pyscf
PySCF: Python-based Simulations of Chemistry Framework
Decision gist · record as of 2026-08-14
Yes, if you need quantum chemistry simulations in Python. PySCF is actively maintained, has no known vulnerabilities, carries a permissive license, and offers a comprehensive framework for electronic structure calculations. Medium install friction is manageable for most platforms via prebuilt wheels. Not suitable if you need only classical molecular dynamics or if your target molecules are extremely large.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires C compiler and development headers for building from source; prebuilt wheels available for common platforms.
- Supports Python 3.7 through 3.14.
- Medium install friction due to compiled C components and multiple platform wheels (macOS x86_64/arm64, Linux aarch64/x86_64).
License · maintenance · safety
Apache-2.0 (permissive) — Apache-2.0 permissive license allows commercial and private use with minimal restrictions; suitable for research, academic, and commercial applications.
last release 2026-07-18 (27 days) · last repo commit 2026-08-11 · 1,650 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 432,442 downloads/mo, #6,709 on PyPI
Alternatives
Verify before relying
pip install pyscf
import pyscf
mol = pyscf.M(atom='H 0 0 0; H 0 0 1', basis='sto-3g')
mf = mol.RHF().run()- Whether pyscf-forge and optional extensions (dispersion, dmrgscf, fciqmc, etc.) are maintained at the same cadence as the base package
- Performance characteristics and scalability limits for large molecular systems
- Specific external library requirements for density functional evaluation (Libxc, XCFun) beyond the listed runtime dependencies
What it is and what it does
PySCF is a Python framework for simulating quantum chemistry and computing electronic structure properties of molecules. It provides implementations of core quantum chemistry methods including Hartree-Fock, density functional theory, and post-Hartree-Fock approaches, allowing researchers to model molecular systems and extract properties like energies, densities, and response functions. The package depends on numpy, scipy, h5py, setuptools, and psutil for numerical computation, data I/O, and system resource management.
The framework is designed for both research and educational use, with a modular architecture that allows users to combine different computational methods. Extensions are available as separate packages for specialized methods. Installation is straightforward via pip with prebuilt wheels for macOS and Linux, though compilation from source requires a C compiler. The project maintains active development with regular releases and a documented API.
Use it for
- Computing ground-state and excited-state energies of molecules using various quantum chemistry methods
- Developing and testing new electronic structure algorithms by leveraging PySCF's modular structure and Python interface
- Performing density functional theory calculations for molecular property prediction in research workflows
- Educational demonstrations of quantum chemistry concepts and computational methods in academic settings
- Integrating quantum chemistry calculations into larger computational pipelines for materials or drug discovery
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you need quantum chemistry simulations in Python.
PySCF is actively maintained, has no known vulnerabilities, carries a permissive license, and offers a comprehensive framework for electronic structure calculations. Medium install friction is manageable for most platforms via prebuilt wheels. Not suitable if you need only classical molecular dynamics or if your target molecules are extremely large.
Install
pyscf on PyPI
Before you install
Medium install friction due to compiled C components and multiple platform wheels (macOS x86_64/arm64, Linux aarch64/x86_64). Active maintenance with a release 27 days old and recent commits; 1650 repository stars indicate established community use.
Requires C compiler and development headers for building from source; prebuilt wheels available for common platforms. Supports Python 3.7 through 3.14.
License in practice
Apache-2.0 permissive license allows commercial and private use with minimal restrictions; suitable for research, academic, and commercial applications.
Quickstart
pip install pyscf
import pyscf
mol = pyscf.M(atom='H 0 0 0; H 0 0 1', basis='sto-3g')
mf = mol.RHF().run()Verify before relying
- Whether pyscf-forge and optional extensions (dispersion, dmrgscf, fciqmc, etc.) are maintained at the same cadence as the base package
- Performance characteristics and scalability limits for large molecular systems
- Specific external library requirements for density functional evaluation (Libxc, XCFun) beyond the listed runtime dependencies
Package facts
| License | Apache-2.0 permissive |
| Python support | Supports the current Python release >=3.7 |
| Install friction | Medium. Platform-specific wheel |
| Runtime dependencies | 5 packagesnumpyscipyh5pysetuptoolspsutil |
| Maintenance | Actively maintained 27 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 432,442 / month, #6,709 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableIntended Audience :: DevelopersIntended Audience :: Science/ResearchLicense :: OSI Approved :: Apache Software LicenseOperating System :: MacOSOperating System :: POSIXOperating System :: UnixProgramming Language :: CProgramming Language :: PythonProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Programming Language :: Python :: 3.7Programming Language :: Python :: 3.8Programming Language :: Python :: 3.9Topic :: Scientific/EngineeringTopic :: Software Development |
Evidence: pyscf-2.14.0-py3-none-macosx_10_9_x86_64.whl; pyscf-2.14.0-py3-none-macosx_11_0_arm64.whl; pyscf-2.14.0-py3-none-manylinux2014_aarch64.manylinux_2_17_aarch64.whl; pyscf-2.14.0-py3-none-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Tags
Let your AI agent find packages like this
Example. Real query, live index.
You found this page by searching. An agent finds it by wishing: SkillFed indexes 14,416 PyPI packages by what they can do, searchable in plain language.
wish › “quantum chemistry simulations”
- pyscfPySCF is a Python framework for quantum chemistry simulations,…
- openfermionOpenFermion compiles and analyzes quantum algorithms to simulate…
- aseASE provides Python tools for setting up, running, and analyzing…
Give your agent the search over MCP, or paste the wish link into any chat.
More Software Development packages
Provides backported and experimental type hints for Python 3.9+, allowing use of newer typing features on older Python versions and enabling early experimentation with type system PEPs before they enter the standard library.
NumPy provides an N-dimensional array object and a comprehensive suite of mathematical, linear algebra, Fourier transform, and random number functions for scientific computing in Python.
FastAPI is a Python web framework for building REST APIs using type hints, with automatic request validation, serialization, and interactive API documentation.
Provides a way to document function parameters, class attributes, return types, and variables inline using Python's `Annotated` type hint syntax instead of traditional docstrings.
Typer builds command-line applications from Python functions using type hints, automatically generating help text, argument parsing, and shell completion.
Install it if you are building CLIs in Python.
Distlib provides low-level packaging utilities for building, distributing, and managing Python software—including metadata handling, version specifiers, wheel support, script installation, and dependency resolution.
See also openfermionpyscf · openfermion · alchemlyb · ase · chemprop · pennylane · dpdata · dscribe · pdb2pqr · chgnet