DEEPBOM Python launcher

This package is a zero-analysis-logic launcher for the same platform-specific DEEPBOM engine used by the npm CLI release. Each wheel binds its operating system, architecture, engine SHA-256, and canonical TFLite WASM SHA-256 in an installed manifest. No parser or numerical rule is reimplemented in Python.

An experimental typed facade invokes that same verified engine and converts its JSON and exit-code contracts into Python values and exceptions:

from deepbom import (
    DeepBomPolicyBlocked, audit, capabilities, capture_contract, diff,
    tensor_inventory, tensors, verify_bom, verify_contract,
)

caps = capabilities()
envelope = audit("model.gguf")
selected = audit("model.gguf", sections=["summary", "findings"])
try:
    gated = audit("model.safetensors", gate="defects")
except DeepBomPolicyBlocked as blocked:
    gated = blocked.document
rows = tensors("model.gguf")
inventory = tensor_inventory("model.gguf")
comparison = diff("baseline.gguf", "candidate.gguf", tensors=True)
baseline = capture_contract("model.onnx")
contract_result = verify_contract("candidate.onnx", "baseline.interface-contract.json")
bom_result = verify_bom("model.onnx", "supplied.cdx.json")

audit() defaults to the canonical envelope, or to analysis selection when sections are supplied without an explicit output. It accepts the CLI-equivalent gate="defects" and policy="engineering"|"regulatory" controls plus explicit timeout and maximum-output-byte bounds. gate and policy are mutually exclusive. Exit 1 raises DeepBomInvocationError, exit 2 raises DeepBomPolicyBlocked, and exit 3 raises DeepBomIncompleteBinding; exit 4 raises DeepBomIdentityMismatch. Policy exceptions retain any completed JSON result as .document. tensors() converts exact counts to Python int and decimal ratios to decimal.Decimal; tensor_inventory() preserves the raw JSON document. The facade is experimental in 1.96.x, and the CLI schemas remain the compatibility contract.

deepbom audit model.tflite --compact
deepbom audit model.onnx --format cyclonedx
deepbom audit model.onnx --format sarif --output deepbom.sarif --fail-on high
deepbom capabilities --compact
deepbom audit Model.mlpackage --compact
deepbom audit safetensors-repository/ --compact
deepbom audit model.pte --executorch-build deepbom.executorch-build.json --compact
deepbom verify model.onnx --bom supplied.cdx.json --render markdown
deepbom contract capture model.onnx -o baseline.interface-contract.json
deepbom capabilities --format agent-text

ONNX external data next to the model is discovered only from safe serialized references. Use --external-data-dir to bind a different explicit root. ExecuTorch PTE audits can additionally bind a selected source/build and binary inventory with --executorch-build; backend execution remains unobserved.

Set DEEPBOM_ENGINE only for a deliberately supplied engine build and bind it with DEEPBOM_ENGINE_SHA256. TensorRT options import configuration or observed parser evidence; NVIDIA runtime libraries are not bundled.

For the installed version, deepbom --help and deepbom capabilities --compact are authoritative. The current source inventory is maintained in the generated CLI reference.

This public channel package is licensed under Apache-2.0. Protected analyzers and private rulepack-generation sources are not included.

Project links

Data verified by PyPI on Sep 13, 2026
Data provided by the project maintainers, verified at the time the release was uploaded to PyPI.

Key dates

PyPI data
Data sourced directly from PyPI's database.
  • Released:
Newer release available (1.103.0)

1 maintainer

PyPI data
Data sourced directly from PyPI's database.
Avatar for junhwanKwon from gravatar.com junhwanKwon

Credits

Author: Jun-Hwan Kwon

GitHub Statistics

Data verified by PyPI on Sep 13, 2026
The GitHub source repository was provided by the project maintainers and verified by PyPI at the time of upload. Stars, forks, and open issues/PRs are derived from that repository and have not been independently verified.

License expression

Apache-2.0
View SPDX License List

Requires

Python >=3.9

Tags

tflite onnx gguf safetensors coreml executorch tensorrt quantization on-device ml-bom cyclonedx sarif mcp model-context-protocol chatgpt

Classifiers

Report project as malware

Download files

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

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distributions

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

deepbom-1.97.4-py3-none-win_arm64.whl (31.3 MB view details)

Uploaded Python 3Windows ARM64

deepbom-1.97.4-py3-none-win_amd64.whl (35.0 MB view details)

Uploaded Python 3Windows x86-64

deepbom-1.97.4-py3-none-manylinux_2_28_x86_64.whl (43.2 MB view details)

Uploaded Python 3manylinux: glibc 2.28+ x86-64

deepbom-1.97.4-py3-none-manylinux_2_28_aarch64.whl (43.0 MB view details)

Uploaded Python 3manylinux: glibc 2.28+ ARM64

deepbom-1.97.4-py3-none-macosx_14_0_x86_64.whl (40.5 MB view details)

Uploaded Python 3macOS 14.0+ x86-64

deepbom-1.97.4-py3-none-macosx_14_0_arm64.whl (39.3 MB view details)

Uploaded Python 3macOS 14.0+ ARM64

File details

Details for the file deepbom-1.97.4-py3-none-win_arm64.whl.

