repo_id stringclasses 400
values | commit_sha stringclasses 400
values | commit_index int32 0 951 | in_repo_split stringclasses 1
value | cross_repo_split stringclasses 1
value | test_file stringlengths 7 121 | test_function stringlengths 1 108 | assertion_type stringclasses 32
values | difficulty stringclasses 8
values | context_lines int32 3 600 | prefix large_stringlengths 44 113k | target large_stringlengths 1 498 | anchor_sha stringclasses 400
values | anchor_index int32 0 951 | qna_source stringclasses 1
value |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_data.py | test_data_info | assert | numeric_literal | 79 | import os.path
from io import StringIO
import numpy as np
import pandas as pd
import pytest
from numpy.testing import assert_array_equal
from scipy.sparse import csr_matrix
from libreco.data import (
DataInfo,
DatasetFeat,
DatasetPure,
TransformedEvalSet,
TransformedSet,
process_data,
)
from l... | 10 | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_feature.py | test_sparse_indices | assert | numeric_literal | 135 | import os
from dataclasses import astuple
from pathlib import Path
import numpy as np
import pandas as pd
import pytest
from numpy.testing import assert_array_equal
from libreco.data import DatasetFeat
from libreco.data.data_info import EmptyFeature, Feature, store_old_info
from libreco.feature.multi_sparse import (
... | 32 | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_split_data.py | test_split_by_ratio | assert | numeric_literal | 36 | from io import StringIO
import pandas as pd
from libreco.data import (
random_split,
split_by_num,
split_by_num_chrono,
split_by_ratio,
split_by_ratio_chrono,
)
raw_data = StringIO(
"""
user,item,label,time
4617,296,2,964138229
4617,296,2,964138221
4617,296,2,964138222
1298,208,4,974849526
45... | 10 | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_split_data.py | test_split_by_num | assert | numeric_literal | 36 | from io import StringIO
import pandas as pd
from libreco.data import (
random_split,
split_by_num,
split_by_num_chrono,
split_by_ratio,
split_by_ratio_chrono,
)
raw_data = StringIO(
"""
user,item,label,time
4617,296,2,964138229
4617,296,2,964138221
4617,296,2,964138222
1298,208,4,974849526
45... | 11 | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_multi_sparse_processing.py | test_multi_sparse_processing | assert | collection | 46 | import os
import pandas as pd
import pytest
from libreco.data import split_multi_value
def test_multi_sparse_processing():
data_path = os.path.join(
os.path.dirname(os.path.realpath(__file__)),
"sample_data",
"sample_movielens_genre.csv",
)
data = pd.read_csv(data_path, sep=",", h... | [] | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_collators.py | test_normal_collator | assert | collection | 109 | from io import StringIO
import numpy as np
import pandas as pd
import pytest
import torch
from libreco.algorithms import DIN, LightGCN, PinSageDGL, RNN4Rec
from libreco.batch.batch_data import BatchData
from libreco.batch.batch_unit import (
PairFeats,
PairwiseBatch,
PointwiseBatch,
PointwiseSepFeatBa... | (3,) | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_collators.py | test_normal_collator | assert | collection | 112 | from io import StringIO
import numpy as np
import pandas as pd
import pytest
import torch
from libreco.algorithms import DIN, LightGCN, PinSageDGL, RNN4Rec
from libreco.batch.batch_data import BatchData
from libreco.batch.batch_unit import (
PairFeats,
PairwiseBatch,
PointwiseBatch,
PointwiseSepFeatBa... | (9,) | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_collators.py | test_pairwise_collator | assert | collection | 124 | from io import StringIO
import numpy as np
import pandas as pd
import pytest
import torch
from libreco.algorithms import DIN, LightGCN, PinSageDGL, RNN4Rec
from libreco.batch.batch_data import BatchData
from libreco.batch.batch_unit import (
PairFeats,
PairwiseBatch,
PointwiseBatch,
PointwiseSepFeatBa... | (6,) | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_consumed.py | test_no_merge | assert | collection | 12 | from libreco.data.consumed import _fill_empty, _merge_dedup, interaction_consumed
def test_no_merge():
num = 4
old_consumed = {0: [1, 2, 3], 1: [4, 5], 2: [0], 3: [99]}
new_consumed = {0: [2, 1], 2: [7, 8]}
consumed = _fill_empty(new_consumed, num, old_consumed)
assert consumed[0] == [2, 1]
ass... | [99] | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_collators.py | test_sparse_collator | assert | collection | 104 | from io import StringIO
import numpy as np
import pandas as pd
import pytest
import torch
from libreco.algorithms import DIN, LightGCN, PinSageDGL, RNN4Rec
from libreco.batch.batch_data import BatchData
from libreco.batch.batch_unit import (
PairFeats,
PairwiseBatch,
PointwiseBatch,
PointwiseSepFeatBa... | (3, 2) | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_consumed.py | test_remove_duplicates | assert | collection | 16 | from libreco.data.consumed import _fill_empty, _merge_dedup, interaction_consumed
def test_remove_duplicates():
user_indices = [1, 1, 1, 2, 2, 1, 2, 3, 2, 3]
item_indices = [11, 11, 999, 0, 11, 11, 999, 11, 999, 0]
user_consumed, item_consumed = interaction_consumed(user_indices, item_indices)
assert i... | [1, 2] | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_consumed.py | test_remove_duplicates | assert | collection | 17 | from libreco.data.consumed import _fill_empty, _merge_dedup, interaction_consumed
def test_remove_duplicates():
user_indices = [1, 1, 1, 2, 2, 1, 2, 3, 2, 3]
item_indices = [11, 11, 999, 0, 11, 11, 999, 11, 999, 0]
user_consumed, item_consumed = interaction_consumed(user_indices, item_indices)
assert i... | [2, 3] | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_consumed.py | test_merge_remove_duplicates | assert | collection | 10 | from libreco.data.consumed import _fill_empty, _merge_dedup, interaction_consumed
def test_merge_remove_duplicates():
num = 3
old_consumed = {0: [1, 2, 3], 1: [4, 5]}
new_consumed = {0: [2, 1], 2: [7, 8]}
consumed = _merge_dedup(new_consumed, num, old_consumed)
assert consumed[0] == [3, 2, 1]
