Note
Go to the end to download the full example code
Benchmark studies¶
How to list, download and upload benchmark studies. In contrast to benchmark suites which hold a list of tasks, studies hold a list of runs. As runs contain all information on flows and tasks, all required information about a study can be retrieved.
# License: BSD 3-Clause
import uuid
from sklearn.ensemble import RandomForestClassifier
import openml
Listing studies¶
Use the output_format parameter to select output type
Default gives
dict, but we’ll usedataframeto obtain an easier-to-work-with data structure
studies = openml.study.list_studies(output_format="dataframe", status="all")
print(studies.head(n=10))
id alias main_entity_type ... status creation_date creator
1 1 Study_1 run ... in_preparation 2015-10-20 15:27:26 2
2 2 Study_2 run ... in_preparation 2015-10-20 15:28:44 2
3 3 Study_3 run ... in_preparation 2015-10-20 15:34:39 2
5 5 Study_5 run ... in_preparation 2015-11-19 11:20:33 749
7 7 Study_7 run ... in_preparation 2016-01-06 17:49:36 64
8 8 Study_8 run ... in_preparation 2016-03-13 13:38:31 1135
10 10 Study_10 run ... in_preparation 2016-03-16 12:16:08 507
11 11 Study_11 run ... in_preparation 2016-03-22 16:48:06 1
12 12 Study_12 run ... in_preparation 2016-03-31 15:05:45 1195
13 13 Study_13 run ... in_preparation 2016-04-05 13:57:41 62
[10 rows x 7 columns]
Downloading studies¶
This is done based on the study ID.
study = openml.study.get_study(123)
print(study)
OpenML Study
============
ID..............: 123
Name............: Linear vs. Non Linear
Status..........: active
Main Entity Type: run
Study URL.......: https://www.openml.org/s/123
# of Data.......: 299
# of Tasks......: 299
# of Flows......: 5
# of Runs.......: 1693
Creator.........: https://www.openml.org/u/1
Upload Time.....: 2019-02-21 19:55:30
Studies also features a description:
print(study.description)
Comparison of linear and non-linear models.
[Jupyter Notebook](https://github.com/janvanrijn/linear-vs-non-linear/blob/master/notebook/Linear-vs-Non-Linear.ipynb)
Studies are a container for runs:
print(study.runs)
[9199877, 9199878, 9199879, 9199880, 9199881, 9199882, 9199883, 9199884, 9199885, 9199886, 9199887, 9199888, 9199889, 9199890, 9199891, 9199892, 9199893, 9199894, 9199895, 9199897, 9199898, 9199899, 9199900, 9199901, 9199902, 9199903, 9199904, 9199905, 9199906, 9199907, 9199908, 9199909, 9199910, 9199911, 9199912, 9199913, 9199914, 9199915, 9199916, 9199917, 9199918, 9199919, 9199920, 9199921, 9199922, 9199923, 9199924, 9199925, 9199926, 9199927, 9199928, 9199929, 9199930, 9199931, 9199932, 9199933, 9199934, 9199935, 9199936, 9199937, 9199938, 9199939, 9199940, 9199941, 9199942, 9199943, 9199944, 9199945, 9199946, 9199947, 9199948, 9199950, 9199951, 9199952, 9199953, 9199954, 9199955, 9199956, 9199957, 9199958, 9199959, 9199960, 9199961, 9199963, 9199964, 9199965, 9199966, 9199967, 9199968, 9199969, 9199970, 9199971, 9199972, 9199973, 9199974, 9199975, 9199976, 9199977, 9199978, 9199979, 9199981, 9199982, 9199983, 9199984, 9199985, 9199986, 9199987, 9199988, 9199989, 9199990, 9199991, 9199992, 9199993, 9199994, 9199995, 9199996, 9199997, 9199998, 9199999, 9200000, 9200001, 9200002, 9200003, 9200004, 9200006, 9200007, 9200008, 9200009, 9200010, 9200011, 9200012, 9200013, 9200014, 9200015, 9200016, 9200017, 9200018, 9200019, 9200020, 9200021, 9200022, 9200023, 9200024, 9200025, 9200026, 9200027, 9200028, 9200029, 9200030, 9200031, 9200032, 9200033, 9200034, 9200035, 9200036, 9200037, 9200038, 9200039, 9200040, 9200041, 9200042, 9200043, 9200044, 9200045, 9200046, 9200047, 9200048, 9200049, 9200050, 9200051, 9200052, 9200053, 9200054, 9200055, 9200056, 9200057, 9200058, 9200059, 9200060, 9200061, 9200062, 9200063, 9200064, 9200065, 9200066, 9200067, 9200068, 9200069, 9200070, 9200071, 9200072, 9200073, 9200074, 9200075, 9200076, 9200077, 9200078, 9200079, 9200080, 9200081, 9200082, 9200083, 9200084, 9200085, 9200086, 9200087, 9200088, 9200089, 9200090, 9200091, 9200092, 9200093, 9200094, 9200095, 9200096, 9200097, 9200098, 9200099, 9200100, 9200101, 9200102, 9200103, 9200104, 9200105, 9200106, 9200107, 9200108, 9200109, 9200110, 9200111, 9200112, 9200113, 9200114, 9200115, 9200116, 9200117, 9200118, 9200119, 9200120, 9200121, 9200122, 9200123, 9200124, 9200125, 9200126, 9200127, 9200128, 9200129, 9200130, 9200131, 9200132, 9200133, 9200134, 9200135, 9200136, 9200137, 9200138, 9200139, 9200140, 9200141, 9200142, 9200143, 9200144, 9200145, 9200146, 9200147, 9200148, 9200149, 9200150, 9200151, 9200152, 9200153, 9200154, 9200155, 9200156, 9200157, 9200158, 9200159, 9200160, 9200161, 9200162, 9200163, 9200164, 9200165, 9200166, 9200167, 9200168, 9200169, 9200171, 9200173, 9200174, 9200175, 9200176, 9200177, 9200178, 9200180, 9200181, 9200182, 9200183, 9200184, 9200185, 9200186, 9200187, 9200188, 9200189, 9200190, 9200191, 9200192, 9200193, 9200194, 9200195, 9200196, 9200197, 9200198, 9200199, 9200200, 9200201, 9200202, 9200203, 9200204, 9200205, 9200206, 9200207, 9200208, 9200209, 9200210, 9200211, 9200212, 9200213, 9200214, 9200215, 9200216, 9200217, 9200218, 9200219, 9200220, 9200221, 9200222, 9200223, 9200224, 9200225, 9200226, 9200227, 9200228, 9200229, 9200230, 9200231, 9200232, 9200233, 9200234, 9200235, 9200236, 9200237, 9200238, 9200239, 9200240, 9200241, 9200242, 9200243, 9200244, 9200245, 9200246, 9200247, 9200248, 9200249, 9200250, 9200251, 9200252, 9200253, 9200254, 9200255, 9200256, 9200257, 9200258, 9200259, 9200260, 9200261, 9200262, 9200263, 9200264, 9200265, 9200266, 9200267, 9200268, 9200269, 9200270, 9200271, 9200272, 9200273, 9200274, 9200275, 9200276, 9200277, 9200278, 9200279, 9200280, 9200281, 9200282, 9200283, 9200284, 9200285, 9200286, 