Migrate data pipeline from SQLite to PostgreSQL + Docker setup

- 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

indicators.py

@@ -7,7 +7,8 @@ and custom functions.
 
 import json
 import os
-import sqlite3
+import psycopg2
+from contextlib import closing
 import importlib
 import logging
 import pandas as pd
@@ -36,9 +37,9 @@ class IndicatorCalculator:
 
     def _get_latest_close(self, coin, timeframe="1m"):
         """Get the latest close price from a candle table."""
-        table = f"{coin}_{timeframe}"
+        table = f"{coin.replace(':', '_')}_{timeframe}"
         try:
-            with sqlite3.connect(self.db_path) as conn:
+            with closing(psycopg2.connect(self.db_path)) as conn:
                 result = conn.execute(
                     f'SELECT close FROM "{table}" ORDER BY timestamp_ms DESC LIMIT 1'
                 ).fetchone()
@@ -49,9 +50,9 @@ class IndicatorCalculator:
 
     def _get_close_n_candles_ago(self, coin, timeframe, n=1):
         """Get the close price from n candles ago (n=1 = most recent completed candle)."""
-        table = f"{coin}_{timeframe}"
+        table = f"{coin.replace(':', '_')}_{timeframe}"
         try:
-            with sqlite3.connect(self.db_path) as conn:
+            with closing(psycopg2.connect(self.db_path)) as conn:
                 result = conn.execute(
                     f'SELECT close FROM "{table}" ORDER BY timestamp_ms DESC LIMIT 1 OFFSET {n}'
                 ).fetchone()
@@ -62,9 +63,9 @@ class IndicatorCalculator:
 
     def _get_all_closes(self, coin, timeframe="1d"):
         """Get all close prices from a candle table, ordered by time."""
-        table = f"{coin}_{timeframe}"
+        table = f"{coin.replace(':', '_')}_{timeframe}"
         try:
-            with sqlite3.connect(self.db_path) as conn:
+            with closing(psycopg2.connect(self.db_path)) as conn:
                 result = conn.execute(
                     f'SELECT close FROM "{table}" ORDER BY timestamp_ms'
                 ).fetchall()
@@ -75,10 +76,10 @@ class IndicatorCalculator:
 
     def _get_all_ratio(self, num_coin, den_coin, timeframe="1d"):
         """Get all ratio values (num/den) from candle tables, ordered by time."""
-        num_table = f"{num_coin}_{timeframe}"
-        den_table = f"{den_coin}_{timeframe}"
+        num_table = f"{num_coin.replace(':', '_')}_{timeframe}"
+        den_table = f"{den_coin.replace(':', '_')}_{timeframe}"
         try:
-            with sqlite3.connect(self.db_path) as conn:
+            with closing(psycopg2.connect(self.db_path)) as conn:
                 result = conn.execute(
                     f'SELECT n.close / d.close as ratio '
                     f'FROM "{num_table}" n '
@@ -92,10 +93,10 @@ class IndicatorCalculator:
 
     def _get_all_spread(self, num_coin, den_coin, timeframe="1d"):
         """Get all spread values (num - den) from candle tables, ordered by time."""
-        num_table = f"{num_coin}_{timeframe}"
-        den_table = f"{den_coin}_{timeframe}"
+        num_table = f"{num_coin.replace(':', '_')}_{timeframe}"
+        den_table = f"{den_coin.replace(':', '_')}_{timeframe}"
         try:
-            with sqlite3.connect(self.db_path) as conn:
+            with closing(psycopg2.connect(self.db_path)) as conn:
                 result = conn.execute(
                     f'SELECT n.close - d.close as spread '
                     f'FROM "{num_table}" n '
@@ -109,10 +110,10 @@ class IndicatorCalculator:
 
     def _get_all_diff_pct(self, num_coin, den_coin, timeframe="1d"):
         """Get all percentage difference values ((num-den)/den*100) from candle tables."""
-        num_table = f"{num_coin}_{timeframe}"
-        den_table = f"{den_coin}_{timeframe}"
+        num_table = f"{num_coin.replace(':', '_')}_{timeframe}"
+        den_table = f"{den_coin.replace(':', '_')}_{timeframe}"
         try:
-            with sqlite3.connect(self.db_path) as conn:
+            with closing(psycopg2.connect(self.db_path)) as conn:
                 result = conn.execute(
                     f'SELECT (n.close - d.close) / d.close * 100 as diff_pct '
                     f'FROM "{num_table}" n '