From ac8ac31d01cdd1b0e69504c0201d8f5b835e5957 Mon Sep 17 00:00:00 2001
From: DiTus <ditus@o2.pl>
Date: Tue, 14 Oct 2025 10:48:26 +0200
Subject: [PATCH] first stategies, import script for BTC histry

---
 __pycache__/logging_utils.cpython-313.pyc | Bin 1838 -> 3013 bytes
 _data/candles/hyperliquid-historical.py   | 231 ++++++++++++++++++++++
 _data/candles/requirements.txt            |   8 +
 _data/market_data.db-shm                  | Bin 0 -> 196608 bytes
 _data/strategies.json                     |  48 +++++
 import_csv.py                             | 147 ++++++++++++++
 logging_utils.py                          |  31 ++-
 main_app.py                               | 217 +++++++++++---------
 strategy_template.py                      | 132 +++++++++++++
 9 files changed, 717 insertions(+), 97 deletions(-)
 create mode 100644 _data/candles/hyperliquid-historical.py
 create mode 100644 _data/candles/requirements.txt
 create mode 100644 _data/market_data.db-shm
 create mode 100644 _data/strategies.json
 create mode 100644 import_csv.py
 create mode 100644 strategy_template.py

diff --git a/__pycache__/logging_utils.cpython-313.pyc b/__pycache__/logging_utils.cpython-313.pyc
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diff --git a/_data/candles/hyperliquid-historical.py b/_data/candles/hyperliquid-historical.py
new file mode 100644
index 0000000..d87bfba
--- /dev/null
+++ b/_data/candles/hyperliquid-historical.py
@@ -0,0 +1,231 @@
+import boto3
+from botocore import UNSIGNED
+from botocore.config import Config
+from botocore.exceptions import ClientError
+import os
+import argparse
+from datetime import datetime, timedelta
+import asyncio
+import lz4.frame
+from pathlib import Path
+import csv
+import json
+
+
+
+# MUST USE PATHLIB INSTEAD
+DIR_PATH = Path(__file__).parent
+BUCKET = "hyperliquid-archive"
+CSV_HEADER = ["datetime", "timestamp", "level", "price", "size", "number"]
+
+# s3 = boto3.client('s3', config=Config(signature_version=UNSIGNED))
+# s3.download_file('hyperliquid-archive', 'market_data/20230916/9/l2Book/SOL.lz4', f"{dir_path}/SOL.lz4")
+
+# earliest date: 20230415/0/
+
+
+
+def get_args():
+    parser = argparse.ArgumentParser(description="Retrieve historical tick level market data from Hyperliquid exchange")
+    subparser = parser.add_subparsers(dest="tool", required=True, help="tool: download, decompress, to_csv")
+
+    global_parser = subparser.add_parser("global_settings", add_help=False)
+    global_parser.add_argument("t", metavar="Tickers", help="Tickers of assets to be downloaded seperated by spaces. e.g. BTC ETH", nargs="+")
+    global_parser.add_argument("--all", help="Apply action to all available dates and times.", action="store_true", default=False)
+    global_parser.add_argument("--anonymous", help="Use anonymous (unsigned) S3 requests. Defaults to signed requests if not provided.", action="store_true", default=False)
+    global_parser.add_argument("-sd", metavar="Start date", help="Starting date as one unbroken string formatted: YYYYMMDD.  e.g. 20230916")
+    global_parser.add_argument("-sh", metavar="Start hour", help="Hour of the starting day as an integer between 0 and 23. e.g. 9  Default: 0", type=int, default=0)
+    global_parser.add_argument("-ed", metavar="End date", help="Ending date as one unbroken string formatted: YYYYMMDD.  e.g. 20230916")
+    global_parser.add_argument("-eh", metavar="End hour", help="Hour of the ending day as an integer between 0 and 23. e.g. 9  Default: 23", type=int, default=23)
+    
+
+    download_parser = subparser.add_parser("download", help="Download historical market data", parents=[global_parser])
+    decompress_parser = subparser.add_parser("decompress", help="Decompress downloaded lz4 data", parents=[global_parser])
+    to_csv_parser = subparser.add_parser("to_csv", help="Convert decompressed downloads into formatted CSV", parents=[global_parser])
+
+
+    return parser.parse_args()
+
+
+
+
+def make_date_list(start_date, end_date):
+    start_date = datetime.strptime(start_date, '%Y%m%d')
+    end_date = datetime.strptime(end_date, '%Y%m%d')
+    
+    date_list = []
+    
+    current_date = start_date
+    while current_date <= end_date:
+        date_list.append(current_date.strftime('%Y%m%d'))
+        current_date += timedelta(days=1)
+    
+    return date_list
+
+
+
+
+def make_date_hour_list(date_list, start_hour, end_hour, delimiter="/"):
+    date_hour_list = []
+    end_date = date_list[-1]
+    hour = start_hour
+    end = 23
+    for date in date_list:
+        if date == end_date:
+            end = end_hour
+
+        while hour <= end:
+            date_hour = date + delimiter + str(hour)
+            date_hour_list.append(date_hour)
+            hour += 1