9200287, 9200288, 9200289, 9200290, 9200291, 9200292, 9200293, 9200294, 9200295, 9200296, 9200297, 9200298, 9200299, 9200300, 9200301, 9200302, 9200303, 9200304, 9200305, 9200306, 9200307, 9200308, 9200310, 9200311, 9200312, 9200313, 9200314, 9200315, 9200316, 9200317, 9200318, 9200319, 9200320, 9200321, 9200322, 9200324, 9200325, 9200326, 9200327, 9200328, 9200329, 9200330, 9200331, 9200332, 9200333, 9200334, 9200335, 9200336, 9200337, 9200338, 9200339, 9200340, 9200341, 9200342, 9200343, 9200344, 9200345, 9200346, 9200347, 9200348, 9200349, 9200350, 9200351, 9200352, 9200353, 9200354, 9200355, 9200356, 9200357, 9200358, 9200359, 9200361, 9200362, 9200364, 9200365, 9200366, 9200367, 9200368, 9200369, 9200370, 9200371, 9200372, 9200373, 9200374, 9200375, 9200376, 9200377, 9200378, 9200379, 9200380, 9200382, 9200383, 9200384, 9200385, 9200386, 9200387, 9200388, 9200389, 9200390, 9200391, 9200392, 9200393, 9200394, 9200395, 9200396, 9200397, 9200398, 9200399, 9200400, 9200401, 9200402, 9200403, 9200404, 9200405, 9200406, 9200407, 9200408, 9200409, 9200410, 9200411, 9200412, 9200413, 9200414, 9200415, 9200416, 9200417, 9200418, 9200419, 9200420, 9200421, 9200422, 9200424, 9200425, 9200426, 9200427, 9200428, 9200429, 9200430, 9200431, 9200432, 9200433, 9200434, 9200435, 9200436, 9200437, 9200438, 9200439, 9200440, 9200441, 9200442, 9200443, 9200444, 9200445, 9200446, 9200447, 9200448, 9200449, 9200450, 9200451, 9200452, 9200453, 9200454, 9200455, 9200456, 9200457, 9200458, 9200459, 9200460, 9200461, 9200462, 9200463, 9200464, 9200465, 9200466, 9200467, 9200468, 9200469, 9200470, 9200471, 9200472, 9200473, 9200474, 9200475, 9200476, 9200477, 9200478, 9200479, 9200480, 9200481, 9200482, 9200483, 9200484, 9200485, 9200486, 9200487, 9200488, 9200489, 9200490, 9200491, 9200492, 9200493, 9200494, 9200495, 9200496, 9200497, 9200498, 9200499, 9200500, 9200501, 9200502, 9200503, 9200504, 9200505, 9200506, 9200507, 9200508, 9200509, 9200510, 9200511, 9200512, 9200513, 9200514, 9200515, 9200516, 9200517, 9200518, 9200519, 9200520, 9200521, 9200522, 9200523, 9200524, 9200525, 9200526, 9200527, 9200528, 9200529, 9200530, 9200531, 9200532, 9200533, 9200534, 9200535, 9200536, 9200537, 9200538, 9200539, 9200540, 9200541, 9200542, 9200543, 9200544, 9200545, 9200546, 9200547, 9200548, 9200549, 9200550, 9200551, 9200552, 9200553, 9200554, 9200555, 9200556, 9200557, 9200558, 9200559, 9200560, 9200561, 9200562, 9200563, 9200564, 9200565, 9200566, 9200567, 9200568, 9200569, 9200570, 9200571, 9200572, 9200573, 9200574, 9200575, 9200576, 9200577, 9200578, 9200579, 9200580, 9200581, 9200582, 9200583, 9200584, 9200585, 9200586, 9200587, 9200588, 9200589, 9200590, 9200591, 9200592, 9200593, 9200594, 9200595, 9200596, 9200597, 9200598, 9200599, 9200600, 9200601, 9200602, 9200603, 9200604, 9200605, 9200606, 9200607, 9200608, 9200609, 9200610, 9200611, 9200612, 9200613, 9200614, 9200615, 9200616, 9200617, 9200618, 9200619, 9200620, 9200621, 9200622, 9200623, 9200624, 9200625, 9200626, 9200627, 9200628, 9200629, 9200630, 9200631, 9200632, 9200633, 9200634, 9200635, 9200636, 9200637, 9200638, 9200639, 9200640, 9200641, 9200642, 9200643, 9200644, 9200645, 9200646, 9200647, 9200648, 9200649, 9200650, 9200651, 9200652, 9200653, 9200654, 9200655, 9200656, 9200657, 9200658, 9200659, 9200660, 9200661, 9200662, 9200663, 9200664, 9200665, 9200666, 9200667, 9200668, 9200669, 9200670, 9200671, 9200672, 9200673, 9200674, 9200675, 9200676, 9200677, 9200678, 9200679, 9200680, 9200681, 9200682, 9200683, 9200684, 9200685, 9200686, 9200687, 9200688, 9200689, 9200690, 9200691, 9200692, 9200693, 9200694, 9200695, 9200696, 9200697, 9200698, 9200699, 9200700, 9200701, 9200702, 9200703, 9200704, 9200705, 9200706, 9200707, 9200708, 9200709, 9200710, 9200711, 9200712, 9200713, 9200714, 9200715, 9200716, 9200717, 9200719, 9200720, 9200721, 9200722, 9200723, 9200724, 9200725, 9200726, 9200727, 9200728, 9200729, 9200730, 9200731, 9200732, 9200733, 9200734, 9200735, 9200736, 9200737, 9200738, 9200739, 9200740, 9200741, 9200742, 9200743, 9200744, 9200745, 9200746, 9200747, 9200748, 9200749, 9200750, 9200751, 9200752, 9200753, 9200754, 9200755, 9200756, 9200757, 9200758, 9200759, 9200760, 9200761, 9200762, 9200763, 9200764, 9200765, 9200766, 9200767, 9200768, 9200769, 9200770, 9200771, 9200772, 9200773, 9200774, 9200775, 9200776, 9200778, 9200779, 9200780, 9200781, 9200782, 9200783, 9200784, 9200785, 9200786, 9200787, 9200788, 9200789, 9200790, 9200791, 9200792, 9200793, 9200794, 9200795, 9200796, 9200797, 9200798, 9200799, 9200800, 9200801, 9200802, 9200803, 9200804, 9200806, 9200807, 9200808, 9200809, 9200810, 9200811, 9200812, 9200813, 9200814, 9200815, 9200816, 9200817, 9200818, 9200819, 9200820, 9200821, 9200822, 9200823, 9200824, 9200825, 9200826, 9200827, 9200828, 9200829, 9200830, 9200831, 9200832, 9200833, 9200834, 9200835, 9200836, 9200837, 9200838, 9200839, 9200840, 9200841, 9200842, 9200843, 9200844, 9200845, 9200846, 9200847, 9200848, 9200849, 9200850, 9200851, 9200852, 9200853, 9200854, 9200855, 9200856, 9200857, 9200858, 9200859, 9200860, 9200861, 9200862, 9200863, 9200864, 9200865, 9200866, 9200867, 9200868, 9200869, 9200870, 9200871, 9200872, 9200873, 9200874, 9200875, 9200876, 9200877, 9200878, 9200879, 9200880, 9200881, 9200882, 9200883, 9200884, 9200885, 9200886, 9200887, 9200888, 9200889, 9200890, 9200891, 9200892, 9200893, 9200894, 9200895, 9200896, 9200897, 9200898, 9200899, 9200900, 9200901, 9200902, 9200903, 9200904, 9200905, 9200906, 9200907, 9200908, 9200909, 9200910, 9200911, 9200912, 9200913, 9200914, 9200915, 9200916, 9200917, 9200918, 9200919, 9200920, 9200921, 9200922, 9200923, 9200924, 9200925, 9200926, 9200927, 9200928, 9200929, 9200930, 