Search Results for "install with"

NeuralProphet bridges the gap between traditional time-series models and deep learning methods. It's based on PyTorch and can be installed using pip. A Neural Network based Time-Series model, inspired by Facebook Prophet and AR-Net, built on PyTorch. You can find the datasets used in the tutorials, including data preprocessing examples, in our neuralprophet-data repository. The documentation page may not we entirely up to date. Docstrings should be reliable, please refer to those when in...

Optopsy is a Python-based, nimble backtesting and statistics library focused on evaluating options trading strategies like calls, puts, straddles, spreads, and more, using pandas-driven analysis. The csv_data() function is a convenience function. Under the hood it uses Panda's read_csv() function to do the import. There are other parameters that can help with loading the csv data, consult the code/future documentation to see how to use them. Optopsy is a small simple library that offloads...

TradingGym is a toolkit (in Python) for creating trading and backtesting environments, especially for reinforcement learning agents, but also for simpler rule-based algorithms. It follows a design inspired by OpenAI Gym, offering various environments, data formats (tick data and OHLC), and tools to simulate trading with costs, position limits, observation windows etc. Licensed under MIT. This training environment was originally designed for tickdata, but also supports OHLC data format. WIP....

...The supported APIs are Robinhood, Gemini, and TD Ameritrade. If you are contributing to this project and would like to use automatic testing for your changes, you will need to install pytest and pytest-dotenv. You will also need to fill out all the fields in .test.env. I recommend that you rename the file as .env once you are done adding in all your personal information.

...Please see https://sourceforge.net/p/formavid/code/ci/master/tree/INSTALL.txt for details. The appliance is specially designed to run on the Google Cloud Platform "Free Tier" https://formavid.org/gce and has it's own custom install script https://sourceforge.net/projects/formavid/files/gcloud-gce-deployment/download with instructions https://sourceforge.net/projects/formavid/files/ provided.

...Installing Zipline is slightly more involved than the average Python package. For a development installation (used to develop Zipline itself), create and activate a virtualenv, then run the etc/dev-install script. Please note that Zipline is not a community-led project. Zipline is maintained by the Quantopian engineering team, and we are quite small and often busy.