+
+        hour = 0
+
+    return date_hour_list
+
+
+
+
+async def download_object(s3, asset, date_hour):
+    date_and_hour = date_hour.split("/")
+    key = f"market_data/{date_hour}/l2Book/{asset}.lz4"
+    dest = f"{DIR_PATH}/downloads/{asset}/{date_and_hour[0]}-{date_and_hour[1]}.lz4"
+    try:
+        s3.download_file(BUCKET, key, dest)
+    except ClientError as e:
+        # Print a concise message and continue. Common errors: 403 Forbidden, 404 Not Found.
+        code = e.response.get('Error', {}).get('Code') if hasattr(e, 'response') else 'Unknown'
+        print(f"Failed to download {key}: {code} - {e}")
+        return
+
+
+
+
+async def download_objects(s3, assets, date_hour_list):
+    print(f"Downloading {len(date_hour_list)} objects...")
+    for asset in assets:
+        await asyncio.gather(*[download_object(s3, asset, date_hour) for date_hour in date_hour_list])
+
+
+
+
+async def decompress_file(asset, date_hour):
+    lz_file_path = DIR_PATH / "downloads" / asset / f"{date_hour}.lz4"
+    file_path = DIR_PATH / "downloads" / asset / date_hour
+
+    if not lz_file_path.is_file():
+        print(f"decompress_file: file not found: {lz_file_path}")
+        return
+
+    with lz4.frame.open(lz_file_path, mode='r') as lzfile: 
+        data = lzfile.read()
+        with open(file_path, "wb") as file:
+            file.write(data)
+
+
+
+
+async def decompress_files(assets, date_hour_list):
+    print(f"Decompressing {len(date_hour_list)} files...")
+    for asset in assets:
+        await asyncio.gather(*[decompress_file(asset, date_hour) for date_hour in date_hour_list])
+
+
+
+
+def write_rows(csv_writer, line):
+    rows = []
+    entry = json.loads(line)
+    date_time = entry["time"]
+    timestamp = str(entry["raw"]["data"]["time"])
+    all_orders = entry["raw"]["data"]["levels"]
+
+    for i, order_level in enumerate(all_orders):
+        level = str(i + 1)
+        for order in order_level:
+            price = order["px"]
+            size = order["sz"]
+            number = str(order["n"])
+            
+            rows.append([date_time, timestamp, level, price, size, number])
+
+    for row in rows:
+        csv_writer.writerow(row)
+
+
+
+
+
+async def convert_file(asset, date_hour):
+    file_path = DIR_PATH / "downloads" / asset / date_hour
+    csv_path = DIR_PATH / "csv" / asset / f"{date_hour}.csv"
+    
+    with open(csv_path, "w", newline='') as csv_file:
+        csv_writer = csv.writer(csv_file, dialect="excel")
+        csv_writer.writerow(CSV_HEADER)
+
+        with open(file_path) as file:
+            for line in file:
+                write_rows(csv_writer, line)
+
+
+
+
+async def files_to_csv(assets, date_hour_list):
+    print(f"Converting {len(date_hour_list)} files to CSV...")
+    for asset in assets:
+        await asyncio.gather(*[convert_file(asset, date_hour) for date_hour in date_hour_list])
+
+
+
+
+
+def main():
+    print(DIR_PATH)
+    args = get_args()
+
+    # Create S3 client according to whether anonymous access was requested.
+    if getattr(args, 'anonymous', False):
+        s3 = boto3.client('s3', config=Config(signature_version=UNSIGNED))
+    else:
+        s3 = boto3.client('s3')
+
+    downloads_path = DIR_PATH / "downloads"
+    downloads_path.mkdir(exist_ok=True)
+
+    csv_path = DIR_PATH / "csv"
+    csv_path.mkdir(exist_ok=True)
+
+    for asset in args.t:
+        downloads_asset_path = downloads_path / asset
+        downloads_asset_path.mkdir(exist_ok=True)
+        csv_asset_path = csv_path / asset
+        csv_asset_path.mkdir(exist_ok=True)
+
+    date_list = make_date_list(args.sd, args.ed)
+    loop = asyncio.new_event_loop()
+    
+    if args.tool == "download":
+        date_hour_list = make_date_hour_list(date_list, args.sh, args.eh)
+        loop.run_until_complete(download_objects(s3, args.t, date_hour_list))
+        loop.close()
+
+    if args.tool == "decompress":
+        date_hour_list = make_date_hour_list(date_list, args.sh, args.eh, delimiter="-")
+        loop.run_until_complete(decompress_files(args.t, date_hour_list))
+        loop.close()
+
+    if args.tool == "to_csv":
+        date_hour_list = make_date_hour_list(date_list, args.sh, args.eh, delimiter="-")
+        loop.run_until_complete(files_to_csv(args.t, date_hour_list))
+        loop.close()
+
+
+    print("Done")
+
+    
+    
+
+
+if __name__ == "__main__":
+    main()
\ No newline at end of file
diff --git a/_data/candles/requirements.txt b/_data/candles/requirements.txt
new file mode 100644
index 0000000..d26aba1
--- /dev/null
+++ b/_data/candles/requirements.txt
@@ -0,0 +1,8 @@
+boto3==1.34.131
+botocore==1.34.131
+jmespath==1.0.1
+lz4==4.3.3
+python-dateutil==2.9.0.post0
+s3transfer==0.10.1