9200931, 9200932, 9200933, 9200934, 9200935, 9200936, 9200937, 9200938, 9200939, 9200940, 9200941, 9200942, 9200943, 9200944, 9200945, 9200946, 9200947, 9200948, 9200949, 9200950, 9200951, 9200952, 9200953, 9200954, 9200955, 9200956, 9200957, 9200958, 9200959, 9200960, 9200961, 9200962, 9200963, 9200964, 9200965, 9200966, 9200967, 9200968, 9200969, 9200970, 9200971, 9200972, 9200973, 9200974, 9200975, 9200976, 9200977, 9200978, 9200979, 9200980, 9200981, 9200982, 9200983, 9200984, 9200985, 9200986, 9200987, 9200988, 9200989, 9200990, 9200991, 9200993, 9200994, 9200995, 9200996, 9200997, 9200998, 9200999, 9201000, 9201001, 9201002, 9201003, 9201004, 9201005, 9201006, 9201007, 9201008, 9201009, 9201010, 9201011, 9201012, 9201013, 9201014, 9201015, 9201016, 9201017, 9201018, 9201019, 9201020, 9201021, 9201022, 9201023, 9201024, 9201025, 9201026, 9201027, 9201028, 9201029, 9201030, 9201031, 9201032, 9201033, 9201034, 9201035, 9201036, 9201037, 9201038, 9201039, 9201040, 9201041, 9201042, 9201043, 9201044, 9201045, 9201046, 9201047, 9201048, 9201049, 9201050, 9201051, 9201052, 9201053, 9201054, 9201055, 9201056, 9201057, 9201058, 9201059, 9201060, 9201061, 9201062, 9201063, 9201064, 9201065, 9201066, 9201067, 9201068, 9201069, 9201070, 9201071, 9201072, 9201073, 9201074, 9201075, 9201076, 9201077, 9201078, 9201079, 9201080, 9201081, 9201082, 9201083, 9201084, 9201085, 9201086, 9201087, 9201088, 9201089, 9201090, 9201091, 9201092, 9201093, 9201094, 9201095, 9201096, 9201097, 9201098, 9201099, 9201100, 9201101, 9201102, 9201103, 9201104, 9201105, 9201106, 9201107, 9201108, 9201109, 9201110, 9201111, 9201112, 9201113, 9201114, 9201115, 9201116, 9201117, 9201118, 9201119, 9201120, 9201121, 9201122, 9201124, 9201125, 9201126, 9201127, 9201128, 9201129, 9201130, 9201131, 9201132, 9201133, 9201134, 9201135, 9201136, 9201137, 9201138, 9201139, 9201140, 9201141, 9201142, 9201143, 9201144, 9201145, 9201146, 9201147, 9201148, 9201149, 9201150, 9201151, 9201152, 9201153, 9201154, 9201155, 9201156, 9201157, 9201158, 9201159, 9201160, 9201161, 9201162, 9201163, 9201164, 9201165, 9201166, 9201167, 9201168, 9201169, 9201170, 9201171, 9201172, 9201173, 9201174, 9201175, 9201176, 9201177, 9201178, 9201179, 9201180, 9201181, 9201182, 9201183, 9201184, 9201185, 9201186, 9201187, 9201188, 9201189, 9201190, 9201191, 9201192, 9201193, 9201194, 9201195, 9201196, 9201197, 9201198, 9201199, 9201200, 9201201, 9201202, 9201203, 9201204, 9201205, 9201206, 9201207, 9201208, 9201209, 9201210, 9201211, 9201212, 9201213, 9201214, 9201215, 9201216, 9201217, 9201218, 9201219, 9201220, 9201221, 9201222, 9201223, 9201224, 9201225, 9201226, 9201227, 9201228, 9201229, 9201230, 9201231, 9201232, 9201233, 9201234, 9201235, 9201236, 9201237, 9201238, 9201239, 9201240, 9201241, 9201242, 9201243, 9201244, 9201245, 9201246, 9201247, 9201248, 9201249, 9201250, 9201251, 9201252, 9201253, 9201254, 9201255, 9201256, 9201257, 9201258, 9201259, 9201260, 9201261, 9201262, 9201263, 9201264, 9201265, 9201266, 9201267, 9201268, 9201269, 9201270, 9201271, 9201272, 9201273, 9201274, 9201275, 9201276, 9201277, 9201278, 9201279, 9201280, 9201281, 9201282, 9201283, 9201284, 9201285, 9201286, 9201287, 9201288, 9201289, 9201290, 9201291, 9201292, 9201293, 9201294, 9201295, 9201296, 9201297, 9201298, 9201299, 9201300, 9201301, 9201302, 9201303, 9201304, 9201305, 9201306, 9201307, 9201308, 9201309, 9201310, 9201311, 9201312, 9201313, 9201314, 9201315, 9201316, 9201317, 9201318, 9201319, 9201320, 9201321, 9201322, 9201323, 9201324, 9201325, 9201326, 9201327, 9201328, 9201329, 9201330, 9201331, 9201332, 9201333, 9201334, 9201335, 9201336, 9201337, 9201338, 9201339, 9201340, 9201341, 9201342, 9201343, 9201344, 9201345, 9201346, 9201347, 9201348, 9201349, 9201350, 9201351, 9201352, 9201353, 9201354, 9201355, 9201356, 9201357, 9201358, 9201359, 9201360, 9201361, 9201362, 9201363, 9201364, 9201365, 9201366, 9201367, 9201368, 9201369, 9201370, 9201371, 9201372, 9201373, 9201374, 9201375, 9201376, 9201377, 9201378, 9201379, 9201380, 9201381, 9201382, 9201384, 9201385, 9201386, 9201387, 9201388, 9201389, 9201390, 9201391, 9201392, 9201393, 9201394, 9201395, 9201396, 9201397, 9201398, 9201399, 9201400, 9201401, 9201402, 9201403, 9201404, 9201405, 9201406, 9201407, 9201408, 9201409, 9201410, 9201411, 9201412, 9201413, 9201414, 9201415, 9201416, 9201417, 9201418, 9201419, 9201420, 9201422, 9201423, 9201424, 9201425, 9201426, 9201427, 9201428, 9201429, 9201430, 9201431, 9201432, 9201433, 9201434, 9201435, 9201436, 9201437, 9201438, 9201439, 9201440, 9201441, 9201442, 9201443, 9201444, 9201445, 9201446, 9201447, 9201448, 9201449, 9201450, 9201451, 9201452, 9201453, 9201454, 9201455, 9201456, 9201457, 9201458, 9201459, 9201460, 9201461, 9201462, 9201463, 9201464, 9201465, 9201466, 9201467, 9201468, 9201469, 9201470, 9201471, 9201472, 9201473, 9201474, 9201475, 9201476, 9201477, 9201478, 9201479, 9201480, 9201481, 9201482, 9201483, 9201484, 9201485, 9201486, 9201487, 9201488, 9201489, 9201490, 9201491, 9201492, 9201493, 9201494, 9201495, 9201496, 9201497, 9201498, 9201499, 9201500, 9201501, 9201502, 9201503, 9201504, 9201505, 9201506, 9201507, 9201508, 9201509, 9201510, 9201511, 9201512, 9201514, 9201515, 9201516, 9201517, 9201518, 9201519, 9201520, 9201521, 9201522, 9201523, 9201524, 9201525, 9201526, 9201527, 9201528, 9201529, 9201530, 9201531, 9201532, 9201533, 9201534, 9201535, 9201536, 9201537, 9201538, 9201539, 9201540, 9201541, 9201542, 9201543, 9201544, 9201545, 9201546, 9201547, 9201548, 9201549, 9201550, 9201551, 9201552, 9201553, 9201554, 9201555, 9201556, 9201557, 9201558, 9201559, 9201560, 9201561, 9201562, 9201563, 9201564, 9201565, 9201566, 9201567, 9201568, 9201569, 9201570, 9201571, 9201572, 9201573, 9201574, 9201575, 9201576, 9201577, 9201578, 9201579, 9201580, 9201581, 9201582, 9201583, 9201584, 9201585, 9201586, 9201587, 9201588, 9201589, 9201590, 9201591]
