llm-quiz-analysis / test /test_data_transformer.py
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"""
Test Data Transformer
Comprehensive tests for data transformation
"""
import sys
import os
# Add project root to Python path
project_root = os.path.abspath(os.path.join(os.path.dirname(__file__), '..'))
sys.path.insert(0, project_root)
import asyncio
from app.modules.processors import DataTransformer
from app.core.logging import setup_logging
setup_logging()
async def test_filter():
"""Test filtering"""
print("\n" + "=" * 60)
print("Test 1: Filter Data")
print("=" * 60)
transformer = DataTransformer()
data = [
{"name": "Laptop", "price": 1299, "category": "Electronics"},
{"name": "Phone", "price": 999, "category": "Electronics"},
{"name": "T-Shirt", "price": 20, "category": "Clothing"},
{"name": "Monitor", "price": 399, "category": "Electronics"}
]
print(f" Original: {len(data)} records")
result = await transformer.execute({
'data': data,
'operations': [
{
'type': 'filter',
'conditions': {
'category': {'eq': 'Electronics'},
'price': {'lt': 1000}
}
}
]
})
print(f"\n Filtered:")
print(f" Records: {len(result.data)}")
print(f" Results: {result.data}")
assert result.success
assert len(result.data) == 2 # Phone and Monitor
print("\nβœ… Filter working")
async def test_sort():
"""Test sorting"""
print("\n" + "=" * 60)
print("Test 2: Sort Data")
print("=" * 60)
transformer = DataTransformer()
data = [
{"name": "Laptop", "price": 1299},
{"name": "Phone", "price": 999},
{"name": "Monitor", "price": 399}
]
result = await transformer.execute({
'data': data,
'operations': [
{'type': 'sort', 'columns': ['price'], 'ascending': True}
]
})
print(f"\n Sorted by price (ascending):")
for item in result.data:
print(f" {item['name']}: ${item['price']}")
assert result.success
assert result.data[0]['price'] == 399 # Cheapest first
print("\nβœ… Sort working")
async def test_aggregate():
"""Test aggregation"""
print("\n" + "=" * 60)
print("Test 3: Aggregate Data")
print("=" * 60)
transformer = DataTransformer()
data = [
{"category": "Electronics", "price": 1299, "sold": 10},
{"category": "Electronics", "price": 999, "sold": 20},
{"category": "Clothing", "price": 20, "sold": 100},
{"category": "Clothing", "price": 30, "sold": 80}
]
print(f" Original: {len(data)} records")
result = await transformer.execute({
'data': data,
'operations': [
{
'type': 'aggregate',
'group_by': 'category',
'aggregations': {
'avg_price': {'column': 'price', 'function': 'avg'},
'total_sold': {'column': 'sold', 'function': 'sum'},
'count': {'function': 'count'}
}
}
]
})
print(f"\n Aggregated:")
for row in result.data:
print(f" {row}")
assert result.success
assert len(result.data) == 2 # 2 categories
print("\nβœ… Aggregate working")
async def test_select_columns():
"""Test column selection"""
print("\n" + "=" * 60)
print("Test 4: Select Columns")
print("=" * 60)
transformer = DataTransformer()
data = [
{"name": "Laptop", "price": 1299, "category": "Electronics", "stock": 5, "rating": 4.5}
]
result = await transformer.execute({
'data': data,
'operations': [
{'type': 'select', 'columns': ['name', 'price']}
]
})
print(f"\n Selected columns:")
print(f" {result.data[0]}")
assert result.success
assert 'name' in result.data[0]
assert 'price' in result.data[0]
assert 'category' not in result.data[0]
print("\nβœ… Select working")
async def test_limit():
"""Test limiting results"""
print("\n" + "=" * 60)
print("Test 5: Limit Results")
print("=" * 60)
transformer = DataTransformer()
data = [{"id": i} for i in range(100)]
print(f" Original: {len(data)} records")
result = await transformer.execute({
'data': data,
'operations': [
{'type': 'limit', 'limit': 5}
]
})
print(f" Limited: {len(result.data)} records")
assert result.success
assert len(result.data) == 5
print("\nβœ… Limit working")
async def test_complex_pipeline():
"""Test complex transformation pipeline"""
print("\n" + "=" * 60)
