Show HN: EcoTrace – Lightweight carbon footprint and energy tracker for Python

EcoTrace v1.4.0, a lightweight Python library for real-time carbon footprint tracking of applications, has been released with new features including a pausable tracking API, WebhookExporter for streaming emissions data to Slack or Discord, side-by-side CLI diff comparisons, filtered CSV exporting, and log maintenance commands, all with zero new mandatory dependencies. The tool provides function-level carbon measurement, hardware detection, and optional GPU and AI insights support, enabling developers to monitor and enforce carbon budgets during development and CI/CD pipelines.

v1.4.0 — Feature Release. Pausable tracking API, WebhookExporter, side-by-side CLI diff comparison, filtered CSV exporting, and log maintenance commands — all with zero new mandatory dependencies. EcoTrace is a lightweight library for granular carbon footprint measurement of Python applications. No configuration files, no background services—just real-time hardware-level transparency. Real-time monitoring | 50+ Global Zones | AI-powered insights | Zero-configuration TIP VS Code Extension:Monitor application carbon footprint in real-time during development. Download here . Function-level carbon measurement with real-time monitoring Feature Release.v1.4.0 adds pausable tracking, side-by-side run comparisons, webhook integrations, filtered CSV exporting, and log rotation capabilities. Pausing API — Temporarily disable carbon tracking using EcoTrace.pause and EcoTrace.resume to exclude setup and teardown overhead. Run Comparisons — Perform side-by-side carbon and execution duration comparisons between two specific runs. ecotrace diff Webhook Integration — Stream carbon emissions data to Slack, Teams, Discord, or a custom API in real-time. WebhookExporter Filtered CSV Exporting — Export filtered subsets of measurement logs with --csv format and --run / --func filters. Log Maintenance Commands — Rotate and trim logs via ecotrace clean , and permanently delete logs using ecotrace reset . Multi-Run History — Every session gets a unique RunID . Use ecotrace history to compare runs and ecotrace trends for an ASCII carbon trend chart.— Programmatic access to all session metrics as a typed dict. Ideal for notebooks, dashboards, and CI assertions. get summary API pip install ecotrace Optional extras: pip install ecotrace gpu NVIDIA GPU support pip install ecotrace ai Gemini AI insights pip install ecotrace all Everything Measure any script without changing a single line of code: ecotrace run my script.py Decorate functions for granular instrumentation: python from ecotrace import EcoTrace eco = EcoTrace region code="US" @eco.track def my function : Your heavy processing here pass my function Export audit-ready reports or check cumulative totals eco.generate pdf report "carbon audit.pdf" print f"Total Carbon Emitted: {eco.total carbon} gCO2" Set a limit and let EcoTrace enforce it: eco = EcoTrace region code="TR", carbon limit=5.0, 5 gCO2 budget on budget exceeded=lambda t, l: print f"Budget exceeded: {t:.4f}/{l:.4f} gCO2" @eco.track def training pipeline : ... training pipeline print f"Remaining budget: {eco.remaining budget} gCO2" When initialized, EcoTrace performs automated hardware detection: EcoTrace INFO: INFO EcoTrace instrumentation session initialized STATIC . EcoTrace INFO: ----------------------------------------------------- EcoTrace INFO: Region : TR 475 gCO2/kWh EcoTrace INFO: Hardware Logic: 13th Gen Intel Core i7-13700H EcoTrace INFO: Specifications: 20 Cores | 45.0W TDP EcoTrace INFO: Energy Sensor : Boavizta Advanced Estimation EcoTrace INFO: Memory Config : 15.6 GB DDR4 EcoTrace INFO: GPU Accelerator: Intel Iris Xe Graphics 15.0W TDP EcoTrace INFO: ----------------------------------------------------- At process exit, a session summary is printed automatically: ======================================================= EcoTrace — Session Summary ======================================================= Duration : 12.34s Functions : 5 tracked Total Carbon : 0.00312000 gCO2 Region : TR 475 gCO2/kWh Budget : 0.003120 / 5.000000 gCO2 0.1% OK Equivalent : 0.4 min of LED bulb 10W ======================================================= Enforce carbon budgets in your pipeline with our official GitHub Action. Add this to your .github/workflows/ci.yml : - name: EcoTrace Carbon Gate uses: Zwony/ecotrace@v1.3.0 with: budget: '10.0' region: 'US' You can also run the gate manually: ecotrace gate --budget 10.0 If total emissions exceed the budget, the gate fails with exit code 1 — preventing carbon-heavy code from being merged. | Feature | EcoTrace v1.0 | CodeCarbon | CarbonTracker | |---|---|---|---| Sampling Interval | 50ms | 15s | Per Epoch | Isolation | Process-scoped | System-wide | System-wide | Budget Enforcement | Built-in | No | No | CI/CD Gate | Built-in | No | No | Idle Noise Subtraction | Automatic | No | No | Async Support | Native | Limited | No | Deep Transparency: Derived from verified manufacturer TDP specifications rather than category averages. Fail-Safe Architecture: Guaranteed application continuity even if hardware drivers or API keys are missing. Actionable AI: Integrates with Google Gemini to provide specific code optimization advice optional . Full documentation is available at ecotrace.readthedocs.io https://ecotrace.readthedocs.io/en/latest/ . — How the energy model and process isolation work. Architecture and Science — GPU tracking, AI insights, benchmarks, and comparison tables. Advanced Usage — Technical documentation for core classes and functions. API Reference — Troubleshooting, region codes, and hardware compatibility. Support and Reference We welcome contributions Please see our CONTRIBUTING.MD /Zwony/ecotrace/blob/main/CONTRIBUTING.MD for guidelines on reporting bugs, suggesting features, or contributing hardware data. Emre Ozkal — GitHub https://github.com/Zwony · ecotraceteam@gmail.com mailto:ecotraceteam@gmail.com MIT License — Use it however you like. Developed for sustainable software development practices.