Bump the python-minor-patch group across 1 directory with 4 updates

[dependabot]

Bumps the python-minor-patch group with 4 updates in the /revenueassurance directory: python-dotenv, scikit-learn, pandas and onnxruntime.

Updates python-dotenv from 1.2.2 to 1.2.3

Release notes

Sourced from python-dotenv's releases.

v1.2.3

Fixed

• Strip a leading UTF-8 BOM from .env file contents so the first variable is no longer silently lost when the file is saved with BOM (e.g. by some JetBrains IDEs on Windows) by [@​h1whelan] in #640
• set_key now escapes backslashes, so values containing them (Windows paths, regular expressions) survive a write/read round-trip. Quoted values ending in an escaped backslash are no longer mis-parsed as an escaped quote, which used to swallow the following lines by [@​dchaudhari7177] in #680
• dotenv run now prints a friendly error instead of a traceback when no command is given by [@​bbc2] in #606
• Cache the parsed result for empty .env files so repeated dotenv_values/load_dotenv calls no longer re-read the file by [@​ReinerBRO] in #638

Changelog

Sourced from python-dotenv's changelog.

[1.2.3] - 2026-08-16

Fixed

• Strip a leading UTF-8 BOM from .env file contents so the first variable is no longer silently lost when the file is saved with BOM (e.g. by some JetBrains IDEs on Windows) by [@​h1whelan] in #640
• set_key now escapes backslashes, so values containing them (Windows paths, regular expressions) survive a write/read round-trip. Quoted values ending in an escaped backslash are no longer mis-parsed as an escaped quote, which used to swallow the following lines by [@​dchaudhari7177] in #680
• dotenv run now prints a friendly error instead of a traceback when no command is given by [@​bbc2] in #606
• Cache the parsed result for empty .env files so repeated dotenv_values/load_dotenv calls no longer re-read the file by [@​ReinerBRO] in #638

Commits

• 49515af Bump version: 1.2.2 → 1.2.3
• 8ac846f chore: add release runbook (RELEASING.md) and make release target
• bb31c94 docs: add 1.2.3 release notes (#606, #638, #680)
• f7b18d9 fix: round-trip backslashes through set_key (#680)
• 751f8c1 ci(deps): bump actions/checkout from 6.0.2 to 6.0.3 in the github-actions gro...
• f1937b6 chore(deps): update mkdocs-include-markdown-plugin requirement from >=6.0.0 t...
• 45b9372 chore(deps): update pytest requirement from >=3.9 to >=9.0.3 (#653)
• 72896e9 docs: fix broken mkdocs link in CONTRIBUTING.md (#636)
• 72754a1 ci(deps): bump peaceiris/actions-gh-pages from 4.0.0 to 4.1.0 in the github-a...
• 078325e ci(security): harden CI/CD supply chain with SHA pinning and least-privilege ...
• Additional commits viewable in compare view

Updates scikit-learn from 1.9.0 to 1.9.1

Release notes

Sourced from scikit-learn's releases.

Scikit-learn 1.9.1

We're happy to announce the 1.9.1 release.

This release contains a few bug fixes and is the first version supporting Python 3.15.

You can see the changelog here: https://scikit-learn.org/stable/whats_new/v1.9.html#version-1-9-1

You can upgrade with pip as usual:

pip install -U scikit-learn

The conda-forge builds can be installed using:

conda install -c conda-forge scikit-learn

Thanks to everyone who contributed to this release !

