Skip to main content
Pre-release

This release is a pre-release and may not be stable for production use.

QiskitFlow. Reproducible quantum experiments.

logo

Platform for tracking, sharing and running quantum experiments in a clean and understandable for developers, researchers and students manner.

Alpha release is in the works. Files from hackathon project are located in hackathon folder

General overview

flow

Hot to run

Flow

Flow of actions while using QiskitFlow is following:

  • Install QiskitFlow if not installed yet
  • Annotate your code with Experiment abstraction QiskitFlow library provides
  • Run your code as usual: QiskitFlow will write metadata of your experiment execution in local folder
  • You can review experiments using CLI interface

We are tracking metrics, parameters, state vectors and counts of experiments. Artifacts, circuits, sourcecode and other useful things are on their way.

Note: qiskitflow creates _experiments folder in place of execution of code, where all serialized information is stored in json format, so it's easy to track it even in git

Installation

pip install qiskitflow

Code annotation

Library for quantum programs annotation

Sample example of annotation:

from qiskitflow import Experiment

with Experiment("awesome_experiment") as experiment:

    # your quantum program here!
    
    experiment.write_metric("test metric", 0.1)
    experiment.write_metric("test metric 2", 2)

    experiment.write_parameter("test parameter", "test parameter value")
    experiment.write_parameter("test parameter 2", "test paraeter value 2")

    experiment.write_counts("measurement", {"00": 1024, "11": 0})
Full example with quantum teleportation

import numpy as np
import time
from qiskit import QuantumCircuit, QuantumRegister, ClassicalRegister, execute, BasicAer, IBMQ
from qiskit.visualization import plot_histogram, plot_bloch_multivector
from qiskit.extensions import Initialize
from qiskit_textbook.tools import random_state, array_to_latex

from qiskitflow import Experiment

with Experiment("quantum teleportation") as experiment:
    start_time = time.time()
    
    # conduct experiment as usual
    psi = random_state(1)
    init_gate = Initialize(psi)
    init_gate.label = "init"
    inverse_init_gate = init_gate.gates_to_uncompute()

    qr = QuantumRegister(3, name="q")
    crz = ClassicalRegister(1, name="crz")
    crx = ClassicalRegister(1, name="crx")
    qc = QuantumCircuit(qr, crz, crx)
    qc.append(init_gate, [0])
    qc.barrier()
    create_bell_pair(qc, 1, 2)
    qc.barrier()
    alice_gates(qc, 0, 1)
    measure_and_send(qc, 0, 1)
    bob_gates(qc, 2, crz, crx)
    qc.append(inverse_init_gate, [2])
    cr_result = ClassicalRegister(1)
    qc.add_register(cr_result)
    qc.measure(2,2)
    backend_name = "qasm_simulator"
    backend = BasicAer.get_backend(backend_name)
    counts = execute(qc, backend, shots=1024).result().get_counts()
    
    end_time = time.time()
    
    runtime = end_time - start_time
    
    # qiskitflow =========

    # log parameters used
    experiment.write_parameter("backend name", backend_name)
    # log metrics of experiment
    experiment.write_metric("runtime", runtime)
    # log counts of experiment
    experiment.write_counts("experiment counts", counts)


CLI

List of experiment runs

qiskitflow runs [--search=<SEARCH_BY_RUN_ID>] [--experiment=<EXPERIMENT_NAME>] [--order_by=<METRIC_TO_ORDER_BY>] [--order_type=<asc or desc>]
experiments list screenshot

list

Experiment run information

qiskitflow run <RUN_ID>
experiment information screenshots

Experiment information info

Share experiment run

qiskitflow share <RUN_ID> --user=<USER> --password=<password> --host=<HOST> --port=<PORT>

Example for local backend server

qiskitflow share 86b6e7ba32f04d34b842a91079482454 --user=<USER> --password=<password> --host=http://localhost --port=8000
experiment share screenshots

Experiment information share


Examples

Jupyter notebook with quantum teleportation example

Run local

  1. Install docker compose
  2. Run
docker-compose up

UI

Screenshots

Experiment information ui

Metadata

Release files for qiskitflow 0.0.11a0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for qiskitflow 0.0.11a0
File Size Uploaded Provenance Actions
qiskitflow-0.0.11a0.tar.gz 12.5 kB Without provenance Details for qiskitflow-0.0.11a0.tar.gz

Built distribution (wheel)

Table of built distributions (wheels) for qiskitflow 0.0.11a0
File Interpreter ABI Platform Actions
qiskitflow-0.0.11a0-py3-none-any.whl Python 3 none any Details for qiskitflow-0.0.11a0-py3-none-any.whl

Total release size: 29.9 kB

Release files / qiskitflow-0.0.11a0.tar.gz

Download URL qiskitflow-0.0.11a0.tar.gz
Size 12.5 kB
Tags Source
SHA-256 checksum
How to use checksums
e0009796ee48351b27c63498566c60f3300bd7a31c9c31cbe8453580dc88a2f2
BLAKE2b-256 checksum
How to use checksums
79877321ea7e8191107a67abb5c953c9ed53ed175411469a6845d504b9bf5137
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.4.1 importlib_metadata/4.6.0 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.61.1 CPython/3.9.6

Release files / qiskitflow-0.0.11a0-py3-none-any.whl

Download URL qiskitflow-0.0.11a0-py3-none-any.whl
Size 17.3 kB
Tags Python 3
SHA-256 checksum
How to use checksums
222da840f953bee130027de4f7fca4eb83615a9cfc77ef61882f4d9df4a16ad6
BLAKE2b-256 checksum
How to use checksums
5e9b5a78110f577cc4a525f9d47fd4a00d97010dac7c3e38b4276b14a19325d1
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.4.1 importlib_metadata/4.6.0 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.61.1 CPython/3.9.6

Security for qiskitflow 0.0.11a0

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

To learn more about protecting yourself from malicious actors, visit our package security documentation.

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page