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Bumps the production-dependencies group with 10 updates in the / directory:

Package From To
pydantic 2.13.4 2.13.5
pyarrow 24.0.0 25.0.1
typer 0.26.8 0.27.2
tqdm 4.68.3 4.70.1
cachetools 7.1.4 7.1.8
fastapi 0.139.0 0.141.1
ado-autoconf 1.8.0 1.9.6
lightgbm 4.6.0 4.7.0
torch 2.12.1 2.14.0
tabpfn 8.0.3 8.5.0

Updates pydantic from 2.13.4 to 2.13.5

Release notes

Sourced from pydantic's releases.

v2.13.5 (2026-08-28)

What's Changed

Fixes

  • Allow reuse of validators when plugins are set by @​Viicos in #13535
  • Fix missing GC traversal on some pydantic-core struct fields by @​Viicos in #13624
  • Fix missing GC traversal in pydantic-core for GeneralFieldsSerializer by @​Viicos in #13629
  • Count validated model fields once in smart unions by @​tamird in #13731
Changelog

Sourced from pydantic's changelog.

v2.13.5 (2026-08-28)

GitHub release

What's Changed

Fixes

  • Allow reuse of validators when plugins are set by @​Viicos in #13535
  • Fix missing GC traversal on some pydantic-core struct fields by @​Viicos in #13624
  • Fix missing GC traversal in pydantic-core for GeneralFieldsSerializer by @​Viicos in #13629
  • Count validated model fields once in smart unions by @​tamird in #13731
Commits
  • 001dea0 Bump pypa/gh-action-pypi-publish action to v1.14.2
  • 558379f Bump twine to v7.0.0
  • 2cfd5d3 Do not check for docs build
  • a735bee Fix more Clippy lints
  • 7eed4a1 Fix Clippy 0.1.95 warnings
  • b353bbb Prepare release v2.13.5
  • 63d2ccc Count validated model fields once in smart unions
  • a53ec2e Speed up PyPy CI tests
  • d65e0f9 Workaround circular import error in Mypy
  • 47a6dbf Fix missing GC traversal in pydantic-core for GeneralFieldsSerializer
  • Additional commits viewable in compare view

Updates pyarrow from 24.0.0 to 25.0.1

Release notes

Sourced from pyarrow's releases.

Apache Arrow 25.0.1

Release Notes URL: https://arrow.apache.org/release/25.0.1.html

Apache Arrow 25.0.1 RC1

Release Notes: Release Candidate: 25.0.1 RC1

Apache Arrow 25.0.1 RC0

Release Notes: Release Candidate: 25.0.1 RC0

Apache Arrow 25.0.0

Release Notes URL: https://arrow.apache.org/release/25.0.0.html

Apache Arrow 25.0.0 RC1

Release Notes: Release Candidate: 25.0.0 RC1

Commits

Updates typer from 0.26.8 to 0.27.2

Release notes

Sourced from typer's releases.

0.27.2

Refactors

  • ♻️ Create exceptions module and TyperException base class. PR #1942 by @​svlandeg.

Docs

  • 🐛 Fix showing fast button as external link in animated terminals in docs. PR #1912 by @​phalberg.

Internal

0.27.1

Features

  • ✨ Make epilog formatting consistent with other parts of the help string. PR #1405 by @​svlandeg.

Docs

Internal

0.27.0

Breaking Changes

Internal

... (truncated)

Changelog

Sourced from typer's changelog.

0.27.2 (2026-08-28)

Refactors

  • ♻️ Create exceptions module and TyperException base class. PR #1942 by @​svlandeg.

Docs

  • 🐛 Fix showing fast button as external link in animated terminals in docs. PR #1912 by @​phalberg.

Internal

0.27.1 (2026-08-03)

Features

  • ✨ Make epilog formatting consistent with other parts of the help string. PR #1405 by @​svlandeg.

