andy
db06108d2b
Adds remaining files from parallel development: - Services: analysis, csv_reader, forecasting, normalizer, recurring - UI: recurring_view, settings_view, sidebar, themes (dark/light) - Tests: analysis, csv_reader, forecasting, import_categorize, normalizer, recurring, integration - App entry point (main.py) and CLAUDE.md 52 tests passing across all modules. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
100 lines
3.7 KiB
Python
100 lines
3.7 KiB
Python
# tests/test_integration.py
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from pathlib import Path
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from sqlalchemy import create_engine
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from sqlalchemy.orm import Session
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from src.db import Base
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from src.models import *
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from src.seed import seed_categories, seed_household, seed_default_rules
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from src.services.importer import ImportService
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from src.services.analysis import AnalysisService
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from src.services.recurring import RecurringDetector
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RAWDATA = Path(__file__).parent.parent / "rawdata"
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def test_full_pipeline():
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engine = create_engine("sqlite:///:memory:")
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Base.metadata.create_all(engine)
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session = Session(engine)
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# Setup
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seed_categories(session)
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andrew = seed_household(session, "Andrew", "self")
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donna = seed_household(session, "Donna", "wife")
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seed_default_rules(session)
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# Create accounts
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chase = Account(name="Chase Freedom", institution="Chase", account_type="credit", owner_id=andrew.id)
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checking = Account(name="WF Checking", institution="Wells Fargo", account_type="checking", owner_id=andrew.id, is_shared=True)
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session.add_all([chase, checking])
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session.flush()
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svc = ImportService(session)
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# Import Chase CSV
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r1 = svc.import_csv(
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RAWDATA / "Chase0372_Activity20260101_20260210_20260210.CSV",
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account_id=chase.id,
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column_map={"date": "Transaction Date", "amount": "Amount", "description": "Description", "source_category": "Category"},
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amount_logic="signed",
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)
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assert r1["imported"] > 100
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# Import Checking CSV
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r2 = svc.import_csv(
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RAWDATA / "Checking1.csv",
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account_id=checking.id,
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column_map={"date": 0, "amount": 1, "description": 4},
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amount_logic="signed",
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)
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assert r2["imported"] > 50
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# Verify some transactions got auto-categorized
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categorized = session.query(Transaction).filter(Transaction.category_id.isnot(None)).count()
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total = session.query(Transaction).count()
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assert categorized > 0, "Expected some transactions to be auto-categorized"
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print(f"Categorized {categorized}/{total} transactions")
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# Verify income attributed to correct people
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income_cat = session.query(Category).filter_by(name="Income").first()
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if income_cat:
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andrew_income = session.query(Transaction).filter(
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Transaction.category_id == income_cat.id,
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Transaction.attributed_to_id == andrew.id,
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).count()
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donna_income = session.query(Transaction).filter(
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Transaction.category_id == income_cat.id,
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Transaction.attributed_to_id == donna.id,
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).count()
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print(f"Andrew income transactions: {andrew_income}")
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print(f"Donna income transactions: {donna_income}")
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# Analysis works
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analysis = AnalysisService(session)
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monthly = analysis.spending_by_period("month")
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assert len(monthly) >= 1, "Expected at least one month of data"
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by_cat = analysis.spending_by_category()
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assert len(by_cat) >= 1, "Expected at least one category"
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by_tag = analysis.spending_by_tag()
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assert len(by_tag) >= 1, "Expected at least one tag"
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# Recurring detection works
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detector = RecurringDetector(session)
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recurring = detector.detect()
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# Print what was found for debugging
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for r in recurring:
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print(f"Recurring: {r['description']} - ${r['typical_amount']:.2f} {r['frequency']} (${r['annual_cost']:.2f}/yr)")
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# Verify no duplicate imports
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r3 = svc.import_csv(
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RAWDATA / "Chase0372_Activity20260101_20260210_20260210.CSV",
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account_id=chase.id,
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column_map={"date": "Transaction Date", "amount": "Amount", "description": "Description"},
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amount_logic="signed",
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)
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assert r3["imported"] == 0, "Re-import should detect all duplicates"
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assert r3["duplicates"] == r1["imported"]
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