diff --git a/.github/pull_request_template.md b/.github/pull_request_template.md index 819c43010..87dda8a1f 100644 --- a/.github/pull_request_template.md +++ b/.github/pull_request_template.md @@ -10,9 +10,9 @@ _Put an `x` in the boxes that apply. You can also fill these out after creating #### General -- [ ] I have read the [CONTRIBUTING](https://github.com/aws/amazon-braket-sdk-python/blob/main/CONTRIBUTING.md) doc -- [ ] I used the commit message format described in [CONTRIBUTING](https://github.com/aws/amazon-braket-sdk-python/blob/main/CONTRIBUTING.md#commit-your-change) -- [ ] I have updated any necessary documentation, including [READMEs](https://github.com/aws/amazon-braket-sdk-python/blob/main/README.md) and [API docs](https://github.com/aws/amazon-braket-sdk-python/blob/main/CONTRIBUTING.md#documentation-guidelines) (if appropriate) +- [ ] I have read the [CONTRIBUTING](https://github.com/amazon-braket/amazon-braket-sdk-python/blob/main/CONTRIBUTING.md) doc +- [ ] I used the commit message format described in [CONTRIBUTING](https://github.com/amazon-braket/amazon-braket-sdk-python/blob/main/CONTRIBUTING.md#commit-your-change) +- [ ] I have updated any necessary documentation, including [READMEs](https://github.com/amazon-braket/amazon-braket-sdk-python/blob/main/README.md) and [API docs](https://github.com/amazon-braket/amazon-braket-sdk-python/blob/main/CONTRIBUTING.md#documentation-guidelines) (if appropriate) #### Tests diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md index 1e659a5b8..7362a17b7 100644 --- a/CONTRIBUTING.md +++ b/CONTRIBUTING.md @@ -30,7 +30,7 @@ information to effectively respond to your bug report or contribution. We welcome you to use the GitHub issue tracker to report bugs or suggest features. -When filing an issue, please check [existing open](https://github.com/aws/amazon-braket-sdk-python/issues) and [recently closed](https://github.com/aws/amazon-braket-sdk-python/issues?utf8=%E2%9C%93&q=is%3Aissue%20is%3Aclosed%20) issues to make sure somebody else hasn't already +When filing an issue, please check [existing open](https://github.com/amazon-braket/amazon-braket-sdk-python/issues) and [recently closed](https://github.com/amazon-braket/amazon-braket-sdk-python/issues?utf8=%E2%9C%93&q=is%3Aissue%20is%3Aclosed%20) issues to make sure somebody else hasn't already reported the issue. Please try to include as much information as you can. Details like these are incredibly useful: * A reproducible test case or series of steps. @@ -199,7 +199,7 @@ If a parameter of a function has a default value, please note what the default i If that default value is `None`, it can also be helpful to explain what happens when the parameter is `None`. If `**kwargs` is part of the function signature, link to the parent class(es) or method(s) so that the reader knows where to find the available parameters. -For an example file with docstrings, see [the `circuit` module](https://github.com/aws/amazon-braket-sdk-python/blob/main/src/braket/circuits/circuit.py). +For an example file with docstrings, see [the `circuit` module](https://github.com/amazon-braket/amazon-braket-sdk-python/blob/main/src/braket/circuits/circuit.py). ### Build and Test Documentation @@ -215,12 +215,12 @@ You can then find the generated HTML files in `build/documentation/html`. ## Find Contributions to Work On -Looking at the existing issues is a great way to find something to contribute on. As our projects, by default, use the default GitHub issue labels ((enhancement/bug/duplicate/help wanted/invalid/question/wontfix), looking at any ['help wanted'](https://github.com/aws/amazon-braket-sdk-python/labels/help%20wanted) issues is a great place to start. +Looking at the existing issues is a great way to find something to contribute on. As our projects, by default, use the default GitHub issue labels ((enhancement/bug/duplicate/help wanted/invalid/question/wontfix), looking at any ['help wanted'](https://github.com/amazon-braket/amazon-braket-sdk-python/labels/help%20wanted) issues is a great place to start. ## Building Integrations -The Amazon Braket SDK supports integrations with popular quantum computing frameworks such as [PennyLane](https://github.com/aws/amazon-braket-pennylane-plugin-python), [Strawberryfields](https://github.com/aws/amazon-braket-strawberryfields-plugin-python) and [DWave's Ocean library](https://github.com/aws/amazon-braket-ocean-plugin-python). These serve as a good reference for a new integration you wish to develop. +The Amazon Braket SDK supports integrations with popular quantum computing frameworks such as [PennyLane](https://github.com/amazon-braket/amazon-braket-pennylane-plugin-python), [Strawberryfields](https://github.com/amazon-braket/amazon-braket-strawberryfields-plugin-python) and [DWave's Ocean library](https://github.com/amazon-braket/amazon-braket-ocean-plugin-python). These serve as a good reference for a new integration you wish to develop. -When developing a new integration with the Amazon Braket SDK, please remember to update the [user agent header](https://datatracker.ietf.org/doc/html/rfc7231#section-5.5.3) to include version information for your integration. An example can be found [here](https://github.com/aws/amazon-braket-pennylane-plugin-python/commit/ccee35604afc2b04d83ee9103eccb2821a4256cb). +When developing a new integration with the Amazon Braket SDK, please remember to update the [user agent header](https://datatracker.ietf.org/doc/html/rfc7231#section-5.5.3) to include version information for your integration. An example can be found [here](https://github.com/amazon-braket/amazon-braket-pennylane-plugin-python/commit/ccee35604afc2b04d83ee9103eccb2821a4256cb). ## Code of Conduct @@ -236,6 +236,6 @@ If you discover a potential security issue in this project we ask that you notif ## Licensing -See the [LICENSE](https://github.com/aws/amazon-braket-sdk-python/blob/main/LICENSE) file for our project's licensing. We will ask you to confirm the licensing of your contribution. +See the [LICENSE](https://github.com/amazon-braket/amazon-braket-sdk-python/blob/main/LICENSE) file for our project's licensing. We will ask you to confirm the licensing of your contribution. We may ask you to sign a [Contributor License Agreement (CLA)](http://en.wikipedia.org/wiki/Contributor_License_Agreement) for larger changes. diff --git a/README.md b/README.md index 1f7fcb460..f276de5da 100644 --- a/README.md +++ b/README.md @@ -2,8 +2,8 @@ [![Latest Version](https://img.shields.io/pypi/v/amazon-braket-sdk.svg)](https://pypi.python.org/pypi/amazon-braket-sdk) [![Supported Python Versions](https://img.shields.io/pypi/pyversions/amazon-braket-sdk.svg)](https://pypi.python.org/pypi/amazon-braket-sdk) -[![Build status](https://github.com/aws/amazon-braket-sdk-python/actions/workflows/python-package.yml/badge.svg?branch=main)](https://github.com/aws/amazon-braket-sdk-python/actions/workflows/python-package.yml) -[![codecov](https://codecov.io/gh/aws/amazon-braket-sdk-python/branch/main/graph/badge.svg?token=1lsqkZL3Ll)](https://codecov.io/gh/aws/amazon-braket-sdk-python) +[![Build status](https://github.com/amazon-braket/amazon-braket-sdk-python/actions/workflows/python-package.yml/badge.svg?branch=main)](https://github.com/amazon-braket/amazon-braket-sdk-python/actions/workflows/python-package.yml) +[![codecov](https://codecov.io/gh/amazon-braket/amazon-braket-sdk-python/branch/main/graph/badge.svg?token=1lsqkZL3Ll)](https://codecov.io/gh/amazon-braket/amazon-braket-sdk-python) [![Documentation Status](https://img.shields.io/readthedocs/amazon-braket-sdk-python.svg?logo=read-the-docs)](https://amazon-braket-sdk-python.readthedocs.io/en/latest/?badge=latest) The Amazon Braket Python SDK is an open source library that provides a framework that you can use to interact with quantum computing hardware devices through Amazon Braket. @@ -44,7 +44,7 @@ pip install amazon-braket-sdk You can also install from source by cloning this repository and running a pip install command in the root directory of the repository: ```bash -git clone https://github.com/aws/amazon-braket-sdk-python.git +git clone https://github.com/amazon-braket/amazon-braket-sdk-python.git cd amazon-braket-sdk-python pip install . ``` @@ -155,7 +155,7 @@ To select a quantum hardware device, specify its ARN as the value of the `device **Important** Quantum tasks may not run immediately on the QPU. The QPUs only execute quantum tasks during execution windows. To find their execution windows, please refer to the [AWS console](https://console.aws.amazon.com/braket/home) in the "Devices" tab. ## Sample Notebooks -Sample Jupyter notebooks can be found in the [amazon-braket-examples](https://github.com/aws/amazon-braket-examples/) repo. +Sample Jupyter notebooks can be found in the [amazon-braket-examples](https://github.com/amazon-braket/amazon-braket-examples/) repo. ## Braket Python SDK API Reference Documentation @@ -233,13 +233,13 @@ tox -e integ-tests -- your-arguments ### Issues and Bug Reports If you encounter bugs or face issues while using the SDK, please let us know by posting -the issue on our [Github issue tracker](https://github.com/aws/amazon-braket-sdk-python/issues/). +the issue on our [Github issue tracker](https://github.com/amazon-braket/amazon-braket-sdk-python/issues/). For other issues or general questions, please ask on the [Quantum Computing Stack Exchange](https://quantumcomputing.stackexchange.com/questions/ask) and add the tag amazon-braket. ### Feedback and Feature Requests If you have feedback or features that you would like to see on Amazon Braket, we would love to hear from you! -[Github issues](https://github.com/aws/amazon-braket-sdk-python/issues/) is our preferred mechanism for collecting feedback and feature requests, allowing other users +[Github issues](https://github.com/amazon-braket/amazon-braket-sdk-python/issues/) is our preferred mechanism for collecting feedback and feature requests, allowing other users to engage in the conversation, and +1 issues to help drive priority. ## License diff --git a/doc/examples-adv-circuits-algorithms.rst b/doc/examples-adv-circuits-algorithms.rst index ea99a475b..b37e87e34 100644 --- a/doc/examples-adv-circuits-algorithms.rst +++ b/doc/examples-adv-circuits-algorithms.rst @@ -7,9 +7,9 @@ Learn more about working with advanced circuits and algoritms. .. toctree:: :maxdepth: 2 -************************************************************************************************************************************************ -`Grover's search algorithm `_ -************************************************************************************************************************************************ +********************************************************************************************************************************************************** +`Grover's search algorithm `_ +********************************************************************************************************************************************************** This tutorial provides a step-by-step walkthrough of Grover's quantum algorithm. You learn how to build the corresponding quantum circuit with simple modular building @@ -17,9 +17,9 @@ blocks using the Amazon Braket SDK. You will learn how to build custom gates that are not part of the basic gate set provided by the SDK. A custom gate can used as a core quantum gate by registering it as a subroutine. -******************************************************************************************************************************************************************************************************** -`Quantum amplitude amplification `_ -******************************************************************************************************************************************************************************************************** +****************************************************************************************************************************************************************************************************************** +`Quantum amplitude amplification `_ +****************************************************************************************************************************************************************************************************************** This tutorial provides a detailed discussion and implementation of the Quantum Amplitude Amplification (QAA) algorithm using the Amazon Braket SDK. QAA is a routine in quantum computing which generalizes the idea behind @@ -29,18 +29,18 @@ target states in a given search space. In a quantum computer, QAA can be used to quadratic speedup over several classical algorithms. -************************************************************************************************************************************************************************************** -`Quantum Fourier transform `_ -************************************************************************************************************************************************************************************** +************************************************************************************************************************************************************************************************ +`Quantum Fourier transform `_ +************************************************************************************************************************************************************************************************ This tutorial provides a detailed implementation of the Quantum Fourier Transform (QFT) and its inverse using Amazon Braket's SDK. The QFT is an important subroutine to many quantum algorithms, most famously Shor's algorithm for factoring and the quantum phase estimation (QPE) algorithm for estimating the eigenvalues of a unitary operator. -*********************************************************************************************************************************************************************************** -`Quantum phase estimation `_ -*********************************************************************************************************************************************************************************** +********************************************************************************************************************************************************************************************* +`Quantum phase estimation `_ +********************************************************************************************************************************************************************************************* This tutorial provides a detailed implementation of the Quantum Phase Estimation (QPE) algorithm using the Amazon Braket SDK. The QPE algorithm is designed to estimate the diff --git a/doc/examples-braket-features.rst b/doc/examples-braket-features.rst index 1bfc9c0d7..75361f172 100644 --- a/doc/examples-braket-features.rst +++ b/doc/examples-braket-features.rst @@ -7,40 +7,40 @@ Learn more about the indivudal features of Amazon Braket. .. toctree:: :maxdepth: 2 -******************************************************************************************************************************************************************************************************************************* -`Getting notifications when a quantum task completes `_ -******************************************************************************************************************************************************************************************************************************* +***************************************************************************************************************************************************************************************************************************************************************** +`Getting notifications when a quantum task completes `_ +***************************************************************************************************************************************************************************************************************************************************************** This tutorial illustrates how Amazon Braket integrates with Amazon EventBridge for event-based processing. In the tutorial, you will learn how to configure Amazon Braket and Amazon Eventbridge to receive text notification about quantum task completions on your phone. -************************************************************************************************************************************************************* -`Allocating Qubits on QPU Devices `_ -************************************************************************************************************************************************************* +*********************************************************************************************************************************************************************** +`Allocating Qubits on QPU Devices `_ +*********************************************************************************************************************************************************************** This tutorial explains how you can use the Amazon Braket SDK to allocate the qubit selection for your circuits manually, when running on QPUs. -***************************************************************************************************************************************************************************************** -`Getting