... | [4, 5] | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_consumed.py | test_merge_remove_duplicates | assert | collection | 11 | from libreco.data.consumed import _fill_empty, _merge_dedup, interaction_consumed
def test_merge_remove_duplicates():
num = 3
old_consumed = {0: [1, 2, 3], 1: [4, 5]}
new_consumed = {0: [2, 1], 2: [7, 8]}
consumed = _merge_dedup(new_consumed, num, old_consumed)
assert consumed[0] == [3, 2, 1]
a... | [7, 8] | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_consumed.py | test_no_merge | assert | collection | 9 | from libreco.data.consumed import _fill_empty, _merge_dedup, interaction_consumed
def test_no_merge():
num = 4
old_consumed = {0: [1, 2, 3], 1: [4, 5], 2: [0], 3: [99]}
new_consumed = {0: [2, 1], 2: [7, 8]}
consumed = _fill_empty(new_consumed, num, old_consumed)
assert consumed[0] == | [2, 1] | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_initializers.py | test_initializers | assert | collection | 18 | import itertools
import numpy as np
import pytest
from libreco.utils.initializers import (
he_init,
truncated_normal,
variance_scaling,
xavier_init,
)
def test_initializers():
np_rng = np.random.default_rng(42)
mean, std, fan_in, fan_out, scale = 0.1, 0.01, 4, 2, 2.5
variables = truncated... | (3, 2) | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_rank_reco.py | test_rank_reco | assert | collection | 38 | import numpy as np
import pytest
from libreco.recommendation import rank_recommendations
def test_rank_reco():
user_ids = [1, 2]
preds = np.array([-0.1, -0.01, 0, 0.1, 0.01, 1, -2, 4, 5, 6])
n_rec = 2
n_items = 5
consumed = {1: [3, 4], 2: [4]}
with pytest.raises(ValueError):
_ = rank_... | (2, 2) | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_rank_reco.py | test_rank_reco | assert | collection | 53 | import numpy as np
import pytest
from libreco.recommendation import rank_recommendations
def test_rank_reco():
user_ids = [1, 2]
preds = np.array([-0.1, -0.01, 0, 0.1, 0.01, 1, -2, 4, 5, 6])
n_rec = 2
n_items = 5
consumed = {1: [3, 4], 2: [4]}
with pytest.raises(ValueError):
_ = rank_... | (2, 4) | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_tf_layers.py | test_positional_encoding | assert | collection | 35 | import sys
import numpy as np
import pytest
from numpy.testing import assert_allclose, assert_array_equal
from libreco.layers import (
conv_nn,
dense_nn,
layer_normalization,
max_pool,
multi_head_attention,
shared_dense,
tf_dense,
tf_rnn,
transformer_decoder_layer,
transformer_... | (3, 3) | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/serving/test_faiss_index.py | test_faiss_index | assert | collection | 16 | import os
import pytest
from libreco.algorithms import BPR
from libserving.serialization import save_faiss_index
from tests.utils_data import SAVE_PATH
def test_faiss_index(embed_model):
import faiss
save_faiss_index(SAVE_PATH, embed_model, 80, 10)
index = faiss.read_index(os.path.join(SAVE_PATH, "faiss... | (1, 10) | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_collators.py | test_normal_collator | assert | collection | 107 | from io import StringIO
import numpy as np
import pandas as pd
import pytest
import torch
from libreco.algorithms import DIN, LightGCN, PinSageDGL, RNN4Rec
from libreco.batch.batch_data import BatchData
from libreco.batch.batch_unit import (
PairFeats,
PairwiseBatch,
PointwiseBatch,
PointwiseSepFeatBa... | (3, 10) | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_collators.py | test_pointwise_collator | assert | collection | 108 | from io import StringIO
import numpy as np
import pandas as pd
import pytest
import torch
from libreco.algorithms import DIN, LightGCN, PinSageDGL, RNN4Rec
from libreco.batch.batch_data import BatchData
from libreco.batch.batch_unit import (
PairFeats,
PairwiseBatch,
PointwiseBatch,
PointwiseSepFeatBa... | (9, 10) | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_collators.py | test_pairwise_collator | assert | collection | 122 | from io import StringIO
import numpy as np
import pandas as pd
import pytest
import torch
from libreco.algorithms import DIN, LightGCN, PinSageDGL, RNN4Rec
from libreco.batch.batch_data import BatchData
from libreco.batch.batch_unit import (
PairFeats,
PairwiseBatch,
PointwiseBatch,
PointwiseSepFeatBa... | (6, 10) | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_consumed.py | test_remove_duplicates | assert | collection | 14 | from libreco.data.consumed import _fill_empty, _merge_dedup, interaction_consumed
def test_remove_duplicates():
user_indices = [1, 1, 1, 2, 2, 1, 2, 3, 2, 3]
item_indices = [11, 11, 999, 0, 11, 11, 999, 11, 999, 0]
user_consumed, item_consumed = interaction_consumed(user_indices, item_indices)
assert i... | [11, 0] | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_feature.py | test_data_info_features | assert | collection | 70 | import os
from dataclasses import astuple
from pathlib import Path
import numpy as np
import pandas as pd
import pytest
from numpy.testing import assert_array_equal
from libreco.data import DatasetFeat
from libreco.data.data_info import EmptyFeature, Feature, store_old_info
from libreco.feature.multi_sparse import (
... | ["age"] | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_feature.py | test_multi_sparse_indices | assert_* | collection | 99 | import os
from dataclasses import astuple
from pathlib import Path
import numpy as np
import pandas as pd
import pytest
from numpy.testing import assert_array_equal
from libreco.data import DatasetFeat
from libreco.data.data_info import EmptyFeature, Feature, store_old_info
from libreco.feature.multi_sparse import (
... | [2, 4]) | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_feature.py | test_multi_sparse_indices | assert_* | collection | 100 | import os
from dataclasses import astuple
from pathlib import Path
import numpy as np
import pandas as pd
import pytest
from numpy.testing import assert_array_equal
from libreco.data import DatasetFeat
from libreco.data.data_info import EmptyFeature, Feature, store_old_info
from libreco.feature.multi_sparse import (
... | [2, 3]) | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_rank_reco.py | test_rank_reco | assert_* | collection | 39 | import numpy as np
