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Python API Client IBM Quantum Experience

The official API Client to use IBM Quantum Experience in Python.

This package can be use in Jupyter Notebook.

Installation

You can install me using pip or easy_install. For example, from the command line:

$ pip install IBMQuantumExperience

To install the package in Jupyter, you have to run in a Notebook:

import pip
def install(package):
   pip.main(['install', package])
install('IBMQuantumExperience')

or, if you want the standard output, one could even use the exclamation bang:

! pip install IBMQuantumExperience

Getting Started

Now it's time to begin doing real work with Python and IBM Quantum Experience.

First, import our API Client:

from IBMQuantumExperience import IBMQuantumExperience

Then, initialize your IBM Quantum Experience connection by supplying your token. You can obtain the token from Account area of Quantum Experience Platform in Personal Access Token section. An optional object knows as config has several extra options to customize, like the url of the API:

api = IBMQuantumExperience("token", config)

By default, the config parameter is defined like:

config = {
   "url": 'https://quantumexperience.ng.bluemix.net/api'
}

Methods

Codes

To get the information of a Code, including the last executions about this Code, you only need the codeId:

api.getCode("idCode")

To get the information about the last Codes, including the last executions about these Codes, you only need call:

api.getLastCodes()

Execution

To get all information (including the Code information) about a specific Execution of a Code, you only need the executionId:

api.getExecution("idExecution")

To get only the Result about a specific Execution of a Code, you only need the executionId:

api.getResultFromExecution("idExecution")

Running QASM 2.0

To execute a QASM 2.0 experiment:

api.runExperiment(qasm, device, shots, name=None, timeout=60)
  • qasm: The QASM 2.0 code to run. Eg: ``` qasm = 'OPENQASM 2.0;\n\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[5];\nh q[0];\ncx q[0],q[2];\nmeasure q[0] -> c[0];\nmeasure q[2] -> c[1];\n'``
  • device: Type of device to run the experiment. Only two option possibles: simulator or real. Eg: device = 'real'
  • shots: Number of shots of the experiments. Maximum 8192 shots. Eg: shots = 1024
  • name: Name of the experiment. This paramater is optional, by default the name will be 'Experiment #YmdHMS'. Eg: ```name = 'bell state experiment'``
  • timeout: Time to wait for the result. The maximum timeout is 300. If the timeout is reached, you obtain the executionId to get the result with the getResultFromExecution method in the future. Eg: ```timeout = 120``

Running Jobs QASM 2.0

To execute jobs about QASM 2.0 experiments:

api.runJobs(qasms, device, shots, maxCredits)
  • qasms: A list of objects with the QASM 2.0 information. Eg:
[
   { 'qasm': 'OPENQASM 2.0;\n\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[5];\nh q[0];\ncx q[0],q[2];\nmeasure q[0] -> c[0];\nmeasure q[2] -> c[1];\n'},
   { 'qasm': 'OPENQASM 2.0;\n\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[5];\nx q[0];\nmeasure q[0] -> c[0];\n'}
]
  • device: Type of device to run the experiment. Only two option possibles: simulator or real. Eg: device = 'real'
  • shots: Number of shots of the experiments. Maximum 8192 shots. Eg: shots = 1024
  • maxCredits: Maximum number of the credits to spend in the executions. If the executions are more expensives, the job is aborted. Eg: maxCredits = 3

To get job information:

api.getJob(idJob)
  • idJob: The identifier of the Job. Eg:
    idJob = '9de64f58316db3eb6db6da53bf9135ff'

Jupyter

To show the result and the code in Jupyter, you can use the next snippet that has some visual representation functions:

# USER, PLEASE SET CONFIG:
token="_TOKEN_"
# ---- UTILS -----
from IBMQuantumExperience import IBMQuantumExperience
from IPython.display import Image, display
import matplotlib.pyplot as plt
import numpy as np
%matplotlib inline
api = IBMQuantumExperience(token)
def showImageCode(idCode):
    if (idCode):
        code = api.getImageCode(idCode)
        if (code.get('error', None)):
            print("Fail to recovery the Code")
        else:
            display(Image(code['url']))
    else:
        print("Invalid IdCode")
def printBars(values, labels):
    N = len(values)
    ind = np.arange(N)  # the x locations for the groups
    width = 0.35       # the width of the bars
    fig, ax = plt.subplots()
    rects1 = ax.bar(ind, values, width, color='r')
    # add some text for labels, title and axes ticks
    ax.set_ylabel('Probabilities')
    ax.set_xticks(ind + (width/2.))
    ax.set_xticklabels(labels)
    def autolabel(rects):
        # attach some text labels
        for rect in rects:
            height = rect.get_height()
            ax.text(rect.get_x() + rect.get_width()/2., 1.05*height,
                    '%f' % float(height),
                    ha='center', va='bottom')
    autolabel(rects1)
    plt.show()
def showResultsByExecution(executionRaw):
    result = executionRaw.get('result', {})
    data = result.get('data', {})
    print('Execution in ' + executionRaw.get('deviceRunType', 'Unknown') + ' at ' + executionRaw.get('endDate', 'Unknown'))
    if (data.get('p', None)):
        values = data['p']['values']
        labels = data['p']['labels']
        printBars(values, labels)
    else:
        print("Not plotted. Results are: "+str(executionRaw))
def showResultsByIdExecution(idExecution):
    execution = api.getResultFromExecution(idExecution)
    if (execution.get('measure', None)):
        values = execution['measure']['values']
        labels = execution['measure']['labels']
        printBars(values, labels)
    else:
        print("Not plotted. Results are: "+str(execution))
def showLastCodes():
    codes = api.getLastCodes()
    for code in codes:
        print("--------------------------------")
        print("Code " + code.get('name', 'Unknown'))
        print(" ")
        showImageCode(code.get('id', None))
        print("------- Executions -------------")
        for execution in code.get('executions', []):
            showResultsByExecution(execution)

License

MIT License

Copyright (c) 2017 IBM Research Emergent Solutions

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

Reference

IBM Quantum Experience Tutorial

IBM Quantun Experience Community

OPENQASM

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A Python library for the Quantum Experience API

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