Devices and Checking Device Properties `_ -***************************************************************************************************************************************************************************************** +*************************************************************************************************************************************************************************************************** +`Getting Devices and Checking Device Properties `_ +*************************************************************************************************************************************************************************************************** This example shows how to interact with the Amazon Braket GetDevice API to retrieve Amazon Braket devices (such as simulators and QPUs) programatically, and how to gain access to their properties. -************************************************************************************************************************************************************************* -`Using the tensor network simulator TN1 `_ -************************************************************************************************************************************************************************* +*********************************************************************************************************************************************************************************** +`Using the tensor network simulator TN1 `_ +*********************************************************************************************************************************************************************************** This notebook introduces the Amazon Braket managed tensor network simulator, TN1. You will learn about how TN1 works, how to use it, and which problems are best suited to run on TN1. -*************************************************************************************************************************************************************** -`Simulating noise on Amazon Braket `_ -*************************************************************************************************************************************************************** +************************************************************************************************************************************************************************* +`Simulating noise on Amazon Braket `_ +************************************************************************************************************************************************************************* This notebook provides a detailed overview of noise simulation on Amazon Braket. You will learn how to define noise channels, apply noise to new or existing circuits, and run those circuits diff --git a/doc/examples-getting-started.rst b/doc/examples-getting-started.rst index 9523320c1..8c9eb90f5 100644 --- a/doc/examples-getting-started.rst +++ b/doc/examples-getting-started.rst @@ -7,15 +7,15 @@ Get started on Amazon Braket with some introductory examples. .. toctree:: :maxdepth: 2 -*********************************************************************************************************************************************** -`Getting started `_ -*********************************************************************************************************************************************** +********************************************************************************************************************************************************* +`Getting started `_ +********************************************************************************************************************************************************* A hello-world tutorial that shows you how to build a simple circuit and run it on a local simulator. -******************************************************************************************************************************************************************************************************************** -`Running quantum circuits on simulators `_ -******************************************************************************************************************************************************************************************************************** +****************************************************************************************************************************************************************************************************************************** +`Running quantum circuits on simulators `_ +****************************************************************************************************************************************************************************************************************************** This tutorial prepares a paradigmatic example for a multi-qubit entangled state, the so-called GHZ state (named after the three physicists Greenberger, Horne, and Zeilinger). @@ -26,9 +26,9 @@ and quantum metrology. **Note:** When a circuit is ran using a simulator, customers are required to use contiguous qubits/indices. -*********************************************************************************************************************************************************************************************************************** -`Running quantum circuits on QPU devices `_ -*********************************************************************************************************************************************************************************************************************** +********************************************************************************************************************************************************************************************************************************* +`Running quantum circuits on QPU devices `_ +********************************************************************************************************************************************************************************************************************************* This tutorial prepares a maximally-entangled Bell state between two qubits, for classical simulators and for QPUs. For classical devices, we can run the circuit on a @@ -36,9 +36,9 @@ local simulator or a cloud-based managed simulator. For the quantum devices, we run the circuit on the superconducting machine from Rigetti, and on the ion-trap machine provided by IonQ. -******************************************************************************************************************************************************************************************************************************************** -`Deep Dive into the anatomy of quantum circuits `_ -******************************************************************************************************************************************************************************************************************************************** +****************************************************************************************************************************************************************************************************************************************************** +`Deep Dive into the anatomy of quantum circuits `_ +****************************************************************************************************************************************************************************************************************************************************** This tutorial discusses in detail the anatomy of quantum circuits in the Amazon Braket SDK. You will learn how to build (parameterized) circuits and display them @@ -47,9 +47,9 @@ more about circuit depth and circuit size. Finally you will learn how to execute the circuit on a device of our choice (defining a quantum task) and how to track, log, recover, or cancel a quantum task efficiently. -***************************************************************************************************************************************************** -`Superdense coding `_ -***************************************************************************************************************************************************** +*************************************************************************************************************************************************************** +`Superdense coding `_ +*************************************************************************************************************************************************************** This tutorial constructs an implementation of the superdense coding protocol using the Amazon Braket SDK. Superdense coding is a method of transmitting two classical diff --git a/doc/examples-hybrid-jobs.rst b/doc/examples-hybrid-jobs.rst index 76b2026eb..af873407c 100644 --- a/doc/examples-hybrid-jobs.rst +++ b/doc/examples-hybrid-jobs.rst @@ -7,27 +7,27 @@ Learn more about hybrid jobs on Amazon Braket. .. toctree:: :maxdepth: 2 -************************************************************************************************************************************************************************************** -`Creating your first Hybrid Job `_ -************************************************************************************************************************************************************************************** +************************************************************************************************************************************************************************************************ +`Creating your first Hybrid Job `_ +************************************************************************************************************************************************************************************************ This tutorial shows how to run your first Amazon Braket Hybrid Job. -*********************************************************************************************************************************************************************************************************************************************************** -`Quantum machine learning in Amazon Braket Hybrid Jobs `_ -*********************************************************************************************************************************************************************************************************************************************************** +********************************************************************************************************************************************************************************************************************************************************************* +`Quantum machine learning in Amazon Braket Hybrid Jobs `_ +********************************************************************************************************************************************************************************************************************************************************************* This notebook demonstrates a typical quantum machine learning workflow, including uploading data, monitoring training, and tuning hyperparameters. -******************************************************************************************************************************************************************************************** -`Using Pennylane with Braket Hybrid Jobs `_ -******************************************************************************************************************************************************************************************** +*************************************************************************************************************************************************************************************************************************** +`Using