Docs

Internal

0.27.0 (2026-07-15)

Breaking Changes

Internal

... (truncated)

Commits

Updates tqdm from 4.68.3 to 4.70.1

Release notes

Sourced from tqdm's releases.

tqdm v4.70.1 stable

  • contrib.concurrent: fix no-len iterables (#1830 <- #1828)
  • tests: major overhaul (#1819)
  • update AI policy in PR template
  • misc lint & tidy
  • CI: bump workflow actions & pre-commit hooks

tqdm v4.70.0 stable

  • contrib.concurrent: major improvements
    • support process_map(mp_context, max_tasks_per_child), thread_map(thread_name_prefix) (#1265)
    • fix total based on shortest iterable length (#1473)
    • use default max_workers (#1543 <- #1530, #1518)
    • support timeout, buffersize (#1576)
    • improve ETA (#1708 <- #1161)
    • update as_completed (#1709 <- #1565)
    • add tqdm.concurrent.intepreter_map (#1777)
  • asyncio: support iterables with only __aiter__ (#1714 <- #1686)
  • support reset(float("inf")) (#1783 <- #1781, #651)
  • framework: test & reduce wheel size (#1782)

tqdm v4.69.1 stable

tqdm v4.69.0 stable

  • add tqdm.asyncio.gather(..., return_exceptions=False) (#1776, #1671 <- #1286)
  • misc minor framework updates
    • bump workflow actions & pre-commit hooks

tqdm v4.68.4 stable

Commits

Updates cachetools from 7.1.4 to 7.1.8

Changelog

Sourced from cachetools's changelog.

v7.1.8 (2026-08-31)

  • Reject negative maxsize in Cache.__init__.

v7.1.7 (2026-08-01)

  • Improve Cache.__setitem__ behavior when replacing an existing cache item with a larger value.

  • Update CI environment.

v7.1.6 (2026-07-24)

  • Minor style improvements to keep ruff happy.

v7.1.5 (2026-07-23)

  • Fix TLRUCache silently keeping stale values on expired overwrites.

  • Reject negative cache item getsizeof values.

  • Update build environment.

Commits
  • 4500e3d Release v7.1.8.
  • 6e49bef Update copilot instructions and review.
  • defc58b Prepare v7.1.8.
  • a39180b Remove somewhat superfluous and slightly incorrect documentation note regardi...
  • dd181c5 Reject negative maxsize in Cache.init
  • b43b953 Use monthly batches for dependabot updates.
  • 01af8e5 Release v7.1.7.
  • ccaa8c8 Minor stylistic improvements.
  • c65b625 Prepare v7.1.7.
  • 89a5928 Bump actions/setup-python from 6.3.0 to 7.0.0 (#411)
  • Additional commits viewable in compare view

Updates fastapi from 0.139.0 to 0.141.1

Release notes

Sourced from fastapi's releases.

0.141.1

Fixes

  • 🐛 Fix support for background tasks and headers from dependencies in app.frontend(). PR #16105 by @​tiangolo.

Docs

0.141.0

Features

  • ✨ Add app.frontend(check_dir="auto"), to make local development more convenient with fastapi dev. PR #16102 by @​tiangolo.

0.140.13

Fixes

Docs

0.140.12

Fixes

0.140.11

Fixes

  • 🐛 Fix response_model_* params ignored for non-generator endpoints with Iterable[..] return type. PR #15093 by @​YuriiMotov.

0.140.10

Fixes

Internal

0.140.9

Fixes

  • 🐛 Fix exclude_defaults not propagated to dict keys and values in jsonable_encoder. PR #16043 by @​MBGrao.

... (truncated)

Commits
  • 95f8322 🔖 Release version 0.141.1 (#16106)
  • f137944 📝 Update release notes
  • d623544 🐛 Fix support for background tasks and headers from dependencies in `app.fron...
  • 1d211b9 📝 Update release notes
  • 8a1f876 📝 Document FASTAPI_ENV in FastAPI CLI guide (#16104)
  • c7e7b65 🔖 Release version 0.141.0 (#16103)
  • 6bceb84 📝 Update release notes
  • 5429fed ✨ Add app.frontend(check_dir="auto"), to make local development more conven...
  • 628663f 🔖 Release version 0.140.13 (#16096)
  • 0b54fd0 📝 Update release notes
  • Additional commits viewable in compare view

Updates ado-autoconf from 1.8.0 to 1.9.6

Updates lightgbm from 4.6.0 to 4.7.0

Release notes

Sourced from lightgbm's releases.

v4.7.0

Highlights

The Python package now supports polars inputs, thanks to narwhals. Thanks to @​borchero for the main implementation and to everyone who contributed design work, especially on lightgbm-org/LightGBM#6204 (@​maxzw @​detrin @​jmoralez @​lcrmorin @​Ic3fr0g @​MarcoGorelli @​kylebarron @​vyasr).

