def test_get_race_result_with_race_name_param(self):
"""Testing to get the DataFrame with word parameters
"""
params = {
netkeiba.url_params.PID: netkeiba.pid_list.RACE_LIST,
netkeiba.url_params.WORD: "有馬記念"
}
df = netkeiba.get_race_result(params)
assert not (df is None)
assert type(df) == pd.DataFrame
assert len(df) > 0
assert all(["有馬記念" in name for name in df["race_name"].to_list()])
def test_get_race_result_with_grade_param(self):
"""Testing to get the DataFrame with grade parameters
"""
params = {
netkeiba.url_params.PID: netkeiba.pid_list.RACE_LIST,
netkeiba.url_params.START_YEAR: 2019,
netkeiba.url_params.GRADE: ["G2"]
}
df = netkeiba.get_race_result(params)
assert not (df is None)
assert type(df) == pd.DataFrame
assert len(df) > 0
assert all(["2" in name for name in df["grade"].to_list()])
def test_get_race_result_with_track_param(self):
"""Testing to get the DataFrame with track parameters
"""
params = {
netkeiba.url_params.PID: netkeiba.pid_list.RACE_LIST,
netkeiba.url_params.START_YEAR: 2019,
netkeiba.url_params.TRACK: ["DIRT"]
}
df = netkeiba.get_race_result(params)
assert not (df is None)
assert type(df) == pd.DataFrame
assert len(df) > 0
assert all(["dirt" in name for name in df["race_category"].to_list()])
def test_get_race_result_with_start_year_params(self):
"""Testing to get the DataFrame with end-year parameters
"""
params = {
netkeiba.url_params.PID: netkeiba.pid_list.RACE_LIST,
netkeiba.url_params.START_YEAR: 2019,
netkeiba.url_params.END_YEAR: 2019
}
df = netkeiba.get_race_result(params)
assert not (df is None)
assert type(df) == pd.DataFrame
assert len(df) > 0
assert any([2019 == dt.year for dt in df["date"].to_list()])
def test_get_race_result_with_distance_to_param(self):
"""Testing to get the DataFrame with distance_from parameters
"""
params = {
netkeiba.url_params.PID: netkeiba.pid_list.RACE_LIST,
netkeiba.url_params.START_YEAR: 2019,
netkeiba.url_params.DISTANCE_TO: 2000
}
df = netkeiba.get_race_result(params)
assert not (df is None)
assert type(df) == pd.DataFrame
assert len(df) > 0
assert all([int(val) <= 2000 for val in df["distance"].to_list()])
def test_get_race_result_with_course_situation_param(self):
"""Testing to get the DataFrame with course situation parameters
"""
params = {
netkeiba.url_params.PID: netkeiba.pid_list.RACE_LIST,
netkeiba.url_params.START_YEAR: 2019,
netkeiba.url_params.TRACK: ["DIRT"],
netkeiba.url_params.COURSE_SITUATION: ["HEAVY_HOLDING"]
}
# [TODO]
# In case of track is hurdle, possibility we get the SOFT_YIELDING data,
# even if we set the search condition to HEAVY_HOLDING.
# So, I check only dirt data.
df = netkeiba.get_race_result(params)
assert not (df is None)
assert type(df) == pd.DataFrame
assert len(df) > 0
assert all(["不" in name for name in df["course_situation"].to_list()])