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-0.7.14.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-0.7.14-cp315-cp315-win_amd64.whl (5.7 MB view details)

Uploaded CPython 3.15Windows x86-64

najaeda-0.7.14-cp315-cp315-manylinux_2_28_x86_64.whl (9.3 MB view details)

Uploaded CPython 3.15manylinux: glibc 2.28+ x86-64

najaeda-0.7.14-cp315-cp315-manylinux_2_28_aarch64.whl (8.5 MB view details)

Uploaded CPython 3.15manylinux: glibc 2.28+ ARM64

najaeda-0.7.14-cp315-cp315-macosx_11_0_arm64.whl (5.5 MB view details)

Uploaded CPython 3.15macOS 11.0+ ARM64

najaeda-0.7.14-cp314-cp314t-manylinux_2_28_x86_64.whl (9.3 MB view details)

Uploaded CPython 3.14tmanylinux: glibc 2.28+ x86-64

najaeda-0.7.14-cp314-cp314t-macosx_11_0_arm64.whl (5.5 MB view details)

Uploaded CPython 3.14tmacOS 11.0+ ARM64

najaeda-0.7.14-cp314-cp314-win_amd64.whl (5.7 MB view details)

Uploaded CPython 3.14Windows x86-64

najaeda-0.7.14-cp314-cp314-manylinux_2_28_x86_64.whl (9.3 MB view details)

Uploaded CPython 3.14manylinux: glibc 2.28+ x86-64

najaeda-0.7.14-cp314-cp314-manylinux_2_28_aarch64.whl (8.5 MB view details)

Uploaded CPython 3.14manylinux: glibc 2.28+ ARM64

najaeda-0.7.14-cp314-cp314-macosx_11_0_arm64.whl (5.5 MB view details)

Uploaded CPython 3.14macOS 11.0+ ARM64

najaeda-0.7.14-cp313-cp313-win_amd64.whl (5.5 MB view details)

Uploaded CPython 3.13Windows x86-64

najaeda-0.7.14-cp313-cp313-manylinux_2_28_x86_64.whl (9.3 MB view details)

Uploaded CPython 3.13manylinux: glibc 2.28+ x86-64

najaeda-0.7.14-cp313-cp313-manylinux_2_28_aarch64.whl (8.5 MB view details)

Uploaded CPython 3.13manylinux: glibc 2.28+ ARM64

najaeda-0.7.14-cp313-cp313-macosx_11_0_arm64.whl (5.5 MB view details)

Uploaded CPython 3.13macOS 11.0+ ARM64

najaeda-0.7.14-cp312-cp312-win_amd64.whl (5.5 MB view details)

Uploaded CPython 3.12Windows x86-64

najaeda-0.7.14-cp312-cp312-manylinux_2_28_x86_64.whl (9.3 MB view details)

Uploaded CPython 3.12manylinux: glibc 2.28+ x86-64

najaeda-0.7.14-cp312-cp312-manylinux_2_28_aarch64.whl (8.5 MB view details)

Uploaded CPython 3.12manylinux: glibc 2.28+ ARM64

najaeda-0.7.14-cp312-cp312-macosx_11_0_arm64.whl (5.5 MB view details)

Uploaded CPython 3.12macOS 11.0+ ARM64

najaeda-0.7.14-cp311-cp311-win_amd64.whl (5.5 MB view details)

Uploaded CPython 3.11Windows x86-64

najaeda-0.7.14-cp311-cp311-manylinux_2_28_x86_64.whl (9.3 MB view details)

Uploaded CPython 3.11manylinux: glibc 2.28+ x86-64

najaeda-0.7.14-cp311-cp311-manylinux_2_28_aarch64.whl (8.5 MB view details)

Uploaded CPython 3.11manylinux: glibc 2.28+ ARM64

najaeda-0.7.14-cp311-cp311-macosx_11_0_arm64.whl (5.5 MB view details)

Uploaded CPython 3.11macOS 11.0+ ARM64

najaeda-0.7.14-cp310-cp310-win_amd64.whl (5.5 MB view details)

Uploaded CPython 3.10Windows x86-64

najaeda-0.7.14-cp310-cp310-manylinux_2_28_x86_64.whl (9.3 MB view details)

Uploaded CPython 3.10manylinux: glibc 2.28+ x86-64

najaeda-0.7.14-cp310-cp310-manylinux_2_28_aarch64.whl (8.5 MB view details)

Uploaded CPython 3.10manylinux: glibc 2.28+ ARM64

najaeda-0.7.14-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-0.7.14.tar.gz.

