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by mckinsey
configs.py3.61 kB
"""Pre-set configs for the Vizro MCP.""" from dataclasses import dataclass from typing import Any, Literal @dataclass class DFMetaData: file_name: str file_path_or_url: str file_location_type: Literal["local", "remote"] read_function_string: Literal["pd.read_csv", "pd.read_json", "pd.read_html", "pd.read_parquet", "pd.read_excel"] column_names_types: dict[str, str] | None = None @dataclass class DFInfo: general_info: str sample: dict[str, Any] IRIS = DFMetaData( file_name="iris_data", file_path_or_url="https://raw.githubusercontent.com/plotly/datasets/master/iris-id.csv", file_location_type="remote", read_function_string="pd.read_csv", column_names_types={ "sepal_length": "float", "sepal_width": "float", "petal_length": "float", "petal_width": "float", "species": "str", }, ) TIPS = DFMetaData( file_name="tips_data", file_path_or_url="https://raw.githubusercontent.com/plotly/datasets/master/tips.csv", file_location_type="remote", read_function_string="pd.read_csv", column_names_types={ "total_bill": "float", "tip": "float", "sex": "str", "smoker": "str", "day": "str", "time": "str", "size": "int", }, ) STOCKS = DFMetaData( file_name="stocks_data", file_path_or_url="https://raw.githubusercontent.com/plotly/datasets/master/stockdata.csv", file_location_type="remote", read_function_string="pd.read_csv", column_names_types={ "Date": "str", "IBM": "float", "MSFT": "float", "SBUX": "float", "AAPL": "float", "GSPC": "float", }, ) GAPMINDER = DFMetaData( file_name="gapminder_data", file_path_or_url="https://raw.githubusercontent.com/plotly/datasets/master/gapminder_unfiltered.csv", file_location_type="remote", read_function_string="pd.read_csv", column_names_types={ "country": "str", "continent": "str", "year": "int", "lifeExp": "float", "pop": "int", "gdpPercap": "float", }, ) SAMPLE_DASHBOARD_CONFIG = """ { `config`: { `pages`: [ { `title`: `Iris Data Analysis`, `controls`: [ { `id`: `species_filter`, `type`: `filter`, `column`: `species`, `targets`: [ `scatter_plot` ], `selector`: { `type`: `dropdown`, `multi`: true } } ], `components`: [ { `id`: `scatter_plot`, `type`: `graph`, `title`: `Sepal Dimensions by Species`, `figure`: { `x`: `sepal_length`, `y`: `sepal_width`, `color`: `species`, `_target_`: `scatter`, `data_frame`: `iris_data`, `hover_data`: [ `petal_length`, `petal_width` ] } } ] } ], `theme`: `vizro_dark`, `title`: `Iris Dashboard` }, `data_infos`: ` [ { \"file_name\": \"iris_data\", \"file_path_or_url\": \"https://raw.githubusercontent.com/plotly/datasets/master/iris-id.csv\", \"file_location_type\": \"remote\", \"read_function_string\": \"pd.read_csv\", } ] ` } """ def get_simple_dashboard_config() -> str: """Very simple Vizro dashboard configuration. Use this config as a starter when no other config is provided.""" return SAMPLE_DASHBOARD_CONFIG

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