Significantly improved GPU support including the first ROCm builds (lightgbm-org/LightGBM#6086) and multi-GPU support for NVIDIA GPUs via NCCL (lightgbm-org/LightGBM#6138). (@​jeffdaily @​shiyu1994 @​StrikerRUS)

Improvements to distributed training / Dask. Lots of bugfixes in this area, still ongoing work, thanks especially to @​wagner-austin for all the help.

Some organizational changes. The project has changed GitHub orgs (Microsoft -> lightgbm-org) and default branch names (master -> main).

Changes

💡 New Features

🔨 Breaking

... (truncated)

Commits
  • 8f7036f release v4.7.0 (#7129)
  • 497b57f [python-package] allow access to eval result attributes by name (#7161)
  • 96dfee9 [python-package] Allow to pass Arrow array & Polars series as position (#7260)
  • b97453d [python-package] Add pandas tests for categorical handling and dtype validati...
  • e455031 [ci] add ppc64le C++ test job (#7345)
  • 18810cb [ci] remove lingering references to 'master' branch (#7353)
  • 0704724 [ci] [R-package] use a Windows-specific download link for SWIG, stop using '<...
  • 75c0190 [python-package] remove unnecessary old import paths in compat.py (#7358)
  • 688d789 [ci] avoid overwriting installed 'build' in build-python.sh (#7356)
  • cf16013 change default branch from 'master' to 'main' (#7287)
  • Additional commits viewable in compare view

Updates torch from 2.12.1 to 2.14.0

Release notes

Sourced from torch's releases.

PyTorch 2.14.0 Release Notes

Highlights

For more details about these highlighted features, you can look at the release blogpost. Below are the full release notes for this release.

Backwards Incompatible Changes

torch.nn

  • torch.nn.LinearCrossEntropyOptions no longer accepts acc_policy="balanced"; use "compact" instead (#188283)

    The "balanced" policy was removed because "compact" provides the same weight-gradient accumulation precision with lower memory use on CUDA, already uses the equivalent scratch layout for mixed-precision inputs on other devices, and was never selected by "auto". Constructing the options with acc_policy="balanced" now raises ValueError: invalid acc_policy: 'balanced'; expected one of 'auto', 'accurate', 'compact'.

    Before:

    options = torch.nn.LinearCrossEntropyOptions(acc_policy="balanced")
loss = torch.nn.functional.linear_cross_entropy(
    input, linear_weight, target, options=options
)

    After:

    options = torch.nn.LinearCrossEntropyOptions(acc_policy="compact")
loss = torch.nn.functional.linear_cross_entropy(

... (truncated)

Commits
  • 2b3ec34 [release/2.14] Import SDPAParams in test_transformers to fix lint (#194970)
  • 08187d9 [cuDNN] Add guards for cuDNN SDPA decode (#194963)
  • 8ceea97 Pin cython < 3.3.0 for the Windows Triton wheel build (#194931)
  • 99ecebc [Cherry-pick][release/2.14] [inductor] Fix loop-local load CSE lifetime (#194...
  • ec283a7 Bump the Python 3.15 numpy pin to 2.5.2 (#194821)
  • 65890f3 Fix docker-release validate job to use the channel matching the pushed image ...
  • 1682388 Fix macOS py3.15 wheel builds: pin Cython < 3.3.0 and bump the cp315 numpy pi...
  • 9724418 Fix Windows py3.15 builds: constrain Cython < 3.3.0 and bump the cp315 numpy ...
  • f1b7554 [MPS] Fix pin_memory() recycling buffers still in use by the GPU (#194662)
  • 9f205f7 [MPS] fail loudly on large reductions (#194661)
  • Additional commits viewable in compare view

Updates tabpfn from 8.0.3 to 8.5.0

Release notes

Sourced from tabpfn's releases.

v8.5.0

Breaking Changes

  • Cache the decoder keys instead of the train embeddings. get_embeddings(model, X_test, data_source="train") is not supported with cached infernce anymore. (#1189)
  • tabpfn.model_loading.download_all_models() now raises an exception if one or more of the models fails to download. It will still download all possible models before raising the exception. (#1195)