import pytest
from libreco.recommendation import rank_recommendations
def test_rank_reco():
user_ids = [1, 2]
preds = np.array([-0.1, -0.01, 0, 0.1, 0.01, 1, -2, 4, 5, 6])
n_rec = 2
n_items = 5
consumed = {1: [3, 4], 2: [4]}
with pytest.raises(ValueError):
_ = rank_... | [2, 1]) | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_tf_layers.py | test_dense_layer | assert | collection | 42 | import sys
import numpy as np
import pytest
from numpy.testing import assert_allclose, assert_array_equal
from libreco.layers import (
conv_nn,
dense_nn,
layer_normalization,
max_pool,
multi_head_attention,
shared_dense,
tf_dense,
tf_rnn,
transformer_decoder_layer,
transformer_... | (100, 3) | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_tf_layers.py | test_dense_layer | assert | collection | 43 | import sys
import numpy as np
import pytest
from numpy.testing import assert_allclose, assert_array_equal
from libreco.layers import (
conv_nn,
dense_nn,
layer_normalization,
max_pool,
multi_head_attention,
shared_dense,
tf_dense,
tf_rnn,
transformer_decoder_layer,
transformer_... | (100, 7) | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_tf_layers.py | test_rnn_layer | assert | collection | 57 | import sys
import numpy as np
import pytest
from numpy.testing import assert_allclose, assert_array_equal
from libreco.layers import (
conv_nn,
dense_nn,
layer_normalization,
max_pool,
multi_head_attention,
shared_dense,
tf_dense,
tf_rnn,
transformer_decoder_layer,
transformer_... | (100, 8) | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_tf_layers.py | test_positional_encoding | assert | collection | 41 | import sys
import numpy as np
import pytest
from numpy.testing import assert_allclose, assert_array_equal
from libreco.layers import (
conv_nn,
dense_nn,
layer_normalization,
max_pool,
multi_head_attention,
shared_dense,
tf_dense,
tf_rnn,
transformer_decoder_layer,
transformer_... | (10, 10) | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_consumed.py | test_remove_duplicates | assert | collection | 12 | from libreco.data.consumed import _fill_empty, _merge_dedup, interaction_consumed
def test_remove_duplicates():
user_indices = [1, 1, 1, 2, 2, 1, 2, 3, 2, 3]
item_indices = [11, 11, 999, 0, 11, 11, 999, 11, 999, 0]
user_consumed, item_consumed = interaction_consumed(user_indices, item_indices)
assert i... | [11, 999] | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_consumed.py | test_remove_duplicates | assert | collection | 15 | from libreco.data.consumed import _fill_empty, _merge_dedup, interaction_consumed
def test_remove_duplicates():
user_indices = [1, 1, 1, 2, 2, 1, 2, 3, 2, 3]
item_indices = [11, 11, 999, 0, 11, 11, 999, 11, 999, 0]
user_consumed, item_consumed = interaction_consumed(user_indices, item_indices)
assert i... | [1, 2, 3] | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_consumed.py | test_merge_remove_duplicates | assert | collection | 9 | from libreco.data.consumed import _fill_empty, _merge_dedup, interaction_consumed
def test_merge_remove_duplicates():
num = 3
old_consumed = {0: [1, 2, 3], 1: [4, 5]}
new_consumed = {0: [2, 1], 2: [7, 8]}
consumed = _merge_dedup(new_consumed, num, old_consumed)
assert consumed[0] == | [3, 2, 1] | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_feature.py | test_multi_sparse_indices | assert_* | collection | 101 | import os
from dataclasses import astuple
from pathlib import Path
import numpy as np
import pandas as pd
import pytest
from numpy.testing import assert_array_equal
from libreco.data import DatasetFeat
from libreco.data.data_info import EmptyFeature, Feature, store_old_info
from libreco.feature.multi_sparse import (
... | [12, 18]) | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_tf_layers.py | test_rnn_layer | assert | collection | 58 | import sys
import numpy as np
import pytest
from numpy.testing import assert_allclose, assert_array_equal
from libreco.layers import (
conv_nn,
dense_nn,
layer_normalization,
max_pool,
multi_head_attention,
shared_dense,
tf_dense,
tf_rnn,
transformer_decoder_layer,
transformer_... | (100, 16) | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_feature.py | test_update_features | assert_* | collection | 111 | import os
from dataclasses import astuple
from pathlib import Path
import numpy as np
import pandas as pd
import pytest
from numpy.testing import assert_array_equal
from libreco.data import DatasetFeat
from libreco.data.data_info import EmptyFeature, Feature, store_old_info
from libreco.feature.multi_sparse import (
... | ["a", "c"]) | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_tf_layers.py | test_conv_layer | assert | collection | 42 | import sys
import numpy as np
import pytest
from numpy.testing import assert_allclose, assert_array_equal
from libreco.layers import (
conv_nn,
dense_nn,
layer_normalization,
max_pool,
multi_head_attention,
shared_dense,
tf_dense,
tf_rnn,
transformer_decoder_layer,
transformer_... | (100, 9, 2) | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_tf_layers.py | test_max_pool_layer | assert | collection | 37 | import sys
import numpy as np
import pytest
from numpy.testing import assert_allclose, assert_array_equal
from libreco.layers import (
conv_nn,
dense_nn,
layer_normalization,
max_pool,
multi_head_attention,
shared_dense,
tf_dense,
tf_rnn,
transformer_decoder_layer,
transformer_... | (100, 9, 10) | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_multi_sparse_processing.py | test_multi_sparse_processing | assert | collection | 47 | import os
import pandas as pd
import pytest
from libreco.data import split_multi_value
def test_multi_sparse_processing():
data_path = os.path.join(
os.path.dirname(os.path.realpath(__file__)),
"sample_data",
"sample_movielens_genre.csv",
)
data = pd.read_csv(data_path, sep=",", h... | ["genre_1", "genre_2", "genre_3"] | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_knn_embed.py | test_knn_embed | pytest.raises | collection | 46 | import sys
import pytest
from libreco.algorithms import ALS, LightGCN, RNN4Rec
from tests.utils_data import set_ranking_labels
@pytest.mark.skipif(
