repo_id stringclasses 409
values | prefix large_stringlengths 34 36.3k | target large_stringlengths 1 498 | assertion_type stringclasses 31
values | difficulty stringclasses 8
values | test_file stringlengths 10 121 | test_function stringlengths 1 104 | test_class stringlengths 0 51 | lineno int32 2 11.3k | commit_idx int32 |
|---|---|---|---|---|---|---|---|---|---|
aiogram/aiogram | import datetime
from typing import Any
from aiogram.handlers import ChatMemberHandler
from aiogram.types import Chat, ChatMemberMember, ChatMemberUpdated, User
class MyHandler(ChatMemberHandler):
async def handle(self) -> Any:
assert self.event == event
assert self... | self.event.from_user | assert | complex_expr | tests/test_handler/test_chat_member.py | handle | MyHandler | 21 | null |
aiogram/aiogram | import datetime
import functools
from typing import Any, NoReturn
import pytest
from pydantic import BaseModel
from aiogram.dispatcher.event.bases import UNHANDLED, SkipHandler
from aiogram.dispatcher.event.handler import HandlerObject
from aiogram.dispatcher.event.telegram import TelegramEventObserver
from aiogram.d... | f | assert | variable | tests/test_dispatcher/test_event/test_telegram.py | test_register | TestTelegramEventObserver | 73 | null |
aiogram/aiogram | from aiogram.methods import AnswerInlineQuery
from aiogram.types import InlineQuery, User
class TestInlineQuery:
def test_answer_alias(self):
inline_query = InlineQuery(
id="id",
from_user=User(id=42, is_bot=False, first_name="name"),
query="query",
offset=""... | value | assert | variable | tests/test_api/test_types/test_inline_query.py | test_answer_alias | TestInlineQuery | 28 | null |
aiogram/aiogram | from unittest.mock import AsyncMock, MagicMock, patch
import pytest
from aiogram.exceptions import CallbackAnswerException
from aiogram.methods import AnswerCallbackQuery
from aiogram.types import CallbackQuery, User
from aiogram.utils.callback_answer import CallbackAnswer, CallbackAnswerMiddleware
class TestCallbac... | callback_answer.text | assert | complex_expr | tests/test_utils/test_callback_answer.py | test_answer | TestCallbackAnswerMiddleware | 173 | null |
aiogram/aiogram | import pytest
from aiogram.dispatcher.flags import Flag, FlagDecorator, FlagGenerator
def flag_fixture() -> Flag:
return Flag("test", True)
def flag_decorator_fixture(flag: Flag) -> FlagDecorator:
return FlagDecorator(flag)
def flag_flag_generator() -> FlagGenerator:
return FlagGenerator()
class TestFl... | generator.foo | assert | complex_expr | tests/test_flags/test_decorator.py | test_getattr | TestFlagGenerator | 59 | null |
aiogram/aiogram | import pytest
from aiogram.types import Video, VideoQuality
def video_quality():
return VideoQuality(
file_id="abc123",
file_unique_id="unique123",
width=1920,
height=1080,
codec="h264",
)
class TestVideoQuality:
def test_instantiation(self, video_quality: VideoQua... | "h264" | assert | string_literal | tests/test_api/test_types/test_video_quality.py | test_instantiation | TestVideoQuality | 23 | null |
aiogram/aiogram | from typing import Any
from aiogram.handlers import InlineQueryHandler
from aiogram.types import InlineQuery, User
class MyHandler(InlineQueryHandler):
async def handle(self) -> Any:
assert self.event == event
assert self.from_user == | self.event.from_user | assert | complex_expr | tests/test_handler/test_inline_query.py | handle | MyHandler | 19 | null |
aiogram/aiogram | import pytest
from aiogram.filters.callback_data import CallbackData
from aiogram.types import (
InlineKeyboardButton,
InlineKeyboardMarkup,
KeyboardButton,
ReplyKeyboardMarkup,
)
from aiogram.utils.keyboard import (
InlineKeyboardBuilder,
KeyboardBuilder,
ReplyKeyboardBuilder,
)
class Tes... | count | assert | variable | tests/test_utils/test_keyboard.py | test_add | TestKeyboardBuilder | 168 | null |
aiogram/aiogram | from typing import Any
from aiogram.handlers import PreCheckoutQueryHandler
from aiogram.types import PreCheckoutQuery, User
class MyHandler(PreCheckoutQueryHandler):
async def handle(self) -> Any:
assert self.event == | event | assert | variable | tests/test_handler/test_pre_checkout_query.py | handle | MyHandler | 19 | null |
aiogram/aiogram | from copy import copy
from inspect import isclass
import pytest
from aiogram.dispatcher.event.handler import FilterObject
from aiogram.filters import StateFilter
from aiogram.fsm.state import State, StatesGroup
from aiogram.types import Update
class TestStateFilter:
async def test_state_copy(self):
clas... | State() | assert | func_call | tests/test_filters/test_state.py | test_state_copy | TestStateFilter | 61 | null |
aiogram/aiogram | import asyncio
import time
from datetime import datetime