Added

  • fit() now recognizes a date-like string column internally, though nothing yet expands it into calendar features: it is still read as a plain category or text. We also added InferenceConfig.MIN_CARDINALITY_FOR_TEXT, to differentiate between category-vs-text and category-vs-number decisions; they default to the same value, since we are still not handling text. (#1205)

Changed

  • Reduced peak host memory during preprocessing: the ensemble preprocessor no longer rebuilds the feature matrix in steps that cannot change it, taking transient RSS from 42.7 GB to 12.0 GB (-72%), and wall time with it, on a 666,667 x 2,000 float64 fit. Preprocessed outputs are unchanged. (#1186)
  • Reduced peak host memory during preprocessing for tables with categorical columns: the reshape and ordinal-encoding steps no longer rebuild the feature matrix to reorder it or to encode part of it, taking transient RSS from 3.33 GB to 2.80 GB (-16%) on a 333,333 x 400 half-categorical fit. Preprocessed outputs are unchanged. (#1187)
  • Speed up modality detection on large string columns. Deciding whether a column holds numbers or dates now stops at the first value that does not parse within a 1024-row prefix, instead of parsing every row first. Detection of a 1-million-row free-text column drops from roughly 14 seconds to under 20 milliseconds; the answers are unchanged. (#1208)

Fixed

  • Fix an "illegal memory access" crash in the backward pass when fine-tuning on large batches: FlashAttention's backward indexes its workspace with 32-bit integers, so the batch is now chunked to keep each call inside that range. (#1184)
  • Fix fit_mode="fit_with_cache" raising TypeError: forward() missing 1 required positional argument: 'task_type' for architectures whose forward pass takes a task_type: the KV cache build now forwards it, like the prediction paths already did. (#1197)
  • fit() no longer crashes the interpreter outright on a table whose text column holds a hash-like value such as "8e2569614270f3d8b9e7038efac9f116". Modality detection asked pandas.to_numeric whether a column was numeric; below pandas 3.0 that function has a signed 32-bit integer overflow in its scientific-notation parser and segfaults on a string whose exponent lands in [2**31, 2**32) (pandas#63650, fixed upstream in pandas 3.0). A segfault cannot be caught with try/except, so below pandas 3.0 the check now reads one value at a time with Python's built-in float, which does not share the bug. On pandas 3.0 and later the check is unchanged. (#1203)
  • Fix TabPFNRegressor rejecting a checkpoint whose config also describes a classification head: the criterion now follows the task the estimator is built for rather than being inferred from max_num_classes. Loading a regression checkpoint into TabPFNClassifier now raises instead of silently building an unused bar distribution. (#1204)

v8.4.0

Added

  • TabPFNRegressor now accepts eval_metric and tuning_config arguments: passing tuning_config={"calibrate_temperature": True} makes fit() calibrate the temperature of the aggregated ensemble distribution on a holdout, sharpening or widening the predicted distribution as the data demands and improving every predict() output type, including the predicted quantiles. Set eval_metric to "nll" (the default, negative log-likelihood), "crps" (continuous ranked probability score, the same implementation used by the finetuning loss) to choose which quantity the calibration optimises; they weight the predicted distribution differently and pick noticeably different temperatures, so pick the metric you will be judged by. (#1172)
  • In the previous setup, all GPUs in finetuning with DDP held all activations of all estimators in memory. This PR divides estimator activations across the available GPUs. (#1182)

Changed

  • The temperature grid searched when calibrating TabPFNClassifier's softmax temperature now contains 1.0 exactly, so calibration can leave a distribution untouched. Previously the grid straddled 1.0 without including it, meaning a calibrated model always applied some correction even when none was warranted. Calibrated temperatures may therefore differ slightly from previous releases. (#1172)
  • fit() cleans large tables with far less memory and time: the redundant float64 copies are gone, cutting both transient memory and wall time by about two thirds on a 5.3 GB all-numeric table. (#1173)
  • fit() uses less memory on tables with categorical columns: the encoded array is now assembled in place instead of being stacked and then reordered, cutting transient memory by about a quarter on a half-string table. (#1174)
  • fit() no longer slows to a crawl on wide tables with categorical columns under pandas < 3: the dtype casts no longer rebuild the frame one column at a time, which took minutes on a 333,333 x 400 table and now takes seconds. (#1180)
  • Reduce peak GPU memory during KV-cache construction by quantizing layers as they are built and temporarily staging completed estimator caches on CPU in memory-saving mode. (#1183)

