Skip to main content

Algorithmic Trading Library by East Empire Trading Company.

Project description

EETC Algo Trading


Algorithmic Trading Python Library by EETC.

This library simplifies writing and running algorithmic trading bots. It integrates EETC services for placing orders and receiving live data, allowing the developer to focus solely on implementing the trading algorithm.

How it works

This library connects to EETC Data Feed and receives live data via ZeroMQ. To place orders for Stocks, Options, Crypto, etc. this library communicates with EETC Order Manager via ZeroMQ.

Example code:

from eetc_algo_trading import EETCTradingBot

def algorithm(bot_instance, topic=None, manual_trigger_details=None):
    bot_instance.algorithm_lock = True  # kinda "obtain" lock
    if topic:
        print("Executing Strategy for Topic: {}".format(topic))
        # whatever logic
    elif manual_trigger_details:
        print("Executing Strategy Manually...")
        print("Request data:", manual_trigger_details)
        # whatever logic
        print("Executing Strategy...")
        # whatever logic

    bot_instance.algorithm_lock = False  # kinda "release" lock

bot = EETCTradingBot(


The only thing a developer needs to do is write the "algorithm" function and pass it to the EETCTradingBot during initialization.

Order management

It is entirely up to the developer to implement their own order management logic. EETC Order Manager provides various APIs where clients can get order information and receive real-time updates.

The most common tactic is to write a helper function for managing orders which will be executed within the algorithm function.

This approach may not be the most user-friendly, but it was chosen because it gives the developer absolute freedom for writing their strategy, which includes order management.

Manual execution via ZeroMQ

Strategies can be triggered either manually via ZeroMQ by sending a request via REQ-REP sockets. What information you put inside this request and how you process it is entirely up to you. One simple use case for this might be when one algorithm is not sure about a trading decision, it can call another algorithm which may be able to do that.

Event-based execution

Strategies can also be triggered whenever a certain kind of data signal comes in (topic). For example on each "candles:BTC/USD:1m" signal, execute the strategy.

Scheduled execution

Coming soon...

System Requirements





Project details

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

eetc-algo-trading-lib-0.1.tar.gz (6.1 kB view hashes)

Uploaded source

Built Distribution

eetc_algo_trading_lib-0.1-py3-none-any.whl (14.0 kB view hashes)

Uploaded py3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page