from unittest.mock import AsyncMock, patch
import pytest
from aiogram import Bot, flags
from aiogram.dispatcher.event.handler import HandlerObject
from aiogram.types import Chat, Message, User
from aiogram.utils.chat_action import ChatActionMiddleware, ChatActi... | bot | assert | variable | tests/test_utils/test_chat_action.py | test_factory | TestChatActionSender | 46 | null |
aiogram/aiogram | from typing import Any
from aiogram.handlers import PollHandler
from aiogram.types import Poll, PollOption
class MyHandler(PollHandler):
async def handle(self) -> Any:
assert self.event == event
assert self.question == self.event.question
assert sel... | self.event.options | assert | complex_expr | tests/test_handler/test_poll.py | handle | MyHandler | 25 | null |
aiogram/aiogram | from aiogram.client.context_controller import BotContextController
from tests.mocked_bot import MockedBot
class TestBotContextController:
def test_via_model_validate(self, bot: MockedBot):
my_model = MyModel.model_validate({"id": 1}, context={"bot": bot})
assert my_model.id == 1
assert my_... | bot | assert | variable | tests/test_api/test_client/test_context_controller.py | test_via_model_validate | TestBotContextController | 13 | null |
aiogram/aiogram | from aiogram.methods import BanChatSenderChat
from tests.mocked_bot import MockedBot
class TestBanChatSenderChat:
async def test_bot_method(self, bot: MockedBot):
prepare_result = bot.add_result_for(BanChatSenderChat, ok=True, result=True)
response: bool = await bot.ban_chat_sender_chat(
... | prepare_result.result | assert | complex_expr | tests/test_api/test_methods/test_ban_chat_sender_chat.py | test_bot_method | TestBanChatSenderChat | 14 | null |
aiogram/aiogram | import asyncio
from collections.abc import AsyncGenerator, AsyncIterable
from typing import (
Any,
AsyncContextManager,
)
from unittest.mock import AsyncMock, patch
import aiohttp_socks
import pytest
from aiohttp import ClientError
from aresponses import ResponsesMockServer
from aiogram import Bot
from aiogra... | None | assert | none_literal | tests/test_api/test_client/test_session/test_aiohttp_session.py | test_create_session | TestAiohttpSession | 32 | null |
aiogram/aiogram | import pytest
from aiogram.dispatcher.event.bases import UNHANDLED, SkipHandler, skip
from aiogram.dispatcher.event.telegram import TelegramEventObserver
from aiogram.dispatcher.router import Router
class TestRouter:
def test_including_routers(self):
router1 = Router()
router2 = Router()
r... | [] | assert | collection | tests/test_dispatcher/test_router.py | test_including_routers | TestRouter | 35 | null |
aiogram/aiogram | from aiogram.methods import AnswerCallbackQuery
from aiogram.types import CallbackQuery, InaccessibleMessage, Message, User
class TestCallbackQuery:
def test_answer_alias(self):
callback_query = CallbackQuery(
id="id", from_user=User(id=42, is_bot=False, first_name="name"), chat_instance="chat"... | value | assert | variable | tests/test_api/test_types/test_callback_query.py | test_answer_alias | TestCallbackQuery | 19 | null |
aiogram/aiogram | from aresponses import ResponsesMockServer
from aiogram import Bot
from aiogram.types import BufferedInputFile, FSInputFile, InputFile, URLInputFile
from tests.mocked_bot import MockedBot
class TestInputFile:
def test_fs_input_file(self):
file = FSInputFile(__file__)
assert isinstance(file, Input... | 0 | assert | numeric_literal | tests/test_api/test_types/test_input_file.py | test_fs_input_file | TestInputFile | 16 | null |
aiogram/aiogram | import sys
import pytest
from aiogram.client.default import Default, DefaultBotProperties
from aiogram.enums import ParseMode
from aiogram.types import LinkPreviewOptions
class TestDefault:
def test_init(self):
default = Default("test")
assert default._name == | "test" | assert | string_literal | tests/test_api/test_client/test_default.py | test_init | TestDefault | 13 | null |
aiogram/aiogram | from aiogram.methods import DeleteBusinessMessages
from tests.mocked_bot import MockedBot
class TestDeleteBusinessMessages:
async def test_bot_method(self, bot: MockedBot):
prepare_result = bot.add_result_for(DeleteBusinessMessages, ok=True, result=True)
response: bool = await bot.delete_business_... | prepare_result.result | assert | complex_expr | tests/test_api/test_methods/test_delete_business_messages.py | test_bot_method | TestDeleteBusinessMessages | 13 | null |
aiogram/aiogram | import datetime
import re
import pytest
from aiogram import F
from aiogram.filters import Command, CommandObject
from aiogram.filters.command import CommandStart
from aiogram.types import BotCommand, Chat, Message, User
from tests.mocked_bot import MockedBot