sys.platform.startswith("win") or sys.platform.startswith("darwin"),
reason="Possible issue on Windows and MaxOS platform using `nmslib`",
)
@pytest.mark.skipif(... | (ImportError, ModuleNotFoundError)) | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_multi_sparse_processing.py | test_multi_sparse_processing | assert | collection | 45 | import os
import pandas as pd
import pytest
from libreco.data import split_multi_value
def test_multi_sparse_processing():
data_path = os.path.join(
os.path.dirname(os.path.realpath(__file__)),
"sample_data",
"sample_movielens_genre.csv",
)
data = pd.read_csv(data_path, sep=",", h... | [["genre_1", "genre_2", "genre_3"]] | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_tf_layers.py | test_transformer_encoder | assert | collection | 44 | import sys
import numpy as np
import pytest
from numpy.testing import assert_allclose, assert_array_equal
from libreco.layers import (
conv_nn,
dense_nn,
layer_normalization,
max_pool,
multi_head_attention,
shared_dense,
tf_dense,
tf_rnn,
transformer_decoder_layer,
transformer_... | (batch_size, max_seq_len, embed_size) | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_dgl.py | test_dgl | assert | none_literal | 28 | import importlib
import sys
import pytest
from libreco.graph import check_dgl
def test_dgl(prepare_feat_data, monkeypatch):
*_, data_info = prepare_feat_data
with monkeypatch.context() as m:
m.setitem(sys.modules, "dgl", None)
with pytest.raises(ModuleNotFoundError):
from libreco... | None | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_feature.py | test_sparse_indices | assert | none_literal | 91 | import os
from dataclasses import astuple
from pathlib import Path
import numpy as np
import pandas as pd
import pytest
from numpy.testing import assert_array_equal
from libreco.data import DatasetFeat
from libreco.data.data_info import EmptyFeature, Feature, store_old_info
from libreco.feature.multi_sparse import (
... | None | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_dgl.py | test_dgl | assert | string_literal | 29 | import importlib
import sys
import pytest
from libreco.graph import check_dgl
def test_dgl(prepare_feat_data, monkeypatch):
*_, data_info = prepare_feat_data
with monkeypatch.context() as m:
m.setitem(sys.modules, "dgl", None)
with pytest.raises(ModuleNotFoundError):
from libreco... | "dgl" | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_knn_embed.py | ptest_knn | assert | string_literal | 27 | import sys
import pytest
from libreco.algorithms import ALS, LightGCN, RNN4Rec
from tests.utils_data import set_ranking_labels
def ptest_knn(model, pd_data):
assert model.get_user_embedding().shape[0] == model.n_users
assert model.get_user_embedding().shape[1] == model.embed_size
assert model.get_item_em... | "cosine" | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/utils_reco.py | ptest_dyn_recommends | assert | func_call | 117 | import numpy as np
import pytest
from libreco.utils.constants import FeatModels, SequenceModels
def recommend_in_former_consumed(data_info, reco, user):
user_id = data_info.user2id[user]
user_consumed = data_info.user_consumed[user_id]
user_consumed_id = [data_info.id2item[i] for i in user_consumed]
r... | len(reco2) | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/utils_reco.py | ptest_dyn_recommends | assert | func_call | 122 | import numpy as np
import pytest
from libreco.utils.constants import FeatModels, SequenceModels
def recommend_in_former_consumed(data_info, reco, user):
user_id = data_info.user2id[user]
user_consumed = data_info.user_consumed[user_id]
user_consumed_id = [data_info.id2item[i] for i in user_consumed]
r... | len(cold2) | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_multiprocessing_seeds.py | test_multiprocessing_seeds | assert | func_call | 54 | import multiprocessing
import random
import numpy as np
import pytest
import torch
from torch.utils.data import DataLoader
def get_data(request):
data_size = 20
same_seed = request.param["same_seed"]
batch_size = request.param["batch_size"]
num_workers = request.param["num_workers"]
batch_data = B... | len(np_random) | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/utils_reco.py | ptest_recommends | assert | func_call | 32 | import numpy as np
import pytest
from libreco.utils.constants import FeatModels, SequenceModels
def recommend_in_former_consumed(data_info, reco, user):
user_id = data_info.user2id[user]
user_consumed = data_info.user_consumed[user_id]
user_consumed_id = [data_info.id2item[i] for i in user_consumed]
r... | len(cold_reco2) | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/utils_reco.py | ptest_recommends | assert | func_call | 22 | import numpy as np
import pytest
from libreco.utils.constants import FeatModels, SequenceModels
def recommend_in_former_consumed(data_info, reco, user):
user_id = data_info.user2id[user]
user_consumed = data_info.user_consumed[user_id]
user_consumed_id = [data_info.id2item[i] for i in user_consumed]
r... | len(reco_take_two) | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_similarities.py | test_similarities | assert_* | func_call | 61 | import functools
from io import StringIO
import numpy as np
import pandas as pd
import pytest
from scipy.sparse import csr_matrix
from libreco.data import DatasetPure
from libreco.utils.similarities import (
_choose_blocks,
cosine_sim,
jaccard_sim,
pearson_sim,
)
raw_data = """
user,item,label
1,8,2
... | invert_sim.toarray()) | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_tf_layers.py | test_multi_head_attention | assert | func_call | 47 | import sys
import numpy as np
import pytest
from numpy.testing import assert_allclose, assert_array_equal
from libreco.layers import (
conv_nn,
dense_nn,
layer_normalization,
max_pool,
multi_head_attention,
shared_dense,
tf_dense,
tf_rnn,
transformer_decoder_layer,
transformer_... | sess.run(output2).shape | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
matin/garth | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | train | train | tests/data/test_body_battery_data.py | test_body_battery_data_list | assert | numeric_literal | 18 | from datetime import date