+six==1.16.0
+urllib3==2.2.2
\ No newline at end of file
diff --git a/_data/market_data.db-shm b/_data/market_data.db-shm
new file mode 100644
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diff --git a/_data/strategies.json b/_data/strategies.json
new file mode 100644
index 0000000..d541d78
--- /dev/null
+++ b/_data/strategies.json
@@ -0,0 +1,48 @@
+{
+    "rsi_strategy_eth": {
+        "enabled": true,
+        "script": "strategy_template.py",
+        "parameters": {
+            "coin": "ETH",
+            "timeframe": "5m",
+            "rsi_period": 14
+        }
+    },
+    "ma_cross_btc": {
+        "enabled": true,
+        "script": "strategy_template.py",
+        "parameters": {
+            "coin": "BTC",
+            "timeframe": "1h",
+            "short_ma": 10,
+            "long_ma": 50
+        }
+    },
+    "sma_125d_btc": {
+        "enabled": true,
+        "script": "strategy_template.py",
+        "parameters": {
+            "coin": "BTC",
+            "timeframe": "1D",
+            "sma_period": 125
+        }
+    },
+    "sma_44d_btc": {
+        "enabled": true,
+        "script": "strategy_template.py",
+        "parameters": {
+            "coin": "BTC",
+            "timeframe": "1D",
+            "sma_period": 44
+        }
+    },
+    "disabled_strategy": {
+        "enabled": false,
+        "script": "strategy_template.py",
+        "parameters": {
+            "coin": "SOL",
+            "timeframe": "15m"
+        }
+    }
+}
+
diff --git a/import_csv.py b/import_csv.py
new file mode 100644
index 0000000..3757ef2
--- /dev/null
+++ b/import_csv.py
@@ -0,0 +1,147 @@
+import argparse
+import logging
+import os
+import sys
+import sqlite3
+import pandas as pd
+from datetime import datetime
+
+# Assuming logging_utils.py is in the same directory
+from logging_utils import setup_logging
+
+class CsvImporter:
+    """
+    Imports historical candle data from a large CSV file into the SQLite database,
+    intelligently adding only the missing data.
+    """
+
+    def __init__(self, log_level: str, csv_path: str, coin: str):
+        setup_logging(log_level, 'CsvImporter')
+        if not os.path.exists(csv_path):
+            logging.error(f"CSV file not found at '{csv_path}'. Please check the path.")
+            sys.exit(1)
+            
+        self.csv_path = csv_path
+        self.coin = coin
+        self.table_name = f"{self.coin}_1m"
+        self.db_path = os.path.join("_data", "market_data.db")
+        self.column_mapping = {
+            'Open time': 'datetime_utc',
+            'Open': 'open',
+            'High': 'high',
+            'Low': 'low',
+            'Close': 'close',
+            'Volume': 'volume',
+            'Number of trades': 'number_of_trades'
+        }
+
+    def run(self):
+        """Orchestrates the entire import and verification process."""
+        logging.info(f"Starting import process for '{self.coin}' from '{self.csv_path}'...")
+
+        with sqlite3.connect(self.db_path) as conn:
+            conn.execute("PRAGMA journal_mode=WAL;")
+            
+            # 1. Get the current state of the database
+            db_oldest, db_newest, initial_row_count = self._get_db_state(conn)
+
+            # 2. Read, clean, and filter the CSV data
+            new_data_df = self._process_and_filter_csv(db_oldest, db_newest)
+
+            if new_data_df.empty:
+                logging.info("No new data to import. Database is already up-to-date with the CSV file.")
+                return
+
+            # 3. Append the new data to the database
+            self._append_to_db(new_data_df, conn)
+
+            # 4. Summarize and verify the import
+            self._summarize_import(initial_row_count, len(new_data_df), conn)
+
+    def _get_db_state(self, conn) -> (datetime, datetime, int):
+        """Gets the oldest and newest timestamps and total row count from the DB table."""
+        try:
+            oldest = pd.read_sql(f'SELECT MIN(datetime_utc) FROM "{self.table_name}"', conn).iloc[0, 0]
+            newest = pd.read_sql(f'SELECT MAX(datetime_utc) FROM "{self.table_name}"', conn).iloc[0, 0]
+            count = pd.read_sql(f'SELECT COUNT(*) FROM "{self.table_name}"', conn).iloc[0, 0]
+            
+            oldest_dt = pd.to_datetime(oldest) if oldest else None
+            newest_dt = pd.to_datetime(newest) if newest else None
+            
+            if oldest_dt:
+                logging.info(f"Database contains data from {oldest_dt} to {newest_dt}.")
+            else:
+                logging.info("Database table is empty. A full import will be performed.")
+                
+            return oldest_dt, newest_dt, count
+        except pd.io.sql.DatabaseError:
