#!/usr/bin/env python3 """ Generates sample data ready for different Highcharts chart types. Useful when the user wants to explore a chart type without having real data. Usage: python sample_data.py --type line python sample_data.py --type pie --items 6 python sample_data.py --type stock --days 365 python sample_data.py --type sankey python sample_data.py --list (lists all available types) Output: JSON with Highcharts options ready to use. """ import sys import json import random import argparse from datetime import datetime, timedelta def sample_line(months: int = 12, series_count: int = 2) -> dict: """Sample data for line/spline/area chart.""" months_list = ['Jan','Feb','Mar','Apr','May','Jun', 'Jul','Aug','Sep','Oct','Nov','Dec'][:months] series = [] for i in range(series_count): base = random.randint(50, 200) data = [round(base + random.gauss(0, 20) + j * random.uniform(-2, 5), 1) for j in range(months)] series.append({"name": f"Series {chr(65+i)}", "data": data}) return {"categories": months_list, "series": series, "suggested_type": "line"} def sample_column(categories: int = 6, series_count: int = 2) -> dict: """Sample data for column/bar chart.""" cats = [f"Category {chr(65+i)}" for i in range(categories)] series = [] for i in range(series_count): data = [random.randint(20, 150) for _ in range(categories)] series.append({"name": f"Group {i+1}", "data": data}) return {"categories": cats, "series": series, "suggested_type": "column"} def sample_pie(items: int = 6) -> dict: """Sample data for pie/donut chart.""" names = ['Technology', 'Healthcare', 'Finance', 'Education', 'Retail', 'Industry', 'Energy', 'Transportation'][:items] values = [random.randint(5, 35) for _ in range(items)] total = sum(values) data = [{"name": n, "y": round(v / total * 100, 1)} for n, v in zip(names, values)] # Highlight the largest slice max_idx = max(range(len(data)), key=lambda i: data[i]["y"]) data[max_idx]["sliced"] = True data[max_idx]["selected"] = True return {"series": [{"name": "Share", "colorByPoint": True, "data": data}], "suggested_type": "pie"} def sample_scatter(points: int = 50) -> dict: """Sample data for scatter chart.""" data_a = [[round(random.gauss(5, 2), 1), round(random.gauss(5, 2), 1)] for _ in range(points)] data_b = [[round(random.gauss(8, 1.5), 1), round(random.gauss(3, 1.5), 1)] for _ in range(points)] return {"series": [ {"name": "Group A", "data": data_a}, {"name": "Group B", "data": data_b} ], "suggested_type": "scatter"} def sample_heatmap(rows: int = 7, cols: int = 12) -> dict: """Sample data for heatmap.""" row_cats = ['Mon','Tue','Wed','Thu','Fri','Sat','Sun'][:rows] col_cats = ['Jan','Feb','Mar','Apr','May','Jun', 'Jul','Aug','Sep','Oct','Nov','Dec'][:cols] data = [[x, y, random.randint(0, 100)] for x in range(cols) for y in range(rows)] return { "xCategories": col_cats, "yCategories": row_cats, "series": [{"data": data}], "suggested_type": "heatmap" } def sample_sankey() -> dict: """Sample data for Sankey diagram.""" data = [ ['Marketing', 'Leads', 1000], ['Direct Sales', 'Leads', 500], ['Referral', 'Leads', 300], ['Leads', 'Qualified', 900], ['Leads', 'Discarded', 900], ['Qualified', 'Proposal', 600], ['Qualified', 'Lost', 300], ['Proposal', 'Closed', 400], ['Proposal', 'Lost', 200], ] return { "series": [{"keys": ["from", "to", "weight"], "data": data}], "suggested_type": "sankey" } def sample_gauge(value: float = None) -> dict: """Sample data for gauge/solid gauge.""" val = value or round(random.uniform(30, 95), 1) return { "series": [{"name": "Performance", "data": [val]}], "suggested_type": "solidgauge", "min": 0, "max": 100 } def sample_treemap() -> dict: """Sample data for treemap.""" data = [ {"name": "Brazil", "value": 211, "colorValue": 1}, {"name": "Mexico", "value": 128, "colorValue": 2}, {"name": "Colombia", "value": 50, "colorValue": 3}, {"name": "Argentina", "value": 45, "colorValue": 4}, {"name": "Peru", "value": 32, "colorValue": 5}, {"name": "Venezuela", "value": 28, "colorValue": 6}, {"name": "Chile", "value": 19, "colorValue": 7}, {"name": "Ecuador", "value": 17, "colorValue": 8}, ] return {"series": [{"data": data}], "suggested_type": "treemap"} def sample_stock(days: int = 365) -> dict: """Sample data for stock chart (OHLC).""" start = datetime(2024, 1, 1) price = 150.0 data = [] for i in range(days): date = start + timedelta(days=i) if date.weekday() >= 5: continue o = round(price + random.gauss(0, 2), 2) h = round(o + abs(random.gauss(0, 3)), 2) l = round(o - abs(random.gauss(0, 3)), 2) c = round(random.uniform(l, h), 2) price = c ts = int(date.timestamp() * 1000) data.append([ts, o, h, l, c]) return {"series": [{"type": "candlestick", "name": "ACME", "data": data}], "suggested_type": "stock"} def sample_funnel() -> dict: """Sample data for funnel chart.""" data = [ ['Website Visitors', 15654], ['Downloads', 4064], ['Registrations', 1987], ['Active Trial', 976], ['Purchase', 846] ] return {"series": [{"data": data}], "suggested_type": "funnel"} GENERATORS = { "line": sample_line, "spline": sample_line, "area": sample_line, "column": sample_column, "bar": sample_column, "pie": sample_pie, "donut": sample_pie, "scatter": sample_scatter, "bubble": sample_scatter, "heatmap": sample_heatmap, "sankey": sample_sankey, "gauge": sample_gauge, "solidgauge": sample_gauge, "treemap": sample_treemap, "stock": sample_stock, "candlestick": sample_stock, "funnel": sample_funnel, "pyramid": sample_funnel, } def main(): parser = argparse.ArgumentParser(description="Generates sample data for Highcharts") parser.add_argument("--type", "-t", choices=list(GENERATORS.keys()), help="Chart type") parser.add_argument("--list", "-l", action="store_true", help="List available types") parser.add_argument("--output", "-o", help="Save to file") args = parser.parse_args() if args.list: print("Available types:") for t in sorted(set(GENERATORS.keys())): print(f" • {t}") return if not args.type: parser.print_help() sys.exit(1) generator = GENERATORS[args.type] result = generator() output = json.dumps(result, ensure_ascii=False, indent=2) if args.output: with open(args.output, 'w', encoding='utf-8') as f: f.write(output) print(f"[INFO] Saved to: {args.output}", file=sys.stderr) else: print(output) if __name__ == "__main__": main()