from unittest.mock import MagicMock
import pytest
from garth import BodyBatteryData, DailyBodyBatteryStress
from garth.http import Client
@pytest.mark.vcr
def test_body_battery_data_list(authed_client: Client):
days = 3
end = date(2023, 7, 20)
body_battery_data = BodyBatteryData... | 0 | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | v2_extractor_at_anchor |
matin/garth | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | train | train | tests/data/test_body_battery_data.py | test_body_battery_data_get_missing_event_data | assert | numeric_literal | 18 | from datetime import date
from unittest.mock import MagicMock
import pytest
from garth import BodyBatteryData, DailyBodyBatteryStress
from garth.http import Client
def test_body_battery_data_get_missing_event_data():
"""Test handling of items with missing event data."""
mock_client = MagicMock()
mock_cli... | 1 | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | v2_extractor_at_anchor |
matin/garth | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | train | train | tests/data/test_body_battery_data.py | test_body_battery_data_get_api_error | assert | collection | 16 | from datetime import date
from unittest.mock import MagicMock
import pytest
from garth import BodyBatteryData, DailyBodyBatteryStress
from garth.http import Client
def test_body_battery_data_get_api_error():
"""Test handling of API errors."""
mock_client = MagicMock()
mock_client.connectapi.side_effect =... | [] | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | v2_extractor_at_anchor |
matin/garth | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | train | train | tests/data/test_body_battery_data.py | test_daily_body_battery_stress_list | assert | variable | 19 | from datetime import date
from unittest.mock import MagicMock
import pytest
from garth import BodyBatteryData, DailyBodyBatteryStress
from garth.http import Client
@pytest.mark.vcr
def test_daily_body_battery_stress_list(authed_client: Client):
days = 3
end = date(2023, 7, 20)
# Use max_workers=1 to avoi... | days | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | v2_extractor_at_anchor |
matin/garth | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | train | train | tests/data/test_body_battery_data.py | test_body_battery_data_get_missing_event_data | assert | none_literal | 19 | from datetime import date
from unittest.mock import MagicMock
import pytest
from garth import BodyBatteryData, DailyBodyBatteryStress
from garth.http import Client
def test_body_battery_data_get_missing_event_data():
"""Test handling of items with missing event data."""
mock_client = MagicMock()
mock_cli... | None | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | v2_extractor_at_anchor |
matin/garth | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | train | train | tests/data/test_hrv_data.py | test_hrv_data_list | assert | variable | 15 | from datetime import date
import pytest
from garth import HRVData
from garth.http import Client
@pytest.mark.vcr
def test_hrv_data_list(authed_client: Client):
days = 2
end = date(2023, 7, 20)
hrv_data = HRVData.list(end, days, client=authed_client, max_workers=1)
assert len(hrv_data) == days
as... | end | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | v2_extractor_at_anchor |
matin/garth | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | train | train | tests/data/test_hrv_data.py | test_hrv_data_get | assert | none_literal | 16 | from datetime import date
import pytest
from garth import HRVData
from garth.http import Client
@pytest.mark.vcr
def test_hrv_data_get(authed_client: Client):
hrv_data = HRVData.get("2023-07-20", client=authed_client)
assert hrv_data
assert hrv_data.user_profile_pk
assert hrv_data.hrv_summary.calenda... | None | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | v2_extractor_at_anchor |
matin/garth | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | train | train | tests/data/test_hrv_data.py | test_hrv_data_list | assert | variable | 14 | from datetime import date
import pytest
from garth import HRVData
from garth.http import Client
@pytest.mark.vcr
def test_hrv_data_list(authed_client: Client):
days = 2
end = date(2023, 7, 20)
hrv_data = HRVData.list(end, days, client=authed_client, max_workers=1)
assert len(hrv_data) == | days | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | v2_extractor_at_anchor |
matin/garth | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | train | train | tests/data/test_hrv_data.py | test_hrv_data_get | assert | func_call | 14 | from datetime import date
import pytest
from garth import HRVData
from garth.http import Client
@pytest.mark.vcr
def test_hrv_data_get(authed_client: Client):
hrv_data = HRVData.get("2023-07-20", client=authed_client)
assert hrv_data
assert hrv_data.user_profile_pk
assert hrv_data.hrv_summary.calend... | date(2023, 7, 20) | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | v2_extractor_at_anchor |
matin/garth | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | train | train | tests/data/test_sleep_data.py | test_sleep_data_list | assert | variable | 14 | from datetime import date
import pytest
from garth import SleepData
from garth.http import Client
@pytest.mark.vcr
def test_sleep_data_list(authed_client: Client):
end = date(2021, 7, 20)
days = 20
sleep_data = SleepData.list(end, days, client=authed_client, max_workers=1)
assert sleep_data[-1].dail... | end | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | v2_extractor_at_anchor |
matin/garth | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | train | train | tests/data/test_sleep_data.py | test_sleep_data_list | assert | variable | 15 | from datetime import date
import pytest
from garth import SleepData
from garth.http import Client
@pytest.mark.vcr
def test_sleep_data_list(authed_client: Client):
end = date(2021, 7, 20)
days = 20
sleep_data = SleepData.list(end, days, client=authed_client, max_workers=1)
assert sleep_data[-1].daily... | days | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | v2_extractor_at_anchor |
