Welcome to the Azure Quantum Development Kit!
This repository contains tooling for the Q# language, specifically:
- compiler: core compiler logic and command-line tooling
- fuzz: fuzz testing infrastructure
- jupyterlab: JupyterLab extension
- language_service: Q# language service and editor features
- library: Q# standard library
- npm: Q# npm package
- pip: Q# Python pip package
- playground: simple website for interacting with Q#
- resource_estimator: Implementation for the Azure Quantum Resource Estimator
- vscode: Visual Studio Code extension
- wasm: The bindings and logic for the WebAssembly module
- widgets: The Q# Jupyter widgets Python package
There are also the tutorials and samples in the ./katas and ./samples directories, respectively.
Code from this repository powers the Q# development experience on https://quantum.microsoft.com.
To build this repository there are dependencies that need to be installed. These are:
- Python (https://python.org)
- Rust (https://www.rust-lang.org/tools/install)
- Node.js (https://nodejs.org/)
- wasm-pack (https://rustwasm.github.io/wasm-pack/installer/)
- cmake (https://cmake.org/) and a C compiler
The build script will check these dependencies and their versions and fail if not met. (Or run
python ./prereqs.py directly to check if the minimum required versions are installed).
To build, in the root directory run python ./build.py. By default this will run a release
build of each project, including running tests and checks such as linting. Run with the
--help option for detailed usage.
To run the "playground" locally, build the repository, then cd into the playground directory, and run npm start.
This will launch a local web server and output the URL to the console; copy that URL and open it in a browser to use the playground.
If you only want to build the functionality necessary to run the playground, you can use python .\build.py --wasm --npm --play.
When building the Python packages (pip and jupyterlab), if the build script does not detect
a current Python virtual environment, it will automatically create one under pip/.venv or
jupyterlab/.venv. When developing locally, you can use these virtual environments to run the
tests by running source .venv/bin/activate (Linux/MacOS) or .venv/Scripts/activate.bat (Windows).
The easiest way to develop in this repo is to use VS Code. When you open the project root, by
default VS Code will recommend you install the extensions listed in .vscode/extensions.json.
These extensions provide language services for editing, as well as linters and formatters to
ensure the code meets the requirements (which are checked by the build.py script and CI).
Some settings are recommended (but not enforced) to make development easier. These are in the
.vscode/*.shared.json files. If the Workspace Config+
extension is installed, this will automatically apply these settings, as well as overrides from
your own corresponding .vscode/*.local.json settings. If you don't install this extension, you can
use these as a reference for editing your own .vscode/*.json settings files. (See the extension
home page for more details).
Besides the usual debugging tools for Rust code and web sites, there is some logging in the code
that may be enabled to help troubleshoot. The qsc command-line compiler makes use of the Rust
crate env_logger, which enables logging via
environment variables, for example RUST_LOG=debug ./target/release/qsc ./samples/Grover.qs.
If you use Q#, Azure Quantum Development Kit, or Azure Quantum Resource Estimator, please cite as follows:
- Azure Quantum Development Kit:
@software{Microsoft_Azure_Quantum_Development,
author = {{Microsoft}},
license = {MIT},
title = {{Azure Quantum Development Kit}},
url = {https://github.com/microsoft/qsharp} }- Q# programming language:
@inproceedings{Svore_2018, series={RWDSL2018},
title={{Q\#: Enabling Scalable Quantum Computing and Development with a High-level DSL}},
url={http://dx.doi.org/10.1145/3183895.3183901},
DOI={10.1145/3183895.3183901},
booktitle={Proceedings of the Real World Domain Specific Languages Workshop 2018},
publisher={ACM},
author={Svore, Krysta and Geller, Alan and Troyer, Matthias and Azariah, John and Granade, Christopher and Heim, Bettina and Kliuchnikov, Vadym and Mykhailova, Mariia and Paz, Andres and Roetteler, Martin},
year={2018},
month=feb, collection={RWDSL2018} }- Azure Quantum Resource Estimator:
@inproceedings{Azure_Quantum_Resource_Estimator,
author = {van Dam, Wim and Mykhailova, Mariia and Soeken, Mathias},
title = {{Using Azure Quantum Resource Estimator for Assessing Performance of Fault Tolerant Quantum Computation}},
year = {2023},
isbn = {9798400707858},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3624062.3624211},
doi = {10.1145/3624062.3624211},
booktitle = {Proceedings of the SC '23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis},
pages = {1414–1419},
numpages = {6},
series = {SC-W '23} }If you have feedback about the content in this repository, please let us know by filing a new issue!
Security issues and bugs should be reported privately following our security issue documentation.
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