class TestCommandObject:
def test_update_handler_flag... | 2 | assert | numeric_literal | tests/test_filters/test_command.py | test_update_handler_flags | TestCommandObject | 227 | null |
aiogram/aiogram | import datetime
import json
from collections.abc import AsyncGenerator
from typing import Any, AsyncContextManager
from unittest.mock import AsyncMock, patch
import pytest
from pytz import utc
from aiogram import Bot
from aiogram.client.default import Default, DefaultBotProperties
from aiogram.client.session.base imp... | api | assert | variable | tests/test_api/test_client/test_session/test_base_session.py | test_init_custom_api | TestBaseSession | 92 | null |
aiogram/aiogram | import datetime
import functools
from typing import Any, NoReturn
import pytest
from pydantic import BaseModel
from aiogram.dispatcher.event.bases import UNHANDLED, SkipHandler
from aiogram.dispatcher.event.handler import HandlerObject
from aiogram.dispatcher.event.telegram import TelegramEventObserver
from aiogram.d... | index + 1 | assert | complex_expr | tests/test_dispatcher/test_event/test_telegram.py | test_register_filters_via_decorator | TestTelegramEventObserver | 135 | null |
aiogram/aiogram | from typing import Any
from aiogram.handlers import InlineQueryHandler
from aiogram.types import InlineQuery, User
class MyHandler(InlineQueryHandler):
async def handle(self) -> Any:
assert self.event == event
assert self.from_user == self.event.from_user
... | self.event.query | assert | complex_expr | tests/test_handler/test_inline_query.py | handle | MyHandler | 20 | null |
aiogram/aiogram | from unittest.mock import patch
import pytest
from aiogram import F
from aiogram.dispatcher.event.handler import HandlerObject
from aiogram.dispatcher.flags import (
check_flags,
extract_flags,
extract_flags_from_object,
get_flag,
)
class TestGetters:
def test_extract_flags_from_object(self):
... | func.aiogram_flag | assert | complex_expr | tests/test_flags/test_getter.py | test_extract_flags_from_object | TestGetters | 23 | null |
aiogram/aiogram | from aiogram.methods import BanChatMember
from tests.mocked_bot import MockedBot
class TestKickChatMember:
async def test_bot_method(self, bot: MockedBot):
prepare_result = bot.add_result_for(BanChatMember, ok=True, result=True)
response: bool = await bot.ban_chat_member(chat_id=-42, user_id=42)
... | prepare_result.result | assert | complex_expr | tests/test_api/test_methods/test_ban_chat_member.py | test_bot_method | TestKickChatMember | 11 | null |
aiogram/aiogram | from typing import Any
from aiogram.handlers import CallbackQueryHandler
from aiogram.types import CallbackQuery, User
class MyHandler(CallbackQueryHandler):
async def handle(self) -> Any:
assert self.event == event
assert self.from_user == self.event.from_user
... | self.message | assert | complex_expr | tests/test_handler/test_callback_query.py | handle | MyHandler | 21 | null |
aiogram/aiogram | import asyncio
import time
from datetime import datetime
from unittest.mock import AsyncMock, patch
import pytest
from aiogram import Bot, flags
from aiogram.dispatcher.event.handler import HandlerObject
from aiogram.types import Chat, Message, User
from aiogram.utils.chat_action import ChatActionMiddleware, ChatActi... | "OK" | assert | string_literal | tests/test_utils/test_chat_action.py | test_call_default | TestChatActionMiddleware | 118 | null |
aiogram/aiogram | from typing import Any
from aiogram.handlers import CallbackQueryHandler
from aiogram.types import CallbackQuery, User
class MyHandler(CallbackQueryHandler):
async def handle(self) -> Any:
assert self.event == | event | assert | variable | tests/test_handler/test_callback_query.py | handle | MyHandler | 18 | null |
aiogram/aiogram | from typing import Any
import pytest
from aiogram.methods import (
SendAnimation,
SendAudio,
SendContact,
SendDice,
SendDocument,
SendGame,
SendInvoice,
SendLocation,
SendMediaGroup,
SendMessage,
SendPaidMedia,
SendPhoto,
SendPoll,
SendSticker,
SendVenue,
... | message.chat.id | assert | complex_expr | tests/test_api/test_types/test_inaccessible_message.py | test_as_reply_parameters | TestMessage | 47 | null |
aiogram/aiogram | import pytest
from pymongo.errors import PyMongoError
from aiogram.fsm.state import State
from aiogram.fsm.storage.pymongo import PyMongoStorage, StorageKey
from tests.conftest import CHAT_ID, USER_ID
PREFIX = "fsm"
class TestStateAndDataDoNotAffectEachOther:
async def test_state_and_data_do_not_affect_each_othe... | "test" | assert | string_literal | tests/test_fsm/storage/test_pymongo.py | test_state_and_data_do_not_affect_each_other_while_getting | TestStateAndDataDoNotAffectEachOther | 111 | null |