Pennylane with Braket Hybrid Jobs `_ +*************************************************************************************************************************************************************************************************************************** In this tutorial, we use PennyLane within Amazon Braket Hybrid Jobs to run the Quantum Approximate Optimization Algorithm (QAOA) on a Max-Cut problem. -******************************************************************************************************************************************************************** -`Bring your own container `_ -******************************************************************************************************************************************************************** +****************************************************************************************************************************************************************************** +`Bring your own container `_ +****************************************************************************************************************************************************************************** Amazon Braket has pre-configured containers for executing Amazon Braket Hybrid Jobs, which are sufficient for many use cases involving the Braket SDK and PennyLane. However, if we want to use custom packages outside the scope of pre-configured containers, we have the ability to supply a custom-built container. In this tutorial, we show how to use Braket Hybrid Jobs to train a quantum machine learning model using BYOC (Bring Your Own Container). diff --git a/doc/examples-hybrid-quantum.rst b/doc/examples-hybrid-quantum.rst index b30083af9..9c7f3aca2 100644 --- a/doc/examples-hybrid-quantum.rst +++ b/doc/examples-hybrid-quantum.rst @@ -7,23 +7,23 @@ Learn more about hybrid quantum algorithms. .. toctree:: :maxdepth: 2 -*************************************************************************************************************************** -`QAOA `_ -*************************************************************************************************************************** +************************************************************************************************************************************* +`QAOA `_ +************************************************************************************************************************************* This tutorial shows how to (approximately) solve binary combinatorial optimization problems using the Quantum Approximate Optimization Algorithm (QAOA). -************************************************************************************************************************************************************************** -`VQE Transverse Ising `_ -************************************************************************************************************************************************************************** +************************************************************************************************************************************************************************************ +`VQE Transverse Ising `_ +************************************************************************************************************************************************************************************ This tutorial shows how to solve for the ground state of the Transverse Ising Model using the variational quantum eigenvalue solver (VQE). -****************************************************************************************************************************************************** -`VQE Chemistry `_ -****************************************************************************************************************************************************** +**************************************************************************************************************************************************************** +`VQE Chemistry `_ +**************************************************************************************************************************************************************** This tutorial shows how to implement the Variational Quantum Eigensolver (VQE) algorithm in Amazon Braket SDK to compute the potential energy surface (PES) for the Hydrogen molecule. diff --git a/doc/examples-ml-pennylane.rst b/doc/examples-ml-pennylane.rst index dae859127..5c7db93aa 100644 --- a/doc/examples-ml-pennylane.rst +++ b/doc/examples-ml-pennylane.rst @@ -7,16 +7,16 @@ Learn more about how to combine PennyLane with Amazon Braket. .. toctree:: :maxdepth: 2 -**************************************************************************************************************************************************************** -`Combining PennyLane with Amazon Braket `_ -**************************************************************************************************************************************************************** +************************************************************************************************************************************************************************** +`Combining PennyLane with Amazon Braket `_ +************************************************************************************************************************************************************************** This tutorial shows you how to construct circuits and evaluate their gradients in PennyLane with execution performed using Amazon Braket. -******************************************************************************************************************************************************************************************************************************************* -`Computing