Skip to main content
PyPI version Apache 2.0 License Join the Matrix chat

najaeda is a Python package for loading, elaborating, navigating, editing, and analysing hardware designs from simple Verilog netlists to large SystemVerilog RTL cores.

from najaeda import netlist

# Load a gate-level Verilog design with a Liberty standard-cell library
netlist.load_liberty(['NangateOpenCellLibrary.lib'])
top = netlist.load_verilog('my_design.v')

# Navigate the hierarchy
for inst in top.get_child_instances():
    print(f'{inst.get_name()}{inst.get_model_name()}')

# Flat connectivity across hierarchy boundaries
for iterm in top.get_term('clk').get_equipotential().get_inst_terms():
    print(iterm)

# Edit: rename, reconnect, delete
top.get_net('old_name').set_name('new_name')

What you can do

  • Load Verilog and elaborated SystemVerilog designs, with or without Liberty standard-cell libraries

  • Navigate hierarchy, nets, and ports at any level of detail — instance-by-instance or flat via equipotentials

  • Edit netlists: rename instances and nets, disconnect and reconnect signals, delete logic

  • Analyse designs with the visitor API and export results to pandas for further processing or visualisation

Installation

pip install najaeda

Requires Python 3.10+. Wheels are published for Linux, macOS, and Windows.

Tutorials

Six hands-on notebooks — open any of them in Google Colab with no local install needed:

#

Topic

Colab

1

Getting started — load Verilog, navigate hierarchy, visualize

Open in Colab

2

Liberty primitives — load a synthesised design with standard cells

Open in Colab

3

Editing a netlist — rename, disconnect, reconnect, delete

Open in Colab

4

SystemVerilog elaboration — load and browse an elaborated SV design

Open in Colab

5

ibex RISC-V core — explore a real-world SV core, collect module stats

Open in Colab

6

Fanout analysis — compute fanout for every net, trace drivers, export to pandas

Open in Colab

License

Apache License 2.0. See the LICENSE file for details.

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

najaeda-0.7.19.tar.gz (15.3 MB view details)

Uploaded Source

Built Distributions

If you're not sure about the file name format, learn more about wheel file names.

najaeda-0.7.19-cp315-cp315-win_amd64.whl (5.7 MB view details)

Uploaded CPython 3.15Windows x86-64

najaeda-0.7.19-cp315-cp315-manylinux_2_28_x86_64.whl (9.3 MB view details)

Uploaded CPython 3.15manylinux: glibc 2.28+ x86-64

najaeda-0.7.19-cp315-cp315-manylinux_2_28_aarch64.whl (8.5 MB view details)

Uploaded CPython 3.15manylinux: glibc 2.28+ ARM64

najaeda-0.7.19-cp315-cp315-macosx_11_0_arm64.whl (5.5 MB view details)

Uploaded CPython 3.15macOS 11.0+ ARM64

najaeda-0.7.19-cp314-cp314t-manylinux_2_28_x86_64.whl (9.3 MB view details)

Uploaded CPython 3.14tmanylinux: glibc 2.28+ x86-64

najaeda-0.7.19-cp314-cp314t-macosx_11_0_arm64.whl (5.5 MB view details)

Uploaded CPython 3.14tmacOS 11.0+ ARM64

najaeda-0.7.19-cp314-cp314-win_amd64.whl (5.7 MB view details)

Uploaded CPython 3.14Windows x86-64

najaeda-0.7.19-cp314-cp314-manylinux_2_28_x86_64.whl (9.3 MB view details)

Uploaded CPython 3.14manylinux: glibc 2.28+ x86-64

najaeda-0.7.19-cp314-cp314-manylinux_2_28_aarch64.whl (8.5 MB view details)

Uploaded CPython 3.14manylinux: glibc 2.28+ ARM64

najaeda-0.7.19-cp314-cp314-macosx_11_0_arm64.whl (5.5 MB view details)

Uploaded CPython 3.14macOS 11.0+ ARM64

najaeda-0.7.19-cp313-cp313-win_amd64.whl (5.6 MB view details)

Uploaded CPython 3.13Windows x86-64

najaeda-0.7.19-cp313-cp313-manylinux_2_28_x86_64.whl (9.3 MB view details)

