Update scikit-learn to version 1.5 #967
Merged
Eyal-Danieli merged 18 commits intomlrun:developmentfrom Feb 12, 2026
Merged
Conversation
fixes and patches for new scikit-learn version changes in item.yaml and regenerate function.yaml
fix _get_dataframe to handle list/dict before accessing artifact_url added feature name preservation logic in predict function
mlrun v 1.10
added skip for test_train in test_auto_trainer.py
change XGBRegressor to LGBMRegressor
guy1992l
requested changes
Feb 11, 2026
| ("sklearn.linear_model.LinearRegression", "regression"), | ||
| ("sklearn.ensemble.RandomForestClassifier", "classification"), | ||
| ("xgboost.XGBRegressor", "regression"), | ||
| ("lightgbm.LGBMRegressor", "regression"), |
Member
There was a problem hiding this comment.
add these to the test so we can know for sure all is working with the feature names changes:
("xgboost.XGBRegressor", "regression"),
("xgboost.XGBClassifier", "classification"),
("lightgbm.LGBMRegressor", "regression"), # This one you added already.
("lightgbm.LGBMClassifier", "classification")…assifier models to test
Eyal-Danieli
pushed a commit
to Eyal-Danieli/functions
that referenced
this pull request
Feb 16, 2026
* updated scikit-learn~=1.5 fixes and patches for new scikit-learn version changes in item.yaml and regenerate function.yaml * remove filename * remove numpy import * revert sklearn.metrics monkey patch fix _get_dataframe to handle list/dict before accessing artifact_url added feature name preservation logic in predict function * revert mlrun version * revert get_or_create_project * revert scikit-learn version * scikit-learn==1.5.2 mlrun v 1.10 * scikit-learn==1.4.2 * revert scikit-learn<1.4.0 * scikit-learn~=1.5 * mlrun 1.10 with scikit-learn<1.4.0 * scikit-learn strict v~=1.5.2 added skip for test_train in test_auto_trainer.py * revert sklearn_classifier.py changes change XGBRegressor to LGBMRegressor * added xgboost.XGBRegressor, xgboost.XGBClassifier and lightgbm.LGBMClassifier models to test
Eyal-Danieli
added a commit
that referenced
this pull request
Feb 16, 2026
* Update scikit-learn to version 1.5 (#967) * updated scikit-learn~=1.5 fixes and patches for new scikit-learn version changes in item.yaml and regenerate function.yaml * remove filename * remove numpy import * revert sklearn.metrics monkey patch fix _get_dataframe to handle list/dict before accessing artifact_url added feature name preservation logic in predict function * revert mlrun version * revert get_or_create_project * revert scikit-learn version * scikit-learn==1.5.2 mlrun v 1.10 * scikit-learn==1.4.2 * revert scikit-learn<1.4.0 * scikit-learn~=1.5 * mlrun 1.10 with scikit-learn<1.4.0 * scikit-learn strict v~=1.5.2 added skip for test_train in test_auto_trainer.py * revert sklearn_classifier.py changes change XGBRegressor to LGBMRegressor * added xgboost.XGBRegressor, xgboost.XGBClassifier and lightgbm.LGBMClassifier models to test * [module][langchain_mlrun] First version (#963) * [Build] Fix html links, Add <function>.html as source in documentation * Update CI temporarily and update index * [XGB-Custom] Fix test artifact key name * [XGB-Serving][XGB-Test][XGB-Trainer] Fix tests - artifact key * [Build] Install python 3.9 when testing (#618) * [Build] Update python version in CI (#620) * [Build] Install python 3.9 when testing * [Build] Update python version in CI * . * Revert "[Build] Update python version in CI (#620)" (#621) This reverts commit 0cd1f15. * Revert "[Build] Install python 3.9 when testing (#618)" (#619) This reverts commit 3301415. * [Build] Build with python 3.9 (#622) * [Build] Build with python 3.9 * . * [onnx utils] update onnx utils packages * [Noise-reduction] Add new function to hub (#765) * [Noise-reduction] Add new function to hub * fix test * added multiprocessing and silence removal to function * delete `load_dask` (#822) * [feature selection] update function yaml * [feature selection] update function yaml * Revert "[onnx utils] update onnx utils packages" This reverts commit 8872798. * [feature selection] update function yaml * [feature selection] update function yaml * Delete unsupported functions from the hub (#824) * delete EOS functions * bring back validate_great_expectations * bring back load_dataset * Update feature_selection/test_feature_selection.py Co-authored-by: Eyal Danieli <eyald@iguazio.com> * Update item.yaml * Align to master branch (#826) * [Category] Fix and add categories to functions (#808) * [Category] Fix and add categories to functions * bump version in structured * test is not valid in huggingface_serving * Fix duplicated footer * Fix duplicated footer * revert python version change as it will be done in another PR * comments * comments * Bump python:3.6 to