File metadata

  • Download URL: deepbom-1.97.4-py3-none-win_arm64.whl
  • Upload date:
  • Size: 31.3 MB
  • Tags: Python 3, Windows ARM64
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/7.0.0 CPython/3.13.14

File hashes

Hashes for deepbom-1.97.4-py3-none-win_arm64.whl
Algorithm Hash digest
SHA256 c4956123ef0e4dbd90b475d77e8c0946ada9c97bc97a085b46730a5ed3943e00
MD5 39bd661803b8173121578ff09da0ac7c
BLAKE2b-256 6b8cfa101e35337b37f291ba580f3e319d5332ad4e06e445a58e8e697a809d34

See more details on using hashes here.

Provenance

The following attestation bundles were made for deepbom-1.97.4-py3-none-win_arm64.whl:

Publisher: release-channels.yml on JunHwan-Kwon/deepbom

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file deepbom-1.97.4-py3-none-win_amd64.whl.

File metadata

  • Download URL: deepbom-1.97.4-py3-none-win_amd64.whl
  • Upload date:
  • Size: 35.0 MB
  • Tags: Python 3, Windows x86-64
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/7.0.0 CPython/3.13.14

File hashes

Hashes for deepbom-1.97.4-py3-none-win_amd64.whl
Algorithm Hash digest
SHA256 f71b6c049c0353bebf68a483ea4b351e72c5bc27adeae86bb8d49870ce32aa74
MD5 cbf919554c9e80c80d633ac0d26d78e6
BLAKE2b-256 3ca54e104b970be65a621eb500772838e7e91646beb62926e9e9e9561d806fe1

See more details on using hashes here.

Provenance

The following attestation bundles were made for deepbom-1.97.4-py3-none-win_amd64.whl:

Publisher: release-channels.yml on JunHwan-Kwon/deepbom

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file deepbom-1.97.4-py3-none-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for deepbom-1.97.4-py3-none-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 40eabbc8e53c0f38478a02804b0a04d0dee632df7198d5913a3600d34914745a
MD5 0c41c60227111f01b27ae484e935cf3f
BLAKE2b-256 316677df96fcba5d1c49c898137e2cebb56a8daa78d9f23e21299afe47f23d31

See more details on using hashes here.

Provenance

The following attestation bundles were made for deepbom-1.97.4-py3-none-manylinux_2_28_x86_64.whl:

Publisher: release-channels.yml on JunHwan-Kwon/deepbom

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file deepbom-1.97.4-py3-none-manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for deepbom-1.97.4-py3-none-manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 2cc2843ca16472d91c0bfca79c34629941268e443881cc53b50193b651a0acac
MD5 94380aa2ea07323fd379ec177bce8cbf
BLAKE2b-256 82cdf32a765917601a01765405bcf9dc2deb63aab95ac78c1d77fb3bfc0b8108

See more details on using hashes here.

Provenance

The following attestation bundles were made for deepbom-1.97.4-py3-none-manylinux_2_28_aarch64.whl:

Publisher: release-channels.yml on JunHwan-Kwon/deepbom

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file deepbom-1.97.4-py3-none-macosx_14_0_x86_64.whl.

File metadata

File hashes

Hashes for deepbom-1.97.4-py3-none-macosx_14_0_x86_64.whl
Algorithm Hash digest
SHA256 f30608245a4bf0655056a25a1f4735c93bd5b409c893c16b4aaa346dd0998556
MD5 114c06aa3393899df80b4314d867a4ae
BLAKE2b-256 b7783c9ee8d3ef00fa8e24901010b406d35dabfc3c73e7c5f8ebf1802d528deb

See more details on using hashes here.

Provenance

The following attestation bundles were made for deepbom-1.97.4-py3-none-macosx_14_0_x86_64.whl:

Publisher: release-channels.yml on JunHwan-Kwon/deepbom

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file deepbom-1.97.4-py3-none-macosx_14_0_arm64.whl.

File metadata

File hashes

Hashes for deepbom-1.97.4-py3-none-macosx_14_0_arm64.whl
Algorithm Hash digest
SHA256 396a6f11f1ed7b988b1a2809da03785bb520262ac7d8682cc969d63534ebf7e9
MD5 f90d2398cd3260543e8e4f7661b7292a
BLAKE2b-256 83709b50c881e2d609ec0cfd729575053420a76e29efebc9ead1fed87f35f5d3

See more details on using hashes here.

Provenance

The following attestation bundles were made for deepbom-1.97.4-py3-none-macosx_14_0_arm64.whl:

Publisher: release-channels.yml on JunHwan-Kwon/deepbom

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Release history Release notifications | RSS feed

1.103.0

6 files

1.102.0

6 files

1.101.0

6 files

1.100.0

6 files

1.99.2

6 files

1.99.1

6 files

1.98.0

6 files

This release

1.97.4 This release

6 files

1.97.3

6 files

1.97.0

6 files

1.96.15

6 files

1.96.14

6 files

1.96.13

6 files

1.96.12

6 files

1.96.11

6 files

1.96.10

6 files

1.96.9

6 files

1.96.8

6 files

1.96.7

6 files

1.96.5

6 files

1.96.4

6 files

1.96.3

6 files

1.96.2

6 files

1.96.1

6 files

1.95.0

6 files

1.94.6

6 files

1.94.5

6 files

1.94.4

6 files

1.94.3

6 files

1.94.2

6 files

0.1.0

2 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