QObserva

Quantum program observability and benchmarking. Local-first, security-first observability for quantum computing.

⚠️ Beta: QObserva is currently in beta. APIs may change.

Quick Start

Prerequisites

• Python 3.10+ (see Python Version Compatibility for SDK-specific requirements)
• No Node.js needed: the dashboard is prebuilt and included

Recommendation: For best compatibility with all SDKs, use Python 3.12.

Installation

From PyPI (recommended):

pip install qobserva

For SDK adapters, install the agent with extras:

pip install qobserva-agent[qiskit]      # Qiskit
pip install qobserva-agent[all-sdks]    # All supported SDKs

From source (development):

git clone https://github.com/BuildersArk/qobserva.git
cd qobserva
pip install -e packages/qobserva_agent
pip install -e packages/qobserva_collector
pip install -e packages/qobserva_local
pip install -e packages/qobserva
# One-time: cd packages/qobserva_ui_react && npm install

Start QObserva

qobserva up

Dashboard opens at http://localhost:3000

Stop QObserva

qobserva down

What is QObserva?

QObserva provides standardized telemetry, metrics, and visualizations for quantum program executions across all major Python quantum SDKs.

Features

• Decorator-first instrumentation: @observe_run() decorator with a simple API
• Multi-SDK support: Qiskit, Braket, Cirq, PennyLane, pyQuil, D-Wave (all tested)
• Professional React dashboard: Modern dark-themed UI with diverse visualizations
  • Home dashboard with KPIs, trends, and run tables
  • Analytics dashboard with performance metrics and comparisons
  • Algorithm analytics for cross-SDK algorithm comparison
  • Run details with comprehensive quantum metrics
  • Compare runs side-by-side, search and filter, PDF report generation
• Local-first: Everything runs locally, no cloud required
• Standardized schema: Common event format across all SDKs
• One-command setup: qobserva up starts collector and dashboard
• Energy metrics: D-Wave optimization metrics (energy, approximation ratio)
• Comprehensive metrics: Entropy, top-K dominance, shot efficiency, runtime analysis

Usage

Instrument Your Code

Always include the sdk tag for reliable adapter selection.

from qobserva import observe_run

@observe_run(
    project="my_project",
    tags={
        "sdk": "qiskit",       # Required
        "algorithm": "vqe"     # Optional but recommended
    },
    benchmark_id="vqe_h2_ground_state",
    benchmark_params={"energy": -1.137, "convergence_iterations": 10}
)
def my_quantum_algorithm():
    # Your quantum code here
    return execute_quantum_circuit()

Supported SDK values: "qiskit", "braket", "cirq", "pennylane", "pyquil", "dwave"

Add an "algorithm" tag (e.g. "vqe", "grover", "qaoa") to enable algorithm-specific dashboards and cross-SDK comparison.

View Dashboard

Open http://localhost:3000 for:

• Home: Real-time run metrics, KPIs, success rate trends
• Analytics: Performance analysis and trends
• Algorithms: Algorithm-specific metrics and cross-SDK comparison (with algorithm tags)
• Compare: Side-by-side run comparison, search and filter

Architecture

• qobserva-agent: Telemetry agent with decorators and adapters for all major quantum SDKs
• qobserva-collector: FastAPI service for ingestion, validation, and storage
• qobserva-local: One-command orchestrator for the local stack (includes React dashboard)
• qobserva: This meta-package and CLI (qobserva up / qobserva down)

The React dashboard is part of the local stack and runs automatically when you run qobserva up.

SDK Support

pip install qobserva-agent[all-sdks]

# Or individual SDKs
pip install qobserva-agent[qiskit]
pip install qobserva-agent[braket]
pip install qobserva-agent[cirq]
pip install qobserva-agent[pennylane]
pip install qobserva-agent[pyquil]
pip install qobserva-agent[dwave]

Python Version Compatibility

Verified by running each SDK's example on Python 3.12, 3.13 and 3.14 (September 2026):

SDK	3.12	3.13	3.14
Qiskit	✅	✅	✅
Braket	✅	✅	✅
Cirq	✅	✅	✅
PennyLane	✅	✅	✅
pyQuil	✅	❌	❌
D-Wave	✅	✅	✅

Recommendations: Use Python 3.12 for all 6 SDKs. pyQuil itself supports only Python 3.11–3.12; every other SDK also runs on 3.13 and 3.14.

Project, Provider, and Backend

• Project: From @observe_run(project="...") — user-defined, for grouping runs.
• Provider: Extracted from the result (e.g. ibm, aws_braket, local_sim), or unknown when the result doesn't say.
• Backend: Extracted from the result (e.g. ibm_brisbane, aer_simulator), or unknown.
• When the SDK result doesn't identify its backend (e.g. Qiskit V2 primitives), pass it: @observe_run(..., backend=AerSimulator()) or backend="statevector_sampler", provider="local_sim".

Filter by these in the dashboard to compare providers and backends. Always set tags={"sdk": "..."} so adapter selection is correct.

Documentation

• Getting Started
• Testing Guide
• API Reference
• SDK Compatibility
• Troubleshooting

Links

• Website: qobserva.com
• Documentation: qobserva.com/docs.html
• GitHub: github.com/BuildersArk/qobserva
• Issues: github.com/BuildersArk/qobserva/issues

Reporting Issues / Getting Help

If you encounter bugs, have questions, or would like to request features for the qobserva CLI / meta-package, please open an issue on GitHub:

• https://github.com/BuildersArk/qobserva/issues

License

The qobserva meta-package and CLI are provided under the QObserva Community License v1.0 (source-available). See the LICENSE file in this package for full terms. Commercial hosting, distribution of modified versions, or commercial products based on QObserva require a separate license from BuildersArk LLC.