450 lines
15 KiB
Python
450 lines
15 KiB
Python
"""
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AUTHOR:
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Khushal P Soonderji
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DATE:
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Tuesday, 21st Jan., 2025.
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OBJECTIVE:
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Live market ticks are broadcasted over Kafka. Here, we try to capture and save those ticks to MongoDb for
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whatever they can be used for later.
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REFERENCES:
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N/A
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DOWNLOADS:
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N/A
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"""
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# *****************************************************************************************************************
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# ***** ****
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# *** IMPORT ***
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# ***** ****
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# *****************************************************************************************************************
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# To make sibling directories accessible for imports:
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import sys
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sys.path.append(".")
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sys.path.append("..")
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# System-level activities:
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import io
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import os
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# My utils:
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from utils_v2.string import json
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from utils_v2.string import regex
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from utils_v2.system import files
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from utils_v2.date_time import date_time
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from utils_v2.database.async_mongo_v2 import AsyncMongo
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from utils_v2.queue.kafka.controllers.async_kafka import ConsumerKafka, get_ssl_context
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from utils_v2.cache.async_redis_cache_v2 import AsyncRedisCache
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from utils_v2.serialization.json_serializer import JSONSerializer
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# To make HTTP calls:
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import httpx
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# To work with date and time:
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import datetime
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import time
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# Controllers:
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from controllers_v2.finstitutions.trading.all_trading import AllTradingController
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# Models:
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from models.core.auth_token import CoreAuthTokenModel
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from models.finstitutions.trading.symbols import TradingSymbol
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from models.finstitutions.trading.ticks import TradingTick
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from models.core.user import CoreUserInfoModel
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# To work with Zerodha's Kite platform:
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from kiteconnect import KiteConnect, KiteTicker
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# To work with SocketIO:
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import socket
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import socketio
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# For asynchronous activities:
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import asyncio
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# To work with various datatypes:
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from typing import List, Literal
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# For MongoDB:
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from bson.objectid import ObjectId
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# Debugging:
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from icecream import IceCreamDebugger
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# *****************************************************************************************************************
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# ***** ****
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# *** MACROS / ONE-TIME INIT ***
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# ***** ****
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# *****************************************************************************************************************
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# Debugging:
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printer = IceCreamDebugger(prefix = "Tick-Save | ", includeContext = True)
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no_context_printer = IceCreamDebugger(prefix = "Tick-Save | ", includeContext = False)
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# To make API calls:
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http_client = httpx.AsyncClient(
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limits = httpx.Limits(
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max_connections = 100, # ............ Maximum number of connections allowed in the pool.
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max_keepalive_connections = 50, # ... Maximum number of connections that can be kept alive.
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),
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timeout = httpx.Timeout(
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pool = 120.0, # .... Time to wait for a free connection from the pool.
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connect = 2.5, # ... Time to wait for establishing a connection to the server.
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write = 10.0, # .... Time to wait for sending data.
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read = 9.9 # ....... Time to wait for receiving data.
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)
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)
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# General:
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SERVER_HOSTNAME = str(socket.gethostname())
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# *****************************************************************************************************************
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# ***** ****
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# *** VARIABLES ***
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# ***** ****
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# *****************************************************************************************************************
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# Redis:
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redis_cache: AsyncRedisCache | None = None
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# For database:
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data_mongo: AsyncMongo | None = None
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# For kafka:
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kafka_consumer: ConsumerKafka | None = None
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# Session-awareness and maintenance of this script's state:
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SCRIPT_DATA = {}
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exclusive_lock = asyncio.Semaphore(1)
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ticks_since_telegram = 0
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# For Zerodha-Kite:
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ZERODHA_INSTRUMENT_TOKENS = []
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ZERODHA_INSTRUMENT_LOOKUP = {}
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# *****************************************************************************************************************
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# ***** ****
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# *** FUNCTIONS ***
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# ***** ****
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# *****************************************************************************************************************
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async def save_ticks(ticks: List[dict]):
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global ticks_since_telegram
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# Parse the date-time in UTC and add the metadata:
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for tick in ticks:
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tick["metadata"] = {"broker": tick["broker"], "brokerToken": tick["brokerToken"]}
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tick["rcvdTs"] = date_time.parse_date_time(tick["rcvdTs"], timezone = date_time.TIMEZONE_UTC)
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tick["tradeTs"] = date_time.parse_date_time(tick["tradeTs"], timezone = date_time.TIMEZONE_UTC)
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tick["exchgTs"] = date_time.parse_date_time(tick["exchgTs"], timezone = date_time.TIMEZONE_UTC)
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# Save the ticks:
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inserted_ids = await data_mongo.insert_many(
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collection = "__cold_zerodhaTicks",
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documents = ticks
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)
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# Send out the alert if needed:
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ticks_since_telegram += len(ticks)
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ticks_threshold = 1_00_000
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if ticks_since_telegram > ticks_threshold:
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await send_telegram(message = f"*Tick-Save Alert*\nSaved {ticks_since_telegram:,} tick(s).")
