Report Generator

Create professional, data-driven reports with charts, tables, and narrative text. Perfect for business reports, analytics dashboards, status updates, and automated reporting pipelines.

Quick Start

from scripts.report_gen import ReportGenerator

Create a simple report

report = ReportGenerator("Monthly Sales Report") report.add_text("This report summarizes sales performance for Q4 2024.") report.add_table(sales_data, title="Sales by Region") report.add_chart(sales_data, chart_type="bar", title="Revenue by Month") report.add_text("Key findings: Revenue increased 25% quarter-over-quarter.") report.generate().save("sales_report.pdf")

From template

report = ReportGenerator.from_template("executive_summary") report.set_data(data_dict) report.generate().save("exec_summary.pdf")

Features

• Multiple Output Formats: PDF, HTML

• Rich Content: Text, tables, charts, images, headers

• Chart Types: Bar, line, pie, scatter, area, heatmap

• Table Formatting: Auto-styling, conditional formatting

• Templates: Pre-built report templates

• Branding: Logo, colors, fonts, headers/footers

• Sections: Table of contents, page numbers, appendices

• Data Integration: CSV, DataFrame, dict inputs

API Reference

Initialization

New report

report = ReportGenerator("Report Title") report = ReportGenerator("Report Title", subtitle="Q4 2024 Analysis")

From template

report = ReportGenerator.from_template("quarterly_review")

With config

report = ReportGenerator("Title", config={ "page_size": "letter", "orientation": "portrait", "margins": {"top": 1, "bottom": 1, "left": 0.75, "right": 0.75} })

Report Metadata

Title and subtitle

report.set_title("Annual Report 2024") report.set_subtitle("Financial Performance Analysis")

Author and date

report.set_author("Analytics Team") report.set_date("December 2024") report.set_date_auto() # Use today

Organization

report.set_organization("Acme Corporation") report.set_logo("logo.png")

Adding Content

Text Content

Simple paragraph

report.add_text("This is a paragraph of analysis text.")

Styled text

report.add_text("Important finding!", style="highlight") report.add_text("Key metric: 42%", style="metric")

Headers

report.add_heading("Executive Summary", level=1) report.add_heading("Revenue Analysis", level=2) report.add_heading("By Region", level=3)

Bullet points

report.add_bullets([ "Revenue increased 25% YoY", "Customer acquisition up 15%", "Churn rate decreased to 3%" ])

Numbered list

report.add_numbered_list([ "Expand to European markets", "Launch mobile application", "Implement AI-driven analytics" ])

Tables

From DataFrame

import pandas as pd df = pd.DataFrame({ 'Region': ['North', 'South', 'East', 'West'], 'Revenue': [100000, 85000, 92000, 78000], 'Growth': ['12%', '8%', '15%', '5%'] }) report.add_table(df, title="Regional Performance")

From dict/list

data = [ {'Product': 'A', 'Sales': 1000, 'Profit': 200}, {'Product': 'B', 'Sales': 1500, 'Profit': 350} ] report.add_table(data, title="Product Summary")

With styling

report.add_table(df, title="Sales Data", highlight_max=['Revenue'], # Highlight max values highlight_min=['Growth'], # Highlight min values currency_cols=['Revenue'], # Format as currency percent_cols=['Growth'], # Format as percent align={'Region': 'left', 'Revenue': 'right'} )

Charts

Bar chart

report.add_chart( data=df, chart_type="bar", x="Region", y="Revenue", title="Revenue by Region" )

Line chart

report.add_chart( data=time_series_df, chart_type="line", x="Month", y=["Sales", "Forecast"], title="Sales Trend" )

Pie chart

report.add_chart( data=category_df, chart_type="pie", values="Amount", labels="Category", title="Budget Allocation" )

Chart options

report.add_chart( data=df, chart_type="bar", x="Region", y="Revenue", title="Revenue Analysis", color="#3498db", width=6, # inches height=4, show_values=True, show_legend=True )

Images

Add image

report.add_image("screenshot.png", caption="Dashboard View") report.add_image("diagram.png", width=5, caption="Architecture Diagram")

Special Elements

Page break

report.add_page_break()

Horizontal line

report.add_divider()

Spacer

report.add_spacer(height=0.5) # inches

Callout box

report.add_callout( "Key Insight: Customer retention improved 20% after implementing the new onboarding flow.", style="info" # info, warning, success, error )

Quote

report.add_quote( "Data is the new oil.", attribution="Clive Humby" )

Sections and Structure

Start a new section

report.start_section("Financial Analysis")

Add content to section

report.add_text("...") report.add_table(...)

