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{ | ||
"ExampleSimplePiece": { | ||
"name": "ExampleSimplePiece", | ||
"ProphetTrainModelPiece": { | ||
"name": "ProphetTrainModelPiece", | ||
"dependency": { | ||
"dockerfile": null, | ||
"requirements_file": "requirements_0.txt" | ||
}, | ||
"tags": [ | ||
"Example" | ||
"Prophet" | ||
], | ||
"style": { | ||
"node_label": "Simple Piece", | ||
"node_label": "Prophet Train", | ||
"node_type": "default", | ||
"node_style": { | ||
"backgroundColor": "#ebebeb" | ||
}, | ||
"useIcon": true, | ||
"icon_class_name": "fas fa-database", | ||
"icon_class_name": "icon-park-outline:robot-one", | ||
"iconStyle": { | ||
"cursor": "pointer" | ||
} | ||
}, | ||
"description": "This is an example of a simple Domino Piece", | ||
"description": "Piece to train a prophet model", | ||
"container_resources": { | ||
"requests": { | ||
"cpu": "100m", | ||
"memory": "128Mi" | ||
"cpu": 100, | ||
"memory": 128 | ||
}, | ||
"limits": { | ||
"cpu": "500m", | ||
"memory": "512Mi" | ||
"cpu": 500, | ||
"memory": 512 | ||
} | ||
}, | ||
"input_schema": { | ||
"title": "InputModel", | ||
"type": "object", | ||
"$defs": { | ||
"GrowthTrend": { | ||
"enum": [ | ||
"linear", | ||
"logistic", | ||
"flat" | ||
], | ||
"title": "GrowthTrend", | ||
"type": "string" | ||
}, | ||
"SeasonalityMode": { | ||
"enum": [ | ||
"additive", | ||
"multiplicative" | ||
], | ||
"title": "SeasonalityMode", | ||
"type": "string" | ||
} | ||
}, | ||
"properties": { | ||
"distribution_name": { | ||
"description": "Name of the distribution to sample from", | ||
"input_data_file": { | ||
"description": "Path to the input data file. Accepted formats: `.csv`, `.json`. Should use the following format: `ds` (datetime), `y` (target).", | ||
"title": "Input Data File", | ||
"type": "string" | ||
}, | ||
"growth_trend": { | ||
"allOf": [ | ||
{ | ||
"$ref": "#/definitions/DistributionType" | ||
"$ref": "#/$defs/GrowthTrend" | ||
} | ||
] | ||
], | ||
"default": "linear", | ||
"description": "The growth trend of the data. Options are `linear`, `logistic` and `flat`. Default is `linear`." | ||
}, | ||
"distribution_mean": { | ||
"title": "Distribution Mean", | ||
"description": "Distribution mean", | ||
"type": "number" | ||
"changepoints": { | ||
"anyOf": [ | ||
{ | ||
"items": { | ||
"format": "date", | ||
"type": "string" | ||
}, | ||
"type": "array" | ||
}, | ||
{ | ||
"type": "null" | ||
} | ||
], | ||
"default": null, | ||
"description": "List of dates at which to include potential changepoints. If not specified, potential changepoints are selected automatically.", | ||
"title": "Changepoints" | ||
}, | ||
"distribution_sd": { | ||
"title": "Distribution Sd", | ||
"description": "Distribution standard deviation", | ||
"default": 1.0, | ||
"exclusiveMinimum": 0.0, | ||
"type": "number" | ||
"n_changepoints": { | ||
"default": 25, | ||
"description": " Number of potential changepoints to include. Not used if input `changepoints` is supplied.", | ||
"maximum": 1000, | ||
"minimum": 0, | ||
"title": "N Changepoints", | ||
"type": "integer" | ||
}, | ||
"seasonality_mode": { | ||
"allOf": [ | ||
{ | ||
"$ref": "#/$defs/SeasonalityMode" | ||
} | ||
], | ||
"default": "additive", | ||
"description": "The seasonality mode of the data. Options are `additive` and `multiplicative`. Default is `additive`." | ||
} | ||
}, | ||
"required": [ | ||
"distribution_name", | ||
"distribution_mean" | ||
"input_data_file" | ||
], | ||
"definitions": { | ||
"DistributionType": { | ||
"title": "DistributionType", | ||
"description": "An enumeration.", | ||
"enum": [ | ||
"gaussian", | ||
"poisson" | ||
], | ||
"title": "InputModel", | ||
"type": "object" | ||
}, | ||
"output_schema": { | ||
"properties": { | ||
"prophet_model_file_path": { | ||
"description": "Path to the file containing the trained model.", | ||
"title": "Prophet model path", | ||
"type": "string" | ||
} | ||
}, | ||
"required": [ | ||
"prophet_model_file_path" | ||
], | ||
"title": "OutputModel", | ||
"type": "object" | ||
}, | ||
"secrets_schema": null, | ||
"source_url": "https://github.com/Tauffer-Consulting/timeseries_domino_pieces/tree/main/pieces/ProphetTrainModelPiece" | ||
}, | ||
"GetYahooFinanceDataPiece": { | ||
"name": "GetYahooFinanceDataPiece", | ||
"dependency": { | ||
"dockerfile": null, | ||