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ticks_since_telegram = 0
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# ---------------------------------------------------------------------------------------------------------------------
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async def ticks_from_kafka(
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consumer: ConsumerKafka,
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fetch_count: int = 100,
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fetch_timeout: float = 1.0
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) -> None:
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"""
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This function must run in the background forever and just keep listening for ticks on Kafka and keep relaying them
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to all the connected clients as per their watchlists.
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:param consumer: The preconfigured Kafka consumer that can listen for ticks in asynchronous mode.
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:param fetch_count: How many messages to consume in one go.
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:param fetch_timeout: How long to wait (in seconds) while consuming messages from Kafka.
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:return: None
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"""
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printer("Starting Kafka consumer (ticks).")
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# Do the next part infinitely:
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while True:
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# Note the time:
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now_utc = date_time.get_current_utc_date_time().timestamp()
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# Get messages form Kafka:
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messages = await consumer.consume(
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count = fetch_count,
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timeout = fetch_timeout
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)
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# If there are no updates to give:
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if not messages: continue
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# We extract all the ticks from the Kafka messages:
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ticks = []
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for m in messages:
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if isinstance(m.value, list): ticks += m.value
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else: ticks.append(m.value)
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# Save the ticks:
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no_context_printer(len(ticks))
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await save_ticks(ticks)
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# ---------------------------------------------------------------------------------------------------------------------
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async def init(
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script_id: str,
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debug: bool
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):
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"""
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To initialize all credentials, instances, and connectivity for this whole script.
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:param script_id: The id to use to load cred and data from the internal service.
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:param debug: Whether, or not, you would like to print the debug messages.
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:return: True if initialized successfully, else False.
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"""
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# Declare the required global variables:
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global SCRIPT_DATA
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global data_mongo
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global redis_cache
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global kafka_consumer
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# Basic stuff:
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if debug: printer.enable()
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printer("Initializing.")
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# ┏┓ ┓ ┓ ┳┓
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# ┃ ┏┓┏┓┏┫ ┏┓┏┓┏┫ ┃┃┏┓╋┏┓
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# ┗┛┛ ┗ ┗┻ ┗┻┛┗┗┻ ┻┛┗┻┗┗┻
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# Get the script credentials:
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response = await http_client.get(
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url = r"https://nexcom.ditscentre.in/internal/cred/get",
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headers = {"X-Script-Id": script_id}
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)
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if response.status_code not in [200]:
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print("FATAL: SCRIPT CREDENTIALS LOADING FAILED!")
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return False
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script_cred = response.json().get("data")
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# Get the script data:
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response = await http_client.get(
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url = r"https://nexcom.ditscentre.in/internal/data/get",
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headers = {"X-Script-Id": script_id}
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)
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if response.status_code not in [200]:
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print("FATAL: SCRIPT DATA LOADING FAILED!")
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return False
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SCRIPT_DATA = response.json().get("data")
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# Done with this step:
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printer("Cred and Data loaded.")