File metadata

  • Download URL: najaeda-0.7.14.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-0.7.14.tar.gz
Algorithm Hash digest
SHA256 4fb5d27e3e919533c2efae349191a6f2e734fec0a2a4cdfb155f32d5284a6340
MD5 5ec7ee0d44bd830535d12ebcc3dbe606
BLAKE2b-256 3de6d377d0145075035d8b717fcb9c33a80c0910e7236bfd17c13a83baf29300

See more details on using hashes here.

File details

Details for the file najaeda-0.7.14-cp315-cp315-win_amd64.whl.

File metadata

  • Download URL: najaeda-0.7.14-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-0.7.14-cp315-cp315-win_amd64.whl
Algorithm Hash digest
SHA256 6476ce3afb1321f819e5862b3e14c6fcb5cb636256c2fec4ad08501e8e5a3404
MD5 3f0f515163f68837ae0ab1e3e53973b9
BLAKE2b-256 70634304c9415f8927177d273b2c3443fc9991e6ede4d89aa2bc77e88151203c

See more details on using hashes here.

File details

Details for the file najaeda-0.7.14-cp315-cp315-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for najaeda-0.7.14-cp315-cp315-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 8c8ea0fff416c17e7292016443493a8f597bfbb8811b437e52457f24f0fa0666
MD5 8068bf7e1b3407ba1109e9544958f6f9
BLAKE2b-256 1b98c2950dcb6d7755397ec620b8ad335e393e255861da7718f68e62a2b87776

See more details on using hashes here.

File details

Details for the file najaeda-0.7.14-cp315-cp315-manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for najaeda-0.7.14-cp315-cp315-manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 ec69cb73eee08ae2cbbf7b478c9a34888ed2b3eb578bfd8ca2b2baeba44876ec
MD5 797bad7f9132345117ad8ff9fed72fc7
BLAKE2b-256 5285442a975afb41b4ac839445bf18d88e94a3e27ec8a2d13724af4c73e8b2c8

See more details on using hashes here.

File details

Details for the file najaeda-0.7.14-cp315-cp315-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for najaeda-0.7.14-cp315-cp315-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 7f3e31b06635f665c680bd9d43ab9ce8cf57e2466bed1e3cd91cc00cae7e7796
MD5 3a98575f02823483915d6cf5c8db0a7d
BLAKE2b-256 3195cd497b8b82f23b3c988e40a51efd22b87036926eab0da009a5de0d2d2e22

See more details on using hashes here.

File details

Details for the file najaeda-0.7.14-cp314-cp314t-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for najaeda-0.7.14-cp314-cp314t-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 b0f97bde4e180f9be795d9e48efb013c19e76e2972b5319cfa7c705612570da5
MD5 8025196b8387a45ff730b38e866c31b4
BLAKE2b-256 4471956e772b1a78ca44a72889c9010469bf1584bf2a0fd5ca8308e692e5a61e

See more details on using hashes here.

File details

Details for the file najaeda-0.7.14-cp314-cp314t-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for najaeda-0.7.14-cp314-cp314t-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 99daef3f402ce61d2d5a9b0f6d62d5480e000031b67179a556eb7f2f90fcf68f
MD5 b52f137760048a4386acd323b06e839c
BLAKE2b-256 2216d7934928751a4c0558b4ecb479e4be04be003cd3a18f0a72d27e218816a5

See more details on using hashes here.

File details

Details for the file najaeda-0.7.14-cp314-cp314-win_amd64.whl.

File metadata

  • Download URL: najaeda-0.7.14-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-0.7.14-cp314-cp314-win_amd64.whl
Algorithm Hash digest
SHA256 70288a82805e38f17662c45a35798e09753c511f5f12018601f6fdfb5c73db87
MD5 fd05a56c8cc024c9a2b3ddda798ae4ed
BLAKE2b-256 e05d14e49c859907c6be0962c19d2c4c7af48515666c4009b468c48d9b607bd1

See more details on using hashes here.

File details

Details for the file najaeda-0.7.14-cp314-cp314-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for najaeda-0.7.14-cp314-cp314-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 e892e36655fe338156072c5647a5011db169fff81bfdc6e2d8f45cd47becd2b8
MD5 42c4764a66d92f08dd9918f7f37a8201
BLAKE2b-256 5b6ed5a47f4e2c1ee112c5448d09eb107c8bfdf2a62d60b9acf4cd138cbe5ecf

See more details on using hashes here.