massquantity/LibRecommender | import pytest
from libreco.bases import Base
def test_base(prepare_pure_data):
_, train_data, _, data_info = prepare_pure_data
with pytest.raises( | ValueError) | pytest.raises | variable | tests/models/test_base.py | test_base | 29 | null | |
massquantity/LibRecommender | 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
... | ValueError) | pytest.raises | variable | tests/test_similarities.py | test_similarities | 58 | null | |
massquantity/LibRecommender | 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... | ValueError) | pytest.raises | variable | tests/test_knn_embed.py | test_get_embeddings | 108 | null | |
massquantity/LibRecommender | import sys
import pytest
import tensorflow as tf
from numpy.testing import assert_array_equal
from libreco.algorithms import YouTubeRanking
from tests.models.utils_tf import ptest_tf_variables
from tests.utils_data import set_ranking_labels
from tests.utils_metrics import get_metrics
from tests.utils_multi_sparse_mod... | ValueError) | pytest.raises | variable | tests/models/test_youtube_ranking.py | test_youtube_ranking | 70 | null | |
massquantity/LibRecommender | import sys
import pytest
import tensorflow as tf
from numpy.testing import assert_array_equal
from libreco.algorithms import TwoTower
from tests.models.utils_tf import ptest_tf_variables
from tests.utils_data import set_ranking_labels
from tests.utils_metrics import get_metrics
from tests.utils_pred import ptest_pred... | ValueError) | pytest.raises | variable | tests/models/test_two_tower.py | test_two_tower | 70 | null | |
massquantity/LibRecommender | import subprocess
import pytest
from libreco.bases import CfBase
from libserving.serialization import knn2redis, save_knn
from tests.utils_data import SAVE_PATH
@pytest.mark.parametrize("knn_model", ["UserCF", "ItemCF"], indirect=True)
def test_knn_serving(knn_model, session, close_server):
assert isinstance(knn... | 3 | assert | numeric_literal | tests/serving/test_knn_serving.py | test_knn_serving | 32 | null | |
massquantity/LibRecommender | 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,
rms_norm,
shared_dense,
tf_dense,
tf_rnn,
)
from libreco.layers.activation ... | labels) | assert_* | variable | tests/test_tf_layers.py | test_layer_norm | 150 | null | |
massquantity/LibRecommender | 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... | ValueError) | pytest.raises | variable | tests/test_data.py | test_dataset_pure | 95 | null | |
massquantity/LibRecommender | import sys
import pytest
import tensorflow as tf
from libreco.algorithms import FM
from tests.models.utils_tf import ptest_tf_variables
from tests.utils_data import SAVE_PATH, remove_path, set_ranking_labels
from tests.utils_metrics import get_metrics
from tests.utils_multi_sparse_models import fit_multi_sparse
from ... | ValueError) | pytest.raises | variable | tests/models/test_fm.py | test_fm | 65 | null | |
massquantity/LibRecommender | import sys
from pathlib import Path
import pandas as pd
import pytest
from libreco.algorithms import RsItemCF, RsUserCF
from libreco.data import DataInfo, DatasetPure, split_by_ratio_chrono
from libreco.evaluation import evaluate
from tests.utils_data import SAVE_PATH, remove_path
from tests.utils_pred import ptest_p... | eval_result["roc_auc"] | assert | complex_expr | tests/retrain/test_rs_cf_retrain.py | test_rs_cf_retrain | 134 | null | |
massquantity/LibRecommender | import os
import sys
from pathlib import Path
import pandas as pd
import pytest
import tensorflow as tf
from numpy.testing import assert_array_equal
from libreco.algorithms import DIN
from libreco.data import DatasetFeat, split_by_ratio_chrono
from tests.models.utils_tf import ptest_tf_variables
from tests.utils_data... | ValueError) | pytest.raises | variable | tests/models/test_din.py | test_din | 73 | null | |
massquantity/LibRecommender | import sys
import pytest
import tensorflow as tf
from libreco.algorithms import LightGCN
from tests.utils_data import remove_path, set_ranking_labels
from tests.utils_metrics import get_metrics
from tests.utils_pred import ptest_preds
from tests.utils_reco import ptest_recommends
from tests.utils_save_load import sav... | AssertionError) | pytest.raises | variable | tests/models/test_lightgcn.py | test_lightgcn | 75 | null | |
massquantity/LibRecommender | import json
import os
import numpy as np
import pytest
from tensorflow.core.protobuf.meta_graph_pb2 import MetaGraphDef
from libreco.bases import CfBase, TfBase
from libreco.tfops import tf
from libserving.serialization import (
embed2redis,
knn2redis,
online2redis,
save_embed,
save_knn,
save... | m["model_name"] | assert | complex_expr | tests/serving/test_serialization.py | check_model_name | 104 | null | |
