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EcoTrace: High-precision carbon tracking engine for production Python. Function-level CPU/GPU emission measurement with 50ms continuous sampling, Boavizta TDP database, and audit-ready PDF reporting.

Project description

EcoTrace Logo

EcoTrace

High-Precision Energy and Emissions Instrumentation


v1.1.2 — Production/Stable Release. Features OpenTelemetry export, Django/Celery integration, and critical stability improvements.

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


PyPI - Version Python 3.9+ License: MIT Downloads Documentation Status VS Code Extension


[!TIP] VS Code Extension: Monitor application carbon footprint in real-time during development. Download here.


EcoTrace Demo

Function-level carbon measurement with real-time monitoring


Core Features in v1.1.2

Enterprise-Grade Monitoring & Export. v1.1.2 adds OpenTelemetry export for cloud platforms, framework integrations, and critical stability enhancements.

  • OpenTelemetry Exporter — Export carbon metrics to Grafana, Datadog, New Relic, and Prometheus without blocking your application.
  • Django & Celery Middleware — WSGI/ASGI request tracking and Celery task-level carbon measurement with response headers and worker signal cleanup.
  • Session Management — Class-level atexit handlers with WeakSet instances prevent memory leaks on repeated module reloads.
  • Exception Transparency — User exceptions now properly propagate after measurement teardown; measurement errors no longer mask failures.
  • Platform Reliability — PowerShell Get-CimInstance (Windows) and dmidecode with sudo fallback (Linux) for robust RAM detection.
  • Critical Fixes — Gemini lazy-loading, cached CPU info reuse, USER_AGENT fallbacks, and version checker robustness. See CHANGELOG.md.

Quick Install

pip install ecotrace

Optional extras:

pip install ecotrace[gpu]   # NVIDIA GPU support
pip install ecotrace[ai]    # Gemini AI insights
pip install ecotrace[all]   # Everything

Quick Start

Option 1: Zero-Code Profiling (CLI)

Measure any script without changing a single line of code:

ecotrace run my_script.py

Option 2: Programmatic Tracking (Library)

Decorate functions for granular instrumentation:

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")

Option 3: Carbon Budget Mode

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")

Expected Output

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)
=======================================================

CI/CD Integration

Official GitHub Action

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@core-v1.1.2
  with:
    budget: '10.0'
    region: 'US'

Manual CLI Integration

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.


Why EcoTrace?

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).

Documentation

Full documentation is available at ecotrace.readthedocs.io.


Contributing

We welcome contributions! Please see our CONTRIBUTING.MD for guidelines on reporting bugs, suggesting features, or contributing hardware data.


Community

Join Discord

CHANGELOG.md · SECURITY.MD


Author and License

Emre OzkalGitHub · ecotraceteam@gmail.com

MIT License — Use it however you like.

Developed for sustainable software development practices.

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