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Essential guidelines and best practices for using BinomoAPI in production environments.
your_project/
├── config/
│ ├── __init__.py
│ ├── settings.py # Configuration
│ └── logging.py # Logging setup
├── strategies/
│ ├── __init__.py
│ ├── base.py # Base strategy class
│ └── implementations/ # Strategy implementations
├── utils/
│ ├── __init__.py
│ ├── analysis.py # Analysis utilities
│ └── validation.py # Input validation
├── services/
│ ├── __init__.py
│ ├── trading.py # Trading service
│ └── monitoring.py # Monitoring service
├── tests/
│ ├── __init__.py
│ ├── test_trading.py
│ └── test_strategies.py
├── main.py # Entry point
└── requirements.txt # Dependencies
from BinomoAPI import BinomoAPI
from typing import Optional, Dict, Any
class TradingService:
"""
Professional trading service implementation.
"""
def __init__(
self,
api: BinomoAPI,
config: Dict[str, Any]
):
self.api = api
self.config = config
async def execute_trade(
self,
asset: str,
direction: str,
amount: float,
duration: int
) -> Dict[str, Any]:
"""
Execute a trade with proper validation.
Args:
asset: Asset to trade
direction: Trade direction (CALL/PUT)
amount: Trade amount
duration: Option duration in seconds
Returns:
Dict containing trade result
Raises:
TradeError: If trade execution fails
"""
# Implementation
import os
from dotenv import load_dotenv
def get_credentials():
"""
Secure credential management.
"""
load_dotenv()
email = os.getenv("BINOMO_EMAIL")
password = os.getenv("BINOMO_PASSWORD")
if not email or not password:
raise ValueError(
"Missing required credentials"
)
return email, password
import asyncio
from datetime import datetime, timedelta
class SessionManager:
def __init__(self, api: BinomoAPI):
self.api = api
self.last_activity = datetime.now()
self.session_timeout = timedelta(hours=1)
async def check_session(self):
"""
Ensure session is valid.
"""
if datetime.now() - self.last_activity > self.session_timeout:
await self.refresh_session()
self.last_activity = datetime.now()
async def refresh_session(self):
"""
Refresh authentication.
"""
# Implementation
import logging
from contextlib import contextmanager
from typing import Generator
@contextmanager
def error_boundary(
operation: str
) -> Generator[None, None, None]:
"""
Professional error boundary implementation.
"""
try:
yield
except Exception as e:
logging.error(
f"Error in {operation}: {str(e)}"
)
raise
import logging
import json
from datetime import datetime
class StructuredLogger:
def __init__(self, name: str):
self.logger = logging.getLogger(name)
self.setup_logging()
def setup_logging(self):
"""
Setup structured logging.
"""
handler = logging.FileHandler('trading.log')
handler.setFormatter(
logging.Formatter(
'%(asctime)s - %(name)s - %(levelname)s - %(message)s'
)
)
self.logger.addHandler(handler)
self.logger.setLevel(logging.INFO)
def log_trade(self, trade_data: dict):
"""
Log trade information.
"""
log_entry = {
"timestamp": datetime.now().isoformat(),
"type": "trade",
"data": trade_data
}
self.logger.info(json.dumps(log_entry))
import asyncio
from datetime import datetime, timedelta
class RateLimiter:
def __init__(
self,
max_requests: int,
time_window: int
):
self.max_requests = max_requests
self.time_window = time_window
self.requests = []
async def acquire(self):
"""
Acquire rate limit token.
"""
now = datetime.now()
# Remove old requests
self.requests = [
req_time for req_time in self.requests
if now - req_time < timedelta(seconds=self.time_window)
]
if len(self.requests) >= self.max_requests:
# Wait for next available slot
sleep_time = (
self.requests[0] +
timedelta(seconds=self.time_window) -
now
).total_seconds()
await asyncio.sleep(sleep_time)
self.requests.append(now)
from typing import List
import aiohttp
class ConnectionPool:
def __init__(self, size: int = 10):
self.size = size
self.connections: List[aiohttp.ClientSession] = []
async def get_connection(self):
"""
Get available connection.
"""
if not self.connections:
return await self.create_connection()
return self.connections.pop()
async def release_connection(
self,
connection: aiohttp.ClientSession
):
"""
Release connection back to pool.
"""
if len(self.connections) < self.size:
self.connections.append(connection)
else:
await connection.close()
async def create_connection(self):
"""
Create new connection.
"""
return aiohttp.ClientSession()
from functools import lru_cache
from typing import Any, Dict
class Cache:
def __init__(self, maxsize: int = 100):
self.maxsize = maxsize
self._cache: Dict[str, Any] = {}
@lru_cache(maxsize=100)
def get_asset_info(self, asset: str) -> Dict:
"""
Cached asset information.
"""
# Implementation
from typing import List, Dict
class BatchProcessor:
def __init__(self, api: BinomoAPI):
self.api = api
self.batch_size = 10
self.queue: List[Dict] = []
async def add_to_batch(self, operation: Dict):
"""
Add operation to batch.
"""
self.queue.append(operation)
if len(self.queue) >= self.batch_size:
await self.process_batch()
async def process_batch(self):
"""
Process queued operations.
"""
if not self.queue:
return
batch = self.queue[:self.batch_size]
self.queue = self.queue[self.batch_size:]
# Process batch
# Implementation
import asyncio
from datetime import datetime
class HealthMonitor:
def __init__(self, api: BinomoAPI):
self.api = api
self.last_check = datetime.now()
async def check_health(self):
"""
Comprehensive health check.
"""
try:
# Check API connection
await self.api.get_balance()
# Check WebSocket
await self.api.ws_client.ping()
# Update status
self.last_check = datetime.now()
return True
except Exception as e:
logging.error(f"Health check failed: {e}")
return False
import time
from typing import Callable, Any
class PerformanceMonitor:
def __init__(self):
self.metrics = {}
async def measure(
self,
name: str,
func: Callable,
*args,
**kwargs
) -> Any:
"""
Measure function performance.
"""
start = time.time()
try:
result = await func(*args, **kwargs)
duration = time.time() - start
self.update_metrics(name, duration)
return result
except Exception as e:
duration = time.time() - start
self.update_metrics(name, duration, error=True)
raise
def update_metrics(
self,
name: str,
duration: float,
error: bool = False
):
"""
Update performance metrics.
"""
if name not in self.metrics:
self.metrics[name] = {
"count": 0,
"total_time": 0,
"errors": 0
}
self.metrics[name]["count"] += 1
self.metrics[name]["total_time"] += duration
if error:
self.metrics[name]["errors"] += 1
Remember to always follow these best practices for reliable and maintainable code!