# canswim
Developer toolkit for CANSLIM investment style practitioners
For a brief introduction read [this blog post](https://medium.com/@ivelin.atanasoff.ivanov/canswim-a-deep-learning-tool-for-canslim-practitioners-2c9740bb0d3d).
[Here is also a video recording](https://www.youtube.com/watch?v=GfC-H0uxXvk&ab_channel=AustinPythonMeetup) of a CANSWIM presentation for the [Python Austin Meetup](https://www.meetup.com/austinpython/).
# Setup
```
pip install canswim
```
## Install canswim package in dev mode
```
pip install -e ./
```
## Command line interface
```
$ 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.
```
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"description": "# canswim\nDeveloper toolkit for CANSLIM investment style practitioners\n\nFor a brief introduction read [this blog post](https://medium.com/@ivelin.atanasoff.ivanov/canswim-a-deep-learning-tool-for-canslim-practitioners-2c9740bb0d3d).\n\n[Here is also a video recording](https://www.youtube.com/watch?v=GfC-H0uxXvk&ab_channel=AustinPythonMeetup) of a CANSWIM presentation for the [Python Austin Meetup](https://www.meetup.com/austinpython/).\n\n# Setup\n\n\n```\npip install canswim\n```\n\n\n## Install canswim package in dev mode\n\n```\npip install -e ./\n```\n\n## Command line interface\n\n```\n$ python -m canswim -h\nusage: canswim [-h] [--forecast_start_date FORECAST_START_DATE] [--new_model NEW_MODEL] [--same_data SAME_DATA] {dashboard,gatherdata,downloaddata,uploaddata,modelsearch,train,forecast}\n\nCANSWIM is a toolkit for CANSLIM style investors. Aims to complement the Simple Moving Average and other technical indicators.\n\npositional arguments:\n {dashboard,gatherdata,downloaddata,uploaddata,modelsearch,train,forecast}\n 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\n 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\n continuous model training. `forecast` to run forecast on stocks and upload dataset to HF Hub.\n\noptions:\n -h, --help show this help message and exit\n --forecast_start_date FORECAST_START_DATE\n 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.\n --new_model NEW_MODEL\n Optional argument for the `train` task. Whether to train a newly created model or continue training an existing pre-trained model.\n --same_data SAME_DATA\n 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).\n\nNOTE: NOT FINANCIAL OR INVESTMENT ADVICE. USE AT YOUR OWN RISK.\n```\n",
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