Skip to main content

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.

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-1.97.3-py3-none-win_arm64.whl (31.3 MB view details)

Uploaded Python 3Windows ARM64

deepbom-1.97.3-py3-none-win_amd64.whl (35.0 MB view details)

Uploaded Python 3Windows x86-64

deepbom-1.97.3-py3-none-manylinux_2_28_x86_64.whl (43.2 MB view details)

Uploaded Python 3manylinux: glibc 2.28+ x86-64

deepbom-1.97.3-py3-none-manylinux_2_28_aarch64.whl (43.0 MB view details)

Uploaded Python 3manylinux: glibc 2.28+ ARM64

deepbom-1.97.3-py3-none-macosx_14_0_x86_64.whl (40.5 MB view details)

Uploaded Python 3macOS 14.0+ x86-64

deepbom-1.97.3-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-1.97.3-py3-none-win_arm64.whl.

File metadata

  • Download URL: deepbom-1.97.3-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-1.97.3-py3-none-win_arm64.whl
Algorithm Hash digest
SHA256 5ff6072fe3766a2bb08bd321fc49d5a0d59917a553903c819fcb568c8b0dfaf8
MD5 084636d6082d8a7071a9a8dd6de5c69e
BLAKE2b-256 b9d7f0b7f26fd8bc02d903f25adfe9588d938a9c7320d7a700ee649ec12fb05f

See more details on using hashes here.

Provenance

The following attestation bundles were made for deepbom-1.97.3-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-1.97.3-py3-none-win_amd64.whl.

File metadata

  • Download URL: deepbom-1.97.3-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-1.97.3-py3-none-win_amd64.whl
Algorithm Hash digest
SHA256 5d5da6b4979caaaed56293cfd339edc940597b485aad2b978f487327bf6d7c2c
MD5 fff25d8f947b5536b43b23930664876c
BLAKE2b-256 ee49e312ddb27dbf5e3810dc0396a32b18f05f9b160be00ba0c23046ca04b60c

See more details on using hashes here.

Provenance

The following attestation bundles were made for deepbom-1.97.3-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-1.97.3-py3-none-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for deepbom-1.97.3-py3-none-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 10d3198f5e0c5f2736552303e35bd8fc599aea324865fcdf3ca597f29d1a71df
MD5 307eb02a84a0c8cc8ea9230ca7d34995
BLAKE2b-256 c6002808c5abe1edf2d46e4933a8d13bce38cc542c67c55493c4fad6b39e8bea

See more details on using hashes here.

Provenance

The following attestation bundles were made for deepbom-1.97.3-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-1.97.3-py3-none-manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for deepbom-1.97.3-py3-none-manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 1595614d2808954c54897fd810838401e3c8372981ea482150303ea4896048d2
MD5 35e31926e403dd7943de672c35456fdd
BLAKE2b-256 4697d2ac461a0a40feadc00a3e8720870d8fc5ec341afed0656b3e95420a275e

See more details on using hashes here.

Provenance

The following attestation bundles were made for deepbom-1.97.3-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-1.97.3-py3-none-macosx_14_0_x86_64.whl.

File metadata

File hashes

Hashes for deepbom-1.97.3-py3-none-macosx_14_0_x86_64.whl
Algorithm Hash digest
SHA256 254dac0a84a1508d8f0bbf85e481db232fcf8471526f4e6a78027dd4def36ff1
MD5 d74669bcfb1f717a887557df80ddd9d6
BLAKE2b-256 de862536026d6506a1462ba1da1a2503cde331a93132b10844e8af728979d783

See more details on using hashes here.

Provenance

The following attestation bundles were made for deepbom-1.97.3-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-1.97.3-py3-none-macosx_14_0_arm64.whl.

File metadata

File hashes

Hashes for deepbom-1.97.3-py3-none-macosx_14_0_arm64.whl
Algorithm Hash digest
SHA256 f11f4f38a95d994684f772cb5f4a374e85883412074d7197cfe8cef685635c93
MD5 42e98858cdc21a8ac0e4ae1d38f26bc1
BLAKE2b-256 656af288bb0d56b93d8484072a40b97b2337545231fbd6341158c08c73f98be2

See more details on using hashes here.

Provenance

The following attestation bundles were made for deepbom-1.97.3-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

1.97.4

6 files

This release

1.97.3 This release

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