Fixed

  • TabPFNRegressor.predict_batched now raises NotImplementedError when the estimator was constructed with a tuning_config, instead of silently returning uncalibrated predictions. The ensemble temperature is calibrated on each dataset's own holdout, so a fused batch has no single temperature to apply; score such datasets individually with predict. This matches the existing guard in TabPFNClassifier.predict_proba_batched. (#1172)

v8.3.0

Added

  • Fine-tuning now supports validation_frequency to run validation and early-stopping checks every N epochs. (#811)
  • Add ManyClassDecoder.attention_weights, the canonical per-training-row attention distribution of the multiclass decoder head, so interpretability tooling can read out which training rows drive a prediction without reimplementing the head's internal forward pass. The method exists only on multiclass models that use this decoder. (#1142)
  • Add fp8 kv cache dtype. (#1157)
  • fit() now warns when a column of X looks like free text. (#1159)
  • Add an opt-in built-model cache to load_model, enabled via the TABPFN_MODEL_CACHE_SIZE environment variable (default off). When set, repeated loads of the same checkpoint reuse the constructed model instead of rebuilding the architecture and re-running load_state_dict. Only the non-mutating (cache_trainset_representation=False) build is cached. (#1162)
  • Add TabPFNRegressor.predict_batched, the regression counterpart to TabPFNClassifier.predict_proba_batched. It preprocesses each (X_train, y_train, X_test) triple exactly as fit + predict does, stacks the datasets on the model's batch dimension and scores them with a single fused forward per estimator, then decodes each dataset with its own target standardisation and per-estimator border transforms. Returns one entry per dataset in input order, each with the same structure predict would return for that dataset. Datasets must share array shapes; constant-target datasets are answered analytically.

... (truncated)

Changelog

Sourced from tabpfn's changelog.

[8.5.0] - 2026-08-27

Breaking Changes

  • Cache the decoder keys instead of the train embeddings. get_embeddings(model, X_test, data_source="train") is not supported with cached infernce anymore. (#1189)
  • tabpfn.model_loading.download_all_models() now raises an exception if one or more of the models fails to download. It will still download all possible models before raising the exception. (#1195)

Added

  • fit() now recognizes a date-like string column internally, though nothing yet expands it into calendar features: it is s...

    Description has been truncated

@dependabot dependabot Bot added dependencies Pull requests that update a dependency file python:uv Pull requests that update python:uv code labels Sep 16, 2026
@dependabot
deps: bump the production-dependencies group across 1 directory with …
4fac6dc 
…10 updates

Bumps the production-dependencies group with 10 updates in the / directory:

| Package | From | To |
| --- | --- | --- |
| [pydantic](https://github.com/pydantic/pydantic) | `2.13.4` | `2.13.5` |
| [pyarrow](https://github.com/apache/arrow) | `24.0.0` | `25.0.1` |
| [typer](https://github.com/fastapi/typer) | `0.26.8` | `0.27.2` |
| [tqdm](https://github.com/tqdm/tqdm) | `4.68.3` | `4.70.1` |
| [cachetools](https://github.com/tkem/cachetools) | `7.1.4` | `7.1.8` |
| [fastapi](https://github.com/fastapi/fastapi) | `0.139.0` | `0.141.1` |
| ado-autoconf | `1.8.0` | `1.9.6` |
| [lightgbm](https://github.com/lightgbm-org/LightGBM) | `4.6.0` | `4.7.0` |
| [torch](https://github.com/pytorch/pytorch) | `2.12.1` | `2.14.0` |
| [tabpfn](https://github.com/priorlabs/tabpfn) | `8.0.3` | `8.5.0` |



Updates `pydantic` from 2.13.4 to 2.13.5
- [Release notes](https://github.com/pydantic/pydantic/releases)
- [Changelog](https://github.com/pydantic/pydantic/blob/v2.13.5/HISTORY.md)
- [Commits](pydantic/pydantic@v2.13.4...v2.13.5)

Updates `pyarrow` from 24.0.0 to 25.0.1
- [Release notes](https://github.com/apache/arrow/releases)
- [Commits](apache/arrow@apache-arrow-24.0.0...apache-arrow-25.0.1)