gradients in parallel with PennyLane-Braket `_ -******************************************************************************************************************************************************************************************************************************************* +***************************************************************************************************************************************************************************************************************************************************** +`Computing gradients in parallel with PennyLane-Braket `_ +***************************************************************************************************************************************************************************************************************************************************** Learn how to speed up training of quantum circuits by using parallel execution on Amazon Braket. Quantum circuit training involving gradients @@ -25,9 +25,9 @@ The tutorial benchmarks SV1 against a local simulator, showing that SV1 outperfo local simulator for both executions and gradient calculations. This illustrates how parallel capabilities can be combined between PennyLane and SV1. -******************************************************************************************************************************************************************************** -`Graph optimization with QAOA `_ -******************************************************************************************************************************************************************************** +****************************************************************************************************************************************************************************************** +`Graph optimization with QAOA `_ +****************************************************************************************************************************************************************************************** In this tutorial, you learn how quantum circuit training can be applied to a problem of practical relevance in graph optimization. It easy it is to train a QAOA circuit in @@ -36,9 +36,9 @@ then extends to a more difficult 20-node graph and uses the parallel capabilitie the Amazon Braket SV1 simulator to speed up gradient calculations and hence train the quantum circuit faster, using around 1-2 minutes per iteration. -***************************************************************************************************************************************************************************************************** -`Hydrogen Molecule geometry with VQE `_ -***************************************************************************************************************************************************************************************************** +*************************************************************************************************************************************************************************************************************** +`Hydrogen Molecule geometry with VQE `_ +*************************************************************************************************************************************************************************************************************** In this tutorial, you will learn how PennyLane and Amazon Braket can be combined to solve an important problem in quantum chemistry. The ground state energy of molecular hydrogen is calculated diff --git a/doc/examples.rst b/doc/examples.rst index e607920a1..87c2e1f7a 100644 --- a/doc/examples.rst +++ b/doc/examples.rst @@ -3,7 +3,7 @@ Examples ######## There are several examples available in the Amazon Braket repo: -https://github.com/aws/amazon-braket-examples. +https://github.com/amazon-braket/amazon-braket-examples. .. toctree:: :maxdepth: 2 @@ -15,4 +15,4 @@ https://github.com/aws/amazon-braket-examples. examples-ml-pennylane.rst examples-hybrid-jobs.rst - \ No newline at end of file + diff --git a/doc/index.rst b/doc/index.rst index 38dce7284..8d996f4cc 100644 --- a/doc/index.rst +++ b/doc/index.rst @@ -6,7 +6,7 @@ The Amazon Braket Python SDK is an open source library to design and build quant submit them to Amazon Braket devices as quantum tasks, and monitor their execution. This documentation provides information about the Amazon Braket Python SDK library. The project -homepage is in Github https://github.com/aws/amazon-braket-sdk-python. The project +homepage is in Github https://github.com/amazon-braket/amazon-braket-sdk-python. The project includes SDK source, installation instructions, and other information. *************** diff --git a/setup.py b/setup.py index 25fca8252..f21f27c3d 100644 --- a/setup.py +++ b/setup.py @@ -62,7 +62,7 @@ ] }, include_package_data=True, - url="https://github.com/aws/amazon-braket-sdk-python", + url="https://github.com/amazon-braket/amazon-braket-sdk-python", author="Amazon Web Services", description=( "An open source library for interacting with quantum computing devices on Amazon Braket" diff --git a/tox.ini b/tox.ini index af1fd9097..59de91a16 100644 --- a/tox.ini +++ b/tox.ini @@ -47,7 +47,7 @@ skip_install = true deps = flake8 flake8-rst-docstrings - git+https://github.com/aws/amazon-braket-build-tools.git + git+https://github.com/amazon-braket/amazon-braket-build-tools.git commands = flake8 {posargs} flake8 --enable-extensions=BCS src @@ -94,5 +94,5 @@ commands = [test-deps] deps = # If you need to test on a certain branch, add @ after .git - git+https://github.com/aws/amazon-braket-schemas-python.git - git+https://github.com/aws/amazon-braket-default-simulator-python.git + git+https://github.com/amazon-braket/amazon-braket-schemas-python.git + git+https://github.com/amazon-braket/amazon-braket-default-simulator-python.git