And we can use the evaluation listing functionality to learn more about the evaluations available for the conducted runs:
evaluations = openml.evaluations.list_evaluations(
function="predictive_accuracy",
output_format="dataframe",
study=study.study_id,
)
print(evaluations.head())
run_id task_id setup_id ... value values array_data
0 9199877 3 7130157 ... 0.974969 None None
1 9199878 6 7130158 ... 0.716500 None None
2 9199879 6 7130159 ... 0.967200 None None
3 9199880 11 7130158 ... 0.886400 None None
4 9199881 11 7130159 ... 0.976000 None None
[5 rows x 14 columns]
We’ll use the test server for the rest of this tutorial.
Warning
This example uploads data. For that reason, this example connects to the test server at test.openml.org. This prevents the main server from crowding with example datasets, tasks, runs, and so on. The use of this test server can affect behaviour and performance of the OpenML-Python API.
openml.config.start_using_configuration_for_example()
/home/runner/work/openml-python/openml-python/examples/30_extended/study_tutorial.py:65: UserWarning: Switching to the test server https://test.openml.org/api/v1/xml to not upload results to the live server. Using the test server may result in reduced performance of the API!
openml.config.start_using_configuration_for_example()
Uploading studies¶
Creating a study is as simple as creating any kind of other OpenML entity. In this examples we’ll create a few runs for the OpenML-100 benchmark suite which is available on the OpenML test server.
# Model to be used
clf = RandomForestClassifier()
# We'll create a study with one run on 3 datasets present in the suite
tasks = [115, 259, 307]
# To verify
suite = openml.study.get_suite(1)
print(all([t_id in suite.tasks for t_id in tasks]))
run_ids = []
for task_id in tasks:
task = openml.tasks.get_task(task_id)
run = openml.runs.run_model_on_task(clf, task)
run.publish()
run_ids.append(run.run_id)
# The study needs a machine-readable and unique alias. To obtain this,
# we simply generate a random uuid.
alias = uuid.uuid4().hex
new_study = openml.study.create_study(
name="Test-Study",
description="Test study for the Python tutorial on studies",
run_ids=run_ids,
alias=alias,
benchmark_suite=suite.study_id,
)
new_study.publish()
print(new_study)
True
/opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/sphinx_gallery/gen_rst.py:722: FutureWarning: Starting from Version 0.15.0 `download_splits` will default to ``False`` instead of ``True`` and be independent from `download_data`. To disable this message until version 0.15 explicitly set `download_splits` to a bool.
exec(self.code, self.fake_main.__dict__)
/home/runner/work/openml-python/openml-python/openml/tasks/functions.py:442: FutureWarning: Starting from Version 0.15 `download_data`, `download_qualities`, and `download_features_meta_data` will all be ``False`` instead of ``True`` by default to enable lazy loading. To disable this message until version 0.15 explicitly set `download_data`, `download_qualities`, and `download_features_meta_data` to a bool while calling `get_dataset`.
dataset = get_dataset(task.dataset_id, *dataset_args, **get_dataset_kwargs)
/home/runner/work/openml-python/openml-python/openml/tasks/task.py:150: FutureWarning: Starting from Version 0.15 `download_data`, `download_qualities`, and `download_features_meta_data` will all be ``False`` instead of ``True`` by default to enable lazy loading. To disable this message until version 0.15 explicitly set `download_data`, `download_qualities`, and `download_features_meta_data` to a bool while calling `get_dataset`.
return datasets.get_dataset(self.dataset_id)
/home/runner/work/openml-python/openml-python/openml/runs/functions.py:789: FutureWarning: Starting from Version 0.15 `download_data`, `download_qualities`, and `download_features_meta_data` will all be ``False`` instead of ``True`` by default to enable lazy loading. To disable this message until version 0.15 explicitly set `download_data`, `download_qualities`, and `download_features_meta_data` to a bool while calling `get_dataset`.
openml.datasets.get_dataset(task.dataset_id).name,
/home/runner/work/openml-python/openml-python/openml/tasks/task.py:150: FutureWarning: Starting from Version 0.15 `download_data`, `download_qualities`, and `download_features_meta_data` will all be ``False`` instead of ``True`` by default to enable lazy loading. To disable this message until version 0.15 explicitly set `download_data`, `download_qualities`, and `download_features_meta_data` to a bool while calling `get_dataset`.
return datasets.get_dataset(self.dataset_id)
/home/runner/work/openml-python/openml-python/openml/runs/functions.py:789: FutureWarning: Starting from Version 0.15 `download_data`, `download_qualities`, and `download_features_meta_data` will all be ``False`` instead of ``True`` by default to enable lazy loading. To disable this message until version 0.15 explicitly set `download_data`, `download_qualities`, and `download_features_meta_data` to a bool while calling `get_dataset`.
openml.datasets.get_dataset(task.dataset_id).name,
/home/runner/work/openml-python/openml-python/openml/tasks/task.py:150: FutureWarning: Starting from Version 0.15 `download_data`, `download_qualities`, and `download_features_meta_data` will all be ``False`` instead of ``True`` by default to enable lazy loading. To disable this message until version 0.15 explicitly set `download_data`, `download_qualities`, and `download_features_meta_data` to a bool while calling `get_dataset`.
