SQL Report Generator

Problem

SQL query results and single charts often sit in scripts, notebooks, terminals, and temporary docs. When a result needs to be shared with stakeholders, the analyst still has to assemble KPI notes, detail tables, filters, anomaly checks, and operational recommendations. Manually stitching HTML or Markdown can miss metric definitions and make reports hard to reproduce.

How It Works

SQL Report Generator is aimed at scenarios where SQL results or sql-dataviz charts already exist. It organizes data into reports using components such as Table, Matrix, Slicer, Button Navigator, text boxes, paginated reports, and ReportBuilder. A typical workflow is to prepare a DataFrame or query result, choose table, matrix, or slicer components, then use the report builder to assemble pages and export HTML, JSON, or PDF. It also includes a statistics-only ai_insights.py module that generates structured insights from data using methods such as Z-score, IQR, linear regression, Pearson correlation, Pareto analysis, distribution checks, and seasonality detection, with Markdown, HTML, or JSON output.

Boundaries

With dependencies installed, the full component set and export options are available; without dependencies, it can only provide structure suggestions, template recommendations, and presentation guidance. For real data, insights must come from statistical analysis rather than hand-written conclusions. Before delivering HTML or PDF, check chart rendering, Chinese text rendering, KPI/table consistency, interaction states, and placeholder leakage.