{"categories":[{"label":"Scientific/Engineering","url":"https://skillfed.io/packages/category/scientific-engineering/3"}],"enrichment":{"capability":"Qiskit is an open-source SDK for building and executing quantum circuits, operators, and primitives on quantum computers and simulators.","skillfed_tags":["quantum-computing","circuit-simulation","hardware-abstraction"],"use_cases":["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"],"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.\n\nThe 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.","worth_installing":"Yes. Qiskit is actively maintained, has no known vulnerabilities, supports Python 3.10\u20133.14, 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."},"id":"qiskit","links":{"html":"https://skillfed.io/packages/qiskit","md":"https://skillfed.io/packages/qiskit.md","pypi":"https://pypi.org/project/qiskit/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-08-13","license_spdx":"Apache-2.0","license_treatment":"permissive","name":"qiskit","python_support":"supports_current","summary":"An open-source SDK for working with quantum computers at the level of extended quantum circuits, operators, and primitives."},"popularity":{"monthly_downloads":1462854,"position":3879,"tier":"top_5000"},"security":{"n_vulnerabilities":0},"version":"2.5.2"}