matin/garth | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | train | train | tests/data/test_sleep_data.py | test_sleep_data_get | assert | func_call | 13 | from datetime import date
import pytest
from garth import SleepData
from garth.http import Client
@pytest.mark.vcr
def test_sleep_data_get(authed_client: Client):
sleep_data = SleepData.get("2021-07-20", client=authed_client)
assert sleep_data
assert sleep_data.daily_sleep_dto.calendar_date == | date(2021, 7, 20) | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | v2_extractor_at_anchor |
matin/garth | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | train | train | tests/stats/test_hrv.py | test_daily_hrv_no_results | assert | collection | 13 | from datetime import date
import pytest
from garth import DailyHRV
from garth.http import Client
@pytest.mark.vcr
def test_daily_hrv_no_results(authed_client: Client):
end = date(1990, 7, 20)
daily_hrv = DailyHRV.list(end, client=authed_client)
assert daily_hrv == | [] | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | v2_extractor_at_anchor |
matin/garth | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | train | train | tests/stats/test_hrv.py | test_daily_hrv | assert | variable | 14 | from datetime import date
import pytest
from garth import DailyHRV
from garth.http import Client
@pytest.mark.vcr
def test_daily_hrv(authed_client: Client):
end = date(2023, 7, 20)
days = 20
daily_hrv = DailyHRV.list(end, days, client=authed_client)
assert daily_hrv[-1].calendar_date == | end | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | v2_extractor_at_anchor |
matin/garth | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | train | train | tests/stats/test_hrv.py | test_daily_hrv | assert | variable | 15 | from datetime import date
import pytest
from garth import DailyHRV
from garth.http import Client
@pytest.mark.vcr
def test_daily_hrv(authed_client: Client):
end = date(2023, 7, 20)
days = 20
daily_hrv = DailyHRV.list(end, days, client=authed_client)
assert daily_hrv[-1].calendar_date == end
asse... | days | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | v2_extractor_at_anchor |
matin/garth | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | train | train | tests/stats/test_intensity_minutes.py | test_daily_intensity_minutes | assert | variable | 14 | from datetime import date
import pytest
from garth import DailyIntensityMinutes, WeeklyIntensityMinutes
from garth.http import Client
@pytest.mark.vcr
def test_daily_intensity_minutes(authed_client: Client):
end = date(2023, 7, 20)
days = 20
daily_im = DailyIntensityMinutes.list(end, days, client=authed_... | end | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | v2_extractor_at_anchor |
matin/garth | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | train | train | tests/stats/test_intensity_minutes.py | test_daily_intensity_minutes | assert | variable | 15 | from datetime import date
import pytest
from garth import DailyIntensityMinutes, WeeklyIntensityMinutes
from garth.http import Client
@pytest.mark.vcr
def test_daily_intensity_minutes(authed_client: Client):
end = date(2023, 7, 20)
days = 20
daily_im = DailyIntensityMinutes.list(end, days, client=authed_... | days | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | v2_extractor_at_anchor |
matin/garth | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | train | train | tests/stats/test_intensity_minutes.py | test_weekly_intensity_minutes | assert | variable | 14 | from datetime import date
import pytest
from garth import DailyIntensityMinutes, WeeklyIntensityMinutes
from garth.http import Client
@pytest.mark.vcr
def test_weekly_intensity_minutes(authed_client: Client):
end = date(2023, 7, 20)
weeks = 12
weekly_im = WeeklyIntensityMinutes.list(end, weeks, client=au... | weeks | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | v2_extractor_at_anchor |
matin/garth | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | train | train | tests/stats/test_intensity_minutes.py | test_weekly_intensity_minutes | assert | func_call | 15 | from datetime import date
import pytest
from garth import DailyIntensityMinutes, WeeklyIntensityMinutes
from garth.http import Client
@pytest.mark.vcr
def test_weekly_intensity_minutes(authed_client: Client):
end = date(2023, 7, 20)
weeks = 12
weekly_im = WeeklyIntensityMinutes.list(end, weeks, client=au... | end.isocalendar()[1] | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | v2_extractor_at_anchor |
matin/garth | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | train | train | tests/stats/test_sleep_stats.py | test_daily_sleep | assert | variable | 14 | from datetime import date
import pytest
from garth import DailySleep
from garth.http import Client
@pytest.mark.vcr
def test_daily_sleep(authed_client: Client):
end = date(2023, 7, 20)
days = 20
daily_sleep = DailySleep.list(end, days, client=authed_client)
assert daily_sleep[-1].calendar_date == | end | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | v2_extractor_at_anchor |
matin/garth | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | train | train | tests/stats/test_sleep_stats.py | test_daily_sleep | assert | variable | 15 | from datetime import date
import pytest
from garth import DailySleep
from garth.http import Client
@pytest.mark.vcr
def test_daily_sleep(authed_client: Client):
end = date(2023, 7, 20)
days = 20
daily_sleep = DailySleep.list(end, days, client=authed_client)
assert daily_sleep[-1].calendar_date == end... | days | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | v2_extractor_at_anchor |
matin/garth | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | train | train | tests/stats/test_steps.py | test_daily_steps | assert | variable | 14 | from datetime import date, timedelta
import pytest
from garth import DailySteps, WeeklySteps
from garth.http import Client
@pytest.mark.vcr
def test_daily_steps(authed_client: Client):
end = date(2023, 7, 20)
days = 20
daily_steps = DailySteps.list(end, days, client=authed_client)
assert daily_steps... | end | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | v2_extractor_at_anchor |
matin/garth | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | train | train | tests/stats/test_steps.py | test_daily_steps | assert | variable | 15 | from datetime import date, timedelta
