[](https://github.com/Qiskit/qiskit-serverless/releases)
[](https://github.com/Qiskit/qiskit-serverless/actions/workflows/client-verify.yaml)
[](https://github.com/qiskit-community/quantum-prototype-template/blob/main/LICENSE.txt)
[](https://github.com/psf/black)
[](https://www.python.org/)
[](https://github.com/Qiskit/qiskit)
# Qiskit Serverless client
# Installation
```shell
pip install qiskit_serverless
```
## Documentation
Full docs can be found at https://qiskit.github.io/qiskit-serverless/
## Usage
### Step 1: write funtion in ./src/function.py
```python
from qiskit_serverless import distribute_task, get, get_arguments, save_result
from qiskit import QuantumCircuit
from qiskit.circuit.random import random_circuit
from qiskit.primitives import StatevectorSampler as Sampler
from qiskit.quantum_info import SparsePauliOp
# 1. let's annotate out function to convert it
# to distributed async function
# using `distribute_task` decorator
@distribute_task()
def distributed_sample(circuit: QuantumCircuit):
"""Calculates quasi dists as a distributed function."""
return Sampler().run([(circuit)]).result()[0].data.meas.get_counts()
# 2. our program will have one arguments
# `circuits` which will store list of circuits
# we want to sample in parallel.
# Let's use `get_arguments` funciton
# to access all program arguments
arguments = get_arguments()
circuits = arguments.get("circuits", [])
# 3. run our functions in a loop
# and get execution references back
function_references = [
distributed_sample(circuit)
for circuit in circuits
]
# 4. `get` function will collect all
# results from distributed functions
collected_results = get(function_references)
# 5. `save_result` will save results of program execution
# so we can access it later
save_result({
"quasi_dists": collected_results
})
```
### Step 2: run function
```python
from qiskit_serverless import ServerlessClient, QiskitFunction
from qiskit.circuit.random import random_circuit
client = ServerlessClient(
token="<TOKEN>",
host="<GATEWAY_ADDRESS>",
)
# create function
function = QiskitFunction(
title="Quickstart",
entrypoint="program.py",
working_dir="./src"
)
client.upload(function)
# create inputs to our program
circuits = []
for _ in range(3):
circuit = random_circuit(3, 2)
circuit.measure_all()
circuits.append(circuit)
# run program
my_function = client.get("Quickstart")
job = my_function.run(circuits=circuits)
```
### Step 3: monitor job status
```python
job.status()
# 'DONE'
# or get logs
job.logs()
```
### Step 4: get results
```python
job.result()
# {'quasi_dists': [
# {'101': 902, '011': 66, '110': 2, '111': 37, '100': 17},
# {'100': 626, '101': 267, '001': 49, '000': 82},
# {'010': 145, '100': 126, '011': 127, '001': 89, '110': 173, '111': 166, '000': 94, '101': 104}
# ]}
```
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"description": "[](https://github.com/Qiskit/qiskit-serverless/releases)\n[](https://github.com/Qiskit/qiskit-serverless/actions/workflows/client-verify.yaml)\n[](https://github.com/qiskit-community/quantum-prototype-template/blob/main/LICENSE.txt)\n[](https://github.com/psf/black)\n[](https://www.python.org/)\n[](https://github.com/Qiskit/qiskit)\n\n# Qiskit Serverless client\n\n\n\n# Installation\n\n```shell\npip install qiskit_serverless\n```\n\n## Documentation\n\nFull docs can be found at https://qiskit.github.io/qiskit-serverless/\n\n## Usage\n\n### Step 1: write funtion in ./src/function.py\n\n```python\nfrom qiskit_serverless import distribute_task, get, get_arguments, save_result\n\nfrom qiskit import QuantumCircuit\nfrom qiskit.circuit.random import random_circuit\nfrom qiskit.primitives import StatevectorSampler as Sampler\nfrom qiskit.quantum_info import SparsePauliOp\n\n# 1. let's annotate out function to convert it\n# to distributed async function\n# using `distribute_task` decorator\n@distribute_task()\ndef distributed_sample(circuit: QuantumCircuit):\n \"\"\"Calculates quasi dists as a distributed function.\"\"\"\n return Sampler().run([(circuit)]).result()[0].data.meas.get_counts()\n\n# 2. our program will have one arguments\n# `circuits` which will store list of circuits\n# we want to sample in parallel.\n# Let's use `get_arguments` funciton\n# to access all program arguments\narguments = get_arguments()\ncircuits = arguments.get(\"circuits\", [])\n\n# 3. run our functions in a loop\n# and get execution references back\nfunction_references = [\n distributed_sample(circuit)\n for circuit in circuits\n]\n\n# 4. `get` function will collect all\n# results from distributed functions\ncollected_results = get(function_references)\n\n# 5. `save_result` will save results of program execution\n# so we can access it later\nsave_result({\n \"quasi_dists\": collected_results\n})\n```\n\n\n### Step 2: run function\n\n```python\nfrom qiskit_serverless import ServerlessClient, QiskitFunction\nfrom qiskit.circuit.random import random_circuit\n\nclient = ServerlessClient(\n token=\"<TOKEN>\",\n host=\"<GATEWAY_ADDRESS>\",\n)\n\n# create function\nfunction = QiskitFunction(\n title=\"Quickstart\",\n entrypoint=\"program.py\",\n working_dir=\"./src\"\n)\nclient.upload(function)\n\n# create inputs to our program\ncircuits = []\nfor _ in range(3):\n circuit = random_circuit(3, 2)\n circuit.measure_all()\n circuits.append(circuit)\n\n# run program\nmy_function = client.get(\"Quickstart\")\njob = my_function.run(circuits=circuits)\n```\n\n### Step 3: monitor job status\n\n```python\njob.status()\n# 'DONE'\n\n# or get logs\njob.logs()\n```\n\n\n### Step 4: get results\n\n```python\njob.result()\n# {'quasi_dists': [\n# {'101': 902, '011': 66, '110': 2, '111': 37, '100': 17},\n# {'100': 626, '101': 267, '001': 49, '000': 82},\n# {'010': 145, '100': 126, '011': 127, '001': 89, '110': 173, '111': 166, '000': 94, '101': 104}\n# ]}\n```\n",
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