massquantity/LibRecommender | 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]) | assert_* | collection | tests/test_rank_reco.py | test_rank_reco | 39 | null | |
massquantity/LibRecommender | import sys
import pytest
import tensorflow as tf
from libreco.algorithms import AutoInt
from tests.models.utils_tf import ptest_tf_variables
from tests.utils_metrics import get_metrics
from tests.utils_multi_sparse_models import fit_multi_sparse
from tests.utils_pred import ptest_preds
from tests.utils_reco import pt... | ValueError) | pytest.raises | variable | tests/models/test_autoint.py | test_autoint | 52 | null | |
massquantity/LibRecommender | import sys
import pytest
import tensorflow as tf
from libreco.algorithms import SVDpp
from libreco.data import DatasetPure
from tests.models.utils_tf import ptest_tf_variables
from tests.utils_data import SAVE_PATH, set_ranking_labels
from tests.utils_metrics import get_metrics
from tests.utils_pred import ptest_pred... | ValueError) | pytest.raises | variable | tests/models/test_svdpp.py | test_svdpp | 59 | null | |
massquantity/LibRecommender | 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) | assert | collection | tests/test_collators.py | test_sparse_collator | 191 | null | |
massquantity/LibRecommender | import sys
import numpy as np
import pytest
import tensorflow as tf
from numpy.testing import assert_array_equal
from libreco.algorithms import SIM
from tests.models.utils_tf import ptest_tf_variables
from tests.utils_data import set_ranking_labels
from tests.utils_metrics import get_metrics
from tests.utils_multi_sp... | len(cold2) | assert | func_call | tests/models/test_sim.py | long_short_seq_ptest | 154 | null | |
massquantity/LibRecommender | 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... | 6 | assert | numeric_literal | tests/test_split_data.py | test_random_split | 51 | null | |
massquantity/LibRecommender | import pytest
import tensorflow as tf
from libreco.algorithms import Transformer
from tests.models.utils_tf import ptest_tf_variables
from tests.utils_metrics import get_metrics
from tests.utils_multi_sparse_models import fit_multi_sparse
from tests.utils_pred import ptest_preds
from tests.utils_reco import ptest_dyn_... | ValueError) | pytest.raises | variable | tests/models/test_transformer.py | test_transformer | 47 | null | |
massquantity/LibRecommender | 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) | assert | func_call | tests/utils_reco.py | ptest_dyn_recommends | 119 | null | |
massquantity/LibRecommender | 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 | assert | numeric_literal | tests/test_collators.py | test_pairwise_collator | 344 | null | |
massquantity/LibRecommender | 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 | assert | numeric_literal | tests/test_data.py | test_data_info | 149 | null | |
massquantity/LibRecommender | import subprocess
from pathlib import Path
from libserving.serialization import embed2redis, save_embed, save_faiss_index
from tests.utils_data import SAVE_PATH, remove_path
def test_embed_serving(embed_model, session, close_server):
save_embed(SAVE_PATH, embed_model)
embed2redis(SAVE_PATH)
faiss_path = s... | 1 | assert | numeric_literal | tests/serving/test_embed_serving.py | test_embed_serving | 26 | null | |
massquantity/LibRecommender | import sys
import numpy as np
import pandas as pd
import pytest
from libreco.algorithms import Swing
from libreco.data import DatasetPure
from tests.utils_data import SAVE_PATH, remove_path, set_ranking_labels
from tests.utils_metrics import get_metrics
from tests.utils_pred import ptest_preds
from tests.utils_reco i... | ValueError) | pytest.raises | variable | tests/models/test_swing.py | test_swing | 48 | null | |
massquantity/LibRecommender | 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... | 0 | assert | numeric_literal | tests/test_split_data.py | test_random_split | 64 | null | |
massquantity/LibRecommender | 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... | negatives[1][:4] | assert | complex_expr | tests/test_collators.py | test_negatives_exceed_sampling_tolerance | 413 | null | |
massquantity/LibRecommender | import json
import os
import numpy as np
import pytest
from tensorflow.core.protobuf.meta_graph_pb2 import MetaGraphDef
from libreco.bases import CfBase, TfBase
from libreco.tfops import tf
from libserving.serialization import (
embed2redis,
knn2redis,
online2redis,
save_embed,
save_knn,
save... | data_info.n_items | assert | complex_expr | tests/serving/test_serialization.py | check_features | 159 | null | |
massquantity/LibRecommender | from pathlib import Path
