gviz-api

import gviz_api import datetime # Define the schema of the table. # The structure is: [(id, type, optional_label), ...] description = [ ("name", "string", "Meal"), ("diet", "string", "Diet Type"), ("calories", "number", "Calories"), ("healthy", "boolean", "Healthy?"), ("serving_date", "date", "Serving Date") ] # Load the data. Data rows must match the schema order. data = [ ("Breakfast", "vegan", 250, True, datetime.date(2024, 4, 13)), ("Lunch", "vegetarian", 400, True, datetime.date(2024, 4, 13)), ("Dinner", "carnivore", 700, False, datetime.date(2024, 4, 12)), ("Snack", "omnivore", 150, True, datetime.date(2024, 4, 13)), ] # Create a DataTable object. data_table = gviz_api.DataTable(description) data_table.AppendData(data) # Output as JSON string (for embedding in a webpage) json_string = data_table.ToJSon(columns_order=("name", "diet", "calories", "healthy", "serving_date"), order_by="calories") print("JSON String:\n", json_string) # Output as JSON response string (for a data source URL) # req_id is often 0 for simple requests. json_response = data_table.ToJSonResponse(columns_order=("name", "calories"), order_by="calories", req_id=0) print("\nJSON Response (for data source):\n", json_response) # Output as JavaScript string (for direct script injection, often for debugging) javascript_string = data_table.ToJS(table_id="myDataTable", columns_order=("name", "calories"), order_by="calories") print("\nJavaScript String (for embedding):\n", javascript_string)