Uploaded CPython 3.13manylinux: glibc 2.28+ x86-64

najaeda-0.7.19-cp313-cp313-manylinux_2_28_aarch64.whl (8.5 MB view details)

Uploaded CPython 3.13manylinux: glibc 2.28+ ARM64

najaeda-0.7.19-cp313-cp313-macosx_11_0_arm64.whl (5.5 MB view details)

Uploaded CPython 3.13macOS 11.0+ ARM64

najaeda-0.7.19-cp312-cp312-win_amd64.whl (5.6 MB view details)

Uploaded CPython 3.12Windows x86-64

najaeda-0.7.19-cp312-cp312-manylinux_2_28_x86_64.whl (9.3 MB view details)

Uploaded CPython 3.12manylinux: glibc 2.28+ x86-64

najaeda-0.7.19-cp312-cp312-manylinux_2_28_aarch64.whl (8.5 MB view details)

Uploaded CPython 3.12manylinux: glibc 2.28+ ARM64

najaeda-0.7.19-cp312-cp312-macosx_11_0_arm64.whl (5.5 MB view details)

Uploaded CPython 3.12macOS 11.0+ ARM64

najaeda-0.7.19-cp311-cp311-win_amd64.whl (5.6 MB view details)

Uploaded CPython 3.11Windows x86-64

najaeda-0.7.19-cp311-cp311-manylinux_2_28_x86_64.whl (9.3 MB view details)

Uploaded CPython 3.11manylinux: glibc 2.28+ x86-64

najaeda-0.7.19-cp311-cp311-manylinux_2_28_aarch64.whl (8.5 MB view details)

Uploaded CPython 3.11manylinux: glibc 2.28+ ARM64

najaeda-0.7.19-cp311-cp311-macosx_11_0_arm64.whl (5.5 MB view details)

Uploaded CPython 3.11macOS 11.0+ ARM64

najaeda-0.7.19-cp310-cp310-win_amd64.whl (5.6 MB view details)

Uploaded CPython 3.10Windows x86-64

najaeda-0.7.19-cp310-cp310-manylinux_2_28_x86_64.whl (9.3 MB view details)

Uploaded CPython 3.10manylinux: glibc 2.28+ x86-64

najaeda-0.7.19-cp310-cp310-manylinux_2_28_aarch64.whl (8.5 MB view details)

Uploaded CPython 3.10manylinux: glibc 2.28+ ARM64

najaeda-0.7.19-cp310-cp310-macosx_11_0_arm64.whl (5.5 MB view details)

Uploaded CPython 3.10macOS 11.0+ ARM64

File details

Details for the file najaeda-0.7.19.tar.gz.

File metadata

  • Download URL: najaeda-0.7.19.tar.gz
  • Upload date:
  • Size: 15.3 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.13

File hashes

Hashes for najaeda-0.7.19.tar.gz
Algorithm Hash digest
SHA256 0652e350cd26086b2fbfed9fec1686c91e9fafa7ebcab3b43ef029c646207420
MD5 a7ebf649df2ec46013e13d629f93954f
BLAKE2b-256 334f6cc9b7b1fd9fc5f2f47ad447f534cb52ae2bcf7e363d54993d4ce54671c1

See more details on using hashes here.

File details

Details for the file najaeda-0.7.19-cp315-cp315-win_amd64.whl.

File metadata

  • Download URL: najaeda-0.7.19-cp315-cp315-win_amd64.whl
  • Upload date:
  • Size: 5.7 MB
  • Tags: CPython 3.15, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.13

File hashes

Hashes for najaeda-0.7.19-cp315-cp315-win_amd64.whl
Algorithm Hash digest
SHA256 a788dfa106a7210f4c5c36ce35d30198575b688eb5d5c618b31051ef6a6cdfb8
MD5 3c611ce30a02bf8694eca834c11feb87
BLAKE2b-256 cbce25b610f7bfcb3a89de509e3443534be700863f0f51647ec09659a37c0834

See more details on using hashes here.

File details

Details for the file najaeda-0.7.19-cp315-cp315-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for najaeda-0.7.19-cp315-cp315-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 fda911bebdb1aa3500d261450093ff70d325750d7e810dbfc599bfd7a6e72bbd
MD5 e00b66d821784509454e2dbf49de4350
BLAKE2b-256 9a7bb660b9de9bbb37f4a44a5bb0830cdf8128b188f74dfd1e870f57185b432b

See more details on using hashes here.

