Developer toolkit for CANSLIM investment style practitioners
For a brief introduction read this blog post.
Here is also a video recording of a CANSWIM presentation for the Python Austin Meetup.
Example forecast chart below:
pip install canswim
pip install -e ./
$ python -m canswim -h
usage: canswim [-h] [--forecast_start_date FORECAST_START_DATE] [--new_model NEW_MODEL] [--same_data SAME_DATA] {dashboard,gatherdata,downloaddata,uploaddata,modelsearch,train,forecast}
CANSWIM is a toolkit for CANSLIM style investors. Aims to complement the Simple Moving Average and other technical indicators.
positional arguments:
{dashboard,gatherdata,downloaddata,uploaddata,modelsearch,train,forecast}
Which canswim task to run: `dashboard` for stock charting and scans of recorded forecasts. 'gatherdata` to gather 3rd party stock market data and save to HF Hub. 'downloaddata` download model training and forecast
data from HF Hub to local data storage. 'uploaddata` upload to HF Hub any interim changes to local train and forecast data. `modelsearch` to find and save optimal hyperparameters for model training. `train` for
continuous model training. `forecast` to run forecast on stocks and upload dataset to HF Hub.
options:
-h, --help show this help message and exit
--forecast_start_date FORECAST_START_DATE
Optional argument for the `forecast` task. Indicate forecast start date in YYYY-MM-DD format. If not specified, forecast will start from the end of the target series.
--new_model NEW_MODEL
Optional argument for the `train` task. Whether to train a newly created model or continue training an existing pre-trained model.
--same_data SAME_DATA
Optional argument for the `dashboard` task. Whether to reuse previously created search database (faster start time) or update with new forecast data (slower start time).
NOTE: NOT FINANCIAL OR INVESTMENT ADVICE. USE AT YOUR OWN RISK.