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Source channel @githubtrending · Post #15371 · Dec 28
#csharp#algorithm#algorithmic_trading_engine#c_sharp#finance#forex#lean_engine#options#python#quantconnect#stock_indicators#trading#trading_algorithms#trading_bot#trading_platform#trading_strategies LEAN is a free, open-source platform for building, backtesting, and live-trading algorithms across stocks, forex, crypto, options, and more. Install the CLI with `pip install lean` to easily create projects, run research in Jupyter, backtest strategies, optimize, or deploy live trades from your terminal using Docker. Its modular design lets you customize everything. This saves you time by streamlining development, avoiding biases, and enabling fast, realistic testing to profit from better trading strategies. https://github.com/QuantConnect/Lean
Search: #array
@djangoproject · Post #316 · 04/28/2017, 06:09 AM
https://github.com/blissnd/easyxls Convert any #spreadsheet into a Python internal #dict/#array data structure, for easy processing. Can also handle pivot tables. For pivot table usage, header_row_start & header_col_start need to be set equal to the top left corner of the pivot table => header_row_start=8, header_col_start='c' in the included example. Column IDs must always be lowercase chars in quotes, e.g. 'a'.
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@djangoproject · Post #129 · 08/31/2016, 03:36 PM
https://pypi.python.org/pypi/numpy #NumPy is a general-purpose #array-processing package designed to efficiently manipulate large #multi-dimensional arrays of arbitrary records without sacrificing too much speed for small multi-dimensional #arrays. NumPy is built on the #Numeric code base and adds features introduced by #numarray as well as an extended #C-API and the ability to create arrays of arbitrary type which also makes NumPy suitable for interfacing with general-purpose #data-base applications.