Commits

• 866c0f5 generate changelog
• 12f135f update upper bounds
• 43ff2f2 bump version
• b851524 DOC Mark dev index as orphan (#34916)
• 01d56d4 DOC Fix wikipedia principal eigenvector example references (#34915)
• b86a1e2 🔒 🤖 CI Update lock files for array-api CI build(s) 🔒 🤖 ...
• d282698 🔒 🤖 CI Update lock files for main CI build(s) 🔒 🤖 (#34897)
• eb34279 🔒 🤖 CI Update lock files for free-threaded CI build(s) 🔒 :rob...
• 7581303 FIX: Fix QuantileTransformer(ignore_implicit_zeros=True) sub-sampling behav...
• ac47f4d FIX: avoid EfficiencyWarning in OPTICS with metric='precomputed' (#34692)
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Updates pandas from 3.0.5 to 3.0.6

Release notes

Sourced from pandas's releases.

pandas 3.0.6

We are pleased to announce the release of pandas 3.0.6. This is a patch release in the 3.0.x series and includes some regression fixes and bug fixes. We recommend that all users of the 3.0.x series upgrade to this version. This is also the first release to support Python 3.15.

See the full whatsnew for a list of all the changes.

Pandas 3.0 supports Python 3.11 and higher. The release can be installed from PyPI:

python -m pip install --upgrade pandas==3.0.*

Or from conda-forge

conda install -c conda-forge pandas=3.0

Please report any issues with the release on the pandas issue tracker.

Thanks to all the contributors who made this release possible.

Commits

• 2905718 RLS: 3.0.6
• 3188ced [backport 3.0.x] BUG: read_csv(sep=None) raised TypeError instead of falling...
• f097905 DOC: cleanup 3.0.6 whatsnew + mention Python 3.15 support (#68965) (#68969)
• 4f68223 [backport 3.0.x] BUG: fix setting with bool column mask into 1-column DataFra...
• e3df0e8 [backport 3.0.x] BUG: full-slice setitem into a pyarrow-backed array shared m...
• b7735f6 Backport PR #66117 on branch 3.0.x (BUG: interpolate leaving NAs unfilled for...
• bca0b77 [backport 3.0.x] BUG: read_csv leaked the string-intern table when a column f...
• bca1e5d [backport 3.0.x] BUG: prevent external mutation of RangeIndex._data (CoW) (#6...
• c95b42c [3.0.x] CI: skip cython-lint on pre-commit.ci (#68910)
• 9cbd884 [backport 3.0.x] Backport of some already merged regression fixes (#68447)
• Additional commits viewable in compare view

Updates onnxruntime from 1.28.0 to 1.30.0

Release notes

Sourced from onnxruntime's releases.

ONNX Runtime v1.30.0

ONNX Runtime 1.30.0 expands generative AI inference, improves CPU and GPU performance, adds Go bindings, and strengthens runtime reliability. These notes cover changes since ONNX Runtime 1.29.1.

Highlights

• Expanded CUDA inference support with variable-length causal convolution for continuous batching, speculative decoding in paged XQA, and INT4 paged KV caches with per-channel scales (#32168, #32340, #32515).
• Improved WebGPU PagedAttention, added GPT-OSS support and INT8 KV-cache block quantization, and extended convolution optimizations (#31727, #32277, #32284, #32420).
• Added fused CPU LinearAttention kernels for AVX-512, Arm64 NEON, and SVE, plus AVX2 LayerNorm/RMSNorm acceleration (#31674, #31973, #32178, #32356).
• Added Go bindings for the ONNX Runtime C API and DeepSeek Engram contrib operators (#29615, #32268).

Announcements & Compatibility

• FP4 QMoE kernels are now enabled by default in CUDA builds, with Windows build support added in this release. Source builds can opt out with -Donnxruntime_USE_FP4_QMOE=OFF (#32096, #32163).
• CUDA fpA-intB builds now default to a compact kernel set for FP16 activations, INT4/INT8 weights, scale-only quantization, and block_size=32. Set -Donnxruntime_USE_FPA_INTB_GEMM_FULL=ON when building from source to retain the full kernel set, including BF16, zero-point, bias, larger-block-size, and native Hopper variants (#32324).
• CPU FP16 Gemm and MatMul execution is gated on hardware acceleration. CPU-assigned FP16 nodes without a matching kernel now fall back to FP32 (#32301, #32197).
• WebGPU plugin EP packaging now supports Linux AArch64. Plugin versions were advanced to WebGPU 0.4.0 and CUDA 0.2 (#32287, #31960, #31970).

