A Python toolkit for cross-framework abstraction of quantum programs.
Project description
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
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
You can also install from source by cloning this repository and running a pip install command in the root directory of the repository:
git clone https://github.com/qBraid/qBraid.git
cd qBraid
pip install -e '.[all]'
Note: The qBraid-SDK requires Python 3.10 or greater.
If using locally, follow linked instructions to configure your qBraid, AWS, and IBMQ credentials.
Check version
You can view the version of the qBraid-SDK you have installed within Python using the following:
In [1]: import qbraid
In [2]: qbraid.__version__
Documentation & Tutorials
qBraid documentation is available at docs.qbraid.com.
See also:
Quickstart
Transpiler
Construct a quantum program of any supported program type.
Below, QPROGRAM_LIBS
lists shorthand identifiers for supported quantum programs, each corresponding to a type in the QPROGRAM
Union. For example, 'qiskit' in QPROGRAM_LIBS
maps to qiskit.QuantumCircuit
in QPROGRAM
. Notably, 'qasm2' and 'qasm3' both represent raw OpenQASM strings. This arrangement simplifies targeting and transpiling between different quantum programming frameworks.
>>> from qbraid import QPROGRAM_LIBS, QPROGRAM
>>> QPROGRAM_LIBS
['braket', 'cirq', 'qiskit', 'pyquil', 'pytket', 'openqasm3', 'qasm2', 'qasm3']
>>> QPROGRAM
typing.Union[
cirq.circuits.circuit.Circuit,
qiskit.circuit.quantumcircuit.QuantumCircuit,
pyquil.quil.Program,
pytket._tket.circuit.Circuit,
braket.circuits.circuit.Circuit,
openqasm3.ast.Program,
str]
Pass any quantum program of type QPROGRAM
to the circuit_wrapper()
and specify a target package
from QPROGRAM_LIBS
to "transpile" your circuit to a new 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: ───@───Rx(0.966π)───
│
1: ───H───X^0.5────────
The same functionality can be achieved using the underlying convert_to_package()
function directly:
>>> from qbraid import convert_to_package
>>> cirq_circuit = convert_to_package(qiskit_circuit, "cirq")
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_ionq_aria2 OFFLINE
aws_rigetti_aspen_m3 ONLINE
ibm_q_brisbane 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_brisbane")
>>> 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_brisbane-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
To use the qBraid-SDK locally (outside of qBraid Lab), you must add your account credentials:
-
Create a qBraid account or log in to your existing account by visiting account.qbraid.com
-
Copy your API Key token from the left side of your account page:
-
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
-
Interested in contributing code, or making a PR? See CONTRIBUTING.md
-
For feature requests and bug reports: Submit an issue
-
For discussions, and specific questions about the qBraid SDK, qBraid Lab, or other topics, join our discord community
-
For questions that are more suited for a forum, post to Quantum Computing Stack Exchange with the
qbraid
tag. -
Want your open-source project featured as its own runtime environment on qBraid Lab? Fill out our New Environment Request Form
License
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
Built Distribution
Hashes for qbraid-0.5.0.dev20231220160122.tar.gz
Algorithm | Hash digest | |
---|---|---|
SHA256 | ad466494c31f5a3674444b465f480c9210fd2363d1f79192e5dd1e0072118ae1 |
|
MD5 | 476c0eb407a5c89bbc271af65aeb9640 |
|
BLAKE2b-256 | 28699308557db95cf29ee6febe1722fd8608f875fefe247779335c82649bdfeb |
Hashes for qbraid-0.5.0.dev20231220160122-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 98b68363285d8bb97afb64152b7ae1db6fe4d87ac03c12134b543f475dc059fe |
|
MD5 | 49dbb1cd6c08016372c495542cd620ba |
|
BLAKE2b-256 | c1aef7103dd942a65b4ba22f8be597b9042d88c54f1ab59c3a2b02cc550a1fb7 |