Metadata-Version: 2.1
Name: enular
Version: 0.2.1
Summary: Enular Library
Home-page: https://enular.com
Author: Adrian Chun Pang Wong, Dylan Fitzsimmons, Enular Limited
Author-email: adrian@enular.com
License: MIT
Description: # Enular Library
         
        pip install enular
        
        NOTE: Alpha version and development in progress. Expect beta release in late 2022.
        
        The Enular Library contains tools for backtesting, evaluating and visualising algorithmic trading strategies. It allows the user to easily combine indicators with complex operations into strategies, similar to neural networks. It also provides indicators, data sources, and paper trading capabilities. Documentation coming soon. Enular.com
        
        Details:
        - Uses Backtrader's Cerebro engine with fixes from Backtrader2
        - Data streaming from Yahoo Finance
        - Indicator and strategy collection
        - Improve accessiblity with simplified architecture
        - Highly scalable strategies: extend classes and redefine trade logic
        - Live trading capabilities
        
        Architecture:
        
        - 1 category of base indicators (INPUT: market data, OUTPUT: single indicator signal)
            - Indicator library with existing technical analysis indicators
        
        - 3 categories of indicator operations (INPUT: two indicator signals, OUTPUT: single indicator signal):
            - Scalar inputs to scalar output
            - Scalar inputs to boolean output
            - Boolean inputs to boolean output (7 basic logic gates)
        
        - 2 categories of strategy operations (INPUT two indicator signals, OUTPUT: order instructions):
            - Scalar inputs to order instructions
            - Boolean inputs to order instructions (7 basic logic gates)
        
        Development in progress:
        - Live trading via IB
        - Indicator library
        - Strategy library
        - Data feed improvements
        - Machine learning capabities
        - Instructional articles on Medium
        - Templates
        - Documentation
        - User forum
Platform: UNKNOWN
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
