Merge branch 'main' into dependabot/github_actions/codecov/codecov-ac…

…tion-4.2.0

.coveragerc

@@ -3,7 +3,7 @@ parallel = True
 branch = True
 source =
     src
-omit = 
+omit =
     **/braket/ir/*
     **/braket/device_schema/*
     **/braket/schema_common/*
@@ -23,9 +23,15 @@ exclude_lines =
     # Have to re-enable the standard pragma
     pragma: no cover
 
+    # Skipping import testing
+    from importlib.metadata import entry_points
+
     # Don't complain if tests don't hit defensive assertion code:
     raise NotImplementedError
 
+    # Avoid situation where system version causes coverage issues
+    if sys.version_info.minor == 9:
+
 [html]
 directory = build/coverage
 

.github/dependabot.yml

@@ -7,7 +7,6 @@ updates:
     directory: "/"
     schedule:
       # Check for updates to GitHub Actions every week
-      interval: "weekly"
+      interval: "monthly"
     commit-message:
       prefix: infra
-

.github/pr-title-checker-config.json

@@ -0,0 +1,17 @@
+{
+  "LABEL": {
+    "name": "title needs formatting",
+    "color": "EEEEEE"
+  },
+  "CHECKS": {
+    "prefixes": ["fix: ", "feat: ", "test: ", "infra: ", "doc: ", "change: ", "break: ", "breaking: ", "deprecation: ", "feature: ", "depr: ", "documentation: "],
+    "regexp": "docs\\(v[0-9]\\): ",
+    "regexpFlags": "i",
+    "ignoreLabels" : ["dont-check-PRs-with-this-label", "meta"]
+  },
+  "MESSAGES": {
+    "success": "All OK",
+    "failure": "Failing CI test",
+    "notice": ""
+  }
+}

.github/workflows/check-format.yml

@@ -26,4 +26,4 @@ jobs:
         pip install tox
     - name: Run code format checks
       run: |
-        tox -e linters_check
+        tox -e linters_check -p auto

.github/workflows/pr-title-checker.yml

@@ -0,0 +1,31 @@
+name: "PR Title Checker"
+
+on:
+  push:
+    branches:
+      - main
+  pull_request:
+    branches:
+      - main
+      - feature/**
+  pull_request_target:
+    types:
+      - opened
+      - edited
+      - synchronize
+      - labeled
+      - unlabeled
+
+permissions:
+  pull-requests: write
+
+jobs:
+  check:
+    runs-on: ubuntu-latest
+    steps:
+      - name: "Check PR Title"
+        uses: thehanimo/pr-title-checker@v1.4.1
+        with:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+          pass_on_octokit_error: false
+          configuration_path: .github/pr-title-checker-config.json #(optional. defaults to .github/pr-title-checker-config.json)

.readthedocs.yml

@@ -12,7 +12,7 @@ sphinx:
 # Optionally build your docs in additional formats such as PDF
 formats:
   - pdf
-  
+
 # setting up build.os and the python version
 build:
   os: ubuntu-22.04

CHANGELOG.md

@@ -1,5 +1,85 @@
 # Changelog
 
+## v1.81.1 (2024-06-17)
+
+### Bug Fixes and Other Changes
+
+ * Error when FreeParameters are named QASM types
+
+## v1.81.0 (2024-06-13)
+
+### Features
+
+ * Add IQM to get compiled program convenience method
+
+## v1.80.1 (2024-06-10)
+
+### Bug Fixes and Other Changes
+
+ * docs: add stack exchange badge to the readme
+ * Implement `braket.ahs.AnalogHamiltonianSimulation.from_ir()`
+
+## v1.80.0 (2024-05-22)
+
+### Features
+
+ * add support for the ARN region
+ * Add support for SerializableProgram abstraction to Device interface
+
+### Bug Fixes and Other Changes
+
+ * job fixture for endpoint support
+
+## v1.79.1 (2024-05-08)
+
+### Bug Fixes and Other Changes
+
+ * check the qubit set length against observables
+
+## v1.79.0 (2024-05-06)
+
+### Features
+
+ * Direct Reservation context manager
+
+### Documentation Changes
+
+ * correct the example in the measure docstring
+
+## v1.78.0 (2024-04-18)
+
+### Features
+
+ * add phase RX gate
+
+## v1.77.6 (2024-04-17)
+
+### Bug Fixes and Other Changes
+
+ * if rydberg local is not pulled, pass in None
+
+## v1.77.5 (2024-04-16)
+
+### Bug Fixes and Other Changes
+
+ * remove optional discretization fields
+
+## v1.77.4 (2024-04-16)
+
+### Bug Fixes and Other Changes
+
+ * discretize method now takes None as an arg
+
+### Documentation Changes
+
+ * Correct miscellaneous spelling mistakes in docstrings
+
+## v1.77.3.post0 (2024-04-15)
+
+### Documentation Changes
+
+ * correct gphase matrix representation
+
 ## v1.77.3 (2024-04-11)
 
 ### Bug Fixes and Other Changes
@@ -38,7 +118,7 @@
 
 ### Bug Fixes and Other Changes
 
- * backwards compatiblity for local detuning
+ * backwards compatibility for local detuning
 
 ## v1.76.1 (2024-04-08)
 

CONTRIBUTING.md

@@ -218,9 +218,9 @@ You can then find the generated HTML files in `build/documentation/html`.
 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/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. 
+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/amazon-braket/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
 

README.md

@@ -5,6 +5,7 @@
 [![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)
+[![Stack Overflow](https://img.shields.io/badge/StackExchange-Ask%20questions-blue?logo=stackexchange)](https://quantumcomputing.stackexchange.com/questions/tagged/amazon-braket)
 
 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.
 
