feat(skore): Support skrub dataops in reports

[jeromedockes]

closes #2133

Still a rough draft. The different reports can now be initialized with a SkrubLearner rather than a regular scikit-learn estimator. This could allow:

• enabling users to benefit from both skrub and skore
• capturing data wrangling / preprocessing operations that would otherwise be invisible to skore
• perhaps exploiting skrub's built-in previews and subsampling, and maybe one day caching
• maybe opportunities for reporting and diagnoses through inspection of the computation graph and intermediate results
• reporting on hyperparameter search as skrub allows easily specifying hyperparameter ranges (or other kinds of tunable choices) and can perform search either backed by scikit-learn or optuna

[glemaitre]

I'm pretty much fine with what is going on. I'm wondering if we could a sort of abstraction to validate both the data and the estimator at the __init__. But it might be only that things needs to be in 2 dedicated functions and then it makes that the rest is clearer.

[github-actions]

Documentation preview @ 81e33ef

[github-actions]

Coverage Report for skore/

File	Stmts	Miss	Cover	Missing
skore/src/skore
__init__.py	28	0	100%
_config.py	44	1	97%	57
exceptions.py	4	4	0%	4, 15, 19, 23
skore/src/skore/_project
__init__.py	0	0	100%
_summary.py	80	1	98%	121
_widget.py	195	0	100%
login.py	13	2	84%	65–66
plugin.py	12	0	100%
project.py	54	2	96%	131, 140
types.py	3	0	100%
skore/src/skore/_sklearn
__init__.py	8	0	100%
_base.py	54	0	100%
compare.py	5	0	100%
evaluate.py	27	1	96%	133
feature_names.py	26	0	100%
find_ml_task.py	61	0	100%
types.py	21	1	95%	29
skore/src/skore/_sklearn/_comparison
__init__.py	7	0	100%
inspection_accessor.py	26	1	96%	352
metrics_accessor.py	97	3	96%	214, 822, 989
report.py	123	7	94%	479, 486, 489, 495, 536–538
skore/src/skore/_sklearn/_cross_validation
__init__.py	9	0	100%
data_accessor.py	36	2	94%	48, 74
inspection_accessor.py	26	1	96%	324
metrics_accessor.py	93	2	97%	821, 965
report.py	154	21	86%	71–73, 77–79, 83, 194, 222, 433, 461, 464–465, 469, 490, 509, 512, 518, 583–585
skore/src/skore/_sklearn/_estimator
__init__.py	9	0	100%
data_accessor.py	48	1	97%	177
inspection_accessor.py	34	0	100%
metrics_accessor.py	260	2	99%	310, 1105
report.py	210	25	88%	44–46, 51, 54, 60, 207–211, 397, 429, 432–433, 477, 484, 487, 506, 508, 514–515, 582–584
skore/src/skore/_sklearn/_plot
__init__.py	3	0	100%
base.py	61	2	96%	61–62
utils.py	142	3	97%	273–274, 453
skore/src/skore/_sklearn/_plot/data
__init__.py	2	0	100%
table_report.py	177	1	99%	670
skore/src/skore/_sklearn/_plot/inspection
__init__.py	0	0	100%
coefficients.py	181	0	100%
impurity_decrease.py	103	2	98%	423, 467
permutation_importance.py	196	1	99%	583
utils.py	32	0	100%
skore/src/skore/_sklearn/_plot/metrics
__init__.py	6	0	100%
confusion_matrix.py	165	0	100%
metrics_summary_display.py	100	0	100%
precision_recall_curve.py	108	0	100%
prediction_error.py	166	0	100%
roc_curve.py	113	0	100%
skore/src/skore/_sklearn/train_test_split
__init__.py	2	0	100%
train_test_split.py	71	0	100%
skore/src/skore/_sklearn/train_test_split/warning
__init__.py	8	0	100%
high_class_imbalance_too_few_examples_warning.py	19	1	94%	83
high_class_imbalance_warning.py	20	0	100%
random_state_unset_warning.py	10	0	100%
shuffle_true_warning.py	9	0	100%
stratify_is_set_warning.py	10	0	100%
time_based_column_warning.py	21	0	100%
train_test_split_warning.py	3	0	100%
skore/src/skore/_utils
__init__.py	6	2	66%	8, 13
_accessor.py	106	7	93%	36, 92–94, 164, 218, 238
_cache.py	37	0	100%
_cache_key.py	35	5	85%	22, 24, 51, 59, 68
_dataframe.py	37	1	97%	56
_environment.py	32	2	93%	41, 44
_fixes.py	8	0	100%
_index.py	5	0	100%
_jupyter.py	8	2	75%	13–14
_logger.py	22	4	81%	15–17, 19
_measure_time.py	10	0	100%
_parallel.py	17	0	100%
_patch.py	21	12	42%	30, 35–39, 42–43, 46–47, 58, 60
_progress_bar.py	41	4	90%	55–56, 66–67
_show_versions.py	38	0	100%
_skrub.py	37	2	94%	19, 74
_testing.py	125	13	89%	24, 33, 71–72, 189, 198, 209–214, 216
skore/src/skore/_utils/repr
__init__.py	2	0	100%
base.py	54	0	100%
data.py	162	0	100%
html_repr.py	40	0	100%
rich_repr.py	81	0	100%
TOTAL	4419	141	96%

Tests	Skipped	Failures	Errors	Time
2058	5 💤	0 ❌	0 🔥	7m 51s ⏱️