import pytest
from garth import DailySteps, WeeklySteps
from garth.http import Client
@pytest.mark.vcr
def test_daily_steps(authed_client: Client):
end = date(2023, 7, 20)
days = 20
daily_steps = DailySteps.list(end, days, client=authed_client)
assert daily_steps[... | days | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | v2_extractor_at_anchor |
matin/garth | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | train | train | tests/stats/test_steps.py | test_weekly_steps | assert | variable | 14 | from datetime import date, timedelta
import pytest
from garth import DailySteps, WeeklySteps
from garth.http import Client
@pytest.mark.vcr
def test_weekly_steps(authed_client: Client):
end = date(2023, 7, 20)
weeks = 52
weekly_steps = WeeklySteps.list(end, weeks, client=authed_client)
assert len(we... | weeks | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | v2_extractor_at_anchor |
matin/garth | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | train | train | tests/stats/test_steps.py | test_weekly_steps | assert | func_call | 15 | from datetime import date, timedelta
import pytest
from garth import DailySteps, WeeklySteps
from garth.http import Client
@pytest.mark.vcr
def test_weekly_steps(authed_client: Client):
end = date(2023, 7, 20)
weeks = 52
weekly_steps = WeeklySteps.list(end, weeks, client=authed_client)
assert len(wee... | end - timedelta(days=6) | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | v2_extractor_at_anchor |
matin/garth | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | train | train | tests/stats/test_stress.py | test_daily_stress | assert | variable | 14 | from datetime import date, timedelta
import pytest
from garth import DailyStress, WeeklyStress
from garth.http import Client
@pytest.mark.vcr
def test_daily_stress(authed_client: Client):
end = date(2023, 7, 20)
days = 20
daily_stress = DailyStress.list(end, days, client=authed_client)
assert daily_... | end | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | v2_extractor_at_anchor |
matin/garth | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | train | train | tests/stats/test_stress.py | test_daily_stress | assert | variable | 15 | from datetime import date, timedelta
import pytest
from garth import DailyStress, WeeklyStress
from garth.http import Client
@pytest.mark.vcr
def test_daily_stress(authed_client: Client):
end = date(2023, 7, 20)
days = 20
daily_stress = DailyStress.list(end, days, client=authed_client)
assert daily_s... | days | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | v2_extractor_at_anchor |
matin/garth | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | train | train | tests/stats/test_stress.py | test_weekly_stress | assert | variable | 14 | from datetime import date, timedelta
import pytest
from garth import DailyStress, WeeklyStress
from garth.http import Client
@pytest.mark.vcr
def test_weekly_stress(authed_client: Client):
end = date(2023, 7, 20)
weeks = 52
weekly_stress = WeeklyStress.list(end, weeks, client=authed_client)
assert l... | weeks | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | v2_extractor_at_anchor |
matin/garth | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | train | train | tests/stats/test_stress.py | test_weekly_stress | assert | func_call | 15 | from datetime import date, timedelta
import pytest
from garth import DailyStress, WeeklyStress
from garth.http import Client
@pytest.mark.vcr
def test_weekly_stress(authed_client: Client):
end = date(2023, 7, 20)
weeks = 52
weekly_stress = WeeklyStress.list(end, weeks, client=authed_client)
assert le... | end - timedelta(days=6) | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | v2_extractor_at_anchor |
matin/garth | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | train | train | tests/test_auth_tokens.py | test_is_expired | assert | bool_literal | 8 | import time
from garth.auth_tokens import OAuth2Token
def test_is_expired(oauth2_token: OAuth2Token):
oauth2_token.expires_at = int(time.time() - 1)
assert oauth2_token.expired is | True | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | v2_extractor_at_anchor |
matin/garth | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | train | train | tests/test_auth_tokens.py | test_str | assert | string_literal | 7 | import time
from garth.auth_tokens import OAuth2Token
def test_str(oauth2_token: OAuth2Token):
assert str(oauth2_token) == | "Bearer bar" | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | v2_extractor_at_anchor |
matin/garth | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | train | train | tests/test_cli.py | test_help_flag | assert | numeric_literal | 15 | import builtins
import getpass
import sys
import pytest
from garth.cli import main
def test_help_flag(monkeypatch, capsys):
# -h should print help and exit with code 0
monkeypatch.setattr(sys, "argv", ["garth", "-h"])
with pytest.raises(SystemExit) as excinfo:
main()
assert excinfo.value.cod... | 0 | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | v2_extractor_at_anchor |
matin/garth | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | train | train | tests/test_cli.py | test_help_flag | assert | func_call | 17 | import builtins
import getpass
import sys
import pytest
from garth.cli import main
def test_help_flag(monkeypatch, capsys):
# -h should print help and exit with code 0
monkeypatch.setattr(sys, "argv", ["garth", "-h"])
with pytest.raises(SystemExit) as excinfo:
main()
assert excinfo.value.code... | out.lower() | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | v2_extractor_at_anchor |
matin/garth | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | train | train | tests/test_cli.py | test_help_flag | pytest.raises | variable | 13 | import builtins
import getpass
import sys
import pytest
from garth.cli import main
def test_help_flag(monkeypatch, capsys):
# -h should print help and exit with code 0
monkeypatch.setattr(sys, "argv", ["garth", "-h"])
with pytest.raises( | SystemExit) | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | v2_extractor_at_anchor |
