109 lines
3.4 KiB
Python
109 lines
3.4 KiB
Python
from datetime import date, timedelta
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from typing import Optional
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from fastapi import APIRouter, Depends, Query
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from sqlalchemy.orm import Session
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from ..database import get_db
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from .. import models
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from ..dependencies import get_current_user
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from ..services.btc import get_btc_price_eur
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router = APIRouter()
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def _first_of_month(year: int, month: int) -> date:
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return date(year, month, 1)
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def _next_month(year: int, month: int) -> tuple[int, int]:
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if month == 12:
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return year + 1, 1
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return year, month + 1
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@router.get("/dca")
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def get_dca(
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monthly_amount: float = Query(..., gt=0),
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start_date: Optional[str] = Query(default=None),
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db: Session = Depends(get_db),
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current_user: models.User = Depends(get_current_user),
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):
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# Determine start date
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if start_date:
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try:
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sim_start = date.fromisoformat(start_date)
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except ValueError:
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sim_start = None
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else:
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sim_start = None
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if sim_start is None:
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earliest = (
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db.query(models.Purchase)
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.filter(models.Purchase.user_id == current_user.id)
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.order_by(models.Purchase.created_at.asc())
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.first()
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)
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if earliest:
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sim_start = earliest.created_at.date()
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else:
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sim_start = date.today() - timedelta(days=365)
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# Load all candles into a lookup dict {date_str: close_price}
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candles_db = db.query(models.OHLCCandle).all()
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price_by_date: dict[str, float] = {c.date: c.close for c in candles_db}
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today = date.today()
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current_price, _ = get_btc_price_eur()
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# Patch today's price in case the candle isn't refreshed yet
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if current_price:
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price_by_date[today.isoformat()] = current_price
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# Walk month by month and simulate buys
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year, month = sim_start.year, sim_start.month
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end_year, end_month = today.year, today.month
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dca_invested = 0.0
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dca_btc = 0.0
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monthly_series = []
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while (year, month) <= (end_year, end_month):
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# Find the closest available candle on or after the 1st of this month
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buy_date = None
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buy_price = None
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for day_offset in range(8):
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candidate = _first_of_month(year, month) + timedelta(days=day_offset)
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key = candidate.isoformat()
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if key in price_by_date:
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buy_date = key
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buy_price = price_by_date[key]
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break
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if buy_price and buy_price > 0:
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btc_bought = monthly_amount / buy_price
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dca_btc += btc_bought
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dca_invested += monthly_amount
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monthly_series.append({
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"month": f"{year:04d}-{month:02d}",
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"price_used": round(buy_price, 2),
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"btc_bought": round(btc_bought, 8),
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"cumulative_btc": round(dca_btc, 8),
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"cumulative_invested": round(dca_invested, 2),
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})
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year, month = _next_month(year, month)
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dca_current_value = dca_btc * current_price if current_price else 0.0
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dca_profit_loss = dca_current_value - dca_invested
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return {
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"start_date": sim_start.isoformat(),
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"monthly_amount": monthly_amount,
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"dca_total_invested": round(dca_invested, 2),
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"dca_total_btc": round(dca_btc, 8),
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"dca_current_value": round(dca_current_value, 2),
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"dca_profit_loss": round(dca_profit_loss, 2),
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"monthly_series": monthly_series,
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}
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