File details

Details for the file najaeda-0.7.14-cp314-cp314-manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for najaeda-0.7.14-cp314-cp314-manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 64f41d161c761dd799533e7238828655dd34b0cd559d3fffc610076cf33d150b
MD5 ca0330f8325d8c5fdf4c101b60f3a944
BLAKE2b-256 f30f5a6a51ee2bcf09cc40566b9b5431374acc0347f7926483c573339457f6b9

See more details on using hashes here.

File details

Details for the file najaeda-0.7.14-cp314-cp314-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for najaeda-0.7.14-cp314-cp314-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 2d7ed79aaff0c618a02db2b63d1d1635f86bbaa04a17f4872c8ae21f135d329c
MD5 42c5d4e9c2cd4681734b49bd1abba6a9
BLAKE2b-256 241db5bb2d3d19c4bc63bcb9b77f7d9efbbb9e81b39873e9d77896bdcc9e8525

See more details on using hashes here.

File details

Details for the file najaeda-0.7.14-cp313-cp313-win_amd64.whl.

File metadata

  • Download URL: najaeda-0.7.14-cp313-cp313-win_amd64.whl
  • Upload date:
  • Size: 5.5 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-0.7.14-cp313-cp313-win_amd64.whl
Algorithm Hash digest
SHA256 29580e6c450b0636dd343b89c7242d9fac74066e00abfec2c54af0bf9262d2df
MD5 6ea9d026d18ce9fc8e2eaa6a9b2d87db
BLAKE2b-256 f16761b6591cc316e33c101502d27219b4c637e3378efcd84a173bc3bdd545ba

See more details on using hashes here.

File details

Details for the file najaeda-0.7.14-cp313-cp313-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for najaeda-0.7.14-cp313-cp313-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 f3e21ac72f674f5109ff91af53be8885464d9b81b302c0bf74134fc7626c6bf2
MD5 f5198fc86b2e6121c8747e9066eb8318
BLAKE2b-256 b5850fdcf5c99a21e59cbfcaa8d44ae117290b23e484ca37b779297e5f828a5d

See more details on using hashes here.

File details

Details for the file najaeda-0.7.14-cp313-cp313-manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for najaeda-0.7.14-cp313-cp313-manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 50bfe6a8fe984d2346955997fcfcbef20c72596e46d7b10e4f1e34c597484d54
MD5 f1cf458ffc411a4f0ddabd3db7c5c609
BLAKE2b-256 ab84ca3d0a7f3e99a4365384e4b0def3d1ca6bf74dfbb73a9baaef8f82be8d5f

See more details on using hashes here.

File details

Details for the file najaeda-0.7.14-cp313-cp313-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for najaeda-0.7.14-cp313-cp313-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 b3feca35b807b1b19cb480cac055318662bd0fa08a3538d0f5dbeb9a974c9670
MD5 212d977897277615fabdb3ac34a69ac5
BLAKE2b-256 d3c9109424ba043b3666a6334ce03dbb3eea3dc0ae38bbcd302727bc0018f9d8

See more details on using hashes here.

File details

Details for the file najaeda-0.7.14-cp312-cp312-win_amd64.whl.

File metadata

  • Download URL: najaeda-0.7.14-cp312-cp312-win_amd64.whl
  • Upload date:
  • Size: 5.5 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-0.7.14-cp312-cp312-win_amd64.whl
Algorithm Hash digest
SHA256 39a300dcf3c8934e12db0c51967a1614095386647fbc565c78503ac34c23899d
MD5 6099caea113d47625d081000bbb3d415
BLAKE2b-256 2373e3a43a73bf5c44f94a091c68698831fc2f1dd1cbd98e3dc00f21f7963b72

See more details on using hashes here.

File details

Details for the file najaeda-0.7.14-cp312-cp312-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for najaeda-0.7.14-cp312-cp312-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 1f3bb1309d7086deabe9ce23e36b6f81a5963f731462f65cfa94818a62e3f478
MD5 2b4dc715c76b5ec33170f114feba3760
BLAKE2b-256 2e26a6ec6e68c619576780eb6b21b9bbfb33314aba40b63adc3e425621a010a6

See more details on using hashes here.

File details

Details for the file najaeda-0.7.14-cp312-cp312-manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for najaeda-0.7.14-cp312-cp312-manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 e46ccf7a982467bfe2046cd2770179bebd311425b1803945ce20ec7c4aadf2b1
MD5 e05f2dd911eb4c1b32ff4d0679ada27e
BLAKE2b-256 cf48d1ac628ee1db81893e3537d776cd7f1787f998de6e7bd67375d34ce82856

See more details on using hashes here.