print("Test 6: Complex Pipeline")
print("=" * 60)
transformer = DataTransformer()
# E-commerce data
data = [
{"product": "Laptop", "price": 1299, "category": "Electronics", "sold": 50, "rating": 4.5},
{"product": "Phone", "price": 999, "category": "Electronics", "sold": 120, "rating": 4.8},
{"product": "T-Shirt", "price": 20, "category": "Clothing", "sold": 500, "rating": 4.2},
{"product": "Jeans", "price": 60, "category": "Clothing", "sold": 300, "rating": 4.6},
{"product": "Monitor", "price": 399, "category": "Electronics", "sold": 80, "rating": 4.3},
{"product": "Shoes", "price": 80, "category": "Clothing", "sold": 200, "rating": 4.4}
]
print(f" Pipeline: Filter β†’ Aggregate β†’ Sort β†’ Limit")
result = await transformer.execute({
'data': data,
'operations': [
# 1. Filter: Only products sold > 100
{
'type': 'filter',
'conditions': {'sold': {'gte': 100}}
},
# 2. Aggregate by category
{
'type': 'aggregate',
'group_by': 'category',
'aggregations': {
'avg_rating': {'column': 'rating', 'function': 'avg'},
'total_sold': {'column': 'sold', 'function': 'sum'},
'products': {'function': 'count'}
}
},
# 3. Sort by total_sold descending
{
'type': 'sort',
'columns': ['total_sold'],
'ascending': False
},
# 4. Top 2 categories
{
'type': 'limit',
'limit': 2
}
]
})
print(f"\n Result:")
for row in result.data:
print(f" {row}")
assert result.success
assert len(result.data) == 2
print("\nβœ… Complex pipeline working")
async def test_join():
"""Test joining datasets"""
print("\n" + "=" * 60)
print("Test 7: Join Datasets")
print("=" * 60)
transformer = DataTransformer()
# Products
products = [
{"id": 1, "name": "Laptop", "category_id": 10},
{"id": 2, "name": "Phone", "category_id": 10}
]
# Categories
categories = [
{"id": 10, "category_name": "Electronics"},
{"id": 20, "category_name": "Clothing"}
]
result = await transformer.execute({
'data': products,
'operations': [
{
'type': 'join',
'right_data': categories,
'left_key': 'category_id',
'right_key': 'id',
'join_type': 'inner'
}
]
})
print(f"\n Joined:")
for row in result.data:
print(f" {row}")
assert result.success
assert 'category_name' in result.data[0]
print("\nβœ… Join working")
async def test_pivot():
"""Test pivot operation"""
print("\n" + "=" * 60)
print("Test 8: Pivot Table")
print("=" * 60)
transformer = DataTransformer()
# Sales data
data = [
{"month": "Jan", "region": "North", "sales": 1000},
{"month": "Jan", "region": "South", "sales": 1500},
{"month": "Feb", "region": "North", "sales": 1200},
{"month": "Feb", "region": "South", "sales": 1800}
]
result = await transformer.execute({
'data': data,
'operations': [
{
'type': 'pivot',
'index': 'month',
'columns': 'region',
'values': 'sales',
'aggfunc': 'sum'
}
]
})
print(f"\n Pivoted:")
for row in result.data:
print(f" {row}")
assert result.success
print("\nβœ… Pivot working")
async def run_all_tests():
"""Run all tests"""
print("\n" + "=" * 80)
print(" " * 23 + "DATA TRANSFORMER TEST SUITE")
print("=" * 80)
tests = [
test_filter,
test_sort,
test_aggregate,
test_select_columns,
test_limit,
test_complex_pipeline,
test_join,
test_pivot
]
passed = 0
failed = 0
for test in tests:
try:
await test()
passed += 1
except Exception as e:
failed += 1
print(f"\n❌ Test failed: {e}")
import traceback
traceback.print_exc()
print("\n" + "=" * 80)
print(" " * 30 + "TEST SUMMARY")
print("=" * 80)
print(f"\n Total: {len(tests)}")
print(f" βœ… Passed: {passed}")
print(f" ❌ Failed: {failed}")
if failed == 0:
print("\nπŸŽ‰ ALL TESTS PASSED!")
print("\nβœ… Data Transformer is production ready!")
print("\nπŸ“Š Verified:")
print(" βœ“ Filtering (multiple conditions)")
print(" βœ“ Sorting (single/multiple columns)")
print(" βœ“ Aggregations (group by, sum, avg, etc.)")
print(" βœ“ Column selection")
print(" βœ“ Limiting results")
print(" βœ“ Complex pipelines")
print(" βœ“ Joining datasets")
print(" βœ“ Pivot tables")
if __name__ == "__main__":
asyncio.run(run_all_tests())