Security & Reliability

Model Loading, Memory, and Input Validation

• Limited nested model-graph depth and canonicalized external-data locations to harden model loading (#32344, #32135).
• Added checked rounding for BFC arena allocations and fixed prepacked-weight reference lifetimes (#32010, #32040).
• Strengthened shape, rank, and parameter validation for Split, Scan, GatherND, ScatterND, SpaceToDepth/DepthToSpace, Crop, Conv, Normalizer, and pooling (#29461, #31668, #32034, #32039, #32076, #32157, #32160, #32161, #32345, #32349).
• Hardened generation and attention input handling, including attention-attribute narrowing, BifurcationDetector inputs, generation subgraph shapes, and QEmbed segment inputs. BeamSearch buffer expansion now uses dynamic shape storage (#31648, #31701, #32009, #32078, #32144).
• Validated TreeEnsemble node references and bounded subtree comparison, rejected non-finite CPU RoiAlign coordinates, and required ImageScaler bias to match the channel count (#32031, #32043, #32011, #32002).
• Added an allowlist of safe LoRA adapter parameter data types, validated MatMulFpQ4 shape inputs, and checked MLAS blockwise quantization/dequantization index ranges (#31682, #32032, #32007).

GPU Bounds and Resource Lifetimes

• Hardened CUDA indexing and buffer-size arithmetic in MatMulNBits, RemovePadding, RotaryEmbedding, SparseAttention, Whisper beam search, NMS, QDQ, and GatherElements (#31643, #31994, #31995, #31996, #31998, #32014, #32029, #32030).
• Fixed overflow in CUDA reduction scans and Softmax offset arithmetic, and handled zero-sized outputs in CUDA random-generator kernels (#32137, #32330, #31997).
• Fixed CUDA MultiHeadAttention shared-cache scratch lifetimes and kept CudaAsyncBuffer staging storage alive across CUDA graph replay (#31968, #32121).
• Fixed WebGPU out-of-bounds subgroup-matrix loads for partial tiles, zero-initialized writable device-allocator buffers, and rejected foreign GPU handles in built-in data transfers (#32364, #32063, #32317).

Dependencies and Tooling

• Upgraded Protobuf to 33.6 and refreshed Python documentation dependencies, including an ONNX security-related update (#29906, #32190, #32424).
• Updated JavaScript dependencies including js-yaml, joi, fast-uri, and the Next.js end-to-end fixture (#32397, #32486, #32488, #32505, #32508).
• Pinned GitHub Actions to full-length commit SHAs and strengthened packaging infrastructure with authenticated package feeds and NPM network isolation (#32176, #32005, #32440).

New Features

Core APIs & Runtime

• Added Go bindings for the ONNX Runtime C API (#29615).
• Extended memory importing with host-pointer support and added access to preallocated outputs through KernelContext::GetPreallocatedOutput (#29726, #32089).
• Added packed-attention workspace recipes and estimates, and made workspace input-shape handling aware of optional inputs (#32283, #32321, #32312).
• Added DeepSeek Engram contrib operators, EngramGate and NGramHashMapping, and expanded kernel coverage for Qwen-3.5 operators (#32268, #32106).

... (truncated)

Commits

• f2c39fe [CUDA] Add INT4 paged KV cache with per-channel scales (#32515)
• 5894ba8 Add portable random-access file reads to Env (#32503)
• a2ee3eb Fix CUDA plugin device discovery on WSL (#32517)
• b652e59 [WebGPU] Prepack Conv weights for the im2col-matmul path (#32420)
• 0f0f29f Get rid of spurious warning about not being able to find spectre mitigation (...
• 23dd651 Register ONNX schemas only when static registration is disabled (#32353)
• 33af5d3 Release external data loaders after graph initialization (#32502)
• 2e3c24d Clarify external initializer and EP context path interaction (#32442)
• e76036b [CUDA] Pin FP8 GEMV residency for grids just past two blocks per SM (#32433)
• 82583c5 Add session option for a BNHS GroupQueryAttention Value cache layout (#32139)
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