import pandas as pd
import pytest
import tensorflow as tf
from libreco.algorithms import TwoTower
from libreco.data import DataInfo, DatasetFeat, split_by_ratio_chrono
from libreco.evaluation import evaluate
from tests.utils_data import SAVE_PATH, remove_path
from tests.utils_pred import ptes... | eval_result["roc_auc"] | assert | complex_expr | tests/retrain/test_two_tower_retrain.py | test_two_tower_retrain | 177 | null | |
massquantity/LibRecommender | 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" | assert | string_literal | tests/test_knn_embed.py | ptest_knn | 68 | null | |
massquantity/LibRecommender | import sys
from pathlib import Path
import numpy as np
import pandas as pd
import pytest
from libreco.algorithms import Swing
from libreco.data import DataInfo, DatasetPure, split_by_ratio_chrono
from libreco.evaluation import evaluate
from tests.utils_data import SAVE_PATH, remove_path
from tests.utils_reco import p... | 0 | assert | numeric_literal | tests/retrain/test_rs_swing_retrain.py | ptest_preds | 174 | null | |
massquantity/LibRecommender | import sys
import pytest
import tensorflow as tf
from numpy.testing import assert_array_equal
from libreco.algorithms import RNN4Rec
from tests.models.utils_tf import ptest_tf_variables
from tests.utils_data import set_ranking_labels
from tests.utils_metrics import get_metrics
from tests.utils_pred import ptest_preds... | ValueError) | pytest.raises | variable | tests/models/test_rnn4rec.py | test_rnn4rec | 70 | null | |
massquantity/LibRecommender | 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... | ValueError) | pytest.raises | variable | tests/test_initializers.py | test_initializers | 41 | null | |
massquantity/LibRecommender | import numpy as np
import pytest
from libreco.recommendation import rank_recommendations
def test_rank_random():
user_ids = [1, 2]
# fmt: off
preds = np.array([-0.1, -1e8, 0, 0.1, 0.01, 1e8, -0.01, 1e7, 0.1, 0.01]) # inf probs
n_rec = 2
n_items = 5
consumed = {1: [3, 4], 2: [4]}
rec_item... | score[i] | assert | complex_expr | tests/test_rank_reco.py | test_rank_random | 143 | null | |
massquantity/LibRecommender | import sys
import pytest
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 con... | [4, 5] | assert | collection | tests/test_consumed.py | test_merge_remove_duplicates | 54 | null | |
massquantity/LibRecommender | 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... | RuntimeError) | pytest.raises | variable | tests/test_data.py | test_dataset_pure | 99 | null | |
massquantity/LibRecommender | 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... | sparse_len | assert | variable | tests/test_collators.py | test_pointwise_collator | 261 | null | |
massquantity/LibRecommender | import sys
import pytest
import tensorflow as tf
from libreco.algorithms import DeepFM
from tests.models.utils_tf import ptest_tf_variables
from tests.utils_data import set_ranking_labels
from tests.utils_metrics import get_metrics
from tests.utils_multi_sparse_models import fit_multi_sparse
from tests.utils_pred imp... | ValueError) | pytest.raises | variable | tests/models/test_deepfm.py | test_deepfm | 64 | null | |
massquantity/LibRecommender | 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) | assert | collection | tests/test_collators.py | test_normal_collator | 109 | null | |
massquantity/LibRecommender | 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... | [1, 2, 8] | assert | collection | tests/test_data.py | test_transformed_evalset | 206 | null | |
massquantity/LibRecommender | import pytest
import tensorflow as tf
from numpy.testing import assert_array_equal
from libreco.algorithms import YouTubeRetrieval
from tests.models.utils_tf import ptest_tf_variables
from tests.utils_data import SAVE_PATH, remove_path, set_ranking_labels
from tests.utils_metrics import get_metrics
from tests.utils_pr... | ValueError) | pytest.raises | variable | tests/models/test_youtube_retrieval.py | test_youtube_retrieval | 96 | null | |
massquantity/LibRecommender | import json
import os
import numpy as np
import pytest
from tensorflow.core.protobuf.meta_graph_pb2 import MetaGraphDef
from libreco.bases import CfBase, TfBase
from libreco.tfops import tf
from libserving.serialization import (
embed2redis,
knn2redis,
online2redis,
save_embed,
save_knn,
save... | user2id | assert | variable | tests/serving/test_serialization.py | check_id_mapping | 121 | null | |
massquantity/LibRecommender | 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... | 2 | assert | numeric_literal | tests/test_data.py | test_dataset_feat | 112 | null | |
massquantity/LibRecommender | from pathlib import Path
