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.
Metadata
Release files for deepbom 1.103.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Built distributions (wheels)
| File | Reset | |||
|---|---|---|---|---|
| deepbom-1.103.0-py3-none-win_arm64.whl | Python 3 | none | Windows ARM64 | Details |
| deepbom-1.103.0-py3-none-win_amd64.whl | Python 3 | none | Windows x86-64 | Details |
| deepbom-1.103.0-py3-none-manylinux_2_28_x86_64.whl | Python 3 | none | Linux glibc 2.28+ x86-64 | Details |
| deepbom-1.103.0-py3-none-manylinux_2_28_aarch64.whl | Python 3 | none | Linux glibc 2.28+ ARM64 | Details |
| deepbom-1.103.0-py3-none-macosx_14_0_x86_64.whl | Python 3 | none | macOS 14.0+ x86-64 | Details |
| deepbom-1.103.0-py3-none-macosx_14_0_arm64.whl | Python 3 | none | macOS 14.0+ ARM64 | Details |
Total release size: 232.5 MB
Release files / deepbom-1.103.0-py3-none-win_arm64.whl
| Download URL | deepbom-1.103.0-py3-none-win_arm64.whl |
|---|---|
| Size | 31.3 MB |
| Tags | Python 3 Windows ARM64 |
|
SHA-256 checksum How to use checksums |
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| Download URL | deepbom-1.103.0-py3-none-win_amd64.whl |
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| Size | 35.1 MB |
| Tags | Python 3 Windows x86-64 |
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SHA-256 checksum How to use checksums |
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Transparency logRelease files / deepbom-1.103.0-py3-none-manylinux_2_28_x86_64.whl
| Download URL | deepbom-1.103.0-py3-none-manylinux_2_28_x86_64.whl |
|---|---|
| Size | 43.2 MB |
| Tags | Linux glibc 2.28+ x86-64 Python 3 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
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| Uploaded via |
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| Download URL | deepbom-1.103.0-py3-none-manylinux_2_28_aarch64.whl |
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| Size | 43.0 MB |
| Tags | Linux glibc 2.28+ ARM64 Python 3 |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
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| Uploaded via |
twine/7.0.0 CPython/3.13.14
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| Download URL | deepbom-1.103.0-py3-none-macosx_14_0_x86_64.whl |
|---|---|
| Size | 40.5 MB |
| Tags | Python 3 macOS 14.0+ x86-64 |
|
SHA-256 checksum How to use checksums |
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| Download URL | deepbom-1.103.0-py3-none-macosx_14_0_arm64.whl |
|---|---|
| Size | 39.3 MB |
| Tags | Python 3 macOS 14.0+ ARM64 |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
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| Uploaded via |
twine/7.0.0 CPython/3.13.14
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Provenance
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