EcoTrace
High-Precision Energy and Emissions Instrumentation
v1.5.0 — Hosted Cloud Integration & Real-Time Observatory. Native CloudExporter, terminal authentication (ecotrace login), 6,980+ CPU TDP database, Python 3.14+ readiness, WebSocket live streaming, and session run filtering.
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] 🌐 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.
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) — Stream carbon metrics directly to your private web dashboard on ecotracelibrary.com usingEcoTrace(api_key="eco_usr_..."). - 🔑 CLI Credential Management (
ecotrace login) — Authenticate your terminal once viaecotrace login --key eco_usr_...so allecotrace runprofiling runs automatically stream to your web dashboard. - ⚡ 6,980+ CPU TDP Database (%100 TDP Validity) — 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 → 3.14+ Compatibility — 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 — Instant live metric updates on your web dashboard via
/api/ws/live. - 🏷️ Session Run Filtering — Filter web dashboard metrics by specific
run_id/run_labelexecution sessions. - ⏸️ Pausing API — Temporarily disable carbon tracking using
EcoTrace.pause()andEcoTrace.resume(). - 📊 Run Comparisons (
ecotrace diff) — Perform side-by-side carbon and duration comparisons between runs.
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 — 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 — 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 — 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
Full documentation is available at ecotracelibrary.com and ecotrace.readthedocs.io.
- Official Website — Live carbon dashboard and web management platform.
- Architecture and Science — How the energy model and process isolation work.
- Advanced Usage — GPU tracking, AI insights, benchmarks, and comparison tables.
- API Reference — Technical documentation for core classes and functions.
- Support and Reference — Troubleshooting, region codes, and hardware compatibility.
Contributing
We welcome contributions! Please see our CONTRIBUTING.MD for guidelines on reporting bugs, suggesting features, or contributing hardware data.
Community
Author and License
Emre Ozkal — GitHub · ecotraceteam@gmail.com
MIT License — Use it however you like.
Developed for sustainable software development practices.
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