File details

Details for the file najaeda-0.7.19-cp315-cp315-manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for najaeda-0.7.19-cp315-cp315-manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 a988de61b33ae63672dbbb699bd66b7108ec5871bde1f4574ec4e8637e6ecf4f
MD5 d143561a540ebf61aa80ce02a9fcf86e
BLAKE2b-256 92283ea4eecb2dc80ad9b82caa343a8f213e07ea51ea66b1fd789a77c4cc7a6a

See more details on using hashes here.

File details

Details for the file najaeda-0.7.19-cp315-cp315-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for najaeda-0.7.19-cp315-cp315-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 459e96d28927ae71e71f9d7a6d861abac306fde69fe11fc3f8ba78bc8f9122ed
MD5 b3fea02e0ef2ef2e0e08c1c32f91f314
BLAKE2b-256 c9cbb08fd7042063a99030712d55c9e3f408bdd96e6624ad43adf1d4f96b9604

See more details on using hashes here.

File details

Details for the file najaeda-0.7.19-cp314-cp314t-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for najaeda-0.7.19-cp314-cp314t-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 ad2cbe297823b5e4d559fa4d76412434c82a94348ed4d7aecb40ffe299c98c4f
MD5 a953b04288132b69f4feeabd864131d9
BLAKE2b-256 dcbd621e41e7c9d7983e99a131b155b57ad56023661877437cfb1d9fb9d76615

See more details on using hashes here.

File details

Details for the file najaeda-0.7.19-cp314-cp314t-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for najaeda-0.7.19-cp314-cp314t-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 e1e29ed31897529498b77f796126ca35385ad53df05cb595e4763729241455e4
MD5 09d530ba2031911b72d6a06de673d4cc
BLAKE2b-256 4f00ccd04da6c6614600901913401e553d7f245e0804de587ec0de9fe224fb32

See more details on using hashes here.

File details

Details for the file najaeda-0.7.19-cp314-cp314-win_amd64.whl.

File metadata

  • Download URL: najaeda-0.7.19-cp314-cp314-win_amd64.whl
  • Upload date:
  • Size: 5.7 MB
  • Tags: CPython 3.14, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.13

File hashes

Hashes for najaeda-0.7.19-cp314-cp314-win_amd64.whl
Algorithm Hash digest
SHA256 89bd3478cf2571ff4478ff645d834ca655de43fd6cea26b8bbf11d2084729005
MD5 7f66c17edd124f5fedf9f9dc40492398
BLAKE2b-256 3a26837ce20844da5be5d8bf06ddd4f01dcd2b1a8ae372e59e9f2338196c1be9

See more details on using hashes here.

File details

Details for the file najaeda-0.7.19-cp314-cp314-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for najaeda-0.7.19-cp314-cp314-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 e19e85df6487e77a305ef085312c9414dd07a81bb260bc67c8e018bf072b98d6
MD5 20187559a826198f4e1a6e6ab91b41ac
BLAKE2b-256 b06405ff315ec5d9ea9bd9b7714d49a824f6be0349ad17b43d2c50b928a9b52a

See more details on using hashes here.

File details

Details for the file najaeda-0.7.19-cp314-cp314-manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for najaeda-0.7.19-cp314-cp314-manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 1074399f4b99de2ae25b87ed91d24b8ea1461cc165ee080a95a20f043c5fdcaa
MD5 3a7ef51ed85090ae4d9e2b426726ffc3
BLAKE2b-256 7151dc39bc47af0c24124a20662b2a78cedd696ba16cf27a84ed1b13978b09bb

See more details on using hashes here.

File details

Details for the file najaeda-0.7.19-cp314-cp314-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for najaeda-0.7.19-cp314-cp314-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 e46a0e7611749cd3c3155aa672b285bc8aaeeb2b9e722e551c69f9bde8d9460a
MD5 3f2192fbc2479958aa076cbbdb5bff73
BLAKE2b-256 6a7bb82f3c34d4b1c0ba201ed809aca5138b13028e3edddfe70f9b8e1e513953

See more details on using hashes here.

File details

Details for the file najaeda-0.7.19-cp313-cp313-win_amd64.whl.

