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author description ms.author ms.date ms.service ms.subservice ms.topic title uid
KittyYeungQ
This document provides a basic guide to submit and run Q# applications in Azure Quantum using Python.
kitty
02/01/2021
azure-quantum
core
conceptual
Submit jobs to Azure Quantum with Python
microsoft.quantum.submit-jobs.python

Submit jobs to Azure Quantum with Python

This document provides a basic guide to submit and run Q# applications in Azure Quantum using Python.

Prerequisites

  • An Azure Quantum workspace in your Azure subscription. To create a workspace, see Create an Azure Quantum workspace.
  • The latest version of the Quantum Development Kit for Python.

Follow the installation steps in the provided link to install Python and the current version of the IQ# kernel, which powers the Q# Jupyter Notebook and Python experiences.

Quantum computing with Q# and Python

  1. The Python environment in the conda environment that you created earlier already includes the qsharp Python package. Make sure you are running your Python script from a terminal where this conda environment is activated.

  2. If you've never used Q# with Python, follow the steps in Create your first Q# program with Python.

  3. Write your Q# operations in a *.qs file. When running import qsharp in Python, the IQ# kernel will automatically detect any .qs files in the same folder, compile them, and report any errors. If compilation is successful, those Q# operations will become available for use directly from within Python.

    • For example, the contents of your .qs file could look something like this:

      namespace Test {
    open Microsoft.Quantum.Intrinsic;
    open Microsoft.Quantum.Measurement;
    open Microsoft.Quantum.Canon;

    operation GenerateRandomBits(n : Int) : Result[] {
        use qubits = Qubit[n];
        ApplyToEach(H, qubits);
        return MultiM(qubits);
    }
}

  4. Create a Python script in the same folder as your *.qs file. Azure Quantum functionality is available by running import qsharp.azure and then calling the Python commands to interact with Azure Quantum. For reference, see the complete list of qsharp.azure Python commands. You'll need the resource ID of your Azure Quantum workspace in order to connect. (The resource ID can be found on your workspace page in the Azure Portal.)

    If your workspace was created in an Azure region other than "West US", you also need to specify this as the location parameter to qsharp.azure.connect().

    For example, your Python script could look like this:

    import qsharp
import qsharp.azure
from Test import GenerateRandomBits

qsharp.azure.connect(
   resourceId="/subscriptions/.../Microsoft.Quantum/Workspaces/WORKSPACE_NAME",
   location="West US")
qsharp.azure.target("ionq.simulator")
result = qsharp.azure.execute(GenerateRandomBits, n=3, shots=1000, jobName="Generate three random bits")
print(result)

    where GenerateRandomBits is the Q# operation in a namespace Test that is defined in your *.qs file, n=3 is the parameter to be passed to that operation, shots=1000 (optional) specifies the number of repetitions to perform, and jobName="Generate three random bits" (optional) is a custom job name to identify the job in the Azure Quantum workspace.

  5. Run your Python script by running the command python test.py, where test.py is the name of your Python file. If successful, you should see your job results displayed to the terminal. For example:

    {'[0,0,0]': 0.125, '[1,0,0]': 0.125, '[0,1,0]': 0.125, '[1,1,0]': 0.125, '[0,0,1]': 0.125, '[1,0,1]': 0.125, '[0,1,1]': 0.125, '[1,1,1]': 0.125}

  6. To view the details of all jobs in your Azure Quantum workspace, run the command qsharp.azure.jobs():

    >>> qsharp.azure.jobs()
[{'id': 'f4781db6-c41b-4402-8d7c-5cfce7f3cde4', 'name': 'GenerateRandomNumber 3 qubits', 'status': 'Succeeded', 'provider': 'ionq', 'target': 'ionq.simulator', 'creation_time': '2020-07-17T21:45:43.4405253Z', 'begin_execution_time': '2020-07-17T21:45:54.09Z', 'end_execution_time': '2020-07-17T21:45:54.101Z'}, {'id': '1b03cc74-b5d5-4ffa-81db-465f08ae6cd0', 'name': 'GenerateRandomBit', 'status': 'Succeeded', 'provider': 'ionq', 'target': 'ionq.simulator', 'creation_time': '2020-07-21T19:44:17.1065156Z', 'begin_execution_time': '2020-07-21T19:44:25.85Z', 'end_execution_time': '2020-07-21T19:44:25.858Z'}]

  7. To view the detailed status of a particular job, pass the job ID to qsharp.azure.status() or qsharp.azure.output(), for example:

    >>> qsharp.azure.status('1b03cc74-b5d5-4ffa-81db-465f08ae6cd0')
{'id': '1b03cc74-b5d5-4ffa-81db-465f08ae6cd0', 'name': 'GenerateRandomBit', 'status': 'Succeeded', 'provider': 'ionq', 'target': 'ionq.simulator', 
'creation_time': '2020-07-21T19:44:17.1065156Z', 'begin_execution_time': '2020-07-21T19:44:25.85Z', 'end_execution_time': '2020-07-21T19:44:25.858Z'}

>>> qsharp.azure.output('1b03cc74-b5d5-4ffa-81db-465f08ae6cd0')
{'0': 0.5, '1': 0.5}

Next steps

Now that you know how to submit jobs to Azure Quantum, you can try to run the different samples we have available or try to submit your own projects.