Files
quantconnect--lean/Algorithm.Python
Jhonathan Abreu 0a9dc2c71c QCAlgorithm's OptionChain() api refactor (#8334)
* Fix pandas converter to handle list of data with different symbols

* Properly convert list of data into dataframe

Take into consideration data for multiple symbols in the same list

* Cleanup

* Index dataframes by symbol object instead of SID string

* Add symbol equality operator to compare against object

* Exclude "ID" from option chain dataframe

* Minor fix

* Add greeks columns directly in option chain dataframe.

Also add pass-through properties for greek values in OptionUniverse

* Some cleanup

* Minor fix

* Add new QCAlgorithm.OptionChains() method

- Use OptionChains as output
- Add DataFrame to OptionChain and OptionChains
- Rename Greeks classes
- Add ISymbolProvider for classes that have a symbol (IBaseData, OptionContract)

* Unify QCAlgorithmOptionChain API

Also refactor OptionContract to handle: (1) Actual market data and option price model data, and (2) OptionUniverse data

* Pass symbol properties to OptionUniverse option chain from algorithm

* Format OptionContract for dataframe

* Minor fix

* Add multiple option chains api regression algorithms and other minor changes

* Address peer review

Add NullGreeks class: keep ModeledGreeks as internal as possible

* Minor fix and add PandasConverter unit tests

* Peer review: Non-thread-safe Lazy for Python

* Handle Greeks unwrapping by PandasData

* PandasData cleanup

* Add data and other minor changes

* Unit test fix

* Update Pythonnet to 2.0.39

* Cleanup

* PandasData handling children class members

Address peer review

* Fix: indexing symbol conversion in pandas mapper

* Fix pandas mapper to convert string keys to symbol only when necessary

* Cleanup

* Cleanup

* Add PandasColumn python class to handle proper indexing

This allows propery hash and equality between Symbols, C# strings and Python strings

* Minor fixes

* Symbol cache improvements

* Minor fix for cache miss

* Revert PandasMapper reserved names and improvements

* Minor fix

* Revert reserved names

* Minor fix for Symbol equality operators

---------

Co-authored-by: Martin Molinero <martin.molinero1@gmail.com>
2024-10-04 12:26:15 -04:00
..

QuantConnect Python Algorithm Project

This document contains information regarding how to use Python with the Lean engine, this includes how to use Python Autocomplete, setting up Lean for Python algorithms, PythonNet compilation for devs, and what imports to use to replicate the web IDE experience in your local development.



Local Python Autocomplete

To enable autocomplete for your local Python IDE, install the quantconnect-stubs package from PyPI using the following command:

pip install quantconnect-stubs

To update your autocomplete to the latest version, you can run the following command:

pip install --upgrade quantconnect-stubs

Copy and paste the imports found here to the top of your project file to enable autocomplete.

In addition, you can use Skylight to automatically sync local changes to the cloud.



Setup Lean Locally with Python

Before setting up python support, follow the installation instructions to get LEAN running C# algorithms on your machine.

Installing Python 3.8:

Next we must prepare a Python installation for Lean to use. Follow the instructions for your OS.


Windows

  1. Use the Windows x86-64 MSI Python 3.8.13 installer from python.org or Anaconda for Windows installer. "Anaconda 5.2" installs 3.5.2 by default, after installation of Anaconda you will need to upgrade python to make it work as expected: conda install -y python=3.8.13
  2. When asked to select the features to be installed, make sure you select "Add python.exe to Path"
  3. Create PYTHONNET_PYDLL environment variable to the location of your python dll in your installation (e.g. C:\Dev\Python38\python38.dll or C:\Anaconda3\python38.dll):
    • Right mouse button on My Computer. Click Properties.
    • Click Advanced System Settings -> Environment Variables -> System Variables
    • Click New.
      • Name: PYTHONNET_PYDLL
      • Value: {python dll location}
  4. Install pandas=1.4.3 and its dependencies.
  5. Install wrapt=1.14.1 module.
  6. Reboot computer to ensure changes are propagated.

macOS

  1. Use the macOS x86-64 package installer from Anaconda and follow "Installing on macOS" instructions from Anaconda documentation page.
  2. Set PYTHONNET_PYDLL environment variable to the location of your python dll in your installation directory (e.g. /Users/{your_user_name}/anaconda3/lib/libpython3.8.dylib):
    • Open ~/.bash-profile with a text editor of your choice.
    • Add a new line to the file containing
    export PYTHONNET_PYDLL="/{your}/{path}/{here}/libpython3.8.dylib"
    
    • Save your changes, and either restart your terminal or execute
    source ~/.bash-profile
    
  3. Install pandas=1.4.3 and its dependencies.
  4. Install wrapt=1.14.1 module.

Linux

  1. Install Python using miniconda by following these commands; by default, miniconda is installed in the users home directory ($HOME):
export PATH="$HOME/miniconda3/bin:$PATH"
wget https://cdn.quantconnect.com/miniconda/Miniconda3-4.5.12-Linux-x86_64.sh
bash Miniconda3-4.5.12-Linux-x86_64.sh -b
rm -rf Miniconda3-4.5.12-Linux-x86_64.sh
conda update -y python conda pip
  1. Create a new Python environment with the needed dependencies
conda create -n qc_lean python=3.8.13 pandas=1.4.3 wrapt=1.14.1
  1. Set PYTHONNET_PYDLL environment variable to location of your python dll in your installation directory (e.g. /home/{your_user_name}/miniconda3/envs/qc_lean/lib/libpython3.8.so):
    • Open /etc/environment with a text editor of your choice.
    • Add a new line to the file containing
    PYTHONNET_PYDLL="/home/{your_user_name}/miniconda3/envs/qc_lean/lib/libpython3.8.so"
    
    • Save your changes, and logout or reboot to reflect these changes

Run Python Algorithms

  1. Update the config to run a python algorithm:
    "algorithm-type-name": "BasicTemplateAlgorithm",
    "algorithm-language": "Python",
    "algorithm-location": "../../../Algorithm.Python/BasicTemplateAlgorithm.py",
    
  2. Build LEAN.
  3. Run LEAN. You should see the same result of the C# algorithm you tested earlier.

Python.NET development - Python.Runtime.dll compilation

LEAN users do not need to compile Python.Runtime.dll. The information below is targeted to developers who wish to improve it. Download QuantConnect/pythonnet github clone or downloading the zip. If downloading the zip - unzip to a local pathway.

Note: QuantConnect's version of pythonnet is an enhanced version of pythonnet with added support for System.Decimal and System.DateTime.

Below are some examples of build commands that create a suitable Python.Runtime.dll.

msbuild pythonnet.sln /nologo /v:quiet /t:Clean;Rebuild 

OR

dotnet build pythonnet.sln

Python Autocomplete Imports

Adding from AlgorithmImports import * to the top of your Python file is enough to enable autocomplete and import the required types for the algorithm at runtime.

Known Issues

  • Python can sometimes have issues when paired with our quantconnect stubs package on Windows. This issue can cause modules not to be found because site-packages directory is not present in the python path. If you have the required modules installed and are seeing errors about them not being found, please try the following steps:
    • remove stubs -> pip uninstall quantconnect-stubs
    • reinstall stubs -> pip install quantconnect-stubs