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EcoTrace

High-Precision Energy and Emissions Instrumentation


v1.5.0 β€” Hosted Cloud Integration & Real-Time Observatory Release. Features native CloudExporter, ecotrace login, 6,980+ CPU TDP database, and Python 3.14+ readiness.

EcoTrace is a lightweight library for granular carbon footprint measurement of Python applications. No configuration files, no background servicesβ€”just real-time hardware-level transparency.

Real-time monitoring | 50+ Global Zones | AI-powered insights | Zero-configuration


Official Website PyPI - Version Python 3.8+ License: MIT Downloads VS Code Extension


[!TIP] 🌐 Live Web Observatory: Stream and monitor your application carbon footprint in real-time on our hosted web platform at ecotracelibrary.com.

[!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 v1.5.0

Major Release. v1.5.0 introduces direct cloud telemetry streaming to ecotracelibrary.com, terminal authentication (ecotrace login), 6,980+ CPU TDP database coverage, Python 3.14+ compatibility, and WebSocket live streaming.

  • Hosted Cloud Observatory (CloudExporter) β€” Stream carbon metrics directly to your private web dashboard on ecotracelibrary.com using EcoTrace(api_key="eco_usr_...").
  • CLI Credential Management (ecotrace login) β€” Authenticate your terminal once via ecotrace login --key eco_usr_... so all ecotrace run profiling runs automatically stream to your web dashboard.
  • 6,980+ CPU TDP Database (%100 TDP Validity) β€” Expanded dataset from 1,806 to 6,983 unique CPU models, including +760% mobile/laptop CPU coverage (Intel 10th-14th Gen, Core Ultra, AMD Ryzen, Apple Silicon M1-M4).
  • Python 3.8 β†’ 3.14+ Compatibility β€” Fully verified runtime compatibility across Python 3.8, 3.9, 3.10, 3.11, 3.12, 3.13, and 3.14+.
  • WebSocket Real-Time Streaming β€” Instant live metric updates on your web dashboard via /api/ws/live.
  • Session Run Filtering β€” Filter web dashboard metrics by specific run_id / run_label execution sessions.

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 + Cloud Sync)

Authenticate your terminal once, then profile any script without changing source code:

# 1. Login with your ingestion key from https://ecotracelibrary.com
ecotrace login --key eco_usr_abc123...

# 2. Run your script β€” metrics automatically stream to your web dashboard!
ecotrace run my_script.py

Option 2: Programmatic Tracking & Cloud Dashboard

Decorate functions for granular instrumentation and stream metrics to your web account:

from ecotrace import EcoTrace

# Connects directly to your hosted account at https://ecotracelibrary.com
eco = EcoTrace(api_key="eco_usr_abc123...", 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 β€” 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@v1.5.0
  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 β€” preventing carbon-heavy code from being merged.


Why EcoTrace?

Feature EcoTrace v1.5 CodeCarbon CarbonTracker
Sampling Interval 50ms 15s Per Epoch
Isolation Process-scoped System-wide System-wide
Cloud Dashboard Sync Native No No
CPU Dataset 6,980+ CPUs Limited Limited
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 6,980+ 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


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 Β· SECURITY.MD


Author and License

Emre Ozkal β€” GitHub Β· ecotraceteam@gmail.com

MIT License β€” Use it however you like.

Developed for sustainable software development practices.