return datasets.get_dataset(self.dataset_id)
/home/runner/work/openml-python/openml-python/openml/runs/functions.py:789: FutureWarning: Starting from Version 0.15 `download_data`, `download_qualities`, and `download_features_meta_data` will all be ``False`` instead of ``True`` by default to enable lazy loading. To disable this message until version 0.15 explicitly set `download_data`, `download_qualities`, and `download_features_meta_data` to a bool while calling `get_dataset`.
openml.datasets.get_dataset(task.dataset_id).name,
/home/runner/work/openml-python/openml-python/openml/tasks/task.py:150: FutureWarning: Starting from Version 0.15 `download_data`, `download_qualities`, and `download_features_meta_data` will all be ``False`` instead of ``True`` by default to enable lazy loading. To disable this message until version 0.15 explicitly set `download_data`, `download_qualities`, and `download_features_meta_data` to a bool while calling `get_dataset`.
return datasets.get_dataset(self.dataset_id)
/home/runner/work/openml-python/openml-python/openml/runs/functions.py:789: FutureWarning: Starting from Version 0.15 `download_data`, `download_qualities`, and `download_features_meta_data` will all be ``False`` instead of ``True`` by default to enable lazy loading. To disable this message until version 0.15 explicitly set `download_data`, `download_qualities`, and `download_features_meta_data` to a bool while calling `get_dataset`.
openml.datasets.get_dataset(task.dataset_id).name,
/home/runner/work/openml-python/openml-python/openml/tasks/task.py:150: FutureWarning: Starting from Version 0.15 `download_data`, `download_qualities`, and `download_features_meta_data` will all be ``False`` instead of ``True`` by default to enable lazy loading. To disable this message until version 0.15 explicitly set `download_data`, `download_qualities`, and `download_features_meta_data` to a bool while calling `get_dataset`.
return datasets.get_dataset(self.dataset_id)
/home/runner/work/openml-python/openml-python/openml/runs/functions.py:789: FutureWarning: Starting from Version 0.15 `download_data`, `download_qualities`, and `download_features_meta_data` will all be ``False`` instead of ``True`` by default to enable lazy loading. To disable this message until version 0.15 explicitly set `download_data`, `download_qualities`, and `download_features_meta_data` to a bool while calling `get_dataset`.
openml.datasets.get_dataset(task.dataset_id).name,
/home/runner/work/openml-python/openml-python/openml/tasks/task.py:150: FutureWarning: Starting from Version 0.15 `download_data`, `download_qualities`, and `download_features_meta_data` will all be ``False`` instead of ``True`` by default to enable lazy loading. To disable this message until version 0.15 explicitly set `download_data`, `download_qualities`, and `download_features_meta_data` to a bool while calling `get_dataset`.
return datasets.get_dataset(self.dataset_id)
/home/runner/work/openml-python/openml-python/openml/runs/functions.py:789: FutureWarning: Starting from Version 0.15 `download_data`, `download_qualities`, and `download_features_meta_data` will all be ``False`` instead of ``True`` by default to enable lazy loading. To disable this message until version 0.15 explicitly set `download_data`, `download_qualities`, and `download_features_meta_data` to a bool while calling `get_dataset`.
openml.datasets.get_dataset(task.dataset_id).name,
/home/runner/work/openml-python/openml-python/openml/tasks/task.py:150: FutureWarning: Starting from Version 0.15 `download_data`, `download_qualities`, and `download_features_meta_data` will all be ``False`` instead of ``True`` by default to enable lazy loading. To disable this message until version 0.15 explicitly set `download_data`, `download_qualities`, and `download_features_meta_data` to a bool while calling `get_dataset`.
return datasets.get_dataset(self.dataset_id)
/home/runner/work/openml-python/openml-python/openml/runs/functions.py:789: FutureWarning: Starting from Version 0.15 `download_data`, `download_qualities`, and `download_features_meta_data` will all be ``False`` instead of ``True`` by default to enable lazy loading. To disable this message until version 0.15 explicitly set `download_data`, `download_qualities`, and `download_features_meta_data` to a bool while calling `get_dataset`.
openml.datasets.get_dataset(task.dataset_id).name,
/home/runner/work/openml-python/openml-python/openml/tasks/task.py:150: FutureWarning: Starting from Version 0.15 `download_data`, `download_qualities`, and `download_features_meta_data` will all be ``False`` instead of ``True`` by default to enable lazy loading. To disable this message until version 0.15 explicitly set `download_data`, `download_qualities`, and `download_features_meta_data` to a bool while calling `get_dataset`.
return datasets.get_dataset(self.dataset_id)
/home/runner/work/openml-python/openml-python/openml/runs/functions.py:789: FutureWarning: Starting from Version 0.15 `download_data`, `download_qualities`, and `download_features_meta_data` will all be ``False`` instead of ``True`` by default to enable lazy loading. To disable this message until version 0.15 explicitly set `download_data`, `download_qualities`, and `download_features_meta_data` to a bool while calling `get_dataset`.
openml.datasets.get_dataset(task.dataset_id).name,
/home/runner/work/openml-python/openml-python/openml/tasks/task.py:150: FutureWarning: Starting from Version 0.15 `download_data`, `download_qualities`, and `download_features_meta_data` will all be ``False`` instead of ``True`` by default to enable lazy loading. To disable this message until version 0.15 explicitly set `download_data`, `download_qualities`, and `download_features_meta_data` to a bool while calling `get_dataset`.
return datasets.get_dataset(self.dataset_id)
/home/runner/work/openml-python/openml-python/openml/runs/functions.py:789: FutureWarning: Starting from Version 0.15 `download_data`, `download_qualities`, and `download_features_meta_data` will all be ``False`` instead of ``True`` by default to enable lazy loading. To disable this message until version 0.15 explicitly set `download_data`, `download_qualities`, and `download_features_meta_data` to a bool while calling `get_dataset`.
openml.datasets.get_dataset(task.dataset_id).name,
/home/runner/work/openml-python/openml-python/openml/tasks/task.py:150: FutureWarning: Starting from Version 0.15 `download_data`, `download_qualities`, and `download_features_meta_data` will all be ``False`` instead of ``True`` by default to enable lazy loading. To disable this message until version 0.15 explicitly set `download_data`, `download_qualities`, and `download_features_meta_data` to a bool while calling `get_dataset`.
return datasets.get_dataset(self.dataset_id)
/home/runner/work/openml-python/openml-python/openml/runs/functions.py:789: FutureWarning: Starting from Version 0.15 `download_data`, `download_qualities`, and `download_features_meta_data` will all be ``False`` instead of ``True`` by default to enable lazy loading. To disable this message until version 0.15 explicitly set `download_data`, `download_qualities`, and `download_features_meta_data` to a bool while calling `get_dataset`.
openml.datasets.get_dataset(task.dataset_id).name,
/home/runner/work/openml-python/openml-python/openml/runs/run.py:650: FutureWarning: Starting from Version 0.15.0 `download_splits` will default to ``False`` instead of ``True`` and be independent from `download_data`. To disable this message until version 0.15 explicitly set `download_splits` to a bool.
