-
Notifications
You must be signed in to change notification settings - Fork 1
/
Copy pathtest_main.py
107 lines (90 loc) · 3.46 KB
/
test_main.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
import pytest
from fastapi.testclient import TestClient
from main import app, WebsiteExperiment, Variant
# Create a test client for the FastAPI app
client = TestClient(app)
# Test the home endpoint
@pytest.mark.asyncio
def test_home():
response = client.get("/")
assert response.status_code == 200
assert "Janus: Bayesian A/B Testing App" in response.text
# Test the health check endpoint
@pytest.mark.asyncio
def test_health_check():
response = client.get("/health")
assert response.status_code == 200
assert response.json() == {"status": "healthy"}
# Test the WebsiteExperiment class
@pytest.mark.asyncio
def test_website_experiment():
variants = [
Variant(name="A", impressions=1000, conversions=100, revenue=1000.0),
Variant(name="B", impressions=1000, conversions=150, revenue=1500.0),
]
experiment = WebsiteExperiment(variants=variants, baseline_variant="A")
experiment.run(show=False)
assert len(experiment.conversion_results) == 2
assert len(experiment.arpu_results) == 2
assert len(experiment.revenue_per_sale_results) == 2
@pytest.mark.asyncio
def test_run_conversion_experiment():
variants = [
Variant(name="A", impressions=1000, conversions=100, revenue=1000.0),
Variant(name="B", impressions=1000, conversions=150, revenue=1500.0),
]
experiment = WebsiteExperiment(variants=variants, baseline_variant="A")
experiment.run_conversion_experiment(show=False)
assert len(experiment.conversion_results) == 2
@pytest.mark.asyncio
def test_run_arpu_experiment():
variants = [
Variant(name="A", impressions=1000, conversions=100, revenue=1000.0),
Variant(name="B", impressions=1000, conversions=150, revenue=1500.0),
]
experiment = WebsiteExperiment(variants=variants, baseline_variant="A")
experiment.run_arpu_experiment(show=False)
assert len(experiment.arpu_results) == 2
@pytest.mark.asyncio
def test_run_revenue_per_sale_experiment():
variants = [
Variant(name="A", impressions=1000, conversions=100, revenue=1000.0),
Variant(name="B", impressions=1000, conversions=150, revenue=1500.0),
]
experiment = WebsiteExperiment(variants=variants, baseline_variant="A")
experiment.run_revenue_per_sale_experiment(show=False)
assert len(experiment.revenue_per_sale_results) == 2
@pytest.mark.asyncio
def test_compile_full_data():
variants = [
Variant(name="A", impressions=1000, conversions=100, revenue=1000.0),
Variant(name="B", impressions=1000, conversions=150, revenue=1500.0),
]
experiment = WebsiteExperiment(variants=variants, baseline_variant="A")
experiment.run(show=False)
compiled_data = experiment.compile_full_data()
assert len(compiled_data) == 2
@pytest.mark.asyncio
def test_get_reports():
variants = [
Variant(name="A", impressions=1000, conversions=100, revenue=1000.0),
Variant(name="B", impressions=1000, conversions=150, revenue=1500.0),
]
experiment = WebsiteExperiment(variants=variants, baseline_variant="A")
experiment.run(show=False)
(
df_summary,
df_conv,
df_arpu,
df_rev_per_sale,
conv_dist,
arpu_dist,
rev_per_sale_dist,
) = experiment.get_reports()
assert not df_summary.empty
assert not df_conv.empty
assert not df_arpu.empty
assert not df_rev_per_sale.empty
assert conv_dist is not None
assert arpu_dist is not None
assert rev_per_sale_dist is not None