Examples Gallery¶

from holysheet import Report, KPI, LineChart, Markdown

# Sample data
monthly_data = [
    {"month": "Jan", "users": 1_200},
    {"month": "Feb", "users": 1_450},
    {"month": "Mar", "users": 1_830},
    {"month": "Apr", "users": 2_100},
    {"month": "May", "users": 2_540},
    {"month": "Jun", "users": 2_890},
]

# Build the report
report = Report(
    title="Basic Report",
    subtitle="A quick overview of key metrics",
    theme="light",
)

# Add a markdown intro
report.add(Markdown(content=(
    "## Welcome\n\n"
    "This is a basic HolySheet report demonstrating KPI cards "
    "and a simple line chart."
)))

# Add KPI cards
report.add(KPI(label="Total Users", value="2,890", delta="+13.8%", status="positive"))
report.add(KPI(label="Active Rate", value=78, delta="+2.1%", status="positive", unit="%"))
report.add(KPI(label="Churn Rate", value="4.2%", delta="-0.5%", status="positive"))

# Add a line chart
report.add(LineChart(
    title="User Growth",
    data=monthly_data,
    x="month",
    y="users",
    height=400,
))

# Export
report.export_html("basic_report.html")
report.export_json("basic_report.json")
print("✓ Exported: basic_report.html, basic_report.json")

from holysheet import (
    KPI, BarChart, DataTable, LineChart, Markdown,
    PieChart, Report, Section,
)

# ── Data ──
monthly_sales = [
    {"month": "Jan", "sales": 245_000, "returns": 12_000},
    {"month": "Feb", "sales": 268_000, "returns": 15_000},
    {"month": "Mar", "sales": 312_000, "returns": 9_000},
    {"month": "Apr", "sales": 298_000, "returns": 11_000},
    {"month": "May", "sales": 342_000, "returns": 14_000},
    {"month": "Jun", "sales": 389_000, "returns": 8_000},
    {"month": "Jul", "sales": 356_000, "returns": 13_000},
    {"month": "Aug", "sales": 410_000, "returns": 10_000},
    {"month": "Sep", "sales": 445_000, "returns": 16_000},
    {"month": "Oct", "sales": 478_000, "returns": 12_000},
    {"month": "Nov", "sales": 512_000, "returns": 18_000},
    {"month": "Dec", "sales": 580_000, "returns": 22_000},
]

region_data = [
    {"region": "North America", "sales": 1_840_000},
    {"region": "Europe", "sales": 1_250_000},
    {"region": "Asia Pacific", "sales": 920_000},
    {"region": "Latin America", "sales": 410_000},
    {"region": "Middle East", "sales": 215_000},
]

channel_data = [
    {"channel": "Direct Sales", "revenue": 2_100_000},
    {"channel": "Online Store", "revenue": 1_500_000},
    {"channel": "Partners", "revenue": 800_000},
    {"channel": "Retail", "revenue": 450_000},
    {"channel": "Referrals", "revenue": 285_000},
]

top_deals = [
    {"deal": "Enterprise Suite - Acme Corp", "rep": "Michael Torres",
     "value": "$450,000", "stage": "Closed Won", "close_date": "2026-11-15"},
    {"deal": "Platform License - GlobalTech", "rep": "Sarah Kim",
     "value": "$320,000", "stage": "Negotiation", "close_date": "2026-12-01"},
    {"deal": "Data Analytics - FinCorp", "rep": "James Wilson",
     "value": "$280,000", "stage": "Closed Won", "close_date": "2026-10-28"},
    {"deal": "Cloud Migration - MedHealth", "rep": "Ana Garcia",
     "value": "$210,000", "stage": "Proposal", "close_date": "2026-12-15"},
    {"deal": "AI Integration - RetailMax", "rep": "David Chen",
     "value": "$195,000", "stage": "Closed Won", "close_date": "2026-11-20"},
]

# ── Build Report ──
report = Report(
    title="Q4 Sales Performance Dashboard",
    subtitle="Sales metrics, pipeline, and regional performance",
    theme="executive",
)

report.add(Markdown(content="""## Sales Overview

Q4 has been our strongest quarter yet, with **$4.64M** in total sales representing
a **23% increase** over Q3. The sales team has exceeded quota by 15%.
"""))

