text2sql / core /tests /test_scores.py
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from django.test import TestCase
from core.models import MutualFund, Stock
from core.mfrating.score_calculator import MutualFundScorer, MFRating
from core.tests.data import test_data
class MutualFundScorerTestCase(TestCase):
"""
Test case for the MutualFundScorer class to test scores.
"""
def setUp(self):
self.stock_data = [
{"isin_number": "INE040A01034", "rank": 10},
{"isin_number": "INE090A01021", "rank": 21},
{"isin_number": "INE002A01018", "rank": 131},
{"isin_number": "INE154A01025", "rank": 99},
{"isin_number": "INE018A01030", "rank": 31},
{"isin_number": "INE280A01028", "rank": 2},
]
self.mutual_fund_data = [
{
"isin_number": "ISIN1",
"fund_name": "Testing Fund 1",
"rank": 1,
"aum": 837.3,
"crisil_rank": 4,
"security_id": "SEC1",
"data": test_data[1],
},
{
"isin_number": "ISIN2",
"fund_name": "Testing Fund 2",
"rank": 2,
"aum": 210.3,
"crisil_rank": 1,
"security_id": "SEC2",
"data": test_data[2],
},
{
"isin_number": "ISIN3",
"fund_name": "Testing Fund 3",
"rank": 3,
"aum": 639.3,
"crisil_rank": 3,
"security_id": "SEC3",
"data": test_data[3],
},
{
"isin_number": "ISIN4",
"fund_name": "Testing Fund 4",
"rank": 4,
"aum": 410.3,
"crisil_rank": 2,
"security_id": "SEC4",
"data": test_data[4],
},
{
"isin_number": "ISIN5",
"fund_name": "Testing Fund 5",
"rank": 5,
"aum": 1881.3,
"crisil_rank": 5,
"security_id": "SEC5",
"data": test_data[5],
},
]
self.create_stock_objects()
self.create_mutual_fund_objects()
self.mf_scorer = MutualFundScorer()
def create_stock_objects(self):
"""
Create stock objects using the predefined stock data.
"""
self.stock_objects = [Stock.objects.create(**data) for data in self.stock_data]
def create_mutual_fund_objects(self):
"""
Create mutual fund objects using the predefined mutual fund data.
"""
self.mutual_fund_objects = [
MutualFund.objects.create(**data) for data in self.mutual_fund_data
]
def test_get_scores_returns_sorted_list(self):
"""
Test whether the get_scores method returns a sorted list of scores.
"""
scores = self.mf_scorer.get_scores()
self.assertEqual(len(scores), 5)
self.assertEqual(
scores, sorted(scores, key=lambda x: x["overall_score"], reverse=True)
)
expected_scores = [0.4263, 0.3348, 0.2962, 0.2447, 0.2101]
for i, expected_score in enumerate(expected_scores):
self.assertAlmostEqual(
scores[i]["overall_score"], expected_score, delta=1e-4
)