"requirements_file": "requirements_0.txt" | ||
}, | ||
"tags": [ | ||
"Example" | ||
], | ||
"style": { | ||
"node_label": "Get Yahoo Finance Data", | ||
"node_type": "default", | ||
"node_style": { | ||
"backgroundColor": "#ebebeb" | ||
}, | ||
"useIcon": true, | ||
"icon_class_name": "fa-solid:database", | ||
"iconStyle": { | ||
"cursor": "pointer" | ||
} | ||
}, | ||
"description": "This piece gets data from Yahoo Finance.", | ||
"container_resources": { | ||
"requests": { | ||
"cpu": 100, | ||
"memory": 128 | ||
}, | ||
"limits": { | ||
"cpu": 500, | ||
"memory": 512 | ||
} | ||
}, | ||
"input_schema": { | ||
"properties": { | ||
"ticker": { | ||
"description": "Ticker of the stock to get data from.", | ||
"title": "Ticker", | ||
"type": "string" | ||
}, | ||
"start_date": { | ||
"description": "Start date of the data to get.", | ||
"format": "date", | ||
"title": "Start Date", | ||
"type": "string" | ||
}, | ||
"end_date": { | ||
"description": "End date of the data to get.", | ||
"format": "date", | ||
"title": "End Date", | ||
"type": "string" | ||
} | ||
}, | ||
"required": [ | ||
"ticker", | ||
"start_date", | ||
"end_date" | ||
], | ||
"title": "InputModel", | ||
"type": "object" | ||
}, | ||
"output_schema": { | ||
"properties": { | ||
"data_path": { | ||
"description": "Path to the file containing the trained model.", | ||
"title": "Data Path", | ||
"type": "string" | ||
} | ||
}, | ||
"required": [ | ||
"data_path" | ||
], | ||
"title": "OutputModel", | ||
"type": "object", | ||
"type": "object" | ||
}, | ||
"secrets_schema": null, | ||
"source_url": "https://github.com/Tauffer-Consulting/timeseries_domino_pieces/tree/main/pieces/GetYahooFinanceDataPiece" | ||
}, | ||
"ProphetPredictPiece": { | ||
"name": "ProphetPredictPiece", | ||
"dependency": { | ||
"dockerfile": null, | ||
"requirements_file": "requirements_0.txt" | ||
}, | ||
"tags": [ | ||
"Prophet" | ||
], | ||
"style": { | ||
"node_label": "Prophet Predict", | ||
"node_type": "default", | ||
"node_style": { | ||
"backgroundColor": "#ebebeb" | ||
}, | ||
"useIcon": true, | ||
"icon_class_name": "icon-park-outline:robot-one", | ||
"iconStyle": { | ||
"cursor": "pointer" | ||
} | ||
}, | ||
"description": "Piece to predict using Prophet", | ||
"container_resources": { | ||
"requests": { | ||
"cpu": 100, | ||
"memory": 128 | ||
}, | ||
"limits": { | ||
"cpu": 500, | ||
"memory": 512 | ||
} | ||
}, | ||
"input_schema": { | ||
"properties": { | ||
"message": { | ||
"title": "Message", | ||
"description": "Output message to log", | ||
"prophet_model_path": { | ||
"description": "Path to the file containing the trained model.", | ||
"title": "Prophet Model Path", | ||
"type": "string" | ||
}, | ||
"sample_result": { | ||
"title": "Sample Result", | ||
"description": "The result of this Piece's processing", | ||
"type": "string" | ||
"periods": { | ||
"description": "Number of periods to forecast.", | ||
"title": "Periods", | ||
"type": "integer" | ||
} | ||
}, | ||
"required": [ | ||
"message", | ||
"sample_result" | ||
] | ||
"prophet_model_path", | ||
"periods" | ||
], | ||
"title": "InputModel", | ||
"type": "object" | ||
}, | ||
"secrets_schema": { | ||
"title": "SecretsModel", | ||
"type": "object", | ||
"output_schema": { | ||
"properties": { | ||
"EXAMPLE_OPERATOR_SECRET_1": { | ||
"title": "Example Operator Secret 1", | ||
"description": "A secret necessary to run this Piece", | ||
"forecast_data_path": { | ||
"description": "Path to the file containing the forecast data.", | ||
"title": "Forecast Data Path", | ||
"type": "string" | ||
}, | ||
"forecast_figure_path": { | ||
"description": "Path to the file containing the results figure.", | ||
"title": "Forecast Figure Path", | ||
"type": "string" | ||
} | ||
}, | ||
"required": [ | ||
"EXAMPLE_OPERATOR_SECRET_1" | ||
] | ||
} | ||
"forecast_data_path", | ||
"forecast_figure_path" | ||
], | ||
"title": "OutputModel", | ||
"type": "object" | ||
}, | ||
"secrets_schema": null, | ||
"source_url": "https://github.com/Tauffer-Consulting/timeseries_domino_pieces/tree/main/pieces/ProphetPredictPiece" | ||
} | ||
} |
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@@ -1 +1,4 @@ | ||
numpy==1.23.5 | ||
prophet==1.1.5 | ||
pandas==2.1.3 | ||
plotly==5.18.0 | ||
yfinance==0.2.38 |
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