matin/garth | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | train | train | tests/test_http.py | test_configure_retry | assert | numeric_literal | 14 | import tempfile
import time
from typing import Any, cast
import pytest
from requests.adapters import HTTPAdapter
from garth.auth_tokens import OAuth1Token, OAuth2Token
from garth.exc import GarthHTTPError
from garth.http import Client
def test_configure_retry(client: Client):
assert client.retries == | 3 | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | v2_extractor_at_anchor |
matin/garth | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | train | train | tests/test_http.py | test_connectapi | assert | numeric_literal | 23 | import tempfile
import time
from typing import Any, cast
import pytest
from requests.adapters import HTTPAdapter
from garth.auth_tokens import OAuth1Token, OAuth2Token
from garth.exc import GarthHTTPError
from garth.http import Client
@pytest.mark.vcr
def test_connectapi(authed_client: Client):
stress = cast(
... | 1 | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | v2_extractor_at_anchor |
matin/garth | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | train | train | tests/test_http.py | test_configure_proxies | assert | collection | 14 | import tempfile
import time
from typing import Any, cast
import pytest
from requests.adapters import HTTPAdapter
from garth.auth_tokens import OAuth1Token, OAuth2Token
from garth.exc import GarthHTTPError
from garth.http import Client
def test_configure_proxies(client: Client):
assert client.sess.proxies == | {} | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | v2_extractor_at_anchor |
matin/garth | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | train | train | tests/test_http.py | test_configure_timeout | assert | numeric_literal | 14 | import tempfile
import time
from typing import Any, cast
import pytest
from requests.adapters import HTTPAdapter
from garth.auth_tokens import OAuth1Token, OAuth2Token
from garth.exc import GarthHTTPError
from garth.http import Client
def test_configure_timeout(client: Client):
assert client.timeout == | 10 | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | v2_extractor_at_anchor |
matin/garth | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | train | train | tests/test_http.py | test_configure_timeout | assert | numeric_literal | 16 | import tempfile
import time
from typing import Any, cast
import pytest
from requests.adapters import HTTPAdapter
from garth.auth_tokens import OAuth1Token, OAuth2Token
from garth.exc import GarthHTTPError
from garth.http import Client
def test_configure_timeout(client: Client):
assert client.timeout == 10
cl... | 99 | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | v2_extractor_at_anchor |
matin/garth | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | train | train | tests/test_http.py | test_configure_backoff_factor | assert | numeric_literal | 14 | import tempfile
import time
from typing import Any, cast
import pytest
from requests.adapters import HTTPAdapter
from garth.auth_tokens import OAuth1Token, OAuth2Token
from garth.exc import GarthHTTPError
from garth.http import Client
def test_configure_backoff_factor(client: Client):
assert client.backoff_fact... | 0.5 | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | v2_extractor_at_anchor |
matin/garth | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | train | train | tests/test_http.py | test_configure_oauth2_token | assert | none_literal | 14 | import tempfile
import time
from typing import Any, cast
import pytest
from requests.adapters import HTTPAdapter
from garth.auth_tokens import OAuth1Token, OAuth2Token
from garth.exc import GarthHTTPError
from garth.http import Client
def test_configure_oauth2_token(client: Client, oauth2_token: OAuth2Token):
a... | None | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | v2_extractor_at_anchor |
matin/garth | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | train | train | tests/test_http.py | test_configure_ssl_verify | assert | bool_literal | 14 | import tempfile
import time
from typing import Any, cast
import pytest
from requests.adapters import HTTPAdapter
from garth.auth_tokens import OAuth1Token, OAuth2Token
from garth.exc import GarthHTTPError
from garth.http import Client
def test_configure_ssl_verify(client: Client):
assert client.sess.verify is | True | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | v2_extractor_at_anchor |
matin/garth | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | train | train | tests/test_http.py | test_configure_backoff_factor | assert | numeric_literal | 20 | import tempfile
import time
from typing import Any, cast
import pytest
from requests.adapters import HTTPAdapter
from garth.auth_tokens import OAuth1Token, OAuth2Token
from garth.exc import GarthHTTPError
from garth.http import Client
def test_configure_backoff_factor(client: Client):
assert client.backoff_facto... | 0.99 | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | v2_extractor_at_anchor |
matin/garth | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | train | train | tests/test_sso.py | test_set_expirations | assert | numeric_literal | 13 | import time
import pytest
from garth import sso
from garth.auth_tokens import OAuth1Token, OAuth2Token
from garth.exc import GarthException, GarthHTTPError
from garth.http import Client
def test_set_expirations(oauth2_token_dict: dict):
token = sso.set_expirations(oauth2_token_dict)
assert ( | 1 | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | v2_extractor_at_anchor |
matin/garth | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | train | train | tests/test_sso.py | test_get_csrf_token | assert | string_literal | 22 | import time
import pytest
from garth import sso
from garth.auth_tokens import OAuth1Token, OAuth2Token
from garth.exc import GarthException, GarthHTTPError
from garth.http import Client
def test_get_csrf_token():
html = """
<html>
<head>
</head>
<body>
<h1>Success</h1>
<input name="_csrf"... | "foo" | 26b5e2eefdd26b5e5b9bb4b48260a702521cc976 | 71 | v2_extractor_at_anchor |
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