Absolutely — I’ll do both parts: a clean README you can use as-is, and honest advice about GitHub value and positioning.

Activity Timeline Analyzer (V2)

A command-line utility for analyzing timestamped event logs and producing time-based activity summaries.

This tool was built as a foundational analytics utility and learning project, focusing on schema-first design, separation of concerns, and incremental feature development.

Features

* Parses structured JSON event logs
* Validates input schema before processing
* Sorts events chronologically
* Aggregates activity by hour
* Optional per-user and per-hour breakdowns
* Console output with selectable modes
* Export results to:
    * **JSON**
    * **CSV**
* Clean separation between:
    * Data loading
    * Analysis
    * Output formatting

Input Format

The tool expects a JSON file containing a list of events with the following schema:

{
  "timestamp": "2025-01-01T09:15:00",
  "user": "alice",
  "status": "success"
}

• timestamp must be ISO-8601 formatted
• status is treated as categorical (no assumption of boolean)

🛠 Usage

Basic analysis (console output)

python activity_timeline_analyzer_v2_export.py \
  --input events.json

Per-hour summary (console)

python activity_timeline_analyzer_v2_export.py \
  --input events.json \
  --mode hour

Export to JSON

python activity_timeline_analyzer_v2_export.py \
  --input events.json \
  --output report.json \
  --format json

Export to CSV (events per hour)

python activity_timeline_analyzer_v2_export.py \
  --input events.json \
  --mode hour \
  --output report.csv \
  --format csv

Output

### JSON
    * Structured, machine-readable output
    * Includes per-hour counts (and additional breakdowns when enabled)
### CSV
    * Tabular export of **events per hour**
    * Designed for spreadsheets and reporting tools

Design Goals

This project intentionally prioritizes: * Clear schema contracts * Predictable data flow * Minimal side effects * Easy extensibility

It is designed to be adapted, not treated as a finished product.

Limitations

* CSV export currently supports hourly aggregation only
* No real-time ingestion (file-based input)
* No visualization layer
* Designed for batch analysis, not streaming

These are deliberate trade-offs to keep the core logic simple and robust.

Possible Extensions

* Per-user CSV export
* Time-window filtering
* Threshold alerts
* Exit codes for monitoring pipelines
* Integration with log collectors or schedulers

License

MIT License

About This Project

This tool was built as part of an ongoing learning journey in Python, data processing, and AI-assisted development. It reflects a focus on building reliable foundations before adding complexity.

Author

Darren Williamson Python Utility Development * Automation * Data Analysis Uk Citizen / Spain-based / Remote LinkedIn: https://www.linkedin.com/in/darren-williamson3/