End section

report.end_section()

Table of contents (auto-generated)

report.enable_toc()

Appendix

report.start_appendix() report.add_heading("Raw Data", level=2) report.add_table(raw_data)

Branding and Styling

Logo and organization

report.set_logo("logo.png", width=150) report.set_organization("Acme Corp")

Colors

report.set_colors( primary="#1e40af", # Headers, accents secondary="#6b7280", # Secondary text background="#ffffff" # Background )

Fonts

report.set_fonts( heading="Helvetica-Bold", body="Helvetica" )

Header and footer

report.set_header("Confidential - Internal Use Only") report.set_footer("Page {page} of {total}")

Watermark

report.set_watermark("DRAFT")

Templates

Available templates

report = ReportGenerator.from_template("executive_summary") report = ReportGenerator.from_template("quarterly_review") report = ReportGenerator.from_template("project_status") report = ReportGenerator.from_template("analytics_dashboard")

Template with data

report = ReportGenerator.from_template("monthly_metrics") report.set_data({ "period": "December 2024", "revenue": 1500000, "growth": 0.15, "customers": 5000, "charts": {"revenue_trend": trend_df} }) report.generate()

Generation and Export

Generate report

report.generate()

Save as PDF

report.save("report.pdf")

Save as HTML

report.save("report.html")

Get bytes

pdf_bytes = report.to_bytes() html_string = report.to_html()

Templates

Executive Summary

• Title page

• Key metrics highlights

• Summary bullets

• Charts section

• Recommendations

Quarterly Review

• Performance overview

• Financial metrics

• Comparison to previous quarter

• Goals progress

• Next quarter outlook

Project Status

• Project overview

• Timeline/milestones

• Risks and issues

• Team updates

• Next steps

Analytics Dashboard

• KPI cards

• Multiple charts

• Trend analysis

• Data tables

• Insights

CLI Usage

Generate from JSON config

python report_gen.py --config report_config.json --output report.pdf

With template

python report_gen.py --template executive_summary --data data.json --output summary.pdf

Quick report from CSV

python report_gen.py --csv data.csv --title "Data Report" --output report.pdf

CLI Arguments

Argument Description Default

--config

Report configuration JSON

--template

Template name

--data

Data JSON file

--csv

CSV data file

--title

Report title Report

--output

Output file path report.pdf

--format

Output format (pdf/html) pdf

Examples

Sales Report

report = ReportGenerator("Q4 Sales Report") report.set_subtitle("October - December 2024") report.set_organization("Sales Department") report.set_logo("company_logo.png")

report.add_heading("Executive Summary", level=1) report.add_text( "Q4 2024 showed strong performance across all regions, " "with total revenue reaching $4.2M, a 23% increase over Q3." )

report.add_callout( "Total Revenue: $4.2M (+23% QoQ)", style="success" )

report.add_heading("Regional Performance", level=2) report.add_chart(regional_data, "bar", x="Region", y="Revenue", title="Revenue by Region") report.add_table(regional_data, title="Detailed Metrics")

report.add_heading("Trends", level=2) report.add_chart(monthly_data, "line", x="Month", y="Revenue", title="Monthly Revenue Trend")

report.add_heading("Recommendations", level=1) report.add_bullets([ "Increase investment in high-growth East region", "Address declining West region performance", "Launch Q1 promotional campaign" ])

report.generate().save("q4_sales_report.pdf")

Analytics Dashboard

report = ReportGenerator("Marketing Analytics") report.set_date_auto()

KPI Summary

report.add_heading("Key Metrics", level=1) kpis = [ ["Visitors", "125,000", "+15%"], ["Conversions", "3,750", "+22%"], ["Revenue", "$187,500", "+18%"], ["CAC", "$45", "-8%"] ] report.add_table(kpis, headers=["Metric", "Value", "Change"])

Traffic Sources

report.add_heading("Traffic Sources", level=2) report.add_chart(traffic_df, "pie", values="Sessions", labels="Source", title="Traffic Distribution")

Conversion Funnel

report.add_heading("Conversion Funnel", level=2) report.add_chart(funnel_df, "bar", x="Stage", y="Users", title="Funnel Analysis", horizontal=True)

Trend Analysis

report.add_heading("Trends", level=2) report.add_chart(daily_df, "line", x="Date", y=["Visitors", "Conversions"], title="Daily Performance")

report.generate().save("marketing_dashboard.pdf")

Dependencies

reportlab>=4.0.0 Pillow>=10.0.0 pandas>=2.0.0 matplotlib>=3.7.0

Limitations

• Charts rendered as static images in PDF

• Complex layouts may need manual adjustment

• Large datasets may impact performance

• HTML output has basic styling (no interactive charts)