Updates `typer` from 0.26.8 to 0.27.2
- [Release notes](https://github.com/fastapi/typer/releases)
- [Changelog](https://github.com/fastapi/typer/blob/master/docs/release-notes.md)
- [Commits](fastapi/typer@0.26.8...0.27.2)

Updates `tqdm` from 4.68.3 to 4.70.1
- [Release notes](https://github.com/tqdm/tqdm/releases)
- [Commits](tqdm/tqdm@v4.68.3...v4.70.1)

Updates `cachetools` from 7.1.4 to 7.1.8
- [Changelog](https://github.com/tkem/cachetools/blob/master/CHANGELOG.rst)
- [Commits](tkem/cachetools@v7.1.4...v7.1.8)

Updates `fastapi` from 0.139.0 to 0.141.1
- [Release notes](https://github.com/fastapi/fastapi/releases)
- [Commits](fastapi/fastapi@0.139.0...0.141.1)

Updates `ado-autoconf` from 1.8.0 to 1.9.6

Updates `lightgbm` from 4.6.0 to 4.7.0
- [Release notes](https://github.com/lightgbm-org/LightGBM/releases)
- [Commits](lightgbm-org/LightGBM@v4.6.0...v4.7.0)

Updates `torch` from 2.12.1 to 2.14.0
- [Release notes](https://github.com/pytorch/pytorch/releases)
- [Changelog](https://github.com/pytorch/pytorch/blob/main/RELEASE.md)
- [Commits](pytorch/pytorch@v2.12.1...v2.14.0)

Updates `tabpfn` from 8.0.3 to 8.5.0
- [Release notes](https://github.com/priorlabs/tabpfn/releases)
- [Changelog](https://github.com/PriorLabs/TabPFN/blob/main/CHANGELOG.md)
- [Commits](PriorLabs/TabPFN@v8.0.3...v8.5.0)

---
updated-dependencies:
- dependency-name: ado-autoconf
  dependency-version: 1.9.6
  dependency-type: direct:production
  update-type: version-update:semver-minor
  dependency-group: production-dependencies
- dependency-name: cachetools
  dependency-version: 7.1.8
  dependency-type: direct:production
  update-type: version-update:semver-patch
  dependency-group: production-dependencies
- dependency-name: fastapi
  dependency-version: 0.141.1
  dependency-type: direct:production
  update-type: version-update:semver-minor
  dependency-group: production-dependencies
- dependency-name: lightgbm
  dependency-version: 4.7.0
  dependency-type: direct:production
  update-type: version-update:semver-minor
  dependency-group: production-dependencies
- dependency-name: pyarrow
  dependency-version: 25.0.1
  dependency-type: direct:production
  update-type: version-update:semver-major
  dependency-group: production-dependencies
- dependency-name: pydantic
  dependency-version: 2.13.5
  dependency-type: direct:production
  update-type: version-update:semver-patch
  dependency-group: production-dependencies
- dependency-name: tabpfn
  dependency-version: 8.5.0
  dependency-type: direct:production
  update-type: version-update:semver-minor
  dependency-group: production-dependencies
- dependency-name: torch
  dependency-version: 2.14.0
  dependency-type: direct:production
  update-type: version-update:semver-minor
  dependency-group: production-dependencies
- dependency-name: tqdm
  dependency-version: 4.70.1
  dependency-type: direct:production
  update-type: version-update:semver-minor
  dependency-group: production-dependencies
- dependency-name: typer
  dependency-version: 0.27.2
  dependency-type: direct:production
  update-type: version-update:semver-minor
  dependency-group: production-dependencies
...

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@dependabot dependabot Bot changed the title deps: bump the production-dependencies group with 10 updates deps: bump the production-dependencies group across 1 directory with 10 updates Sep 16, 2026
@dependabot
dependabot Bot force-pushed the dependabot/uv/production-dependencies-8a0737f0f1 branch from 3fc5196 to 4fac6dc Compare September 16, 2026 09:40
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Welcome to Codecov 🎉

Once you merge this PR into your default branch, you're all set! Codecov will compare coverage reports and display results in all future pull requests.

Thanks for integrating Codecov - We've got you covered ☂️

@dependabot @github

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Looks like these dependencies are updatable in another way, so this is no longer needed.

@dependabot dependabot Bot closed this Sep 30, 2026
@dependabot
dependabot Bot deleted the dependabot/uv/production-dependencies-8a0737f0f1 branch September 30, 2026 18:09
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