Reporting Use Case
Examples of using gtext for dynamic report generation.
Daily Status Report
# Daily Status Report
**Date**: ```include
cli: date +"%Y-%m-%d"
```
## Git Activity
```include
cli: git log --since="24 hours ago" --pretty=format:"- %h %s" --no-merges
```
## Test Results
```include
cli: pytest --tb=no -q
```
## Code Coverage
```include
cli: pytest --cov --cov-report=term-missing | tail -20
```
Weekly Summary
# Weekly Summary
**Week**: ```include
cli: date +"%Y-W%V"
```
## Commits This Week
```include
cli: git log --since="1 week ago" --oneline | wc -l
``` commits
## Top Contributors
```include
cli: git shortlog -sn --since="1 week ago" | head -5
```
## Files Changed
```include
cli: git diff --stat HEAD~7..HEAD
```
System Monitoring
# System Status
**Generated**: ```include
cli: date
```
## Disk Usage
```include
cli: df -h
```
## Memory Usage
```include
cli: free -h
```
## Top Processes
```include
cli: ps aux --sort=-%mem | head -10
```
Database Report
Script (scripts/db_stats.py):
#!/usr/bin/env python3
import sqlite3
conn = sqlite3.connect("app.db")
cursor = conn.cursor()
# Table stats
cursor.execute("""
SELECT name, COUNT(*) as count
FROM sqlite_master
WHERE type='table'
""")
print("## Tables\n")
for name, count in cursor.fetchall():
cursor.execute(f"SELECT COUNT(*) FROM {name}")
rows = cursor.fetchone()[0]
print(f"- **{name}**: {rows} rows")
Report (db-report.md.gtext):
Sales Dashboard
# Sales Dashboard
**Period**: ```include
cli: date +"%B %Y"
```
## Total Sales
```include
cli: python scripts/sales_total.py --month current
```
## Top Products
```include
cli: python scripts/top_products.py --limit 10 --format markdown
```
## Regional Breakdown
```include
cli: python scripts/sales_by_region.py --format table
```
CI/CD Pipeline Report
# Pipeline Status
**Build**: ```include
cli: cat .build-number
```
## Test Results
```include
cli: cat test-results.txt
```
## Deployment Status
```include
cli: kubectl get pods -n production
```
## Recent Releases
```include
cli: git tag --sort=-creatordate | head -5
```
Performance Report
# Performance Metrics
## Load Times
```include
cli: python scripts/measure_load_times.py
```
## Response Times
```include
cli: python scripts/analyze_logs.py --metric response-time
```
## Error Rates
```include
cli: python scripts/error_rate.py --last 24h
```