+            logging.info(f"Table '{self.table_name}' not found. It will be created.")
+            return None, None, 0
+
+    def _process_and_filter_csv(self, db_oldest: datetime, db_newest: datetime) -> pd.DataFrame:
+        """Reads the CSV and returns a DataFrame of only the missing data."""
+        logging.info("Reading and processing CSV file. This may take a moment for large files...")
+        df = pd.read_csv(self.csv_path, usecols=self.column_mapping.keys())
+        
+        # Clean and format the data
+        df.rename(columns=self.column_mapping, inplace=True)
+        df['datetime_utc'] = pd.to_datetime(df['datetime_utc'])
+        
+        # Filter the data to find only rows that are outside the range of what's already in the DB
+        if db_oldest and db_newest:
+            # Get data from before the oldest record and after the newest record
+            df_filtered = df[(df['datetime_utc'] < db_oldest) | (df['datetime_utc'] > db_newest)]
+        else:
+            # If the DB is empty, all data is new
+            df_filtered = df
+        
+        logging.info(f"Found {len(df_filtered):,} new rows to import.")
+        return df_filtered
+
+    def _append_to_db(self, df: pd.DataFrame, conn):
+        """Appends the DataFrame to the SQLite table."""
+        logging.info(f"Appending {len(df):,} new rows to the database...")
+        df.to_sql(self.table_name, conn, if_exists='append', index=False)
+        logging.info("Append operation complete.")
+
+    def _summarize_import(self, initial_count: int, added_count: int, conn):
+        """Prints a final summary and verification of the import."""
+        logging.info("--- Import Summary & Verification ---")
+        
+        try:
+            final_count = pd.read_sql(f'SELECT COUNT(*) FROM "{self.table_name}"', conn).iloc[0, 0]
+            new_oldest = pd.read_sql(f'SELECT MIN(datetime_utc) FROM "{self.table_name}"', conn).iloc[0, 0]
+            new_newest = pd.read_sql(f'SELECT MAX(datetime_utc) FROM "{self.table_name}"', conn).iloc[0, 0]
+
+            print(f"\n{'Status':<20}: SUCCESS")
+            print("-" * 40)
+            print(f"{'Initial Row Count':<20}: {initial_count:,}")
+            print(f"{'Rows Added':<20}: {added_count:,}")
+            print(f"{'Final Row Count':<20}: {final_count:,}")
+            print("-" * 40)
+            print(f"{'New Oldest Record':<20}: {new_oldest}")
+            print(f"{'New Newest Record':<20}: {new_newest}")
+            
+            # Verification check
+            if final_count == initial_count + added_count:
+                logging.info("Verification successful: Final row count matches expected count.")
+            else:
+                logging.warning("Verification warning: Final row count does not match expected count.")
+        except Exception as e:
+            logging.error(f"Could not generate summary. Error: {e}")
+
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser(description="Import historical CSV data into the SQLite database.")
+    parser.add_argument("--file", required=True, help="Path to the large CSV file to import.")
+    parser.add_argument("--coin", default="BTC", help="The coin symbol for this data (e.g., BTC).")
+    parser.add_argument(
+        "--log-level",
+        default="normal",
+        choices=['off', 'normal', 'debug'],
+        help="Set the logging level for the script."
+    )
+    args = parser.parse_args()
+    
+    importer = CsvImporter(log_level=args.log_level, csv_path=args.file, coin=args.coin)
+    importer.run()
diff --git a/logging_utils.py b/logging_utils.py
index 9ad66af..490363e 100644
--- a/logging_utils.py
+++ b/logging_utils.py
@@ -1,5 +1,29 @@
 import logging
 import sys
+from datetime import datetime
+
+class LocalTimeFormatter(logging.Formatter):
+    """
+    Custom formatter to display time with milliseconds and a (UTC+HH) offset.
+    """
+    def formatTime(self, record, datefmt=None):
+        # Convert log record's creation time to a local, timezone-aware datetime object
+        dt = datetime.fromtimestamp(record.created).astimezone()
+        
+        # Format the main time part
+        time_part = dt.strftime('%Y-%m-%d %H:%M:%S')
+        
+        # Get the UTC offset and format it as (UTC+HH)
+        offset = dt.utcoffset()
+        offset_str = ""
+        if offset is not None:
+            offset_hours = int(offset.total_seconds() / 3600)
+            sign = '+' if offset_hours >= 0 else ''
+            offset_str = f" (UTC{sign}{offset_hours})"
+
+        # --- FIX: Cast record.msecs from float to int before formatting ---
+        # Combine time, milliseconds, and the offset string
+        return f"{time_part},{int(record.msecs):03d}{offset_str}"
 
