الخطوط القابلة للتكرار واختبارات القبول

import pandas as pd
from pandas.testing import assert_frame_equal

def calculate(frame):
    return frame.assign(line_total=lambda value: value['units'] * value['price']).sort_values('item').reset_index(drop=True)

source = pd.DataFrame({'item': ['I2', 'I1'], 'units': [3, 2], 'price': [7, 5]})
result = source.pipe(calculate)
expected = pd.DataFrame({'item': ['I1', 'I2'], 'units': [2, 3], 'price': [5, 7], 'line_total': [10, 21]})
assert_frame_equal(result, expected, check_dtype=True, check_exact=True)
print(result['line_total'].tolist())

[10, 21]

المتوقع [10,21] بالمخطط والترتيب المعلنين؛ ولم تنفذ assert_frame_equal.

source = [{'item': 'I2', 'units': 3, 'price': 7}, {'item': 'I1', 'units': 2, 'price': 5}]
snapshot = [dict(row) for row in source]
result = sorted([{**row, 'line_total': row['units'] * row['price']} for row in source], key=lambda row: row['item'])
assert source == snapshot
assert [row['line_total'] for row in result] == [10, 21]
print([row['item'] for row in result])

['I1', 'I2']

يحفظ تحويل السجلات المدخل والترتيب المتوقع، ولا يختبر تساوي pandas أو CoW.