# KPIs
report.add(KPI(label="Total Sales", value="$4.64M", delta="+23%", status="positive"))
report.add(KPI(label="Deals Closed", value=127, delta="+18", status="positive"))
report.add(KPI(
    label="Win Rate", value=68, unit="%", delta="+4.2%", status="positive",
    description="Up from 63.8% last quarter",
))
report.add(KPI(label="Avg Deal Size", value="$36.5K", delta="+$2.1K", status="positive"))

# Sales trend
report.add(LineChart(
    title="Monthly Sales Trend",
    data=monthly_sales, x="month", y="sales", height=400,
))

# Regional breakdown
report.add(Section(
    title="Regional & Channel Analysis",
    description="Sales distribution by geography and channel",
    children=[
        BarChart(title="Sales by Region", data=region_data, x="region", y="sales"),
        PieChart(title="Revenue by Channel", data=channel_data, name="channel", value="revenue"),
    ],
))

# Top deals
report.add(DataTable(
    title="Top Deals This Quarter",
    data=top_deals,
    columns=["deal", "rep", "value", "stage", "close_date"],
))

# Export
report.export_html("sales_dashboard.html")

from holysheet import (
    KPI, BarChart, DataTable, LineChart, Markdown,
    PieChart, Report, Section,
)

# ── Data ──
revenue_data = [
    {"month": "Jan", "revenue": 820_000, "target": 800_000},
    {"month": "Feb", "revenue": 910_000, "target": 850_000},
    {"month": "Mar", "revenue": 1_050_000, "target": 900_000},
    {"month": "Apr", "revenue": 980_000, "target": 950_000},
    {"month": "May", "revenue": 1_120_000, "target": 1_000_000},
    {"month": "Jun", "revenue": 1_250_000, "target": 1_050_000},
]

team_data = [
    {"team": "Platform", "delivered": 47, "planned": 52},
    {"team": "ML Ops", "delivered": 38, "planned": 40},
    {"team": "Frontend", "delivered": 55, "planned": 50},
    {"team": "Data Eng", "delivered": 32, "planned": 35},
]

budget_data = [
    {"category": "Engineering", "amount": 2_400_000},
    {"category": "Infrastructure", "amount": 800_000},
    {"category": "Marketing", "amount": 600_000},
    {"category": "Operations", "amount": 450_000},
]

projects_data = [
    {"project": "AIFlow Core v3", "owner": "Sarah Chen", "risk": "Low",
     "status": "On Track", "completion": "87%", "budget": "€1.2M"},
    {"project": "ML Pipeline", "owner": "Marcus Johnson", "risk": "Medium",
     "status": "At Risk", "completion": "62%", "budget": "€890K"},
    {"project": "Client Portal 2.0", "owner": "Ana Rodriguez", "risk": "Low",
     "status": "On Track", "completion": "91%", "budget": "€540K"},
    {"project": "Data Warehouse", "owner": "James Park", "risk": "High",
     "status": "Delayed", "completion": "45%", "budget": "€1.8M"},
]

# ── Build ──
report = Report(
    title="AIFlow Executive Portfolio Report",
    subtitle="Q4 2026 · Portfolio risk and delivery intelligence",
    theme="dark",
)

report.add(Markdown(content="""## Executive Summary

Portfolio health remains **strong** with 42 active projects delivering on schedule.
Risk-adjusted returns are trending positively, with a **12% improvement** in delivery
confidence over the past quarter.

- Revenue exceeded targets for 6 consecutive months
- Frontend team delivered 110% of planned capacity
- One project (Data Warehouse) requires executive attention
"""))

report.add(KPI(label="Total Revenue", value="€14.96M", delta="+18.2%", status="positive"))
report.add(KPI(label="Active Projects", value=42, delta="+3", status="positive"))
report.add(KPI(label="On-Track Rate", value=87, unit="%", delta="+5.2%", status="positive"))
report.add(KPI(label="Risk Score", value=38, delta="-34", status="positive",
               description="Lower is better"))

report.add(Section(
    title="Revenue & Financial",
    children=[
        LineChart(title="Monthly Revenue vs Target", data=revenue_data,
                  x="month", y=["revenue", "target"]),
        PieChart(title="Budget Allocation", data=budget_data,
                 name="category", value="amount"),
    ],
))

report.add(Section(
    title="Delivery & Operations",
    children=[
        BarChart(title="Team Delivery", data=team_data,
                 x="team", y=["delivered", "planned"]),
    ],
))

report.add(DataTable(title="Project Portfolio", data=projects_data))
report.export_html("portfolio_report.html")