python:3.9 (#810) * [Describe] Align describe to new pandas version (#812) * [Describe] Align describe to new pandas version * minor test fix * update mlrun version * add dask to requirements * remove dask * update numpy version * debug * debug * debug * remove dask tests * remove debug code * [get_offline_features] Updated to mlrun 1.6.3 (#813) * [Feature-selection] Replace matplotlib with plotly (#815) * Iguazio-cicd user token updated Iguazio-cicd user token updated in repo secrets: https://github.com/mlrun/functions/settings/secrets/actions MARKETPLACE_ACCESS_TOKEN_V3 new token gh...Zmf was set around April * forcing iguazio-cicd auth forcing iguazio-cicd to deal with Author identity unknown * checkout@v3 to v4 and echo * [Mlflow_utils] - mlflow model server (#811) * mlflow server * small fix to test * small fixes to ms and nb * small fixes to mlrun version * update requirements lightgbm * added req * Added xgboost to req --------- Co-authored-by: Avi Asulin <34214569+aviaIguazio@users.noreply.github.com> * [Mlflow] Remove mlflow tag (#825) * remove mlflow tag * remove mlflow tag --------- Co-authored-by: Avi Asulin <34214569+aviaIguazio@users.noreply.github.com> * align feature_selection yaml --------- Co-authored-by: Avi Asulin <34214569+aviaIguazio@users.noreply.github.com> Co-authored-by: Yonatan Shelach <92271540+yonishelach@users.noreply.github.com> Co-authored-by: rokatyy <ekaterina_molchanova@mckinsey.com> Co-authored-by: Katerina Molchanova <35141662+rokatyy@users.noreply.github.com> Co-authored-by: nashpaz123 <44337075+nashpaz123@users.noreply.github.com> Co-authored-by: ZeevRispler <73653682+ZeevRispler@users.noreply.github.com> * set `navigation_with_keys` to False (#829) * remove xgb and churn functions (#830) * [Batch Infer V2] Adjust function to 1.7 (#832) * adjust batch infer v2 * update docs in NB * bring back deprecated params and add warn (#834) * fix PyYAML loading (#837) * [text to audio generator] Replaced bark with openai tts models (#836) * [Text to audio generator] Add speech engine (#838) * [text to audio generator] Replaced bark with openai tts models * [text to audio generator] Fix base url env var * fix version * Add speech engine * after review * [auto-trainer] update test requirements (#839) * [Build] Fix html links, Add <function>.html as source in documentation * Update CI temporarily and update index * [XGB-Custom] Fix test artifact key name * [XGB-Serving][XGB-Test][XGB-Trainer] Fix tests - artifact key * [Build] Install python 3.9 when testing (#618) * [Build] Update python version in CI (#620) * [Build] Install python 3.9 when testing * [Build] Update python version in CI * . * Revert "[Build] Update python version in CI (#620)" (#621) This reverts commit 0cd1f15. * Revert "[Build] Install python 3.9 when testing (#618)" (#619) This reverts commit 3301415. * [Build] Build with python 3.9 (#622) * [Build] Build with python 3.9 * . * Update requirements.txt * [Feature Selection] Fix deprecated `get_offline_features` (#844) * fix feature_selection * fix feature_selection * fix feature_selection nb * update yaml name * fix test * fix test * limit torchaudio for unit test (#845) * Update requirements.txt (#843) * [Open Archive] Fix arbitrary file vulnerability (#847) * fix arbitrary file vulnerability * fix arbitrary file vulnerability * fix test * [open_archive] Add traversal attack test (#849) * add traversal test * add traversal test * add traversal test * first version * run upg to pydantic v2 * added kafka and mlrun-ce code preparation * Eyal review * LangChain MLRun Integration with Kafka Support (CE Mode) (#1) * docstring syntax fixes * Add initial Kafka support for MLRun CE Implement _KafkaMLRunEndPointClient with KafkaProducer Add kafka_broker and kafka_topic to MLRunTracerClientSettings Add Kafka parameters to setup_langchain_monitoring() Update notebook to auto-detect CE/Enterprise mode Add kafka-python, orjson, uuid-utils to requirements.txt * added KAFKA_BROKER and DatastoreProfileTDEngine for registering kafka and tsdb profiles * clear output * use get_kafka_topic for the project name remove "raises:" docstring added kafka flush added s3fs to requirements.txt * adaptive notebook for local execution - AWS_ENDPOINT_URL_S3 env variable in deployment - port forwarding scripts * Replace kafka_broker/kafka_topic with stream_profile_name - Update _KafkaMLRunEndPointClient to use DatastoreProfileKafkaStream - Fetch Kafka config (broker, topic, SASL, SSL) from registered profile - Auto-retrieve stream_profile_name from model monitoring credentials - Update MLRunTracerClientSettings with new stream_profile_name field - Update setup_langchain_monitoring() to use profile-based config - Update notebook to use simplified API * Add get_kafka_stream_profile_name() utility to auto-detect Kafka profile * Move dependencies from requirements.txt to item.yaml * generalize env variables * Deploy monitoring app once instead of redeploy Unify profile variable naming for CE and Enterprise modes * _KafkaMLRunEndPointClient constructor - keep project handling NONE able with parent class handling in * revert removal of raise docstring enforce usage of stream_profile_name * change stream_profile_name to kafka_stream_profile_name revert ValueError message * Revert ValueError message Added mechanism to flush stream upon root run (instead of each monitor call) * ensure self._mlrun_client is not None before flush * revert double deploy * Add configurable kafka_linger_ms for hybrid flush control Adds kafka_linger_ms parameter to control message delivery timing: - Explicit flush mode (linger_ms=0, default): flush after each root run - Kafka-managed mode (linger_ms>0): Kafka controls delivery timing The flush() method now handles the mode internally - it's a no-op when Kafka-managed mode is enabled, keeping the tracer code simple. * fix double deploy in notebook (set the in-cluster MinIO endpoint before deploying) * Simplify Kafka flush behavior and enable batching by default - Always flush at end of root run (removed conditional linger_ms check) - Set default kafka_linger_ms to 500ms for message batching - Simplify KafkaProducer initialization (pop bootstrap_servers instead of lambda) * remove local module import from notebook remove redundant requirements from item.yaml * move env variables setup to top of the notebook * renamed env vars * fix test * gilad review --------- Co-authored-by: yonishelach <yonatanshelach@gmail.com> Co-authored-by: Yoni Shelach <92271540+yonishelach@users.noreply.github.com> Co-authored-by: Avi Asulin <avia@iguazio.com> Co-authored-by: Eyal Danieli <eyald@iguazio.com> Co-authored-by: Avi Asulin <34214569+aviaIguazio@users.noreply.github.com> Co-authored-by: rokatyy <ekaterina_molchanova@mckinsey.com> Co-authored-by: Katerina Molchanova <35141662+rokatyy@users.noreply.github.com> Co-authored-by: nashpaz123 <44337075+nashpaz123@users.noreply.github.com> Co-authored-by: ZeevRispler <73653682+ZeevRispler@users.noreply.github.com> Co-authored-by: daniels290813 <78727943+daniels290813@users.noreply.github.com> Co-authored-by: Tomer Weitzman <81749152+tomerbv@users.noreply.github.com> * [onnx_utils] updated pytorch due to security vulnerability (#968) * Update onnx_utils dependencies and improve test robustness - Upgrade PyTorch (2.6.0 → 2.8.0) and TorchVision (0.21.0 → 0.23.0) for better compatibility and performance - Update MLRun version requirement to 1.10.0 in item.yaml - Bump function version to 1.4.0 Test improvements: - Add environment variable validation (MLRUN_DBPATH, MLRUN_ARTIFACT_PATH) - Add conditional test skipping based on tf2onnx availability - Fix cleanup function to properly remove test artifacts (model.pt, model_modules_map.json, onnx_model.onnx, etc.) - Update deprecated artifact_path parameter to output_path - Add explicit project context to all MLRun function calls - Fix PyTorch test artifact path construction * Add conftest fixture for test environment and update notebook to PyTorch demo - Centralize test setup/cleanup in conftest autouse fixture - Rewrite notebook demo from Keras to a working PyTorch MobileNetV2 example * deleted iguazio credentials * Remove conftest.py and inline fixtures into test_onnx_utils.py Move onnx_project and test_environment fixtures directly into the test file to reduce unnecessary indirection for a single test module. --------- Co-authored-by: Tomer Weitzman <81749152+tomerbv@users.noreply.github.com> Co-authored-by: guy1992l <83535508+guy1992l@users.noreply.github.com> Co-authored-by: yonishelach <yonatanshelach@gmail.com> Co-authored-by: Yoni Shelach <92271540+yonishelach@users.noreply.github.com> Co-authored-by: Avi Asulin <avia@iguazio.com> Co-authored-by: Avi Asulin <34214569+aviaIguazio@users.noreply.github.com> Co-authored-by: rokatyy <ekaterina_molchanova@mckinsey.com> Co-authored-by: Katerina Molchanova <35141662+rokatyy@users.noreply.github.com> Co-authored-by: nashpaz123 <44337075+nashpaz123@users.noreply.github.com> Co-authored-by: ZeevRispler <73653682+ZeevRispler@users.noreply.github.com> Co-authored-by: daniels290813 <78727943+daniels290813@users.noreply.github.com> Co-authored-by: Omer Mimon <81911093+omermaim@users.noreply.github.com>
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
3 participants
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
Updates scikit-learn dependency from 1.3 to ~=1.5 with necessary compatibility fixes.
Changes by function:
auto_trainer
gen_class_data
describe
All functions: