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"""
Tests for Models API Server
Comprehensive test suite for FastAPI inference server.
"""
import pytest
import asyncio
from fastapi.testclient import TestClient
import sys
import os
sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
from src.inference.api_server import app
class TestAPIServer:
"""Test suite for Models API Server."""
@pytest.fixture
def client(self):
"""Create test client."""
return TestClient(app)
@pytest.fixture
def sample_contracts(self):
"""Sample contract data for testing."""
return [
{
"id": "CT001",
"description": "Aquisição de computadores",
"value": 50000.0,
"supplier": "Tech Company A",
"date": "2024-01-15",
"organ": "Ministry of Education"
},
{
"id": "CT002",
"description": "Aquisição de computadores",
"value": 500000.0,
"supplier": "Tech Company B",
"date": "2024-01-20",
"organ": "Ministry of Education"
}
]
def test_root_endpoint(self, client):
"""Test root endpoint returns API info."""
response = client.get("/")
assert response.status_code == 200
data = response.json()
assert data["api"] == "Cidadão.AI Models"
assert data["version"] == "1.0.0"
assert data["status"] == "operational"
assert "anomaly_detector" in data["models"]
assert "endpoints" in data
def test_health_check(self, client):
"""Test health check endpoint."""
response = client.get("/health")
assert response.status_code == 200
data = response.json()
assert data["status"] == "healthy"
assert data["models_loaded"] is True
assert "anomaly_detector" in data["models"]
def test_detect_anomalies_endpoint(self, client, sample_contracts):
"""Test anomaly detection endpoint."""
response = client.post(
"/v1/detect-anomalies",
json={
"contracts": sample_contracts,
"threshold": 0.7
}
)
assert response.status_code == 200
data = response.json()
assert "anomalies" in data
assert "total_analyzed" in data
assert "anomalies_found" in data
assert "confidence_score" in data
assert "model_version" in data
assert data["total_analyzed"] == len(sample_contracts)
assert isinstance(data["anomalies"], list)
assert 0 <= data["confidence_score"] <= 1
def test_analyze_patterns_endpoint(self, client):
"""Test pattern analysis endpoint."""
response = client.post(
"/v1/analyze-patterns",
json={
"data": {
"contracts": [{"value": 100000}, {"value": 200000}],
"period": "2024-Q1"
},
"analysis_type": "temporal"
}
)
assert response.status_code == 200
data = response.json()
assert "patterns" in data
assert "pattern_count" in data
assert "confidence" in data
assert "insights" in data
assert isinstance(data["patterns"], list)
assert data["pattern_count"] >= 0
assert 0 <= data["confidence"] <= 1
assert isinstance(data["insights"], list)
def test_analyze_spectral_endpoint(self, client):
"""Test spectral analysis endpoint."""
response = client.post(
"/v1/analyze-spectral",
json={
"time_series": [100, 200, 150, 300, 250, 400, 350],
"sampling_rate": 1.0
}
)
assert response.status_code == 200
data = response.json()
assert "frequencies" in data
assert "amplitudes" in data
assert "dominant_frequency" in data
assert "periodic_patterns" in data
assert isinstance(data["frequencies"], list)
assert isinstance(data["amplitudes"], list)
assert isinstance(data["dominant_frequency"], float)
assert isinstance(data["periodic_patterns"], list)
def test_metrics_endpoint(self, client):
"""Test Prometheus metrics endpoint."""
# Make some requests first
client.get("/")
client.get("/health")
response = client.get("/metrics")
assert response.status_code == 200
metrics = response.text
assert "cidadao_models_requests_total" in metrics
assert "cidadao_models_request_duration_seconds" in metrics
assert "cidadao_models_anomalies_total" in metrics
def test_invalid_endpoint(self, client):
"""Test invalid endpoint returns 404."""
response = client.get("/invalid/endpoint")
assert response.status_code == 404
def test_empty_contracts_handling(self, client):
"""Test handling of empty contracts list."""
response = client.post(
"/v1/detect-anomalies",
json={
"contracts": [],
"threshold": 0.7
}
)
assert response.status_code == 200
data = response.json()
assert data["total_analyzed"] == 0
assert data["anomalies_found"] == 0
assert data["anomalies"] == []
def test_invalid_request_format(self, client):
"""Test handling of invalid request format."""