import pandas as pd
import pytest
import tensorflow as tf
from libreco.algorithms import DIN
from libreco.data import DataInfo, DatasetFeat, split_by_ratio_chrono
from libreco.evaluation import evaluate
from tests.utils_data import SAVE_PATH, remove_path
from tests.utils_pred import ptest_pre... | eval_result["roc_auc"] | assert | complex_expr | tests/retrain/test_tfmodel_retrain_feat.py | test_tfmodel_retrain_feat | 159 | null | |
massquantity/LibRecommender | import os
import sys
from pathlib import Path
import pandas as pd
import pytest
import tensorflow as tf
from numpy.testing import assert_array_equal
from libreco.algorithms import DIN
from libreco.data import DatasetFeat, split_by_ratio_chrono
from tests.models.utils_tf import ptest_tf_variables
from tests.utils_data... | loaded_dyn_rec) | assert_* | variable | tests/models/test_din.py | test_din_multi_sparse | 130 | null | |
massquantity/LibRecommender | 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,) | assert | collection | tests/test_collators.py | test_normal_collator | 114 | null | |
massquantity/LibRecommender | import sys
import pytest
from libreco.data.consumed import _fill_empty, _merge_dedup, interaction_consumed
@pytest.mark.skipif(
sys.version_info[:2] < (3, 7),
reason="Rust implementation only supports Python >= 3.7.",
)
def test_remove_consecutive_duplicates():
user_indices = [1, 1, 1, 2, 2, 1, 2, 3, 2, ... | [1, 2] | assert | collection | tests/test_consumed.py | test_remove_consecutive_duplicates | 24 | null | |
massquantity/LibRecommender | import sys
import pytest
import tensorflow as tf
from libreco.algorithms import BPR
from tests.models.utils_tf import ptest_tf_variables
from tests.utils_data import remove_path
from tests.utils_metrics import get_metrics
from tests.utils_pred import ptest_preds
from tests.utils_reco import ptest_recommends
from test... | RuntimeError) | pytest.raises | variable | tests/models/test_bpr.py | test_bpr | 111 | null | |
massquantity/LibRecommender | 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) | assert | func_call | tests/test_multiprocessing_seeds.py | test_multiprocessing_seeds | 91 | null | |
massquantity/LibRecommender | from pathlib import Path
import pandas as pd
import tensorflow as tf
from libreco.algorithms import GraphSage
from libreco.data import DataInfo, DatasetFeat, split_by_ratio_chrono
from libreco.evaluation import evaluate
from tests.utils_data import SAVE_PATH, remove_path
from tests.utils_pred import ptest_preds
from ... | eval_result["roc_auc"] | assert | complex_expr | tests/retrain/test_thmodel_retrain_feat.py | test_torchmodel_retrain_feat | 173 | null | |
massquantity/LibRecommender | import itertools
import numpy as np
import pytest
from libreco.utils.initializers import (
he_init,
truncated_normal,
variance_scaling,
xavier_init,
)
def variables_in_range(variables, mean, std):
for v in itertools.chain.from_iterable(variables):
assert (mean - 3 * std) < | v | assert | variable | tests/test_initializers.py | variables_in_range | 47 | null | |
massquantity/LibRecommender | import sys
import pytest
import tensorflow as tf
from libreco.algorithms import SVD
from tests.models.utils_tf import ptest_tf_variables
from tests.utils_data import set_ranking_labels
from tests.utils_metrics import get_metrics
from tests.utils_pred import ptest_preds
from tests.utils_reco import ptest_recommends
fr... | ValueError) | pytest.raises | variable | tests/models/test_svd.py | test_svd | 57 | null | |
massquantity/LibRecommender | import pytest
from libreco.algorithms import ALS
from libreco.algorithms.als import least_squares, least_squares_cg
from libreco.evaluation import evaluate
from tests.utils_data import SAVE_PATH, remove_path, set_ranking_labels
from tests.utils_metrics import get_metrics
from tests.utils_pred import ptest_preds
from t... | TypeError) | pytest.raises | variable | tests/models/test_als.py | test_als | 78 | null | |
massquantity/LibRecommender | 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 | assert | none_literal | tests/test_dgl.py | test_dgl | 28 | null | |
massquantity/LibRecommender | 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]) | assert_* | collection | tests/test_feature.py | test_multi_sparse_indices | 297 | null | |
massquantity/LibRecommender | import sys
import pytest
import tensorflow as tf
from numpy.testing import assert_array_equal
from libreco.algorithms import RNN4Rec
from tests.models.utils_tf import ptest_tf_variables
from tests.utils_data import set_ranking_labels
from tests.utils_metrics import get_metrics
from tests.utils_pred import ptest_preds... | RuntimeError) | pytest.raises | variable | tests/models/test_rnn4rec.py | test_rnn4rec | 123 | null | |
