Skip to main content

naja-schematic (Python package)

Interactive schematic viewer for najaeda netlists: the naja-schematic WASM viewer, packaged with the Python backend that answers it from a live najaeda netlist.

naja-schematic demo: tracing an output port back to its drivers, then extending the schematic pin by pin

pip install naja-schematic

In a notebook (Jupyter, Google Colab, VSCode)

Try it in Colab: a walkthrough of every widget feature below, runnable as is. Then a real design: a RISC-V core.

from najaeda import netlist
import naja_schematic

netlist.load_primitives("xilinx")
top = netlist.load_verilog("design.v")

naja_schematic.show()          # interactive view in the cell output

The view is answered from the netlist in the running kernel, so it shows the design as the notebook has built or edited it so far; call show() again after an edit for a fresh view. Diagnoses (e.g. from a formal equivalence check) can be overlaid:

view = naja_schematic.show()
view.annotate([{"kind": "instance", "path": ["u_sub"], "severity": "error",
                "message": "not equivalent", "source": "kepler-formal"}])
view

The view and your najaeda code can point each other at instances. show_instance() takes a najaeda Instance, a list of instance ids (as Instance.pathIDs) or a list of instance names (a plain string is one name, never split on /, since escaped names can contain it). Anonymous instances have no name to go by: reach them with an Instance or ids. The viewer opens its tree down to that instance, selects it, and draws it alone in the schematic. Each pin there is open, so you can click one to add its net and grow the schematic from the instance. In the other direction, the instance selected in the viewer (click it in the tree or the schematic) is available as a najaeda Instance:

view.show_instance(netlist.get_instance_by_path(["u_sub", "u_and"]))
view.show_instance(["u_sub", "u_and"]) # same thing

inst = view.selected                   # what the user clicked, or None
inst.get_model_name()

view.on_select(lambda inst: print("selected", inst))

naja_schematic.show(inst) (or show(["u_sub", "u_and"])) starts a new view on it. After editing or reloading the design in later cells, view.design_changed() refreshes an existing view in place.

From a shell

naja-schematic --verilog design.v --liberty cells.lib --open
naja-schematic --sv top.sv --top top --diagnosis report.json --open

serves the viewer page and its WebSocket on http://localhost:8081/ and opens it in a browser. --stdio speaks the same protocol as JSON lines on stdin/stdout instead, for a host (e.g. an editor extension) that relays messages itself. naja-schematic --help lists every option.

From an application that already holds the design

A tool that loads and edits the design itself (with najaeda or the raw naja bindings) can serve the viewer on it without loading anything:

import threading, naja_schematic

design_lock = threading.RLock()   # held by the host while it edits the design
server = naja_schematic.ViewerServer(lock=design_lock)   # port 0: any free port
server.start()
server.open_browser()             # or hand server.url to the user

server.annotate(items)            # diagnosis overlay, kept across reloads
server.show_instance([3, 7])      # instance ids, names, or a najaeda Instance
server.on_select(lambda id_path, path: print("selected", path))
with server.replacing_design():   # holds design_lock, then viewers reload
    netlist.load_verilog("other.v")
server.stop()

Viewer requests are answered on a background thread while lock is held (or pass run= to answer them on a thread of your choosing). The page's URL carries a random access token, and other web pages can't connect to the WebSocket. Once the design is replaced, anything a viewer asked about or selected in the old one is ignored, even if it arrives late or names instance ids the new design reuses.

Development

The viewer bundle (naja_schematic/static/naja-schematic.js) is built from the C++ sources, not checked in. From the repository root:

emcmake cmake -S . -B build-wasm-module -DCMAKE_BUILD_TYPE=Release -DNAJA_SCHEMATIC_WASM_MODULE=ON
cmake --build build-wasm-module
export NAJA_SCHEMATIC_BUNDLE=$PWD/build-wasm-module/naja-schematic.js   # or copy it into static/
pip install -e "python[test]" && pytest python/tests

Releases are built and published by .github/workflows/python-package.yml on a v<version> tag (e.g. v0.1.0).

Metadata

Release files for naja-schematic 0.1.9

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

Source distribution (sdist)

Source distribution for naja-schematic 0.1.9
File Size Uploaded
naja_schematic-0.1.9.tar.gz 847.7 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for naja-schematic 0.1.9
File Interpreter ABI Platform
naja_schematic-0.1.9-py3-none-any.whl Python 3 none any Details

Total release size: 1.7 MB

Release files / naja_schematic-0.1.9.tar.gz

Download URL naja_schematic-0.1.9.tar.gz
Size 847.7 kB
Tags Source
SHA-256 checksum
How to use checksums
6dcc13215c03289b271e02b85c6267f3b499a05c1163b93930b09e72310a2642
BLAKE2b-256 checksum
How to use checksums
4fd77186e43904e53416320fe406586e9bbc5a3e290cc05a7abe06cd4a7be499
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/7.0.0 CPython/3.13.14

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.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Oct 6, 2026.

Transparency log

Release files / naja_schematic-0.1.9-py3-none-any.whl

Download URL naja_schematic-0.1.9-py3-none-any.whl
Size 840.1 kB
Tags Python 3
SHA-256 checksum
How to use checksums
34169cfa2583f36e4061b2b95f1ec017df167295647647383befb844b20f0f3d
BLAKE2b-256 checksum
How to use checksums
eaf4d95511b17c43c407d6df55fe9e8296e8f2455e82c848b034da77e91efc9a
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/7.0.0 CPython/3.13.14

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.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Oct 6, 2026.

Transparency log

Release history Release notifications | RSS feed

0.2.0

2 release files

This release

0.1.9 This release

2 release files

0.1.8

2 release files

0.1.7

2 release files

0.1.6

2 release files

0.1.4

2 release files

0.1.3

2 release files

0.1.2

2 release files

0.1.1

2 release files

0.1.0

2 release files

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