# Missing required field
response = client.post(
"/v1/detect-anomalies",
json={"threshold": 0.7} # Missing contracts
)
assert response.status_code == 422 # Validation error
# Invalid data type
response = client.post(
"/v1/detect-anomalies",
json={
"contracts": "not_a_list",
"threshold": 0.7
}
)
assert response.status_code == 422
def test_cors_headers(self, client):
"""Test CORS headers are properly set."""
response = client.options("/")
assert "access-control-allow-origin" in response.headers
assert response.headers["access-control-allow-origin"] == "*"
@pytest.mark.parametrize("num_contracts,max_time", [
(10, 1.0), # 10 contracts in < 1s
(100, 2.0), # 100 contracts in < 2s
(500, 5.0), # 500 contracts in < 5s
])
def test_performance_requirements(self, client, num_contracts, max_time):
"""Test API performance with different loads."""
import time
# Generate test data
contracts = [
{
"id": f"CT{i:06d}",
"description": f"Contract {i}",
"value": 50000.0 + (i * 100),
"supplier": f"Company {i % 20}",
"date": f"2024-01-{(i % 28) + 1:02d}",
"organ": f"Ministry {i % 5}"
}
for i in range(num_contracts)
]
start_time = time.time()
response = client.post(
"/v1/detect-anomalies",
json={
"contracts": contracts,
"threshold": 0.7
}
)
elapsed_time = time.time() - start_time
assert response.status_code == 200
assert elapsed_time < max_time
class TestAPIServerIntegration:
"""Integration tests for API Server."""
@pytest.fixture
def client(self):
"""Create test client."""
return TestClient(app)
def test_full_workflow(self, client):
"""Test complete workflow from detection to analysis."""
# Step 1: Detect anomalies
contracts = [
{
"id": f"CT{i:03d}",
"description": f"Contract {i}",
"value": 100000.0 if i != 5 else 1000000.0, # One anomaly
"supplier": f"Company {i % 3}",
"date": f"2024-01-{i+1:02d}",
"organ": "Ministry A"
}
for i in range(10)
]
anomaly_response = client.post(
"/v1/detect-anomalies",
json={"contracts": contracts}
)
assert anomaly_response.status_code == 200
anomaly_data = anomaly_response.json()
assert anomaly_data["anomalies_found"] > 0
# Step 2: Analyze patterns in the data
pattern_response = client.post(
"/v1/analyze-patterns",
json={
"data": {
"anomaly_results": anomaly_data,
"contracts": contracts
},
"analysis_type": "temporal"
}
)
assert pattern_response.status_code == 200
pattern_data = pattern_response.json()
assert len(pattern_data["patterns"]) > 0
# Step 3: Perform spectral analysis on values
values = [c["value"] for c in contracts]
spectral_response = client.post(
"/v1/analyze-spectral",
json={
"time_series": values,
"sampling_rate": 1.0
}
)
assert spectral_response.status_code == 200
spectral_data = spectral_response.json()
assert spectral_data["dominant_frequency"] >= 0
def test_concurrent_requests(self, client):
"""Test handling of concurrent requests."""
import concurrent.futures
def make_request(request_id):
return client.post(
"/v1/detect-anomalies",
json={
"contracts": [
{
"id": f"REQ{request_id}-CT001",
"description": "Test contract",
"value": 100000.0,
"supplier": "Test Company",
"date": "2024-01-01",
"organ": "Test Ministry"
}
]
}
)
# Make 10 concurrent requests
with concurrent.futures.ThreadPoolExecutor(max_workers=10) as executor:
futures = [
executor.submit(make_request, i)
for i in range(10)
]
results = [
future.result()
for future in concurrent.futures.as_completed(futures)
]
# All should succeed
assert all(r.status_code == 200 for r in results)
assert len(results) == 10 |