kfactory
KLayout API implementation of gdsfactory
Decision gist · record as of 2026-08-14
Yes, if you are designing photonic or electronic chips and want a Python-native parametric layout framework. The active maintenance, low install friction, and rich feature set (routing, schematics, verification) make it a solid choice for chip design workflows. Verify the license treatment before use in proprietary contexts, and confirm klayout system dependencies match your environment.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.12 or later; klayout system dependency may need separate installation depending on your platform.
- Low friction; pure Python wheel with 18 runtime dependencies including well-maintained packages like pydantic, loguru, and scipy.
- Active maintenance with a release 18 days ago.
License · maintenance · safety
(unclear) — License treatment is unclear in the fact sheet; the description excerpt mentions MIT licensing, but the metadata does not confirm this. Verify the actual license before adopting in a commercial or restricted context.
last release 2026-07-27 (18 days)
0 known vulnerabilities (OSV.dev, 2026-08-14) · 242,878 downloads/mo, #8,833 on PyPI
Alternatives
Verify before relying
pip install kfactory
import kfactory as kf
@kf.cell
def my_waveguide() -> kf.KCell:
return kf.KCell(name="waveguide")- Whether the MIT license mentioned in the description excerpt is the authoritative license for this version
- Whether klayout requires system-level installation or is bundled with the package
- Performance characteristics and scalability limits for large chip designs
- Compatibility guarantees with specific KLayout versions
What it is and what it does
KFactory is a Python framework for designing photonic and electronic chip layouts, built on KLayout's C++ geometry engine. It abstracts chip design into parametric cells that can be cached and reused, provides routing algorithms for optical and electrical paths, and supports cross-section definitions for waveguide profiles. The framework integrates schematic-driven workflows with netlist extraction and layout-vs-schematic verification, allowing designers to move between logical schematics and physical layouts.
The package works with both integer (DBU) and floating-point (µm) coordinate systems, includes Jupyter integration for live preview in KLayout, and bundles a PDK system for packaging technology definitions. It requires Python 3.12 or later and depends on 18 runtime packages spanning geometry (scipy, rectangle-packer), configuration (pydantic, ruamel-yaml), and version management (semver). No known security vulnerabilities are reported.
Use it for
- Design parametric photonic circuits with automatic cell deduplication and caching
- Route optical waveguides and electrical traces with Manhattan and all-angle primitives
- Define reusable cross-sections and automatically generate cladding layers via Minkowski sums
- Extract netlists from physical layouts and verify consistency with schematics
- Develop technology PDKs that bundle layers, factories, and design rules for reuse
- Interactively preview and edit chip layouts in Jupyter notebooks with KLive integration
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you are designing photonic or electronic chips and want a Python-native parametric layout framework.
The active maintenance, low install friction, and rich feature set (routing, schematics, verification) make it a solid choice for chip design workflows. Verify the license treatment before use in proprietary contexts, and confirm klayout system dependencies match your environment.
Install
kfactory on PyPI
Before you install
Low friction; pure Python wheel with 18 runtime dependencies including well-maintained packages like pydantic, loguru, and scipy. Active maintenance with a release 18 days ago. Requires Python 3.12 or later.
Requires Python 3.12 or later; klayout system dependency may need separate installation depending on your platform.
License in practice
License treatment is unclear in the fact sheet; the description excerpt mentions MIT licensing, but the metadata does not confirm this. Verify the actual license before adopting in a commercial or restricted context.
Quickstart
pip install kfactory
import kfactory as kf
@kf.cell
def my_waveguide() -> kf.KCell:
return kf.KCell(name="waveguide")Verify before relying
- Whether the MIT license mentioned in the description excerpt is the authoritative license for this version
- Whether klayout requires system-level installation or is bundled with the package
- Performance characteristics and scalability limits for large chip designs
- Compatibility guarantees with specific KLayout versions
Package facts
| License | Not declared unclear |
| Python support | Supports the current Python release >=3.12 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 18 packagesaenumcachetoolskfnetlistklayoutlogurupydanticpydantic-extra-typespydantic-settingspygit2rapidfuzzrectangle-packerrequestsruamel-yamlruamel-yaml-stringscipysemvertoolztyper |
| Maintenance | Actively maintained 18 days since the last release |
| First released | |
| Downloads | 242,878 / month, #8,833 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Operating System :: OS IndependentProgramming Language :: Python :: 3 :: OnlyProgramming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14 |
Evidence: kfactory-3.0.4-py3-none-any.whl
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See also elvis-lvs · gdsfactory · klayout · kwasm · salamandra · sax · gdsfactoryplus · gplugins · dvsim · lambdapdk