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# ┳┳┓
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# ┃┃┃┏┓┏┓┏┓┏┓
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# ┛ ┗┗┛┛┗┗┫┗┛
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# ┛
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data_mongo = AsyncMongo(
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connection_string = script_cred["mongoDb"]["data"]["connectionString"],
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database_name = "markets", # script_cred["mongoDb"]["data"]["dbName"],
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max_connections = script_cred["mongoDb"]["data"]["poolSize"],
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debug = debug
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)
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await data_mongo.connect()
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# ┳┓ ┓• ┏┓ ┓
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# ┣┫┏┓┏┫┓┏ ━━ ┃ ┏┓┏┣┓┏┓
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# ┛┗┗ ┗┻┗┛ ┗┛┗┻┗┛┗┗
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redis_cache = AsyncRedisCache(
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connection_string = script_cred["redisCache"]["general"]["connectionString"],
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serializer = JSONSerializer(),
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debug = debug,
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debug_prefix = "General Cache | "
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)
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await redis_cache.connect()
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# ┓┏┓ ┏┓ ┏┓┓•
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# ┃┫ ┏┓╋┃┏┏┓ ┃ ┃┓┏┓┏┓╋┏
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# ┛┗┛┗┻┛┛┗┗┻ ┗┛┗┗┗ ┛┗┗┛
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# Create the consumer that will listen to changes in watchlist:
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consumer_creds = script_cred["kafka"]["consumer"]
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kafka_consumer = ConsumerKafka(
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topic = consumer_creds["topic"],
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group_id = "tick_save",
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bootstrap_servers = consumer_creds["config"]["bootstrapServers"],
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security_protocol = consumer_creds["config"].get("securityProtocol", "PLAINTEXT"),
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ssl_context = get_ssl_context(
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ca_file = consumer_creds["config"].get("caFile"),
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cert_file = consumer_creds["config"].get("certFile"),
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key_file = consumer_creds["config"].get("keyFile"),
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),
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serializer = JSONSerializer(),
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debug = debug
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)
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if not await kafka_consumer.connect():
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print("FATAL: KAFKA CONSUMER NOT CREATED!")
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return False
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printer("Kafka consumer ready.")
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# ┳┓
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# ┃┃┏┓┏┓┏┓
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# ┻┛┗┛┛┗┗
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# If everything went well, we return with success:
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printer("Initialization done.")
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return True
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# ---------------------------------------------------------------------------------------------------------------------
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async def send_telegram(
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message: str,
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chat_id: str = None,
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message_type: Literal["info", "warning", "error"] = "info"
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):
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"""
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To send out alerts and heartbeats to inform about th script being alive.
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:param message: The text to send.
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:param chat_id: The destination chat identifier.
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:param message_type: The kind of message to send. Decides the presentation of the header.
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:return:
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"""
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try:
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# Create the JSON for sending to the API endpoint:
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json_input = {
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"chatClient": "telegram",
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"message": message,
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"type": message_type
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}
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if chat_id: json_input["chatId"] = json_input
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# Make the API call to send the ticks:
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response = await http_client.post(
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url = r"https://api.thecaoffice.com/converse/tech/alert/chat/backend",
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json = json_input
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)
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# Raise an exception if the call was not successful:
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response.raise_for_status()
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# If something goes wrong:
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except Exception as exception:
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printer(exception)
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# ---------------------------------------------------------------------------------------------------------------------
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async def heartbeat(interval_seconds: float = 300):
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while True:
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await send_telegram(message = f"*Tick-Save Heartbeat*\nInterval: `{interval_seconds:,} seconds`")
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await asyncio.sleep(interval_seconds)
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# ---------------------------------------------------------------------------------------------------------------------
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async def main(debug: bool = False):
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tasks = [
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ticks_from_kafka(
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consumer = kafka_consumer,
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fetch_count = 500,
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fetch_timeout = 2.5
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),
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heartbeat(interval_seconds = 1_800)
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]
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await asyncio.gather(*tasks)
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# *****************************************************************************************************************
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# ***** ****
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# *** MAIN PROGRAM ***
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# ***** ****
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# *****************************************************************************************************************
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if __name__ == "__main__":
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printer("Main.")
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# To get args from the terminal:
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import argparse
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# Get the config from the command-line:
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parser = argparse.ArgumentParser(description = f"SocketIO to serve live market data (and a general passthrough).")
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parser.add_argument(
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"-s", "--script-id",
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type = str,
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help = "The id of this script (will affect the loaded config)."
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)
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# parser.add_argument(
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# "-t", "--token-key", "--token-id",
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# dest = "token_key",
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# type = str,
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# help = "The 'key' to use to retrieve the auth-token for accessing the broker account."
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# )
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parser.add_argument(
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"-d", "--debug",
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action = "store_true",
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help = "Whether, or not, you want to see debugging messages in the terminal.",
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default = False
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)
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args = parser.parse_args()
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async def runner():
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# Startup message:
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printer.enable()
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printer(str(args.debug))
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printer.disable()
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# Initialize and then run the script:
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if await init(
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script_id = args.script_id,
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debug = args.debug
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): await main(
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debug = args.debug
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)
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asyncio.run(runner())
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