Skip to main content

An open source library that contains the schemas for Amazon Braket

Reason this release was yanked:

Deprecated

Project description

Amazon Braket Python Schemas

Latest Version Supported Python Versions Build Status codecov Documentation Status Code Style: Black

Amazon Braket Python Schemas is an open source library that contains the schemas for Braket, including:

  • intermediate representations (IR) for Amazon Braket quantum tasks and offers serialization and deserialization of those IR payloads. Think of the IR as the contract between the Amazon Braket SDK and Amazon Braket API for quantum programs.
  • schemas for the S3 results of each quantum task
  • schemas for the device capabilities of each device

Installation

Prerequisites

  • Python 3.7+

Steps

The preferred way to get Amazon Braket Python Schemas is by installing the Amazon Braket Python SDK, which will pull in the schemas. Follow the instructions in the README for setup.

However, if you only want to use the schemas, it can be installed on its own as follows:

pip install amazon-braket-schemas

You can 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/aws/amazon-braket-schemas-python.git
cd amazon-braket-schemas-python
pip install .

You can check your currently installed version of amazon-braket-schemas with pip show:

pip show amazon-braket-schemas

or alternatively from within Python:

>>> import braket._schemas as braket_schemas
>>> braket_schemas.__version__

Usage

There are currently two types of IR, including jacqd (JsonAwsQuantumCircuitDescription) and annealing. See below for their usage.

Serializing python structures

from braket.ir.jaqcd import CNot, H, Program, Expectation
from braket.ir.annealing import Problem, ProblemType

program = Program(instructions=[H(target=0), CNot(control=0, target=1)])
print(program.json(indent=2))

"""
{
  "braketSchemaHeader": {
    "name": "braket.ir.jaqcd.program",
    "version": "1"
  },
  "instructions": [
    {
      "target": 0,
      "type": "h"
    },
    {
      "control": 0,
      "target": 1,
      "type": "cnot"
    }
  ],
  "results": null,
  "basis_rotation_instructions": null,
}
"""

program = Program(
    instructions=[H(target=0), CNot(control=0, target=1)],
    results=[Expectation(targets=[0], observable=['x'])],
    basis_rotation_instructions=[H(target=0)]
)
print(program.json(indent=2))

"""
{
  "braketSchemaHeader": {
    "name": "braket.ir.jaqcd.program",
    "version": "1"
  },
  "instructions": [
    {
      "target": 0,
      "type": "h"
    },
    {
      "control": 0,
      "target": 1,
      "type": "cnot"
    }
  ],
  "results": [
    {
      "observable": [
        "x"
      ],
      "targets": [
        0
      ],
      "type": "expectation"
    }
  ],
  "basis_rotation_instructions": [
    {
      "target": 0,
      "type": "h"
    }
  ]
}
"""

problem = Problem(type=ProblemType.QUBO, linear={0: 0.3, 4: -0.3}, quadratic={"0,5": 0.667})
print(problem.json(indent=2))

"""
{
  "braketSchemaHeader": {
    "name": "braket.ir.annealing.problem",
    "version": "1"
  },
  "type": "QUBO",
  "linear": {0: 0.3, 4: -0.3},
  "quadratic": {"0,5": 0.667}
}
"""

Deserializing into python structures

from braket.ir.jaqcd import Program
from braket.ir.annealing import Problem

jaqcd_string = """
{
  "instructions": [
    {
      "target": 0,
      "type": "h"
    },
    {
      "control": 0,
      "target": 1,
      "type": "cnot"
    }
  ],
  "results": [
    {
      "observable": [
        "x"
      ],
      "targets": [
        0
      ],
      "type": "expectation"
    }
  ],
  "basis_rotation_instructions": [
    {
      "target": 0,
      "type": "h"
    }
  ]
}
"""

program = Program.parse_raw(jaqcd_string)
print(program)

"""
braketSchemaHeader=BraketSchemaHeader(name='braket.ir.jaqcd.program', version='1') instructions=[H(target=0, type=<Type.h: 'h'>), CNot(control=0, target=1, type=<Type.cnot: 'cnot'>)] results=[Expectation(observable=['x'], targets=[0], type=<Type.expectation: 'expectation'>)] basis_rotation_instructions=[H(target=0, type=<Type.h: 'h'>)]
"""

annealing_string = """
{
  "type": "QUBO",
  "linear": {0: 0.3, 4: -0.3},
  "quadratic": {"0,5": 0.667}
}
"""

problem = Problem.parse_raw(annealing_string)
print(problem)

"""
braketSchemaHeader=BraketSchemaHeader(name='braket.ir.annealing.problem', version='1') type=<ProblemType.QUBO: 'QUBO'>, linear={0: 0.3, 4: -0.3}, quadratic={'0,5': 0.667}
"""

Documentation

Detailed documentation, including the API reference, can be found on Read the Docs.

You can also generate the docs from source. First, install tox:

pip install tox

To build the Sphinx docs, run the following command in the root repo directory:

tox -e docs

You can then find the generated HTML files in build/documentation/html.

Testing

Make sure to install test dependencies first:

pip install -e "amazon-braket-schemas-python[test]"

To run the unit tests:

tox -e unit-tests

You can also pass in various pytest arguments to run selected tests:

tox -e unit-tests -- your-arguments

To run linters and doc generators and unit tests:

tox

For more information, please see pytest usage.

License

This project is licensed under the Apache-2.0 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

amazon-braket-schemas-1.1.0.post2.tar.gz (23.0 kB view details)

Uploaded Source

Built Distribution

File details

Details for the file amazon-braket-schemas-1.1.0.post2.tar.gz.

File metadata

  • Download URL: amazon-braket-schemas-1.1.0.post2.tar.gz
  • Upload date:
  • Size: 23.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.3.0 pkginfo/1.6.1 requests/2.25.1 setuptools/51.1.0 requests-toolbelt/0.9.1 tqdm/4.55.1 CPython/3.8.7

File hashes

Hashes for amazon-braket-schemas-1.1.0.post2.tar.gz
Algorithm Hash digest
SHA256 89fe76dccf4a64e0147f0181809ab19ca4b81101565bb328ed88e5f83a79254b
MD5 86defa344d0c88b8e6758799934283f1
BLAKE2b-256 fbb51a27577ad4ba2429e8c5239463490a6c21e76d9eaff10ba4d0e975278f69

See more details on using hashes here.

File details

Details for the file amazon_braket_schemas-1.1.0.post2-py3-none-any.whl.

File metadata

  • Download URL: amazon_braket_schemas-1.1.0.post2-py3-none-any.whl
  • Upload date:
  • Size: 60.6 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.3.0 pkginfo/1.6.1 requests/2.25.1 setuptools/51.1.0 requests-toolbelt/0.9.1 tqdm/4.55.1 CPython/3.8.7

File hashes

Hashes for amazon_braket_schemas-1.1.0.post2-py3-none-any.whl
Algorithm Hash digest
SHA256 a763f962faab27cea36002df263c30919a6ff37e16033a3e7c3f6fc427a66aa4
MD5 a2ced216e8f89cb07a7d6b9d93e18592
BLAKE2b-256 188cbeb0a5c6a3e7af01c6d5ba69e4561e7ac4984557fe5e903ee2703b7ae8bd

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