vamseeachanta Engineering Report Generator
Quick Start
import plotly.express as px
import pandas as pd
from pathlib import Path
from datetime import datetime
# Load data
df = pd.read_csv("../data/processed/results.csv")
# Create visualization
fig = px.line(df, x="date", y="value", title="Analysis Results")
# Generate HTML report
html = f"""<!DOCTYPE html>
<html>
<head><title>Engineering Report</title></head>
<body>
<h1>Analysis Report - {datetime.now().strftime('%Y-%m-%d')}</h1>
{fig.to_html(full_html=False, include_plotlyjs="cdn")}
</body>
</html>"""
Path("../reports/analysis.html").write_text(html)
print("Report generated: reports/analysis.html")
When to Use
- Creating analysis reports with charts and visualizations
- Building interactive dashboards from CSV/data sources
- Generating technical documentation with plots
- Producing client-deliverable HTML reports
- Summarizing engineering calculations with graphics
Report Structure
Standard Sections
- Header - Title, date, project info, version
- Executive Summary - Key findings and metrics at a glance
- Methodology - Analysis approach and assumptions
- Results - Data tables and interactive visualizations
- Discussion - Interpretation of results
- Conclusions - Summary and recommendations
- Appendix - Supporting data, references
Implementation Pattern
Basic Report Generation
import plotly.express as px
import plotly.graph_objects as go
from plotly.subplots import make_subplots
import pandas as pd
from pathlib import Path
from datetime import datetime
def generate_report(
data_path: str,
*See sub-skills for full details.*
### Visualization Patterns
```python
def create_visualizations(df: pd.DataFrame, chart_configs: list) -> list:
"""Create Plotly figures from configuration."""
figures = []
for config in chart_configs:
chart_type = config.get('type', 'line')
if chart_type == 'line':
fig = px.line(
*See sub-skills for full details.*
### HTML Template
```python
def build_html_report(title: str, sections: dict, figures: list) -> str:
"""Build complete HTML report."""
# Convert figures to HTML
chart_html = '\n'.join([
f'<div class="chart-container">{fig.to_html(full_html=False, include_plotlyjs="cdn")}</div>'
for fig in figures
])
*See sub-skills for full details.*
## Integration
### With YAML Workflow
```yaml
task: generate_report
input:
data_path: data/processed/results.csv
output:
report_path: reports/analysis.html
config:
title: "Analysis Report"
charts:
- type: line
x: time
y: value
With Data Pipeline
# Pipeline output -> Report input
pipeline_results = process_data(raw_data)
pipeline_results.to_csv('data/processed/results.csv')
generate_report(
data_path='data/processed/results.csv',
output_path='reports/analysis.html',
title='Pipeline Results'
)
Related Skills
- xlsx - Excel data handling
- pdf - PDF report generation
- data-pipeline-processor - Data preparation
- yaml-workflow-executor - Workflow automation
Version History
- 1.1.0 (2026-01-02): Upgraded to SKILL_TEMPLATE_v2 format with Quick Start, Error Handling, Metrics, Execution Checklist, additional examples
- 1.0.0 (2024-10-15): Initial release with Plotly visualizations, HTML templates, responsive design
Sub-Skills
- Example 1: Production Analysis Report (+2)
- Do (+4)
Sub-Skills
- Error Handling
- Execution Checklist
- Metrics