predictions = arff.dumps(self._generate_arff_dict())
/home/runner/work/openml-python/openml-python/openml/tasks/functions.py:442: FutureWarning: Starting from Version 0.15 `download_data`, `download_qualities`, and `download_features_meta_data` will all be ``False`` instead of ``True`` by default to enable lazy loading. To disable this message until version 0.15 explicitly set `download_data`, `download_qualities`, and `download_features_meta_data` to a bool while calling `get_dataset`.
dataset = get_dataset(task.dataset_id, *dataset_args, **get_dataset_kwargs)
/opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/sphinx_gallery/gen_rst.py:722: FutureWarning: Starting from Version 0.15.0 `download_splits` will default to ``False`` instead of ``True`` and be independent from `download_data`. To disable this message until version 0.15 explicitly set `download_splits` to a bool.
exec(self.code, self.fake_main.__dict__)
/home/runner/work/openml-python/openml-python/openml/tasks/task.py:150: FutureWarning: Starting from Version 0.15 `download_data`, `download_qualities`, and `download_features_meta_data` will all be ``False`` instead of ``True`` by default to enable lazy loading. To disable this message until version 0.15 explicitly set `download_data`, `download_qualities`, and `download_features_meta_data` to a bool while calling `get_dataset`.
return datasets.get_dataset(self.dataset_id)
/home/runner/work/openml-python/openml-python/openml/runs/functions.py:789: FutureWarning: Starting from Version 0.15 `download_data`, `download_qualities`, and `download_features_meta_data` will all be ``False`` instead of ``True`` by default to enable lazy loading. To disable this message until version 0.15 explicitly set `download_data`, `download_qualities`, and `download_features_meta_data` to a bool while calling `get_dataset`.
openml.datasets.get_dataset(task.dataset_id).name,
/home/runner/work/openml-python/openml-python/openml/tasks/task.py:150: FutureWarning: Starting from Version 0.15 `download_data`, `download_qualities`, and `download_features_meta_data` will all be ``False`` instead of ``True`` by default to enable lazy loading. To disable this message until version 0.15 explicitly set `download_data`, `download_qualities`, and `download_features_meta_data` to a bool while calling `get_dataset`.
return datasets.get_dataset(self.dataset_id)
/home/runner/work/openml-python/openml-python/openml/runs/functions.py:789: FutureWarning: Starting from Version 0.15 `download_data`, `download_qualities`, and `download_features_meta_data` will all be ``False`` instead of ``True`` by default to enable lazy loading. To disable this message until version 0.15 explicitly set `download_data`, `download_qualities`, and `download_features_meta_data` to a bool while calling `get_dataset`.
openml.datasets.get_dataset(task.dataset_id).name,
/home/runner/work/openml-python/openml-python/openml/tasks/task.py:150: FutureWarning: Starting from Version 0.15 `download_data`, `download_qualities`, and `download_features_meta_data` will all be ``False`` instead of ``True`` by default to enable lazy loading. To disable this message until version 0.15 explicitly set `download_data`, `download_qualities`, and `download_features_meta_data` to a bool while calling `get_dataset`.
return datasets.get_dataset(self.dataset_id)
/home/runner/work/openml-python/openml-python/openml/runs/functions.py:789: FutureWarning: Starting from Version 0.15 `download_data`, `download_qualities`, and `download_features_meta_data` will all be ``False`` instead of ``True`` by default to enable lazy loading. To disable this message until version 0.15 explicitly set `download_data`, `download_qualities`, and `download_features_meta_data` to a bool while calling `get_dataset`.
openml.datasets.get_dataset(task.dataset_id).name,
/home/runner/work/openml-python/openml-python/openml/tasks/task.py:150: FutureWarning: Starting from Version 0.15 `download_data`, `download_qualities`, and `download_features_meta_data` will all be ``False`` instead of ``True`` by default to enable lazy loading. To disable this message until version 0.15 explicitly set `download_data`, `download_qualities`, and `download_features_meta_data` to a bool while calling `get_dataset`.
return datasets.get_dataset(self.dataset_id)
/home/runner/work/openml-python/openml-python/openml/runs/functions.py:789: FutureWarning: Starting from Version 0.15 `download_data`, `download_qualities`, and `download_features_meta_data` will all be ``False`` instead of ``True`` by default to enable lazy loading. To disable this message until version 0.15 explicitly set `download_data`, `download_qualities`, and `download_features_meta_data` to a bool while calling `get_dataset`.
openml.datasets.get_dataset(task.dataset_id).name,
/home/runner/work/openml-python/openml-python/openml/tasks/task.py:150: FutureWarning: Starting from Version 0.15 `download_data`, `download_qualities`, and `download_features_meta_data` will all be ``False`` instead of ``True`` by default to enable lazy loading. To disable this message until version 0.15 explicitly set `download_data`, `download_qualities`, and `download_features_meta_data` to a bool while calling `get_dataset`.
return datasets.get_dataset(self.dataset_id)
/home/runner/work/openml-python/openml-python/openml/runs/functions.py:789: FutureWarning: Starting from Version 0.15 `download_data`, `download_qualities`, and `download_features_meta_data` will all be ``False`` instead of ``True`` by default to enable lazy loading. To disable this message until version 0.15 explicitly set `download_data`, `download_qualities`, and `download_features_meta_data` to a bool while calling `get_dataset`.
openml.datasets.get_dataset(task.dataset_id).name,
/home/runner/work/openml-python/openml-python/openml/tasks/task.py:150: FutureWarning: Starting from Version 0.15 `download_data`, `download_qualities`, and `download_features_meta_data` will all be ``False`` instead of ``True`` by default to enable lazy loading. To disable this message until version 0.15 explicitly set `download_data`, `download_qualities`, and `download_features_meta_data` to a bool while calling `get_dataset`.
return datasets.get_dataset(self.dataset_id)
/home/runner/work/openml-python/openml-python/openml/runs/functions.py:789: FutureWarning: Starting from Version 0.15 `download_data`, `download_qualities`, and `download_features_meta_data` will all be ``False`` instead of ``True`` by default to enable lazy loading. To disable this message until version 0.15 explicitly set `download_data`, `download_qualities`, and `download_features_meta_data` to a bool while calling `get_dataset`.
openml.datasets.get_dataset(task.dataset_id).name,
/home/runner/work/openml-python/openml-python/openml/tasks/task.py:150: FutureWarning: Starting from Version 0.15 `download_data`, `download_qualities`, and `download_features_meta_data` will all be ``False`` instead of ``True`` by default to enable lazy loading. To disable this message until version 0.15 explicitly set `download_data`, `download_qualities`, and `download_features_meta_data` to a bool while calling `get_dataset`.
return datasets.get_dataset(self.dataset_id)
/home/runner/work/openml-python/openml-python/openml/runs/functions.py:789: FutureWarning: Starting from Version 0.15 `download_data`, `download_qualities`, and `download_features_meta_data` will all be ``False`` instead of ``True`` by default to enable lazy loading. To disable this message until version 0.15 explicitly set `download_data`, `download_qualities`, and `download_features_meta_data` to a bool while calling `get_dataset`.
