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* Log warning instead of fatal when parsing float get under/overflow.

For texts that resolve to infinity, under or overflow should be
accepted.

* Remove outdated unit test.

* empty commit to trigger ci

* replace pytest.parametrize

* add informative message for assert

[python] improving the syntax of the fstring in the file : tests/python_package_test/test_dask.py (#4358)

* updated the old syntax with fstrings

* Updated the strings with + catenation to fstrings

* Updated the strings with + catenation to fstrings

* Update tests/python_package_test/test_dask.py
Co-authored-by: James Lamb <jaylamb20@gmail.com>

* Add linear leaf models to json output

* Add closing bracket

* Move test into test_engine.py and add asserts

* Update tests/python_package_test/test_engine.py
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* Update tests/python_package_test/test_engine.py
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* Update tests/python_package_test/test_engine.py
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

[python] improving the syntax of the fstring in the file : tests/python_package_test/test_basic.py (#4312)

* run Dask tests on aarch64 architecture

* make random Dask test to fail

* Revert "make random Dask test to fail"

This reverts commit c43c98507f818994bb08b4f7d289ecad3b3449eb.

* empty commit

* empty commit

* empty commit

* empty commit
Co-authored-by: James Lamb <jaylamb20@gmail.com>

* handle arbitrary length feature names in Python-package

* added tests

* New build option: USE_PRECISE_TEXT_PARSER.

Use fast_double_parser for text file parsing. For each number, fallback
to strtod in case of parse failure.

* Add benchmark for CSVParser with Atof and AtofPrecise.

* Fix lint complaint.

* Fix typo in open result error message.

* Revert "Fix lint complaint."

This reverts commit 92ab0b6bce9f17d7be9eaeb20f19d4a0a36f0387.

* Revert "Add benchmark for CSVParser with Atof and AtofPrecise."

This reverts commit 4f8639abd06c679d4382eb715a1793afd94df3d2.

* Use AtofPrecise in Common::__StringToTHelper.

* [option] precise_float_parser: precise float number parsing for text input.

* Remove USE_PRECISE_TEXT_PARSER compile option.

* test: add test for Common::AtofPrecise.

* test: remove ChunkedArrayTest with 0 length.

This triggers Log::Fatal which aborts the test program.

* fix lint, add copyright.

* Revert "test: remove ChunkedArrayTest with 0 length."

This reverts commit 346c76affe9e78b6ca2738c4a56dbb9c00f31102.

* Use LightGBM::Common::Sign

* save precise_float_parser in model file.

* Fix error checking in AtofPrecise. Add more test cases.

* Remove test case that can't pass under macOS.

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

* 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>

* run cpp tests at CI

* Update docs/Installation-Guide.rst
Co-authored-by: James Lamb <jaylamb20@gmail.com>
Co-authored-by: James Lamb <jaylamb20@gmail.com>

* add test for interaction constraints and monotone constraints

* enforce interaction constraints in RecomputeBestSplitForLeaf

* code formatting

* code formatting

* move interaction constraint test to test_engine

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

* replace client fixture with cluster fixture

* wait on persist before rebalance

* 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

* test all boosting types

* lint

* bring scores comparison back and set y as second argument in assert_eq

* Update chunked_array.hpp

* Update ChunkedArray_API_extensions.i

* Update StringArray.i

* apply cpplint to cpp tests

* Update test_chunked_array to please cpplint (#4121)

* Update test_chunked_array to please cpplint

* Simplify var name

* Add comment
Co-authored-by: Alberto Ferreira <AlbertoEAF@users.noreply.github.com>

* Update test_dask.py

* Update test_dask.py

* 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

* make one categorical variable informative. increase n_samples. reduce n_features for regression

* adjust tolerances in checks

* [feature] Add ChunkedArray to SWIG

* Add ChunkedArray
* Add ChunkedArray_API_extensions.i
* Add SWIG class wrappers

* Address some review comments

* Fix linting issues

* Move test to tests/test_ChunkedArray_manually.cpp

* Add test note

* Move ChunkedArray to include/LightGBM/utils/

* Declare more explicit types of ChunkedArray in the SWIG API.

* Port ChunkedArray tests to googletest

* Please C++ linter

* Address StrikerRUS' review comments

* Update SWIG doc & disable ChunkedArray<int64_t>

* Use CHECK_EQ instead of assert

* Change include order (linting)

* Rename ChunkedArray -> chunked_array files

* Change header guards

* Address last comments from StrikerRUS

* simplify Dask tests code

* enable CI

* disable CI

* Add CMake option to enable sanitizer

* Set up gtest

* Address reviewer's feedback

* Address reviewer's feedback

* Update CMakeLists.txt
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

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

* uncomment

* avoid test failure

* Revert "avoid test failure"

This reverts commit 9442bdf00f193a19a923dc0deb46b7822cb6f601.

* include multiclass-classification task and task_to_model_factory dicts

* define centers coordinates. flatten init_scores within each partition for multiclass-classification

* include issue comment and fix linting error

* 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

* [dask] [ci] add support for scikit-learn 0.24+ in tests (fixes #4031)

* Update tests/python_package_test/test_dask.py
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* try upgrading mixtexsetup

* they changed the executable name UGH

* more changes for executable name

* another path change

* changing package mirrors

* undo experiments
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* simplify fit calls in Dask tests

* Update .vsts-ci.yml

* Update .vsts-ci.yml

* 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

* Update test_engine.py

* Update python_package.yml

* Update python_package.yml

* Update test_engine.py

* hotfix

* use socket.bind with port 0 and client.run to find random open ports

* include test for found ports

* find random open ports as default

* parametrize local_listen_port. type hint to _find_random_open_port. fid open ports only on workers with data.

* make indentation consistent and pass list of workers to client.run

* remove socket import

* change random port implementation

* fix test