File metadata

  • Download URL: najaeda-0.7.19-cp313-cp313-win_amd64.whl
  • Upload date:
  • Size: 5.6 MB
  • Tags: CPython 3.13, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.13

File hashes

Hashes for najaeda-0.7.19-cp313-cp313-win_amd64.whl
Algorithm Hash digest
SHA256 d7415a08df7b920ef647cf014d68a6e7cc1c64cc38866d83b8e1fb19e463fcb1
MD5 abdf8fc73d8e055939492a4d92cc3c49
BLAKE2b-256 fd546ec2bb4a12fde4a7ae70b8a68c2088fdcb25e70869101cb66200679ac1a8

See more details on using hashes here.

File details

Details for the file najaeda-0.7.19-cp313-cp313-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for najaeda-0.7.19-cp313-cp313-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 699d1217cc3740271bc4bc65aeda7f416c4c00a87b6db85bb36a93bb71f64d50
MD5 78ffac52b9ec195e2b86f9ae855a5e2a
BLAKE2b-256 a7268dcedd6e4b80aa60417b30cc735741cad2f6813952f9de70029b58460b66

See more details on using hashes here.

File details

Details for the file najaeda-0.7.19-cp313-cp313-manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for najaeda-0.7.19-cp313-cp313-manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 81f97be231e842314902360fb3c0513f6cb6af14efeba6164471aa440ed2b6f4
MD5 58399a7ee94e6b65dcfd5f76eeae2580
BLAKE2b-256 92f712e48927df1814d16c67bbec7dc1c0e4d68d3411e8375abfdb77c5878a82

See more details on using hashes here.

File details

Details for the file najaeda-0.7.19-cp313-cp313-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for najaeda-0.7.19-cp313-cp313-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 3a4f69043ee278ba9052a5d21e45684897fd3b1295aaf243f158b05a6f122e4e
MD5 b82f0a95a67384f87f40b092405d584c
BLAKE2b-256 940ddf93280e08da2a3d62e6707c67f5f3e1ca788e1cad285d0596315c94e347

See more details on using hashes here.

File details

Details for the file najaeda-0.7.19-cp312-cp312-win_amd64.whl.

File metadata

  • Download URL: najaeda-0.7.19-cp312-cp312-win_amd64.whl
  • Upload date:
  • Size: 5.6 MB
  • Tags: CPython 3.12, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.13

File hashes

Hashes for najaeda-0.7.19-cp312-cp312-win_amd64.whl
Algorithm Hash digest
SHA256 27c97c93f1aba4520d6dda6933a14a16fe38f8761f1ed7b000382935c9ac6bb0
MD5 1315b2e15ddedb788d20044829c83b1d
BLAKE2b-256 92c2a14688dc0e0fab3d7d821ba59d3dbd2e20475bdda23af1a2ee1fc9c8a507

See more details on using hashes here.

File details

Details for the file najaeda-0.7.19-cp312-cp312-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for najaeda-0.7.19-cp312-cp312-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 2cc4dbc6d716fa81d922be0f6a41dcba7d588b5fae3fbacb1fac78f2c4947565
MD5 9bf7a85c3dc7de83c956b51051b92175
BLAKE2b-256 16809990db32946beeaa362382bd1ad4c826804ec6a12cf3deeb9f258b150405

See more details on using hashes here.

File details

Details for the file najaeda-0.7.19-cp312-cp312-manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for najaeda-0.7.19-cp312-cp312-manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 9d2da0e2e50aa8ad2c9434529c553739e0b89b784b053577e9a381fe0d8fff0e
MD5 ef6707bb75aa9c64fb1c738f01053289
BLAKE2b-256 0cf1cfbbcadb71f5bdbf3858ea0123297001437b638bde302fbe7fa19dc1bf35

See more details on using hashes here.

File details

Details for the file najaeda-0.7.19-cp312-cp312-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for najaeda-0.7.19-cp312-cp312-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 57e844b73916bc046f3f0396cf7b7f538b4d661900ec12a4242d7156044e496a
MD5 e74e9dfebded779a636d2c85d60e849d
BLAKE2b-256 c28dbdabf463749fd9463f7879531c48d5e2433197dc9993a73d1bbe1534b2bb

See more details on using hashes here.

