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Lottery_Project/tests/lottery_predictor/test_analyze.py
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Python
Executable File

from datetime import datetime
import numpy as np
import pytest
import lottery_predictor.analyze as analyze
def test_load_dataframe_by_date() -> None:
pb_start = datetime(2015, 10, 4)
mm_start = datetime(2025, 4, 5)
date_end = datetime(2026, 3, 8)
assert int(
analyze.load_dataframe_by_dates(
game='Powerball', start_date=pb_start, end_date=date_end,
).count()['draw_date'],
) >= 1324
assert int(
analyze.load_dataframe_by_dates(
game='MegaMillions', start_date=mm_start, end_date=date_end,
).count()['draw_date'],
) >= 96
with pytest.raises(KeyError):
analyze.load_dataframe_by_dates(game='SomeNonExistentGameName')
def test_load_dataframe_most_recent() -> None:
assert len(analyze.load_dataframe_most_recent(game='Powerball')) == 10
assert len(analyze.load_dataframe_most_recent(game='MegaMillions')) == 10
assert len(
analyze.load_dataframe_most_recent(game='Powerball', limit=105),
) == 105
assert len(
analyze.load_dataframe_most_recent(game='MegaMillions', limit=45),
) == 45
with pytest.raises(ValueError):
analyze.load_dataframe_most_recent(game='Powerball', limit=-1)
analyze.load_dataframe_most_recent(game='DoesntExist')
def test_prepare_split_data() -> None:
mm_start = datetime(2025, 4, 5)
date_end = datetime(2026, 3, 8)
mega = analyze.load_dataframe_by_dates(
game='MegaMillions', start_date=mm_start, end_date=date_end,
)
x, y1, y2 = analyze.prepare_split_data(
data=mega.values, window_size=len(mega) - 1,
)
assert isinstance(x, np.ndarray)
assert isinstance(y1, np.ndarray)
assert isinstance(y2, np.ndarray)
def test_make_prediction() -> None:
pb_start = datetime(2015, 10, 4)
date_end = datetime(2026, 3, 8)
power = analyze.load_dataframe_by_dates(
game='Powerball', start_date=pb_start, end_date=date_end,
)
main, game = analyze.make_prediction(data_frame=power, window_size=10)
assert isinstance(main, np.ndarray)
assert isinstance(game, np.int64)
def test_least_and_most_common_number() -> None:
pb_start = datetime(2015, 10, 4)
mm_start = datetime(2025, 4, 5)
date_end = datetime(2026, 3, 8)
pb_df = analyze.load_dataframe_by_dates(
game='Powerball', start_date=pb_start, end_date=date_end,
)
mm_df = analyze.load_dataframe_by_dates(
game='MegaMillions', start_date=mm_start, end_date=date_end,
)
assert analyze.get_most_common_number(pb_df, top=5) == [61, 21, 23, 28, 33]
assert analyze.get_least_common_number(pb_df, bottom=5) == [
13, 49, 26, 46, 34,
]
assert analyze.get_most_common_number(mm_df, top=5) == [42, 18, 40, 49, 10]
assert analyze.get_least_common_number(mm_df, bottom=5) == [
35, 51, 61, 1, 20,
]
assert analyze.get_most_common_number(
pb_df, columns=['powerball'], top=1,
) == [4]
assert analyze.get_least_common_number(
pb_df, columns=['powerball'], bottom=1,
) == [16]
assert analyze.get_most_common_number(
mm_df, columns=['mega_ball'], top=1,
) == [24]
assert analyze.get_least_common_number(
mm_df, columns=['mega_ball'], bottom=1,
) == [20]
def test_calculate_probabilities() -> None:
"""tests build_binary_matrix, build_next_targets and
calculate_number_probability"""
pb_start = datetime(2015, 10, 4)
mm_start = datetime(2025, 4, 5)
date_end = datetime(2026, 3, 8)
pb_df = analyze.load_dataframe_by_dates(
game='Powerball', start_date=pb_start, end_date=date_end,
)
pb_probabilities = analyze.calculate_probabilities(
data_frame=pb_df, max_number=69,
)
mm_df = analyze.load_dataframe_by_dates(
game='MegaMillions', start_date=mm_start, end_date=date_end,
)
mm_probabilities = analyze.calculate_probabilities(
data_frame=mm_df, max_number=70,
)
assert pb_probabilities[1] == 0.3142857142857143
assert mm_probabilities[1] == 0.04225352112676056
def test_hot_cold_numbers() -> None:
"""tests get_hot_numbers and get_cold_numbers"""
pb_start = datetime(2015, 10, 4)
mm_start = datetime(2025, 4, 5)
date_end = datetime(2026, 3, 8)
pb_df = analyze.load_dataframe_by_dates(
game='Powerball', start_date=pb_start, end_date=date_end,
)
pb_probs = analyze.calculate_probabilities(data_frame=pb_df, max_number=69)
mm_df = analyze.load_dataframe_by_dates(
game='MegaMillions', start_date=mm_start, end_date=date_end,
)
mm_probs = analyze.calculate_probabilities(data_frame=mm_df, max_number=70)
assert (analyze.get_hot_numbers(probabilities=pb_probs) ==
[
(13, 1.0), (61, 0.7), (21, 0.6714285714285715),
(23, 0.6428571428571428), (28, 0.6428571428571428),
])
assert (analyze.get_cold_numbers(probabilities=pb_probs) ==
[
(49, 0.10000000000000009), (26, 0.11428571428571432),
(46, 0.11428571428571432),
(34, 0.17142857142857149), (65, 0.18571428571428572),
])
assert (analyze.get_hot_numbers(probabilities=mm_probs) ==
[
(42, 0.19718309859154928), (18, 0.18309859154929578),
(40, 0.18309859154929578),
(10, 0.16901408450704225), (49, 0.16901408450704225),
])
assert (analyze.get_cold_numbers(probabilities=mm_probs) ==
[
(35, 0.028169014084507043), (51, 0.028169014084507043),
(1, 0.04225352112676056),
(3, 0.04225352112676056), (20, 0.04225352112676056),
])