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Report Generator

$19

Build formatted reports from CSV, JSON, or SQLite data: filter, group, aggregate, sort, and render to Markdown, HTML, CSV, or JSON with summary stats and ASCII charts.

📁 11 files
JSONMarkdownPython

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📁 File Structure 11 files

report-generator/ ├── LICENSE ├── README.md ├── examples/ │ ├── report_generator_config.json │ └── sample_data.csv ├── free-sample.zip ├── guide/ │ ├── 01_features.md │ ├── 02_quick-start.md │ ├── 03_output.md │ └── 04_license.md ├── index.html └── src/ └── report_generator.py

📖 Documentation Preview README excerpt

Report Generator

Build formatted reports from tabular data (CSV, JSON, SQLite). Filter, group, aggregate, sort, and render to Markdown, HTML, CSV, or JSON — all with Python stdlib, no external dependencies. Includes summary statistics and inline ASCII bar charts for group aggregates.

Features

  • Multi-source input — CSV files, JSON files (flat or nested), SQLite databases
  • Row filtering — Keep rows matching conditions (eq, ne, gt, lt, gte, lte, contains, regex, in, not_null, is_null)
  • Computed columns — Add derived fields via arithmetic expressions or string templates
  • Group-by aggregation — Group by one or more fields with count, sum, avg, min, max
  • Sorting — Sort results by any column, ascending or descending
  • Multiple output formats — Markdown tables, self-contained styled HTML, CSV, JSON
  • Summary statistics — Automatic count, sum, avg, min, max, stdev for every numeric column
  • ASCII bar charts — Inline horizontal bar charts for each aggregate metric
  • JSON report definitions — Declare complete reports in a config file for repeatable generation
  • Automatic type coercion — CSV string values are converted to int/float when possible

Requirements

  • Python 3.10+
  • No external dependencies (stdlib only)

Quick Start


# Simple detail report from CSV
python src/report_generator.py --source examples/sample_data.csv --format markdown

# Group by department with aggregated metrics
python src/report_generator.py --source examples/sample_data.csv \
    --group-by department \
    --metrics "revenue:sum,revenue:avg,deals_closed:sum,satisfaction:avg" \
    --sort "revenue_sum:desc" \
    --title "Department Summary"

# Full report from a JSON config file
python src/report_generator.py --config examples/report_generator_config.json

# HTML report written to a file
python src/report_generator.py --source examples/sample_data.csv \
    --group-by department --metrics "revenue:sum" \
    --format html --output department_report.html

# Filter rows before aggregating
python src/report_generator.py --source examples/sample_data.csv \
    --filter "region:eq:North" \
    --group-by department --metrics "revenue:sum"

Configuration Reference

CLI Options

FlagShortDefaultDescription
--source-s—Source data file (CSV, JSON, or SQLite)
--format-fmarkdownOutput format: markdown, md, html, csv, json
--group-by-g—Comma-separated fields to group by
--metrics-m—Metric specs: field:agg (e.g. revenue:sum,hours:avg)
--output-ostdoutOutput file path

... continues with setup instructions, usage examples, and more.

📄 Code Sample .py preview

src/report_generator.py #!/usr/bin/env python3 """ Report Generator — Automation Hub (DataNest) Build formatted reports from tabular data (CSV, JSON, SQLite). Supports filtering, group-by with aggregations (count/sum/avg/min/max), sorting, computed columns, and rendering to Markdown, HTML, CSV, or JSON. Includes summary statistics and inline ASCII bar charts for group aggregates. Usage: python report_generator.py --source data.csv --format markdown python report_generator.py --source sales.csv --group-by region --metrics "revenue:sum" python report_generator.py --config examples/report_generator_config.json python report_generator.py --source data.json --format html --output report.html Dependencies: Python 3.10+ stdlib only (no pip packages) License: MIT """ from __future__ import annotations import argparse import csv import io import json import logging import re import sqlite3 import textwrap import time from collections import defaultdict from dataclasses import dataclass, field from datetime import datetime, timezone from html import escape as html_escape from pathlib import Path from typing import Any # --------------------------------------------------------------------------- # Constants # --------------------------------------------------------------------------- LOG_FORMAT = "%(asctime)s [%(levelname)s] %(name)s: %(message)s" CHART_BAR_CHAR = "\u2588" # full-block character: █ CHART_MAX_WIDTH = 36 VERSION = "1.0.0" logger = logging.getLogger("report_generator") # --------------------------------------------------------------------------- # ... 849 more lines ...
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