 def setup_logging(log_level: str, process_name: str):
     """
@@ -29,10 +53,9 @@ def setup_logging(log_level: str, process_name: str):
 
     handler = logging.StreamHandler(sys.stdout)
     
-    # --- FIX: Added a date format that includes the timezone name (%Z) ---
-    formatter = logging.Formatter(
-        f'%(asctime)s - {process_name} - %(levelname)s - %(message)s',
-        datefmt='%Y-%m-%d %H:%M:%S %Z' 
+    # This will produce timestamps like: 2025-10-13 14:30:00,123 (UTC+2)
+    formatter = LocalTimeFormatter(
+        f'%(asctime)s - {process_name} - %(levelname)s - %(message)s'
     )
     handler.setFormatter(formatter)
     logger.addHandler(handler)
diff --git a/main_app.py b/main_app.py
index b3f446a..6cd9306 100644
--- a/main_app.py
+++ b/main_app.py
@@ -17,121 +17,141 @@ WATCHED_COINS = ["BTC", "ETH", "SOL", "BNB", "HYPE", "ASTER", "ZEC", "PUMP", "SU
 COIN_LISTER_SCRIPT = "list_coins.py"
 MARKET_FEEDER_SCRIPT = "market.py"
 DATA_FETCHER_SCRIPT = "data_fetcher.py"
-RESAMPLER_SCRIPT = "resampler.py" # Restored resampler script
+RESAMPLER_SCRIPT = "resampler.py" 
+STRATEGY_CONFIG_FILE = os.path.join("_data", "strategies.json")
 PRICE_DATA_FILE = os.path.join("_data", "current_prices.json")
 DB_PATH = os.path.join("_data", "market_data.db")
 STATUS_FILE = os.path.join("_data", "fetcher_status.json")
+LOGS_DIR = "_logs" # Directory to store logs from background processes
 
 
 def run_market_feeder():
-    """Target function to run the market.py script in a separate process."""
-    setup_logging('off', 'MarketFeedProcess')
-    logging.info("Market feeder process started.")
-    try:
-        # Pass the log level to the script
-        subprocess.run([sys.executable, MARKET_FEEDER_SCRIPT, "--log-level", "off"], check=True)
-    except subprocess.CalledProcessError as e:
-        logging.error(f"Market feeder script failed with error: {e}")
-    except KeyboardInterrupt:
-        logging.info("Market feeder process stopping.")
+    """Target function to run market.py and redirect its output to a log file."""
+    log_file = os.path.join(LOGS_DIR, "market_feeder.log")
+    while True:
+        try:
+            with open(log_file, 'a') as f:
+                subprocess.run(
+                    [sys.executable, MARKET_FEEDER_SCRIPT, "--log-level", "normal"], 
+                    check=True, stdout=f, stderr=subprocess.STDOUT
+                )
+        except (subprocess.CalledProcessError, Exception) as e:
+            logging.error(f"Market feeder script failed: {e}. Restarting...")
+        time.sleep(5)
 
 
 def run_data_fetcher_job():
-    """Defines the job to be run by the scheduler for the data fetcher."""
-    logging.info(f"Scheduler starting data_fetcher.py task for {', '.join(WATCHED_COINS)}...")
+    """Defines the job for the data fetcher, redirecting output to a log file."""
+    log_file = os.path.join(LOGS_DIR, "data_fetcher.log")
+    logging.info(f"Scheduler starting data_fetcher.py task...")
     try:
-        command = [sys.executable, DATA_FETCHER_SCRIPT, "--coins"] + WATCHED_COINS + ["--days", "7", "--log-level", "off"]
-        subprocess.run(command, check=True)
-        logging.info("data_fetcher.py task finished successfully.")
+        command = [sys.executable, DATA_FETCHER_SCRIPT, "--coins"] + WATCHED_COINS + ["--days", "7", "--log-level", "normal"]
+        with open(log_file, 'a') as f:
+            subprocess.run(command, check=True, stdout=f, stderr=subprocess.STDOUT)
     except Exception as e:
         logging.error(f"Failed to run data_fetcher.py job: {e}")
 
 
 def data_fetcher_scheduler():
-    """Schedules and runs the data_fetcher.py script periodically."""
+    """Schedules the data_fetcher.py script."""
     setup_logging('off', 'DataFetcherScheduler')
     run_data_fetcher_job()
     schedule.every(1).minutes.do(run_data_fetcher_job)
-    logging.info("Data fetcher scheduled to run every 1 minute.")
     while True:
         schedule.run_pending()
         time.sleep(1)
 
-# --- Restored Resampler Functions ---
+
 def run_resampler_job():
-    """Defines the job to be run by the scheduler for the resampler."""
-    logging.info(f"Scheduler starting resampler.py task for {', '.join(WATCHED_COINS)}...")
+    """Defines the job for the resampler, redirecting output to a log file."""
+    log_file = os.path.join(LOGS_DIR, "resampler.log")
+    logging.info(f"Scheduler starting resampler.py task...")
     try:
-        # Uses default timeframes configured within resampler.py
-        command = [sys.executable, RESAMPLER_SCRIPT, "--coins"] + WATCHED_COINS + ["--log-level", "off"]
-        subprocess.run(command, check=True)
-        logging.info("resampler.py task finished successfully.")
+        command = [sys.executable, RESAMPLER_SCRIPT, "--coins"] + WATCHED_COINS + ["--log-level", "normal"]
+        with open(log_file, 'a') as f:
+            subprocess.run(command, check=True, stdout=f, stderr=subprocess.STDOUT)
     except Exception as e:
         logging.error(f"Failed to run resampler.py job: {e}")
 