openml.datasets.get_dataset(task.dataset_id).name,
/home/runner/work/openml-python/openml-python/openml/tasks/task.py:150: FutureWarning: Starting from Version 0.15 `download_data`, `download_qualities`, and `download_features_meta_data` will all be ``False`` instead of ``True`` by default to enable lazy loading. To disable this message until version 0.15 explicitly set `download_data`, `download_qualities`, and `download_features_meta_data` to a bool while calling `get_dataset`.
return datasets.get_dataset(self.dataset_id)
/home/runner/work/openml-python/openml-python/openml/runs/functions.py:789: FutureWarning: Starting from Version 0.15 `download_data`, `download_qualities`, and `download_features_meta_data` will all be ``False`` instead of ``True`` by default to enable lazy loading. To disable this message until version 0.15 explicitly set `download_data`, `download_qualities`, and `download_features_meta_data` to a bool while calling `get_dataset`.
openml.datasets.get_dataset(task.dataset_id).name,
/home/runner/work/openml-python/openml-python/openml/tasks/task.py:150: FutureWarning: Starting from Version 0.15 `download_data`, `download_qualities`, and `download_features_meta_data` will all be ``False`` instead of ``True`` by default to enable lazy loading. To disable this message until version 0.15 explicitly set `download_data`, `download_qualities`, and `download_features_meta_data` to a bool while calling `get_dataset`.
return datasets.get_dataset(self.dataset_id)
/home/runner/work/openml-python/openml-python/openml/runs/functions.py:789: FutureWarning: Starting from Version 0.15 `download_data`, `download_qualities`, and `download_features_meta_data` will all be ``False`` instead of ``True`` by default to enable lazy loading. To disable this message until version 0.15 explicitly set `download_data`, `download_qualities`, and `download_features_meta_data` to a bool while calling `get_dataset`.
openml.datasets.get_dataset(task.dataset_id).name,
/home/runner/work/openml-python/openml-python/openml/tasks/task.py:150: FutureWarning: Starting from Version 0.15 `download_data`, `download_qualities`, and `download_features_meta_data` will all be ``False`` instead of ``True`` by default to enable lazy loading. To disable this message until version 0.15 explicitly set `download_data`, `download_qualities`, and `download_features_meta_data` to a bool while calling `get_dataset`.
return datasets.get_dataset(self.dataset_id)
/home/runner/work/openml-python/openml-python/openml/runs/functions.py:789: FutureWarning: Starting from Version 0.15 `download_data`, `download_qualities`, and `download_features_meta_data` will all be ``False`` instead of ``True`` by default to enable lazy loading. To disable this message until version 0.15 explicitly set `download_data`, `download_qualities`, and `download_features_meta_data` to a bool while calling `get_dataset`.
openml.datasets.get_dataset(task.dataset_id).name,
/home/runner/work/openml-python/openml-python/openml/runs/run.py:650: FutureWarning: Starting from Version 0.15.0 `download_splits` will default to ``False`` instead of ``True`` and be independent from `download_data`. To disable this message until version 0.15 explicitly set `download_splits` to a bool.
predictions = arff.dumps(self._generate_arff_dict())
/home/runner/work/openml-python/openml-python/openml/tasks/functions.py:442: FutureWarning: Starting from Version 0.15 `download_data`, `download_qualities`, and `download_features_meta_data` will all be ``False`` instead of ``True`` by default to enable lazy loading. To disable this message until version 0.15 explicitly set `download_data`, `download_qualities`, and `download_features_meta_data` to a bool while calling `get_dataset`.
dataset = get_dataset(task.dataset_id, *dataset_args, **get_dataset_kwargs)
/opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/sphinx_gallery/gen_rst.py:722: FutureWarning: Starting from Version 0.15.0 `download_splits` will default to ``False`` instead of ``True`` and be independent from `download_data`. To disable this message until version 0.15 explicitly set `download_splits` to a bool.
exec(self.code, self.fake_main.__dict__)
/home/runner/work/openml-python/openml-python/openml/tasks/task.py:150: FutureWarning: Starting from Version 0.15 `download_data`, `download_qualities`, and `download_features_meta_data` will all be ``False`` instead of ``True`` by default to enable lazy loading. To disable this message until version 0.15 explicitly set `download_data`, `download_qualities`, and `download_features_meta_data` to a bool while calling `get_dataset`.
return datasets.get_dataset(self.dataset_id)
/home/runner/work/openml-python/openml-python/openml/runs/functions.py:789: FutureWarning: Starting from Version 0.15 `download_data`, `download_qualities`, and `download_features_meta_data` will all be ``False`` instead of ``True`` by default to enable lazy loading. To disable this message until version 0.15 explicitly set `download_data`, `download_qualities`, and `download_features_meta_data` to a bool while calling `get_dataset`.
openml.datasets.get_dataset(task.dataset_id).name,
/home/runner/work/openml-python/openml-python/openml/tasks/task.py:150: FutureWarning: Starting from Version 0.15 `download_data`, `download_qualities`, and `download_features_meta_data` will all be ``False`` instead of ``True`` by default to enable lazy loading. To disable this message until version 0.15 explicitly set `download_data`, `download_qualities`, and `download_features_meta_data` to a bool while calling `get_dataset`.
return datasets.get_dataset(self.dataset_id)
/home/runner/work/openml-python/openml-python/openml/runs/functions.py:789: FutureWarning: Starting from Version 0.15 `download_data`, `download_qualities`, and `download_features_meta_data` will all be ``False`` instead of ``True`` by default to enable lazy loading. To disable this message until version 0.15 explicitly set `download_data`, `download_qualities`, and `download_features_meta_data` to a bool while calling `get_dataset`.
openml.datasets.get_dataset(task.dataset_id).name,
/home/runner/work/openml-python/openml-python/openml/tasks/task.py:150: FutureWarning: Starting from Version 0.15 `download_data`, `download_qualities`, and `download_features_meta_data` will all be ``False`` instead of ``True`` by default to enable lazy loading. To disable this message until version 0.15 explicitly set `download_data`, `download_qualities`, and `download_features_meta_data` to a bool while calling `get_dataset`.
return datasets.get_dataset(self.dataset_id)
/home/runner/work/openml-python/openml-python/openml/runs/functions.py:789: FutureWarning: Starting from Version 0.15 `download_data`, `download_qualities`, and `download_features_meta_data` will all be ``False`` instead of ``True`` by default to enable lazy loading. To disable this message until version 0.15 explicitly set `download_data`, `download_qualities`, and `download_features_meta_data` to a bool while calling `get_dataset`.
openml.datasets.get_dataset(task.dataset_id).name,
/home/runner/work/openml-python/openml-python/openml/tasks/task.py:150: FutureWarning: Starting from Version 0.15 `download_data`, `download_qualities`, and `download_features_meta_data` will all be ``False`` instead of ``True`` by default to enable lazy loading. To disable this message until version 0.15 explicitly set `download_data`, `download_qualities`, and `download_features_meta_data` to a bool while calling `get_dataset`.
