---
id: qiskit
version: "2.5.2"
license: Apache-2.0
license_treatment: permissive
maintenance: active
---

# qiskit — An open-source SDK for working with quantum computers at the level of extended quantum circuits, operators, and primitives.

License: permissive · Maintenance: active · Downloads: 1.5M/mo

## What it is and what it does

Qiskit is a Python SDK for quantum computing that lets you define quantum circuits using standard gates (Hadamard, CNOT, phase gates), compose them into larger programs, and execute them on simulators or real quantum hardware. The core library provides QuantumCircuit for circuit construction, quantum operators and information toolbox for advanced state manipulation, and two main execution primitives: Sampler (for sampling measurement outcomes) and Estimator (for computing expectation values of observables). It also includes a transpiler that optimizes and maps circuits to specific hardware constraints like basis gates and qubit connectivity.

The library depends on numpy, scipy, rustworkx, dill, stevedore, and typing-extensions. It exposes both a Python API (primary interface) and a C API for lower-level access to Qiskit's Rust-based internal data model. Typical workflows involve building a circuit, optionally transpiling it for target hardware, and running it through a primitive to get results. For scaling beyond classical simulation, you connect to real quantum hardware through provider packages that implement the BaseSamplerV2 and BaseEstimatorV2 interfaces.

Use it for:

- Design and simulate quantum algorithms locally using statevector simulation before running on real hardware
- Optimize quantum circuits for specific hardware constraints using the transpiler with custom basis gates and coupling maps
- Compute expectation values of quantum observables using the Estimator primitive for variational algorithms
- Sample measurement outcomes from quantum circuits to study probability distributions and quantum state properties
- Build entangled states and test quantum phenomena like GHZ states in a controlled environment

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

Qiskit is an open-source SDK for building and executing quantum circuits, operators, and primitives on quantum computers and simulators.

Yes. Qiskit is actively maintained, has no known vulnerabilities, supports Python 3.10–3.14, and is the standard entry point for quantum circuit programming in Python. Install it if you're learning quantum computing, prototyping algorithms, or need to integrate with quantum hardware ecosystems. Medium install friction is typical for scientific packages with compiled components.

## Install

pip install qiskit
uv add qiskit
poetry add qiskit

## Installing qiskit

Before you install: Medium install friction due to compiled wheels for multiple platforms (macOS, Linux, Windows, ARM). Active maintenance with release 1 day ago and 7706 repository stars. Requires Python 3.10 or later.

License in practice: Apache-2.0 permissive license allows free use, modification, and distribution in commercial and private projects with minimal restrictions.

Quickstart:

pip install qiskit

from qiskit import QuantumCircuit
import numpy as np

qc = QuantumCircuit(3)
qc.h(0)
qc.p(np.pi / 2, 0)
qc.cx(0, 1)
qc.cx(0, 2)

Requires Python 3.10 or later; Rust compiler needed only for building from source, not for pip installation.

Verify before relying:

- Performance characteristics and simulation limits for large quantum circuits
- Integration requirements with specific quantum hardware providers beyond documented examples

## Package facts

- License: Apache-2.0 (permissive)
- Python support: supports_current
- Install friction: medium
- Maintenance: active
- Downloads: 1.5M/month (top 5,000 on PyPI)
- Known vulnerabilities: none known

## Tags

quantum circuit programming, quantum computing sdk, quantum circuit design, quantum simulator, quantum gates and operators, quantum algorithm development, quantum transpiler, quantum-computing, circuit-simulation, hardware-abstraction

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