update live trading

Readme.md

@@ -60,26 +60,30 @@ Overall, I tend to pick decent or promising libraries that closely related to sy
 
 > Event Driven Frameworks
 
-- [aat](https://github.com/AsyncAlgoTrading/aat) | `Python`, `C++` | - an asynchronous, event-driven framework for writing algorithmic trading strategies in python with optional acceleration in C++. It is designed to be modular and extensible, with support for a wide variety of instruments and strategies, live trading across (and between) multiple exchanges.
+Note: the one marked as `Live Trading` has reasonable live trading support for at least 1 broker. Otherwise, backtest
+ function only.
+
+- [aat](https://github.com/AsyncAlgoTrading/aat) | `Python`, `C++`, `Live Trading`| - an asynchronous, event-driven framework for writing algorithmic trading strategies in python with optional acceleration in C++. It is designed to be modular and extensible, with support for a wide variety of instruments and strategies, live trading across (and between) multiple exchanges.
 - [backtesting.py](https://github.com/kernc/backtesting.py) | `Python` | - Backtesting.py is a Python framework for inferring viability of trading strategies on historical (past) data. Improved upon the vision of Backtrader, and by all means surpassingly comparable to other accessible alternatives, Backtesting.py is lightweight, fast, user-friendly, intuitive, interactive, intelligent and, hopefully, future-proof.
-- [backtrader](https://github.com/mementum/backtrader) | `Python` | - Event driven Python Backtesting library for trading strategies
+- [backtrader](https://github.com/mementum/backtrader) | `Python`, `Live Trading` | - Event driven Python Backtesting library for trading strategies
 - [FinRL](https://github.com/AI4Finance-Foundation/FinRL) | `Python` | - FinRL is the first open-source framework to demonstrate the great potential of applying deep reinforcement learning in quantitative finance.
+- [finmarketpy](https://github.com/cuemacro/finmarketpy) | `Python` | - Python library for backtesting trading strategies & analyzing financial markets (formerly pythalesians) 
 - [lumibot](https://github.com/Lumiwealth/lumibot/tree/8da88cadfe9ee35399dd69c94aa5ed3cf995f417) | `Python` | - A very simple yet useful backtesting and sample based live trading framework
-- [nautilus_trader](https://github.com/nautechsystems/nautilus_trader) | `Python`, `Cython`, `Rust` | - A high-performance algorithmic trading platform and event-driven backtester
+- [nautilus_trader](https://github.com/nautechsystems/nautilus_trader) | `Python`, `Cython`, `Rust`, `Live Trading` | - A high-performance algorithmic trading platform and event-driven backtester
 - [QLib (Microsoft)](https://github.com/microsoft/qlib) | `Python`, `Cython` | - Qlib is an AI-oriented quantitative investment platform, which aims to realize the potential, empower the research, and create the value of AI technologies in quantitative investment. With Qlib, you can easily try your ideas to create better Quant investment strategies. An increasing number of SOTA Quant research works/papers are released in Qlib.
-- [QuantConnect](https://github.com/QuantConnect/Lean) | `C#`, `.NET` | - Lean Algorithmic Trading Engine by QuantConnect (Python, C#)
-- [QUANTAXIS](https://github.com/QUANTAXIS/QUANTAXIS) | `Python` | - QUANTAXIS 支持任务调度 分布式部署的 股票/期货/期权/港股/虚拟货币 数据/回测/模拟/交易/可视化/多账户 纯本地量化解决方案
+- [QuantConnect](https://github.com/QuantConnect/Lean) | `C#`, `.NET`, `Live Trading` | - Lean Algorithmic Trading Engine by QuantConnect (Python, C#)
+- [QUANTAXIS](https://github.com/QUANTAXIS/QUANTAXIS) | `Python`, `Live Trading` | - QUANTAXIS 支持任务调度 分布式部署的 股票/期货/期权/港股/虚拟货币 数据/回测/模拟/交易/可视化/多账户 纯本地量化解决方案
 - [Rqalpha](https://github.com/ricequant/rqalpha) | `Python` | - A extendable, replaceable Python algorithmic backtest && trading framework supporting multiple securities
 - [quanttrader](https://github.com/letianzj/quanttrader) | `Python` | - Backtest and live trading in Python. Event based. Similar to backtesting.py. 
 - [sdoosa-algo-trade-python](https://github.com/sreenivasdoosa/sdoosa-algo-trade-python) | `Python` | - This project is mainly for newbies into algo trading who are interested in learning to code their own trading algo using python interpreter.
-- [vnpy](https://github.com/vnpy/vnpy) | `Python`, `Stock`, `Futures`, `Crypto` | - Python-based open source quantitative trading system development framework, officially released in January 2015, has grown step by step into a full-featured quantitative trading platform
+- [vnpy](https://github.com/vnpy/vnpy) | `Python`, `Stock`, `Futures`, `Crypto`, `Live Trading` | - Python-based open source quantitative trading system development framework, officially released in January 2015, has grown step by step into a full-featured quantitative trading platform
 - [zvt](https://github.com/zvtvz/zvt) | `Python`, `Stock`, `Backtest` | - Modular quant framework
 - [zipline](https://github.com/quantopian/zipline) | `Python` | - Zipline is a Pythonic algorithmic trading library. It is an event-driven system for backtesting.
 
 > Vector Based Frameworks
 
 - [bt](https://github.com/pmorissette/bt) | `Python` | -  Flexible backtesting for Python based on Algo and Strategy Tree
-- [pysystemtrade](https://github.com/robcarver17/pysystemtrade) | `Python` | - Systematic Trading in python from book <Systematic Trading> by Rob Carver
+- [pysystemtrade](https://github.com/robcarver17/pysystemtrade) | `Python`, `Live Trading` | - Systematic Trading in python from book <Systematic Trading> by Rob Carver
 - [vectorbt](https://github.com/polakowo/vectorbt) | `Python`, `numba` | - vectorbt takes a novel approach to backtesting: it operates entirely on pandas and NumPy objects, and is accelerated by Numba to analyze any data at speed and scale. This allows for testing of many thousands of strategies in seconds.
 
 ### Crypto currency focus