Skip to main content

A Python toolkit for cross-framework abstraction of quantum programs.

Project description

qbraid-sdk-header

CI codecov Documentation Status PyPI version Downloads License Discord

The qBraid-SDK is a Python toolkit for cross-framework abstraction, transpilation, and execution of quantum programs.

Features

  • Unified quantum frontend interface. Transpile quantum circuits between supported packages. Leverage the capabilities of multiple frontends through simple, consistent protocols.
  • Build once, target many. Create quantum programs using your preferred circuit-building package, and execute on any backend that interfaces with a supported frontend.
  • Benchmark, compare, interpret results. Built-in compatible post-processing enables comparing results between runs and across backends.

Installation & Setup

qbraid-sdk-env

For the best experience, install the qBraid-SDK environment on lab.qbraid.com. Login (or create an account) and follow the steps to install an environment.

Using the SDK on qBraid Lab means direct, pre-configured access to all Amazon Braket supported devices with no additional access keys or API tokens required. See qBraid Quantum Jobs for more.

Local install

The qBraid-SDK, and all of its dependencies, can also be installed using pip:

pip install qbraid

If using locally, follow linked instructions to configure your qBraid, AWS, and IBMQ credentials.

Documentation & Tutorials

qBraid documentation is available at docs.qbraid.com.

See also:

Quickstart

Transpiler

Construct a quantum program of any supported program type,

>>> from qbraid import QPROGRAM_LIBS
>>> QPROGRAM_LIBS
['braket', 'cirq', 'qiskit', 'pyquil', 'pytket', 'qasm2', 'qasm3']

and use the circuit_wrapper() to convert to any other supported program type:

>>> from qbraid import circuit_wrapper
>>> from qbraid.interface import random_circuit
>>> qiskit_circuit = random_circuit("qiskit")
>>> cirq_circuit = circuit_wrapper(qiskit_circuit).transpile("cirq")
>>> print(qiskit_circuit)
          ┌────────────┐
q_0: ──■──┤ Rx(3.0353) 
     ┌─┴─┐└───┬────┬───┘
q_1:  H ├────┤ X ├────
     └───┘    └────┘
>>> print(cirq_circuit)
0: ───H───X^0.5────────
      
1: ───@───Rx(0.966π)───

Devices & Jobs

Search for quantum backend(s) on which to execute your program.

>>> from qbraid import get_devices
>>> get_devices()
Device status updated 0 minutes ago

Device ID                           Status
---------                           ------
aws_oqc_lucy                        ONLINE
aws_rigetti_aspen_m2                OFFLINE
aws_rigetti_aspen_m3                ONLINE
ibm_q_perth                         ONLINE
...

Apply the device_wrapper(), and send quantum jobs to any supported backend, from any supported program type:

>>> from qbraid import device_wrapper, get_jobs
>>> aws_device = device_wrapper("aws_oqc_lucy")
>>> ibm_device = device_wrapper("ibm_q_perth")
>>> aws_job = aws_device.run(qiskit_circuit, shots=1000)
>>> ibm_job = ibm_device.run(cirq_circuit, shots=1000)
>>> get_jobs()
Displaying 2 most recent jobs:

Job ID                                              Submitted                  Status
------                                              ---------                  ------
aws_oqc_lucy-exampleuser-qjob-zzzzzzz...            2023-05-21T21:13:47.220Z   QUEUED
ibm_q_perth-exampleuser-qjob-xxxxxxx...             2023-05-21T21:13:48.220Z   RUNNING
...

Compare results in a consistent, unified format:

>>> aws_result = aws_job.result()
>>> ibm_result = ibm_job.result()
>>> aws_result.measurement_counts()
{'00': 483, '01': 14, '10': 486, '11': 17}
>>> ibm_result.measurement_counts()
{'00': 496, '01': 12, '10': 479, '11': 13}

Local account setup

api_key

To use the qBraid-SDK locally (outside of qBraid Lab), you must add your account credentials:

  1. Create a qBraid account or log in to your existing account by visiting account.qbraid.com

  2. Copy your API Key token from the left side of your account page:

  3. Save your API key from step 2 by calling QbraidSession.save_config():

from qbraid.api import QbraidSession

session = QbraidSession(api_key='API_KEY')
session.save_config()

The command above stores your credentials locally in a configuration file ~/.qbraid/qbraidrc, where ~ corresponds to your home ($HOME) directory. Once saved, you can then connect to the qBraid API and leverage functions such as get_devices() and get_jobs().

Load Account from Environment Variables

Alternatively, the qBraid-SDK can discover credentials from environment variables:

export JUPYTERHUB_USER='USER_EMAIL'
export QBRAID_API_KEY='QBRAID_API_KEY'

Then instantiate the session without any arguments

from qbraid.api import QbraidSession

session = QbraidSession()

Launch on qBraid

The "Launch on qBraid" button (below) can be added to any public GitHub repository. Clicking on it automaically opens qBraid Lab, and performs a git clone of the project repo into your account's home directory. Copy the code below, and replace YOUR-USERNAME and YOUR-REPOSITORY with your GitHub info.

Use the badge in your project's README.md:

[<img src="https://qbraid-static.s3.amazonaws.com/logos/Launch_on_qBraid_white.png" width="150">](https://account.qbraid.com?gitHubUrl=https://github.com/YOUR-USERNAME/YOUR-REPOSITORY.git)

Use the badge in your project's README.rst:

.. image:: https://qbraid-static.s3.amazonaws.com/logos/Launch_on_qBraid_white.png
    :target: https://account.qbraid.com?gitHubUrl=https://github.com/YOUR-USERNAME/YOUR-REPOSITORY.git
    :width: 150px

Contributing

License

GNU General Public License v3.0

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

qbraid-0.4.4.dev20230814144805.tar.gz (12.5 MB view details)

Uploaded Source

Built Distribution

qbraid-0.4.4.dev20230814144805-py3-none-any.whl (129.9 kB view details)

Uploaded Python 3

File details

Details for the file qbraid-0.4.4.dev20230814144805.tar.gz.

File metadata

File hashes

Hashes for qbraid-0.4.4.dev20230814144805.tar.gz
Algorithm Hash digest
SHA256 5bb38474de5d11960d5210c203e55650055aa9de654e4c24b01f1b27810a32e3
MD5 8ba7ad61f821e2b4b6412714caa8b4c7
BLAKE2b-256 2b53886a2a4c102842075593d51901c26e00de16cbdadc8103903f82369e4069

See more details on using hashes here.

File details

Details for the file qbraid-0.4.4.dev20230814144805-py3-none-any.whl.

File metadata

File hashes

Hashes for qbraid-0.4.4.dev20230814144805-py3-none-any.whl
Algorithm Hash digest
SHA256 c827155ffa5959c9420f85e65f6e301e900bedaca615ce36888b673f71be124c
MD5 aacca1ec08acd1e5587f10ec04320cd9
BLAKE2b-256 b64766da2d24f1248142a2365ed938871da597159cefb96a0bfc3c69a08b01be

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page