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The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by QuantConnect. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. QuantConnect makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. All investments involve risk, including loss of principal. You should consult with an investment professional before making any investment decisions.
I want to use my own Jupyter Notebook or Spyder IDE for all coding and backtesting. How can I do that?Â
Hi Rich,
Since Lean is written in C# using pythonnet as an interface to allow executing algorithms written in Python, it is not straightforward to develop algorithms using all the features of an IDE (namely debugging). The one setup we could figure out involves Visual Studio. We welcome suggestions on how to do it with other IDEs, namely Spyder and Visual Code.
The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by QuantConnect. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. QuantConnect makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. All investments involve risk, including loss of principal. You should consult with an investment professional before making any investment decisions.
Can you provide some REST endpoints for syncing the code at local to the server?That is, a REST API which can upload the code to my account.Some more endpoints for building and backtesting would be very helpful too. I am accustomed to writing code in Vim and tracking the changes with Git frequently.
As the code getting larger, my velocity of development is slowing down as I have to be worried about unconscious mistakes without any backups (and copy them to somewhere by hand is cumbersome).
Â
The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by QuantConnect. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. QuantConnect makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. All investments involve risk, including loss of principal. You should consult with an investment professional before making any investment decisions.
Hello,
Before I start I would just like to know some pre-requirements :Â
Can we upload files? Like keras pre-train models?Â
Do you have S&P500 Futures (ES) Data with market depth (level II)Â Â with 1-second refresh rate?Â
Do you have any type of API so I can use in my own computer (do not develop inside the site)?
Cheers! Â
Hi Birinhos,
Welcome to QuantConnect, and thank you for all these valuable questions.
For the first one, users are allowed to upload their custom data needed for their own algorithms. This page gives you the details. On the other hand, we are sorry to say that for now it is not possible to retrieve pre-train models. However, it is convenient and easy to train algorithms using ML libraries (Pytorch, TensorFlow, etc.) in QC. You can find all supported libraries in this whitelist.
For the second one, for now we don't have market depth data.
For the last one, you are welcome to work locally. We recommend you follow the installation instruction on this page to set up. After that, you can debug python in a very convenient way with the tutorial here. The API documentation is the same as the online one, and you will find many plugins very helpful in Visual Studio.
Hope these help!
Hi
The link to the tutorial above is dead
 Hi BoÂ
https://www.quantconnect.com/tutorials/open-source/debugging-pythonÂ
The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by QuantConnect. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. QuantConnect makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. All investments involve risk, including loss of principal. You should consult with an investment professional before making any investment decisions.
Hello, is it possible to completely override a class in the online IDE (for instance, the PortfolioStatistics class)? Thank you for your time!
Its real C#/Py
The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by QuantConnect. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. QuantConnect makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. All investments involve risk, including loss of principal. You should consult with an investment professional before making any investment decisions.
Ok, so I figured out that I could "overwrite" classes in the IDE simply by copying and pasting the subject classes, but that I may need to "overwrite" a few extra classes in the IDE (literally a copy and paste) probably do to structural differences between the IDE and the local environment. Now that I know this, how can I access the final portfolio statistics?
I have attempted to use "using QuantConnect.Lean.Engine.Results" in an attempt to access the backtest result statistics; however, I get the error that "the namespace 'Lean' does not exist in the namespace 'QuantConnect.'" I'm not sure why this is since the documentation on github shows similar use of the namespace in other classes? I'd like to display my custom statistics in the IDE results and/or print to the console or csv. Any help here would be greatly appreciated, thank you!
Hey Tony; please start a new discussion in the LEAN forum about this project.Â
The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by QuantConnect. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. QuantConnect makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. All investments involve risk, including loss of principal. You should consult with an investment professional before making any investment decisions.
The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by QuantConnect. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. QuantConnect makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. All investments involve risk, including loss of principal. You should consult with an investment professional before making any investment decisions.
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