetime_utc, timestamp_ms (PK), open, high, low, close, volume, number_of_trades
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Also creates an index on datetime_utc for time-range queries.
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"""
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with conn.cursor() as cur:
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cur.execute(f'''
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CREATE TABLE IF NOT EXISTS "{table_name}" (
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datetime_utc TIMESTAMP,
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timestamp_ms BIGINT PRIMARY KEY,
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open REAL,
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high REAL,
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low REAL,
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close REAL,
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volume REAL,
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number_of_trades INTEGER
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)
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''')
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cur.execute(
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f'CREATE INDEX IF NOT EXISTS "idx_{table_name}_time" ON "{table_name}"(datetime_utc)'
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)
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conn.commit()
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def upsert_candles(conn, table_name, records):
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"""
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Batch upsert candle records using PostgreSQL ON CONFLICT.
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Args:
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conn: psycopg2 connection
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table_name: sanitized table name (e.g., 'BTC_1m')
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records: list of tuples (datetime_utc, timestamp_ms, open, high,
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low, close, volume, number_of_trades)
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Returns:
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Number of records upserted.
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"""
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if not records:
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return 0
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with conn.cursor() as cur:
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execute_values(
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cur,
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f'''
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INSERT INTO "{table_name}"
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(datetime_utc, timestamp_ms, open, high, low, close, volume, number_of_trades)
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VALUES %s
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ON CONFLICT (timestamp_ms) DO UPDATE SET
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datetime_utc = EXCLUDED.datetime_utc,
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open = EXCLUDED.open,
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high = EXCLUDED.high,
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low = EXCLUDED.low,
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close = EXCLUDED.close,
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volume = EXCLUDED.volume,
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number_of_trades = EXCLUDED.number_of_trades
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''',
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records,
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page_size=1000
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)
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conn.commit()
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return len(records)
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def get_last_timestamp(conn, table_name):
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"""Return the most recent timestamp_ms from a table, or None."""
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with conn.cursor() as cur:
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cur.execute(f'SELECT MAX(timestamp_ms) FROM "{table_name}"')
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result = cur.fetchone()
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return result[0] if result and result[0] is not None else None
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def get_table_count(conn, table_name):
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"""Return the total row count of a table."""
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with conn.cursor() as cur:
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cur.execute(f'SELECT COUNT(*) FROM "{table_name}"')
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return cur.fetchone()[0]
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def table_exists(conn, table_name):
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"""Check if a table exists in the database."""
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with conn.cursor() as cur:
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cur.execute(
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"SELECT EXISTS (SELECT 1 FROM information_schema.tables WHERE table_name = %s)",
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(table_name,)
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)
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return cur.fetchone()[0]
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def get_table_columns(conn, table_name):
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"""Return a list of column names for a table."""
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with conn.cursor() as cur:
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cur.execute(
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"SELECT column_name FROM information_schema.columns WHERE table_name = %s",
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(table_name,)
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)
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return [row[0] for row in cur.fetchall()]
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