File details

Details for the file najaeda-0.7.14-cp312-cp312-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for najaeda-0.7.14-cp312-cp312-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 2298f7a6b5ea65794745d6f9b66322c41a2d3ef2fcd05f78cada0357254c642e
MD5 4217b81aa29421e4632fd1b84f047396
BLAKE2b-256 a3f643b721527f18ec8daf0ba1129225bab9f5babf16dfef4b3c9cfd7a326b8e

See more details on using hashes here.

File details

Details for the file najaeda-0.7.14-cp311-cp311-win_amd64.whl.

File metadata

  • Download URL: najaeda-0.7.14-cp311-cp311-win_amd64.whl
  • Upload date:
  • Size: 5.5 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-0.7.14-cp311-cp311-win_amd64.whl
Algorithm Hash digest
SHA256 6a0338b2620e93174d4afe2cdbc95422bd57cf0217eabef32bbc62f8baebedde
MD5 db2c0e00fb19e93ce106924d6005e97f
BLAKE2b-256 42062f632b979ff3f1ff905b90db0153fd7180e3094d7bd6f00e3e87b0f7fc64

See more details on using hashes here.

File details

Details for the file najaeda-0.7.14-cp311-cp311-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for najaeda-0.7.14-cp311-cp311-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 b6934cd063fac00457f82f87c34c44dce83a982a16fd83576f390461979162cc
MD5 912b1ca2d9c7115909d22c47134ea24e
BLAKE2b-256 64aa5865c9a4ef31323884ab43e72bdbffd9319f7a3b2990eabfa0e1767103cf

See more details on using hashes here.

File details

Details for the file najaeda-0.7.14-cp311-cp311-manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for najaeda-0.7.14-cp311-cp311-manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 0cf0c014810da1758d132846aae073a67afe722c15f9d79f5cc0b97f7c566de7
MD5 e55f4d1e5763eda0b78b108e4abeaef9
BLAKE2b-256 77c295cc6165bb7f9f6fc188f46b9b2a6a0126b2a5f1a6d4c7da07e1e33ba826

See more details on using hashes here.

File details

Details for the file najaeda-0.7.14-cp311-cp311-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for najaeda-0.7.14-cp311-cp311-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 822dc5094e4f891bd8a4fc0f5bed38756547534f3bbd95b3223c5bbba7987efb
MD5 adbed589afd43a4de35b9615bed83cb7
BLAKE2b-256 2a69aebfd69e7f0791ebb58fbc137961b4fc80c5ca78af1c9ab9bcceedd8592c

See more details on using hashes here.

File details

Details for the file najaeda-0.7.14-cp310-cp310-win_amd64.whl.

File metadata

  • Download URL: najaeda-0.7.14-cp310-cp310-win_amd64.whl
  • Upload date:
  • Size: 5.5 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-0.7.14-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 36ccee93ebebe0abc0ec232fc338cfdeb772cd106912b891ad9da899837a3cec
MD5 668b34ca7daa090dbea7fd3089da8b52
BLAKE2b-256 9c0277934d0c123d0d14b98d160ea732f2073208a13fecf3416b8e960df24613

See more details on using hashes here.

File details

Details for the file najaeda-0.7.14-cp310-cp310-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for najaeda-0.7.14-cp310-cp310-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 17e6963be8ce5e64fdcbd0b030760f57a1581f9fe18c30677c9b01d40c903326
MD5 4532d48dfe468d70b0c11954987b5dd4
BLAKE2b-256 946822e2f480d78f64491a1528a248b55aba78e466d8817ab78d88256e931a1e

See more details on using hashes here.

File details

Details for the file najaeda-0.7.14-cp310-cp310-manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for najaeda-0.7.14-cp310-cp310-manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 34e1becb25ca3d8066b176d6b7bbd79f47d5fe37b133045c1fa843c1a027f99b
MD5 77e5eef6c162f4232199109d3040480c
BLAKE2b-256 fac00c287107d2e4c6cc7c37492bcf190fcfcc9100ed29dc74428daa6e69e46b

See more details on using hashes here.

File details

Details for the file najaeda-0.7.14-cp310-cp310-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for najaeda-0.7.14-cp310-cp310-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 7c065423364671cc2df8b13e3e71b61c9e4e01992dc877a998226ea5381673e9
MD5 740cfaccff84ef4ec61222457c63bcf1
BLAKE2b-256 b3d0f7de033a022e18802d35b2ce1fd01928b8f030430d850790422e91f0b491

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