 
 def resampler_scheduler():
-    """Schedules and runs the resampler.py script periodically."""
+    """Schedules the resampler.py script."""
     setup_logging('off', 'ResamplerScheduler')
     run_resampler_job()
     schedule.every(4).minutes.do(run_resampler_job)
-    logging.info("Resampler scheduled to run every 4 minutes.")
     while True:
         schedule.run_pending()
         time.sleep(1)
-# --- End of Restored Functions ---
+
+
+def run_strategy(strategy_name: str, config: dict):
+    """Target function to run a strategy, redirecting its output to a log file."""
+    log_file = os.path.join(LOGS_DIR, f"strategy_{strategy_name}.log")
+    script_name = config['script']
+    params_str = json.dumps(config['parameters'])
+    command = [sys.executable, script_name, "--name", strategy_name, "--params", params_str, "--log-level", "normal"]
+    while True:
+        try:
+            with open(log_file, 'a') as f:
+                f.write(f"\n--- Starting strategy '{strategy_name}' at {datetime.now()} ---\n")
+                subprocess.run(command, check=True, stdout=f, stderr=subprocess.STDOUT)
+        except (subprocess.CalledProcessError, Exception) as e:
+            logging.error(f"Strategy '{strategy_name}' failed: {e}. Restarting...")
+        time.sleep(10)
+
 
 class MainApp:
-    def __init__(self, coins_to_watch: list):
+    def __init__(self, coins_to_watch: list, processes: dict):
         self.watched_coins = coins_to_watch
         self.prices = {}
         self.last_db_update_info = "Initializing..."
-        self._lines_printed = 0 # To track how many lines we printed last time
+        self._lines_printed = 0
+        self.background_processes = processes
+        self.process_status = {}
 
     def read_prices(self):
         """Reads the latest prices from the JSON file."""
-        if not os.path.exists(PRICE_DATA_FILE):
-            return
-        try:
-            with open(PRICE_DATA_FILE, 'r', encoding='utf-8') as f:
-                self.prices = json.load(f)
-        except (json.JSONDecodeError, IOError):
-            logging.debug("Could not read price file (might be locked).")
+        if os.path.exists(PRICE_DATA_FILE):
+            try:
+                with open(PRICE_DATA_FILE, 'r', encoding='utf-8') as f:
+                    self.prices = json.load(f)
+            except (json.JSONDecodeError, IOError):
+                logging.debug("Could not read price file.")
 
     def get_overall_db_status(self):
         """Reads the fetcher status from the status file."""
-        if not os.path.exists(STATUS_FILE):
-            self.last_db_update_info = "Status file not found."
-            return
-        try:
-            with open(STATUS_FILE, 'r', encoding='utf-8') as f:
-                status = json.load(f)
-            coin = status.get("last_updated_coin")
-            timestamp_utc_str = status.get("last_run_timestamp_utc")
-            num_candles = status.get("num_updated_candles", 0)
+        if os.path.exists(STATUS_FILE):
+            try:
+                with open(STATUS_FILE, 'r', encoding='utf-8') as f:
+                    status = json.load(f)
+                coin = status.get("last_updated_coin")
+                timestamp_utc_str = status.get("last_run_timestamp_utc")
+                num_candles = status.get("num_updated_candles", 0)
+                if timestamp_utc_str:
+                    dt_utc = datetime.fromisoformat(timestamp_utc_str.replace('Z', '+00:00')).replace(tzinfo=timezone.utc)
+                    dt_local = dt_utc.astimezone(None)
+                    
+                    # --- FIX: Manually format the UTC offset ---
+                    offset = dt_local.utcoffset()
+                    offset_hours = int(offset.total_seconds() / 3600)
+                    sign = '+' if offset_hours >= 0 else ''
+                    offset_str = f"(UTC{sign}{offset_hours})"
+                    timestamp_display = f"{dt_local.strftime('%Y-%m-%d %H:%M:%S')} {offset_str}"
+                else:
+                    timestamp_display = "N/A"
+                self.last_db_update_info = f"{coin} at {timestamp_display} ({num_candles} candles)"
+            except (IOError, json.JSONDecodeError):
+                self.last_db_update_info = "Error reading status file."
 
-            if timestamp_utc_str:
-                dt_naive = datetime.strptime(timestamp_utc_str, '%Y-%m-%d %H:%M:%S')
-                dt_utc = dt_naive.replace(tzinfo=timezone.utc)
-                dt_local = dt_utc.astimezone(None)
-                timestamp_display = dt_local.strftime('%Y-%m-%d %H:%M:%S %Z')
-            else:
-                timestamp_display = "N/A"
-
-            self.last_db_update_info = f"{coin} at {timestamp_display} ({num_candles} candles)"
-        except (IOError, json.JSONDecodeError) as e:
-            self.last_db_update_info = "Error reading status file."
-            logging.error(f"Could not read status file: {e}")
+    def check_process_status(self):
+        """Checks if the background processes are still running."""
+        for name, process in self.background_processes.items():
+            self.process_status[name] = "Running" if process.is_alive() else "STOPPED"
 
     def display_dashboard(self):
-        """Displays a formatted table for prices and DB status without blinking."""
-        # Move the cursor up to overwrite the previous output
-        if self._lines_printed > 0:
-            print(f"\x1b[{self._lines_printed}A", end="")
-
-        # Build the output as a single string
-        output_lines = []
-        output_lines.append("--- Market Dashboard ---")
+        """Displays a formatted table without blinking."""
+        if self._lines_printed > 0: print(f"\x1b[{self._lines_printed}A", end="")
+        output_lines = ["--- Market Dashboard ---"]
         table_width = 26
         output_lines.append("-" * table_width)
         output_lines.append(f"{'#':<2} | {'Coin':<6} | {'Live Price':>10} |")
@@ -140,23 +160,25 @@ class MainApp:
             price = self.prices.get(coin, "Loading...")
             output_lines.append(f"{i:<2} | {coin:<6} | {price:>10} |")
         output_lines.append("-" * table_width)
-        output_lines.append(f"DB Status: Last coin updated -> {self.last_db_update_info}")
         
