Personal-Finance-Management/app/routes/dashboard.py

from flask import Blueprint, render_template, request, jsonify
from flask_login import login_required, current_user
from sqlalchemy import func, extract
from app.extensions import db
from app.models.account import Account
from app.models.transaction import Transaction
from app.models.category import Category
from app.services.fx_service import get_today_rate, get_rate_history
from app.services.ai_service import get_latest_daily_insight
from app.services.account_service import get_total_assets, get_total_liabilities
from datetime import date, datetime, timedelta
import calendar

dashboard_bp = Blueprint('dashboard', __name__)


def _parse_date_range(period):
    """Return (date_from, date_to, label) for a given period string."""
    today = date.today()
    if period == 'last_month':
        first = (today.replace(day=1) - timedelta(days=1)).replace(day=1)
        last = today.replace(day=1) - timedelta(days=1)
        label = first.strftime('%B %Y')
    elif period == 'custom':
        try:
            date_from = datetime.strptime(request.args.get('date_from', ''), '%Y-%m-%d').date()
            date_to = datetime.strptime(request.args.get('date_to', ''), '%Y-%m-%d').date()
        except ValueError:
            date_from = today.replace(day=1)
            date_to = today
        return date_from, date_to, 'Custom Range'
    else:  # this_month (default)
        first = today.replace(day=1)
        last = today
        label = first.strftime('%B %Y')
    return first, last, label


@dashboard_bp.route('/')
@login_required
def index():
    period = request.args.get('period', 'this_month')
    date_from, date_to, period_label = _parse_date_range(period)

    # ── Summary cards ────────────────────────────────
    total_income = db.session.query(
        func.coalesce(func.sum(Transaction.amount), 0)
    ).filter(
        Transaction.transaction_type == 'income',
        Transaction.date >= date_from,
        Transaction.date <= date_to,
    ).scalar()

    total_expense = db.session.query(
        func.coalesce(func.sum(Transaction.amount), 0)
    ).filter(
        Transaction.transaction_type == 'expense',
        Transaction.date >= date_from,
        Transaction.date <= date_to,
    ).scalar()

    net_cash_flow = float(total_income) - float(total_expense)

    # ── Accounts ─────────────────────────────────────
    accounts = Account.query.filter_by(is_active=True).order_by(Account.name).all()
    total_assets = get_total_assets()
    total_liabilities = get_total_liabilities()
    net_worth = total_assets - total_liabilities

    # ── Top expense categories ────────────────────────
    top_categories = db.session.query(
        Category.name,
        Category.color,
        Category.icon,
        func.sum(Transaction.amount).label('total')
    ).join(Transaction, Transaction.category_id == Category.id)\
     .filter(
        Transaction.transaction_type == 'expense',
        Transaction.date >= date_from,
        Transaction.date <= date_to,
     ).group_by(Category.id)\
      .order_by(func.sum(Transaction.amount).desc())\
      .limit(5).all()

    # ── Cash flow chart (last 6 months) ──────────────
    chart_months = []
    chart_income = []
    chart_expense = []
    today = date.today()
    for i in range(5, -1, -1):
        # go back i months from current
        month_date = (today.replace(day=1) - timedelta(days=i * 28)).replace(day=1)
        last_day = calendar.monthrange(month_date.year, month_date.month)[1]
        m_start = month_date
        m_end = month_date.replace(day=last_day)

        inc = db.session.query(
            func.coalesce(func.sum(Transaction.amount), 0)
        ).filter(
            Transaction.transaction_type == 'income',
            Transaction.date >= m_start,
            Transaction.date <= m_end,
        ).scalar()

        exp = db.session.query(
            func.coalesce(func.sum(Transaction.amount), 0)
        ).filter(
            Transaction.transaction_type == 'expense',
            Transaction.date >= m_start,
            Transaction.date <= m_end,
        ).scalar()

        chart_months.append(month_date.strftime('%b %Y'))
        chart_income.append(float(inc))
        chart_expense.append(float(exp))

    # ── Recent transactions ───────────────────────────
    recent_txns = Transaction.query\
        .filter(Transaction.transaction_type.in_(['income', 'expense']))\
        .order_by(Transaction.date.desc(), Transaction.id.desc())\
        .limit(8).all()

    # ── USD/VND rate ──────────────────────────────────
    fx = get_today_rate()
    fx_history = get_rate_history(30)
    fx_history_data = {
        'dates': [r.date.strftime('%b %d') for r in fx_history],
        'rates': [float(r.usd_to_vnd) for r in fx_history],
    }

    # ── AI insight ──────────────────────────────────────
    ai_insight = get_latest_daily_insight()

    return render_template('dashboard/index.html',
                           period=period,
                           period_label=period_label,
                           date_from=date_from,
                           date_to=date_to,
                           total_income=float(total_income),
                           total_expense=float(total_expense),
                           net_cash_flow=net_cash_flow,
                           accounts=accounts,
                           total_assets=total_assets,
                           total_liabilities=total_liabilities,
                           net_worth=net_worth,
                           top_categories=top_categories,
                           chart_months=chart_months,
                           chart_income=chart_income,
                           chart_expense=chart_expense,
                           recent_txns=recent_txns,
                           fx=fx,
                           fx_history_data=fx_history_data,
                           ai_insight=ai_insight)


@dashboard_bp.route('/api/fx-history')
@login_required
def fx_history_api():
    history = get_rate_history(30)
    return jsonify({
        'dates': [r.date.strftime('%b %d') for r in history],
        'rates': [float(r.usd_to_vnd) for r in history],
    })