return datasets.get_dataset(self.dataset_id)
/home/runner/work/openml-python/openml-python/openml/runs/functions.py:789: FutureWarning: Starting from Version 0.15 `download_data`, `download_qualities`, and `download_features_meta_data` will all be ``False`` instead of ``True`` by default to enable lazy loading. To disable this message until version 0.15 explicitly set `download_data`, `download_qualities`, and `download_features_meta_data` to a bool while calling `get_dataset`.
openml.datasets.get_dataset(task.dataset_id).name,
/home/runner/work/openml-python/openml-python/openml/tasks/task.py:150: FutureWarning: Starting from Version 0.15 `download_data`, `download_qualities`, and `download_features_meta_data` will all be ``False`` instead of ``True`` by default to enable lazy loading. To disable this message until version 0.15 explicitly set `download_data`, `download_qualities`, and `download_features_meta_data` to a bool while calling `get_dataset`.
return datasets.get_dataset(self.dataset_id)
/home/runner/work/openml-python/openml-python/openml/runs/functions.py:789: FutureWarning: Starting from Version 0.15 `download_data`, `download_qualities`, and `download_features_meta_data` will all be ``False`` instead of ``True`` by default to enable lazy loading. To disable this message until version 0.15 explicitly set `download_data`, `download_qualities`, and `download_features_meta_data` to a bool while calling `get_dataset`.
openml.datasets.get_dataset(task.dataset_id).name,
/home/runner/work/openml-python/openml-python/openml/tasks/task.py:150: FutureWarning: Starting from Version 0.15 `download_data`, `download_qualities`, and `download_features_meta_data` will all be ``False`` instead of ``True`` by default to enable lazy loading. To disable this message until version 0.15 explicitly set `download_data`, `download_qualities`, and `download_features_meta_data` to a bool while calling `get_dataset`.
return datasets.get_dataset(self.dataset_id)
/home/runner/work/openml-python/openml-python/openml/runs/functions.py:789: FutureWarning: Starting from Version 0.15 `download_data`, `download_qualities`, and `download_features_meta_data` will all be ``False`` instead of ``True`` by default to enable lazy loading. To disable this message until version 0.15 explicitly set `download_data`, `download_qualities`, and `download_features_meta_data` to a bool while calling `get_dataset`.
openml.datasets.get_dataset(task.dataset_id).name,
/home/runner/work/openml-python/openml-python/openml/tasks/task.py:150: FutureWarning: Starting from Version 0.15 `download_data`, `download_qualities`, and `download_features_meta_data` will all be ``False`` instead of ``True`` by default to enable lazy loading. To disable this message until version 0.15 explicitly set `download_data`, `download_qualities`, and `download_features_meta_data` to a bool while calling `get_dataset`.
return datasets.get_dataset(self.dataset_id)
/home/runner/work/openml-python/openml-python/openml/runs/functions.py:789: FutureWarning: Starting from Version 0.15 `download_data`, `download_qualities`, and `download_features_meta_data` will all be ``False`` instead of ``True`` by default to enable lazy loading. To disable this message until version 0.15 explicitly set `download_data`, `download_qualities`, and `download_features_meta_data` to a bool while calling `get_dataset`.
openml.datasets.get_dataset(task.dataset_id).name,
/home/runner/work/openml-python/openml-python/openml/tasks/task.py:150: FutureWarning: Starting from Version 0.15 `download_data`, `download_qualities`, and `download_features_meta_data` will all be ``False`` instead of ``True`` by default to enable lazy loading. To disable this message until version 0.15 explicitly set `download_data`, `download_qualities`, and `download_features_meta_data` to a bool while calling `get_dataset`.
return datasets.get_dataset(self.dataset_id)
/home/runner/work/openml-python/openml-python/openml/runs/functions.py:789: FutureWarning: Starting from Version 0.15 `download_data`, `download_qualities`, and `download_features_meta_data` will all be ``False`` instead of ``True`` by default to enable lazy loading. To disable this message until version 0.15 explicitly set `download_data`, `download_qualities`, and `download_features_meta_data` to a bool while calling `get_dataset`.
openml.datasets.get_dataset(task.dataset_id).name,
/home/runner/work/openml-python/openml-python/openml/tasks/task.py:150: FutureWarning: Starting from Version 0.15 `download_data`, `download_qualities`, and `download_features_meta_data` will all be ``False`` instead of ``True`` by default to enable lazy loading. To disable this message until version 0.15 explicitly set `download_data`, `download_qualities`, and `download_features_meta_data` to a bool while calling `get_dataset`.
return datasets.get_dataset(self.dataset_id)
/home/runner/work/openml-python/openml-python/openml/runs/functions.py:789: FutureWarning: Starting from Version 0.15 `download_data`, `download_qualities`, and `download_features_meta_data` will all be ``False`` instead of ``True`` by default to enable lazy loading. To disable this message until version 0.15 explicitly set `download_data`, `download_qualities`, and `download_features_meta_data` to a bool while calling `get_dataset`.
openml.datasets.get_dataset(task.dataset_id).name,
/home/runner/work/openml-python/openml-python/openml/tasks/task.py:150: FutureWarning: Starting from Version 0.15 `download_data`, `download_qualities`, and `download_features_meta_data` will all be ``False`` instead of ``True`` by default to enable lazy loading. To disable this message until version 0.15 explicitly set `download_data`, `download_qualities`, and `download_features_meta_data` to a bool while calling `get_dataset`.
return datasets.get_dataset(self.dataset_id)
/home/runner/work/openml-python/openml-python/openml/runs/functions.py:789: FutureWarning: Starting from Version 0.15 `download_data`, `download_qualities`, and `download_features_meta_data` will all be ``False`` instead of ``True`` by default to enable lazy loading. To disable this message until version 0.15 explicitly set `download_data`, `download_qualities`, and `download_features_meta_data` to a bool while calling `get_dataset`.
openml.datasets.get_dataset(task.dataset_id).name,
/home/runner/work/openml-python/openml-python/openml/runs/run.py:650: FutureWarning: Starting from Version 0.15.0 `download_splits` will default to ``False`` instead of ``True`` and be independent from `download_data`. To disable this message until version 0.15 explicitly set `download_splits` to a bool.
predictions = arff.dumps(self._generate_arff_dict())
/home/runner/work/openml-python/openml-python/openml/tasks/functions.py:442: FutureWarning: Starting from Version 0.15 `download_data`, `download_qualities`, and `download_features_meta_data` will all be ``False`` instead of ``True`` by default to enable lazy loading. To disable this message until version 0.15 explicitly set `download_data`, `download_qualities`, and `download_features_meta_data` to a bool while calling `get_dataset`.
dataset = get_dataset(task.dataset_id, *dataset_args, **get_dataset_kwargs)
OpenML Study
============
ID..............: 724
Name............: Test-Study
Status..........: None
Main Entity Type: run
Study URL.......: https://test.openml.org/s/724
# of Runs.......: 3
openml.config.stop_using_configuration_for_example()
Total running time of the script: (2 minutes 7.702 seconds)