quapp-common 0.0.12.dev3

Quapp common library supporting Quapp Platform for Quantum Computing

quapp-common

Quapp common library supporting Quapp Platform for Quantum Computing.

Overview

quapp-common is a Python library designed to support the Quapp Platform for Quantum Computing by providing common utilities, configurations, and abstractions for working with quantum providers and devices. Recent improvements add first-class asynchronous job processing with a cross-process JobManager, background task execution, and standardized result models for immediate client responses while work continues in the background. Version 0.0.12.dev1 introduces multi-language SDK support, enabling dispatching quantum tasks to non-Python runtimes (e.g., JavaScript) via subprocess with circuit adaptation and result serialization. Version 0.0.12.dev2 fixes the JavaScript handler runner path in SubprocessDispatcher so that the subprocess command resolves correctly.

Features

• Provider and device factory for quantum computing platforms.
• Logging and configuration utilities with improved and detailed log messages.
• Support for AWS Braket, OQC Cloud, Qiskit, PennyLane, DWave Ocean, and Quapp quantum simulators.
• Refactored classes and utilities to remove tenant-specific request, response, and promise classes.
• Standardized naming by renaming ProjectHeader to CustomHeader.
• Enhanced error handling and job metadata update mechanisms.
• Simplified and cleaner HTTP request/response logging and URL parsing utilities.
• Asynchronous job processing:
  • AsyncInvocationTask to run handlers in a background thread pool and return immediate responses.
  • JobManager for cross-process job registry with atomic add/update/get and pub-sub updates.
  • Standard Event/Result (Success, Error) models for consistent async responses.
  • Scheduler integration via callback URL; local updates are patched to the scheduler.
  • Safety: updates to jobs already DONE/FAILED are ignored to prevent post-completion mutations.
• Multi-language SDK support (v0.0.12.dev1):
  • Language enum for validating and resolving Python/JavaScript runtimes.
  • SubprocessDispatcher to delegate tasks to non-Python runtimes via subprocess with timeout management and JSON payload processing.
  • SubprocessBridge integrating dispatcher, circuit adapter, and result serializer for seamless JS-Python handler interaction.
  • CircuitAdapter for converting JS subprocess circuit outputs into native SDK formats (OpenQASM, QUBO, JSON) across Qiskit, Braket, PennyLane, etc.
  • ResultSerializer for converting complex job results into JSON-serializable dictionaries for subprocess communication.

Installation

Install via pip:

pip install quapp-common

Notes:

• From version 0.0.11.dev7, starlette is a direct dependency to support background execution helpers.
• From version 0.0.12.dev1, qibo and dimod are added as dependencies to support Qibo and D-Wave Ocean SDK integrations.

Recently Changes Highlights

v0.0.12.dev2

• Version bumps to 0.0.12.dev2.
• Fix: correct JavaScript handler runner path in SubprocessDispatcher.RUNNER_MAP — removed the erroneous function/ directory prefix so the subprocess command resolves to handler_runner.js relative to the working directory.

v0.0.12.dev1

• Version bump to 0.0.12.dev1 and dependency update (add qibo, dimod).
• Introduce multi-language SDK support primitives:
  • Language enum for validating and resolving Python/JavaScript runtimes.
  • SubprocessDispatcher for delegating tasks to non-Python runtimes via subprocess with runner configuration and timeout management.
  • SubprocessBridge integrating dispatcher, circuit adapter, and result serializer for JS-Python handler interaction.
  • CircuitAdapter for converting JS subprocess circuit outputs into native SDK formats (OpenQASM, QUBO, JSON) across Qiskit, Braket, PennyLane, etc.
  • ResultSerializer for converting complex job results (numpy, complex numbers, Enums, datetime) into JSON-serializable dictionaries.

v0.0.11.dev7 – v0.0.11.dev10

• Version bump to 0.0.11.dev7 and dependency update (add starlette).
• Introduce asynchronous job processing primitives:
  • AsyncInvocationTask for background execution with immediate client response.
  • Event and standardized Result models (Success, Error).
• Introduce JobManager for cross-process job management and update publication.
• Integrate JobManager into Request to register jobs and carry scheduler callback URL.
• Modularize update_job_metadata with clearer helpers; patch scheduler on local state changes.
• Fix: ignore updates for jobs that are already DONE or FAILED.
• Improve logging and error handling (use full tracebacks, cleaner logs).

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For detailed usage and API references, please refer to the in-code documentation or contact the maintainers.