File details

Details for the file najaeda-0.7.19-cp311-cp311-win_amd64.whl.

File metadata

  • Download URL: najaeda-0.7.19-cp311-cp311-win_amd64.whl
  • Upload date:
  • Size: 5.6 MB
  • Tags: CPython 3.11, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.13

File hashes

Hashes for najaeda-0.7.19-cp311-cp311-win_amd64.whl
Algorithm Hash digest
SHA256 6ba68e6cb2155aa248b300fab520690c721e5683865577ae8a61bc0797a92450
MD5 3217f0347f13a35886bceecdc760c62e
BLAKE2b-256 4594b396b0f3c87e89b58066059c1ffc777554ccc7f4ed712c1259c6997d1365

See more details on using hashes here.

File details

Details for the file najaeda-0.7.19-cp311-cp311-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for najaeda-0.7.19-cp311-cp311-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 4fde7cba877ef786b4ac083a4b909482bde2ebac5421f7a69faa50b3de56c1a7
MD5 22d3b336fc932ba1df2c3dcc09fc66ab
BLAKE2b-256 012278ee92d6ff983358893f37692eef6b320a2268887d99e3d8c7a333afea75

See more details on using hashes here.

File details

Details for the file najaeda-0.7.19-cp311-cp311-manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for najaeda-0.7.19-cp311-cp311-manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 f43f2349956b0c358a9b4cc1337895e4a3e815a61f873c0ca7df0832dc120ee3
MD5 589f2855f1679699d4e5ce7b80be49be
BLAKE2b-256 0d012b54002f8958c6e51f435cf60ae332920dc3a83899481823a8ad898d3fba

See more details on using hashes here.

File details

Details for the file najaeda-0.7.19-cp311-cp311-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for najaeda-0.7.19-cp311-cp311-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 469be008c3cd1f091e303b21c3ea59aaa1d191a22909342d9dcc0da61a564c43
MD5 5076586818cafac74b9d95d5675d2adf
BLAKE2b-256 394d165535aa506bd099a5168b4ad31a258057b37978d64be7d763c104ca6055

See more details on using hashes here.

File details

Details for the file najaeda-0.7.19-cp310-cp310-win_amd64.whl.

File metadata

  • Download URL: najaeda-0.7.19-cp310-cp310-win_amd64.whl
  • Upload date:
  • Size: 5.6 MB
  • Tags: CPython 3.10, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.13

File hashes

Hashes for najaeda-0.7.19-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 78d821734ee2e86ab12ce4c46de0925efaa7984dab43feb36d33d9252e49243f
MD5 c8900b07421039dffa1bcf0510f929d1
BLAKE2b-256 d20a24ddd7916bc98ca95ace0b2831fad06cf374175135f2ca780bb94f64d171

See more details on using hashes here.

File details

Details for the file najaeda-0.7.19-cp310-cp310-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for najaeda-0.7.19-cp310-cp310-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 eed09c1d266c0dc46cde3eda391bb2b9104cd7302baf3ee0d5d34232f28ad71d
MD5 c0a72c1389a986c5e6b277012ae91bab
BLAKE2b-256 ffbffe0377d1a734ac0a8f7e43d5ec58462bc07188f2bc5f46b3d83ced99d5fa

See more details on using hashes here.

File details

Details for the file najaeda-0.7.19-cp310-cp310-manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for najaeda-0.7.19-cp310-cp310-manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 4225141738dcbd0d4457421acd2678f36596318e33a2511a0e3e4da1a4d13f92
MD5 e2fd3b123eafd30034b90847eaa54c9a
BLAKE2b-256 1ce269a3a089caefbb63999a4518c74a6dd467c8339ea47dc5f3513ae872c74b

See more details on using hashes here.

File details

Details for the file najaeda-0.7.19-cp310-cp310-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for najaeda-0.7.19-cp310-cp310-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 1e2223ed04e92369f69aa004da31d328278f199a2bddfd96ec3258e6fc9c1d40
MD5 d124b817b6426beb4b8b3a71fa0086a4
BLAKE2b-256 a68fd2fd033917b73dcd9282181fd3f860d7e49aefd80ff7220daf5bc55cef02

See more details on using hashes here.

Release history Release notifications | RSS feed

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page