massquantity/LibRecommender | 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) | assert | func_call | tests/utils_reco.py | ptest_dyn_recommends | 124 | null | |
massquantity/LibRecommender | import sys
import pytest
import tensorflow as tf
from libreco.algorithms import WideDeep
from tests.models.utils_tf import ptest_tf_variables
from tests.utils_data import set_ranking_labels
from tests.utils_metrics import get_metrics
from tests.utils_multi_sparse_models import fit_multi_sparse
from tests.utils_pred i... | ValueError) | pytest.raises | variable | tests/models/test_wide_deep.py | test_wide_deep | 70 | null | |
massquantity/LibRecommender | import sys
import pytest
import tensorflow as tf
from numpy.testing import assert_array_equal
from libreco.algorithms import RNN4Rec
from tests.models.utils_tf import ptest_tf_variables
from tests.utils_data import set_ranking_labels
from tests.utils_metrics import get_metrics
from tests.utils_pred import ptest_preds... | AssertionError) | pytest.raises | variable | tests/models/test_rnn4rec.py | test_rnn4rec | 67 | null | |
massquantity/LibRecommender | 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... | 1 | assert | numeric_literal | tests/test_data.py | test_dataset_feat | 111 | null | |
massquantity/LibRecommender | import json
import os
import numpy as np
import pytest
from tensorflow.core.protobuf.meta_graph_pb2 import MetaGraphDef
from libreco.bases import CfBase, TfBase
from libreco.tfops import tf
from libserving.serialization import (
embed2redis,
knn2redis,
online2redis,
save_embed,
save_knn,
save... | id2item | assert | variable | tests/serving/test_serialization.py | check_id_mapping | 133 | null | |
massquantity/LibRecommender | import sys
import pytest
import tensorflow as tf
from libreco.algorithms import AutoInt
from tests.models.utils_tf import ptest_tf_variables
from tests.utils_metrics import get_metrics
from tests.utils_multi_sparse_models import fit_multi_sparse
from tests.utils_pred import ptest_preds
from tests.utils_reco import pt... | RuntimeError) | pytest.raises | variable | tests/models/test_autoint.py | test_autoint_multi_sparse | 98 | null | |
massquantity/LibRecommender | 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... | model.n_items | assert | complex_expr | tests/test_knn_embed.py | test_get_embeddings | 98 | null | |
massquantity/LibRecommender | import sys
import numpy as np
import pytest
import tensorflow as tf
from numpy.testing import assert_array_equal
from libreco.algorithms import SIM
from tests.models.utils_tf import ptest_tf_variables
from tests.utils_data import set_ranking_labels
from tests.utils_metrics import get_metrics
from tests.utils_multi_sp... | loaded_dyn_rec) | assert_* | variable | tests/models/test_sim.py | test_sim_multi_sparse | 130 | null | |
massquantity/LibRecommender | import numpy as np
from libreco.prediction import predict_data_with_feats
def ptest_preds(model, task, pd_data, with_feats):
user = pd_data.user.iloc[0]
item = pd_data.item.iloc[0]
pred = model.predict(user=user, item=item)
# prediction in range
if task == "rating":
assert 1 <= | pred | assert | variable | tests/utils_pred.py | ptest_preds | 12 | null | |
massquantity/LibRecommender | import sys
import pytest
import tensorflow as tf
from libreco.algorithms import NCF
from tests.models.utils_tf import ptest_tf_variables
from tests.utils_data import set_ranking_labels
from tests.utils_metrics import get_metrics
from tests.utils_pred import ptest_preds
from tests.utils_reco import ptest_recommends
fr... | AssertionError) | pytest.raises | variable | tests/models/test_ncf.py | test_ncf | 61 | null | |
massquantity/LibRecommender | 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,
rms_norm,
shared_dense,
tf_dense,
tf_rnn,
)
from libreco.layers.activation ... | (100, 9, 2) | assert | collection | tests/test_tf_layers.py | test_conv_layer | 100 | null | |
massquantity/LibRecommender | from pathlib import Path
import pandas as pd
from libreco.algorithms import NGCF
from libreco.data import DataInfo, DatasetPure, split_by_ratio_chrono
from libreco.evaluation import evaluate
from tests.utils_data import SAVE_PATH, remove_path
from tests.utils_pred import ptest_preds
from tests.utils_reco import ptest... | eval_result["roc_auc"] | assert | complex_expr | tests/retrain/test_thmodel_retrain_pure.py | test_torchmodel_retrain_pure | 134 | null | |
massquantity/LibRecommender | 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 (
... | dense_cols | assert | variable | tests/test_feature.py | test_sparse_indices | 171 | null |
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