-        # Join lines and add a code to clear from cursor to end of screen
-        # This prevents artifacts if the new output is shorter than the old one.
+        output_lines.append("DB Status:")
+        output_lines.append(f"  Last update -> {self.last_db_update_info}")
+        
+        output_lines.append("--- Background Processes ---")
+        for name, status in self.process_status.items():
+            output_lines.append(f"{name:<25}: {status}")
+            
         final_output = "\n".join(output_lines) + "\n\x1b[J"
         print(final_output, end="")
-        
-        # Store the number of lines printed for the next iteration
         self._lines_printed = len(output_lines)
-        
         sys.stdout.flush()
 
     def run(self):
-        """Main loop to read and display data."""
+        """Main loop to read data, display dashboard, and check processes."""
         while True:
             self.read_prices()
             self.get_overall_db_status()
+            self.check_process_status()
             self.display_dashboard()
             time.sleep(2)
 
@@ -164,6 +186,10 @@ class MainApp:
 if __name__ == "__main__":
     setup_logging('normal', 'MainApp')
 
+    # Create logs directory if it doesn't exist
+    if not os.path.exists(LOGS_DIR):
+        os.makedirs(LOGS_DIR)
+
     logging.info(f"Running coin lister: '{COIN_LISTER_SCRIPT}'...")
     try:
         subprocess.run([sys.executable, COIN_LISTER_SCRIPT], check=True, capture_output=True, text=True)
@@ -171,35 +197,40 @@ if __name__ == "__main__":
         logging.error(f"Failed to run '{COIN_LISTER_SCRIPT}'. Error: {e.stderr}")
         sys.exit(1)
 
-    logging.info(f"Starting market feeder ('{MARKET_FEEDER_SCRIPT}')...")
-    market_process = multiprocessing.Process(target=run_market_feeder, daemon=True)
-    market_process.start()
+    processes = {}
     
-    logging.info(f"Starting historical data fetcher ('{DATA_FETCHER_SCRIPT}')...")
-    fetcher_process = multiprocessing.Process(target=data_fetcher_scheduler, daemon=True)
-    fetcher_process.start()
+    # Start Data Pipeline Processes
+    processes["Market Feeder"] = multiprocessing.Process(target=run_market_feeder, daemon=True)
+    processes["Data Fetcher"] = multiprocessing.Process(target=data_fetcher_scheduler, daemon=True)
+    processes["Resampler"] = multiprocessing.Process(target=resampler_scheduler, daemon=True)
     
-    # --- Restored Resampler Process Start ---
-    logging.info(f"Starting resampler ('{RESAMPLER_SCRIPT}')...")
-    resampler_process = multiprocessing.Process(target=resampler_scheduler, daemon=True)
-    resampler_process.start()
-    # --- End Resampler Process Start ---
+    # Start Strategy Processes based on config
+    try:
+        with open(STRATEGY_CONFIG_FILE, 'r') as f:
+            strategy_configs = json.load(f)
+        for name, config in strategy_configs.items():
+            if config.get("enabled", False):
+                proc = multiprocessing.Process(target=run_strategy, args=(name, config), daemon=True)
+                processes[f"Strategy: {name}"] = proc
+    except (FileNotFoundError, json.JSONDecodeError) as e:
+        logging.error(f"Could not load strategies from '{STRATEGY_CONFIG_FILE}': {e}")
+
+    # Launch all processes
+    for name, proc in processes.items():
+        logging.info(f"Starting process '{name}'...")
+        proc.start()
     
     time.sleep(3)
 
-    app = MainApp(coins_to_watch=WATCHED_COINS)
+    app = MainApp(coins_to_watch=WATCHED_COINS, processes=processes)
     try:
         app.run()
     except KeyboardInterrupt:
         logging.info("Shutting down...")
-        market_process.terminate()
-        fetcher_process.terminate()
-        # --- Restored Resampler Shutdown ---
-        resampler_process.terminate()
-        market_process.join()
-        fetcher_process.join()
-        resampler_process.join()
-        # --- End Resampler Shutdown ---
+        for proc in processes.values():
+            if proc.is_alive(): proc.terminate()
+        for proc in processes.values():
+            if proc.is_alive(): proc.join()
         logging.info("Shutdown complete.")
         sys.exit(0)
 
diff --git a/strategy_template.py b/strategy_template.py
new file mode 100644
index 0000000..911fb7c
--- /dev/null
+++ b/strategy_template.py
@@ -0,0 +1,132 @@
+import argparse
+import logging
+import sys
+import time
+import pandas as pd
+import sqlite3
+import json
+import os
+
+from logging_utils import setup_logging
+
+class TradingStrategy:
+    """
+    A template for a trading strategy that reads data from the SQLite database
+    and executes its logic in a loop.
+    """
+
+    def __init__(self, strategy_name: str, params: dict, log_level: str):
+        self.strategy_name = strategy_name
+        self.params = params
+        self.coin = params.get("coin", "N/A")
+        self.timeframe = params.get("timeframe", "N/A")
+        self.db_path = os.path.join("_data", "market_data.db")
+        
+        # Load strategy-specific parameters
+        self.rsi_period = params.get("rsi_period")
+        self.short_ma = params.get("short_ma")
+        self.long_ma = params.get("long_ma")
+        self.sma_period = params.get("sma_period")
+        
+        setup_logging(log_level, f"Strategy-{self.strategy_name}")
+        logging.info(f"Initializing strategy with parameters: {self.params}")
+
+    def load_data(self) -> pd.DataFrame:
+        """Loads historical data for the configured coin and timeframe from the database."""
+        table_name = f"{self.coin}_{self.timeframe}"
+        # Ensure we load enough data for the longest indicator period
+        limit = 500
+        if self.sma_period and self.sma_period > limit:
+            limit = self.sma_period + 50 # Add a buffer
+        elif self.long_ma and self.long_ma > limit:
+            limit = self.long_ma + 50
+
+        try:
+            with sqlite3.connect(f"file:{self.db_path}?mode=ro", uri=True) as conn:
+                query = f'SELECT * FROM "{table_name}" ORDER BY datetime_utc DESC LIMIT {limit}'
+                df = pd.read_sql(query, conn)
+                df['datetime_utc'] = pd.to_datetime(df['datetime_utc'])
+                df.set_index('datetime_utc', inplace=True)
+                df.sort_index(inplace=True) # Ensure data is chronological
+                return df
+        except Exception as e:
+            logging.error(f"Failed to load data from table '{table_name}': {e}")
+            return pd.DataFrame()
+
+    def run_logic(self):
+        """
+        The main loop where the strategy's logic is executed.
+        This should be implemented with your specific trading rules.
+        """
+        logging.info(f"Starting main logic loop for {self.coin} on {self.timeframe} timeframe.")
+        while True:
+            data = self.load_data()
+
+            if data.empty:
+                logging.warning("No data loaded. Waiting before retrying...")
+                time.sleep(60)
+                continue
+
+            last_close = data['close'].iloc[-1]
+            logging.info(f"Latest data loaded. Last close price for {self.coin}: {last_close}")
+            
+            # --- SMA Strategy Logic ---
+            if self.sma_period:
+                if len(data) < self.sma_period:
+                    logging.warning(f"Not enough data to calculate {self.sma_period}-period SMA. "
+                                    f"Need {self.sma_period}, have {len(data)}.")
+                else:
+                    # Calculate the Simple Moving Average
+                    sma = data['close'].rolling(window=self.sma_period).mean().iloc[-1]
+                    logging.info(f"Current Price: {last_close}, {self.sma_period}-period SMA: {sma:.4f}")
+
+                    if last_close > sma:
+                        logging.warning("--- BUY SIGNAL --- (Price is above SMA)")
+                    elif last_close < sma:
+                        logging.warning("--- SELL SIGNAL --- (Price is below SMA)")
+                    else:
+                        logging.info("--- HOLD SIGNAL --- (Price is at SMA)")
+
+            # --- RSI Strategy Logic (Placeholder) ---
+            if self.rsi_period:
+                logging.info(f"RSI Period is set to: {self.rsi_period}. (RSI calculation not implemented).")
+
+            # --- MA Cross Strategy Logic (Placeholder) ---
+            if self.short_ma and self.long_ma:
+                logging.info(f"Short MA: {self.short_ma}, Long MA: {self.long_ma}. (MA Cross logic not implemented).")
+            
+            logging.info("Logic execution finished. Waiting for next cycle.")
+            time.sleep(60)
+
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser(description="Run a trading strategy.")
+    parser.add_argument("--name", required=True, help="The name of the strategy instance from the config.")
+    parser.add_argument("--params", required=True, help="A JSON string of the strategy's parameters.")
+    parser.add_argument(
+        "--log-level",
+        default="normal",
+        choices=['off', 'normal', 'debug'],
+        help="Set the logging level for the script."
+    )
+    
+    args = parser.parse_args()
+
+    try:
+        strategy_params = json.loads(args.params)
+        strategy = TradingStrategy(
+            strategy_name=args.name, 
+            params=strategy_params,
+            log_level=args.log_level
+        )
+        strategy.run_logic()
+    except json.JSONDecodeError:
+        logging.error("Failed to decode JSON from --params argument.")
+        sys.exit(1)
+    except KeyboardInterrupt:
+        logging.info("Strategy process stopped.")
+        sys.exit(0)
+    except Exception as e:
+        logging.error(f"A critical error occurred: {e}")
+        sys.exit(1)
+