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* [dask] pass predict() kwargs through when input is a Dask Array

* add tests

* Apply suggestions from code review
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* add prediction early stopping params
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* add type hints to python-package/setup.py

* fix return type hints on python-package/setup.py
Co-authored-by: James Lamb <jaylamb20@gmail.com>
Co-authored-by: James Lamb <jaylamb20@gmail.com>

* handle arbitrary length feature names in Python-package

* added tests

* added f-string

* fix missing parentheses and other string formatting

* remove extra trailing parenthesis

* one more missing parenthesis

* fix pandas categoricals

* update uses of +

* Apply suggestions from code review
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>
Co-authored-by: James Lamb <jaylamb20@gmail.com>
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* added f-string to dask.py

* Update python-package/lightgbm/dask.py
Co-authored-by: James Lamb <jaylamb20@gmail.com>

* Update python-package/lightgbm/dask.py
Co-authored-by: James Lamb <jaylamb20@gmail.com>

* Updated branch

* Updated file as per specifications

* Removed warning as per specification

* update other places

* Apply suggestions from code review
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* revert unnecessary change

* Apply suggestions from code review
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>
Co-authored-by: James Lamb <jaylamb20@gmail.com>
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* Migrate to f-strings in python-package\lightgbm\plotting.py

* Apply suggestion from review

* Apply suggestions from code review
Co-authored-by: James Lamb <jaylamb20@gmail.com>
Co-authored-by: James Lamb <jaylamb20@gmail.com>

* added f-string

* fixed indent issues

* fixed some linting issues

* trying to fix E225 for 233:65

* Update python-package/lightgbm/callback.py

* first_metric_only log message

* Apply suggestions from code review
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>
Co-authored-by: James Lamb <jaylamb20@gmail.com>
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

[docs] clarify docs for LGBM_BoosterGetEvalNames and LGBM_BoosterGetEvalCounts (fixes #4264) (#4270)

* Correct spelling

Most changes were in comments, and there were a few changes to literals for log output.

There were no changes to variable names, function names, IDs, or functionality.

* Clarify a phrase in a comment
Co-authored-by: James Lamb <jaylamb20@gmail.com>

* Clarify a phrase in a comment
Co-authored-by: James Lamb <jaylamb20@gmail.com>

* Clarify a phrase in a comment
Co-authored-by: James Lamb <jaylamb20@gmail.com>

* Correct spelling

Most are code comments, but one case is a literal in a logging message.

There are a few grammar fixes too.
Co-authored-by: James Lamb <jaylamb20@gmail.com>

* chanche MRO

* fix MRO resolution

* fix typo in dask _train as mentioned in 4101

* Update python-package/lightgbm/dask.py
Co-authored-by: James Lamb <jaylamb20@gmail.com>

* Migrate to f-strings in python-package/lightgbm/sklearn.py

* Apply suggestions from code review
Co-authored-by: James Lamb <jaylamb20@gmail.com>

* Update python-package/lightgbm/sklearn.py
Co-authored-by: James Lamb <jaylamb20@gmail.com>

* Apply suggestions from code review
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* Add suggestions from code review

* resolve conflicts

* Apply suggestions from code review
Co-authored-by: James Lamb <jaylamb20@gmail.com>

* Update sklearn.py
Co-authored-by: James Lamb <jaylamb20@gmail.com>
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* added type hints; implemented one workaround

* resolving some linting errors

* Added doc strings

* fixed more linting errors

* Made documentation more imperative.

* removed one type hint

* more specific type hinting
Co-authored-by: James Lamb <jaylamb20@gmail.com>

* added import

* Apply suggestions from code review
Co-authored-by: James Lamb <jaylamb20@gmail.com>

* made a class and function private

* Apply suggestions from code review

Make the documentation clearer.
Co-authored-by: James Lamb <jaylamb20@gmail.com>

* linting error fix

* more linting errors

* removing the decorator

* ignore mypy function attribute errors

* fix lints
Co-authored-by: James Lamb <jaylamb20@gmail.com>

* include voting_parallel tree_learner in test_regressor, test_classifier and test_ranker

* remove test for warnings and test for error when using feature_parallel

* use real names for tree_learner intest and include test for aliases. use the error message in the test for error in feature parallel

* split all tests with rf in test_classifier

* remove task parametrization for tree_learner aliases test. smaller input data from feature_parallel error

* define task for tree_learner aliases

* [dask] make random port search more resilient to random collisions

* linting

* more reliable ports check

* address review comments

* add error message

* added f-strings to setup.py

* Update python-package/setup.py
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* [dask] run one training task on each worker

* add comment on pure

* missing ticks

* empty commit

* include test for prediction with raw_score

* close client

* initial comments

* update data creation and include ranking task

* linting

* update _create_data

* compare unique raw_predictions with values in leaves_df

* Some mypy fixes

* address James' comments

* Re-introduce pass in empty classes

* Update compat.py

Remove extra lines

* [python-package] add type hints on Booster.set_network()

* change behavior

* Update Parallel-Learning-Guide.rst

* Update test.sh

* fix path

* address review comments

* [dask] raise more informative error for duplicates in 'machines'

* uncomment

* avoid test failure

* Revert "avoid test failure"

This reverts commit 9442bdf00f193a19a923dc0deb46b7822cb6f601.

* include support for init_score

* use dataframe from init_score and test difference with and without init_score in local model

* revert refactoring

* initial docs. test between distributed models with and without init_score

* remove ranker from tests

* test value for root node and change docs

* comma

* re-include parametrize

* fix incorrect merge

* use single init_score and the booster_ attribute

* use np.float64 instead of float

* include support for column array as label

* remove nested ifs

* fix linting errors

* include tests for sklearn regressors

* include docstring for numpy_1d_array_to_dtype

* include . at end of docstring

* remove pandas import and test for regression, classification and ranking

* check predictions of sklearn models as well

* test training only in dask. drop pandas series tests

* use PANDAS_INSTALLED and pd_Series

* inline imports

* use col array in fit for test_dask

* include review comments