@@ -93,7 +94,8 @@ Many quantum algorithms need to run multiple independent circuits, and submittin
 ```python
 circuits = [bell for _ in range(5)]
 batch = device.run_batch(circuits, shots=100)
-print(batch.results()[0].measurement_counts)  # The result of the first quantum task in the batch
+# The result of the first quantum task in the batch
+print(batch.results()[0].measurement_counts)  
 ```
 
 ### Running a hybrid job
@@ -139,14 +141,14 @@ from braket.aws import AwsDevice
 device = AwsDevice("arn:aws:braket:::device/qpu/rigetti/Aspen-8")
 
 bell = Circuit().h(0).cnot(0, 1)
-task = device.run(bell) 
+task = device.run(bell)
 print(task.result().measurement_counts)
 ```
 
 When you execute your task, Amazon Braket polls for a result. By default, Braket polls for 5 days; however, it is possible to change this by modifying the `poll_timeout_seconds` parameter in `AwsDevice.run`, as in the example below. Keep in mind that if your polling timeout is too short, results may not be returned within the polling time, such as when a QPU is unavailable, and a local timeout error is returned. You can always restart the polling by using `task.result()`.
 
 ```python
-task = device.run(bell, poll_timeout_seconds=86400)  # 1 day 
+task = device.run(bell, poll_timeout_seconds=86400)  # 1 day
 print(task.result().measurement_counts)
 ```
 
@@ -205,6 +207,12 @@ To run linters and doc generators and unit tests:
 tox
 ```
 
+or if your machine can handle multithreaded workloads, run them in parallel with:
+
+```bash
+tox -p auto
+```
+
 ### Integration Tests
 
 First, configure a profile to use your account to interact with AWS. To learn more, see [Configure AWS CLI](https://docs.aws.amazon.com/cli/latest/userguide/cli-chap-configure.html).
@@ -232,15 +240,15 @@ 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/amazon-braket/amazon-braket-sdk-python/issues/).  
+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/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?Tags=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/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. 
+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/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.
 
 ### Code contributors
 

doc/conf.py

@@ -7,7 +7,7 @@
 project = "amazon-braket-sdk"
 version = version(project)
 release = version
-copyright = "{}, Amazon.com".format(datetime.datetime.now().year)
+copyright = f"{datetime.datetime.now().year}, Amazon.com"
 
 extensions = [
     "sphinxcontrib.apidoc",
@@ -26,7 +26,7 @@
 default_role = "py:obj"
 
 html_theme = "sphinx_rtd_theme"
-htmlhelp_basename = "{}doc".format(project)
+htmlhelp_basename = f"{project}doc"
 
 language = "en"
 

doc/examples-adv-circuits-algorithms.rst

@@ -2,49 +2,49 @@
 Advanced circuits and algorithms
 ################################
 
-Learn more about working with advanced circuits and algoritms.
+Learn more about working with advanced circuits and algorithms.
 
 .. toctree::
     :maxdepth: 2
-  
+
 **********************************************************************************************************************************************************
 `Grover's search algorithm <https://github.com/amazon-braket/amazon-braket-examples/blob/main/examples/advanced_circuits_algorithms/Grover/Grover.ipynb>`_
 **********************************************************************************************************************************************************
 
-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 
-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 
+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
+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 <https://github.com/amazon-braket/amazon-braket-examples/blob/main/examples/advanced_circuits_algorithms/Quantum_Amplitude_Amplification/Quantum_Amplitude_Amplification.ipynb>`_
 ******************************************************************************************************************************************************************************************************************
 
-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 
-Grover's famous search algorithm, with applications across many quantum algorithms. QAA uses an iterative 
-approach to systematically increase the probability of finding one or multiple 
-target states in a given search space. In a quantum computer, QAA can be used to obtain a 
+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
+Grover's famous search algorithm, with applications across many quantum algorithms. QAA uses an iterative
+approach to systematically increase the probability of finding one or multiple
+target states in a given search space. In a quantum computer, QAA can be used to obtain a
 quadratic speedup over several classical algorithms.
 
 
 ************************************************************************************************************************************************************************************************
 `Quantum Fourier transform <https://github.com/amazon-braket/amazon-braket-examples/blob/main/examples/advanced_circuits_algorithms/Quantum_Fourier_Transform/Quantum_Fourier_Transform.ipynb>`_
 ************************************************************************************************************************************************************************************************
 
-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. 
+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 <https://github.com/amazon-braket/amazon-braket-examples/blob/main/examples/advanced_circuits_algorithms/Quantum_Phase_Estimation/Quantum_Phase_Estimation.ipynb>`_
 *********************************************************************************************************************************************************************************************
 
-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 
-eigenvalues of a unitary operator. Eigenvalue problems can be found across many 
-disciplines and application areas, including principal component analysis (PCA) 
-as used in machine learning and the solution of differential equations in mathematics, physics, 
-engineering and chemistry. 
+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
+eigenvalues of a unitary operator. Eigenvalue problems can be found across many
+disciplines and application areas, including principal component analysis (PCA)
+as used in machine learning and the solution of differential equations in mathematics, physics,
+engineering and chemistry.