Metadata-Version: 2.4
Name: quickreport
Version: 0.1.0
Summary: Instantly turn any CSV into a beautiful, shareable HTML report with charts and statistics.
License: MIT
Project-URL: Homepage, https://github.com/yourusername/quickreport
Project-URL: Issues, https://github.com/yourusername/quickreport/issues
Keywords: csv,report,html,data,visualization,cli
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Topic :: Scientific/Engineering :: Visualization
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE
Provides-Extra: dev
Requires-Dist: pytest>=7.0; extra == "dev"
Dynamic: license-file

# 📊 quickreport

> Instantly turn any CSV into a beautiful, shareable HTML report — with charts, statistics, and data preview. Zero dependencies.

[![Python 3.8+](https://img.shields.io/badge/python-3.8+-blue.svg)](https://www.python.org/)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](LICENSE)

---

## 🤔 Why quickreport?

You have a CSV. You want to share insights with someone who doesn't know pandas. `quickreport` generates a single self-contained HTML file you can email, share, or open in any browser.

```bash
quickreport sales.csv
# ✅ Report generated: sales_report.html
# 📊 500 rows × 8 columns
# 🌐 Opening in browser...
```

---

## 📦 Installation

```bash
pip install quickreport
```

---

## 🚀 Usage

### CLI
```bash
quickreport data.csv                     # auto-opens report in browser
quickreport data.csv report.html         # custom output filename
quickreport data.csv --no-open           # don't auto-open browser
```

### Library
```python
from quickreport import Report, generate

# Full control
r = Report("sales.csv")
print(r.rows)       # 500
print(r.columns)    # 8
print(r.summary)    # dict of key stats
r.generate("report.html")

# One-liner
generate("sales.csv", "report.html")

# Get HTML as string (for web apps, email, etc.)
html = r.to_html()
```

---

## 📋 What's in the report

- **Summary bar** — rows, columns, missing values, duplicate rows, file size
- **Per-column cards** with:
  - Numeric columns → min, max, mean, median, null count + bar chart
  - Text columns → unique count, null count, top 5 most common values
- **Data preview** — first 10 rows in a clean table
- **Single HTML file** — no internet needed, share it anywhere

---

## 🆚 quickreport vs pandas-profiling

| Feature | quickreport | pandas-profiling |
|---|---|---|
| Zero dependencies | ✅ | ❌ (pandas, scipy, ...) |
| Install size | tiny | ~500MB |
| Speed on large files | ✅ Fast | ⚠️ Slow |
| Output | Single HTML | Single HTML |
| Charts | ✅ Built-in | ✅ |
| Beginner-friendly | ✅ | ⚠️ |

---

## 🧪 Running Tests

```bash
pip install pytest
pytest tests/ -v
```

---

## 📄 License

MIT — free to use in personal and commercial projects.
