Get Daily Statistics (get_daily_stats)

Sugar method: Returns comprehensive trading statistics for specific day.

API Information:

• Method: sugar.get_daily_stats(target_date)
• Returns: DailyStats dataclass with complete statistics
• Layer: HIGH (MT5Sugar)

---

Method Signature

async def get_daily_stats(self, target_date: Optional[date] = None) -> DailyStats

---

🔽 Input Parameters

Parameter	Type	Required	Default	Description
target_date	Optional[date]	No	None	Date to get stats for (None = today)

---

Return Value

DailyStats dataclass with the following fields:

Field	Type	Description
date	date	The date for these statistics
deals_count	int	Number of closed positions
profit	float	Total gross profit/loss
commission	float	Total commission paid
swap	float	Total swap (rollover)
volume	float	Total volume traded in lots

Calculated field:

• net_profit = profit + commission + swap (calculate manually)

---

🏛️ Essentials

What it does:

• Fetches all closed positions for specified day
• Calculates comprehensive statistics
• Returns structured DailyStats object
• Includes commission and swap breakdown

Key behaviors:

• Defaults to today if no date specified
• Fetches up to 10,000 positions
• Commission is usually negative
• Swap can be positive or negative
• Returns stats even if no deals (all zeros)

---

⚡ Under the Hood

MT5Sugar.get_daily_stats()
    ↓ converts date to datetime range
    ↓ calls
MT5Service.get_positions_history()
    ↓ iterates positions
    ↓ sums profit, commission, swap, volume
    ↓ returns DailyStats dataclass

Call chain:

1. Sugar converts date to datetime range (00:00:00 to 23:59:59)
2. Sugar calls Service.get_positions_history() for day
3. Sugar iterates through history_positions
4. Sugar sums: profit, commission, swap, volume
5. Returns DailyStats dataclass with results

Related files:

• Sugar: src/pymt5/mt5_sugar.py:2061
• DailyStats: src/pymt5/mt5_sugar.py:209
• Service: src/pymt5/mt5_service.py:810

---

When to Use

Use get_daily_stats() when:

• Need complete daily breakdown
• Tracking commission costs
• Analyzing net profit after fees
• Daily performance reports
• Volume analysis

Don't use when:

• Only need gross profit (use get_profit())
• Need deal details (use get_deals())
• Need multi-day statistics (call multiple times)

---

🔗 Examples

Example 1: Today's Complete Stats

from pymt5 import MT5Sugar, MT5Service, MT5Account

async def daily_report():
    account = MT5Account.create(
        user=591129415,
        password="your_password",
        grpc_server="mt5.mrpc.pro:443"
    )
    service = MT5Service(account)
    sugar = MT5Sugar(service)

    await sugar.quick_connect("FxPro-MT5 Demo")

    # Get today's statistics
    stats = await sugar.get_daily_stats()

    # Calculate net profit
    net_profit = stats.profit + stats.commission + stats.swap

    print(f"Daily Report for {stats.date}:")
    print(f"  Trades: {stats.deals_count}")
    print(f"  Volume: {stats.volume} lots")
    print(f"  Gross Profit: ${stats.profit:.2f}")
    print(f"  Commission: ${stats.commission:.2f}")
    print(f"  Swap: ${stats.swap:.2f}")
    print(f"  Net Profit: ${net_profit:.2f}")

# Output:
# Daily Report for 2026-02-03:
#   Trades: 12
#   Volume: 1.5 lots
#   Gross Profit: $180.50
#   Commission: $-15.30
#   Swap: $-2.10
#   Net Profit: $163.10

Example 2: Compare Multiple Days

from datetime import date, timedelta

async def compare_days():
    account = MT5Account.create(
        user=591129415,
        password="your_password",
        grpc_server="mt5.mrpc.pro:443"
    )
    service = MT5Service(account)
    sugar = MT5Sugar(service)

    await sugar.quick_connect("FxPro-MT5 Demo")

    # Get last 5 days
    print("Last 5 Days Performance:")

    for i in range(5):
        target = date.today() - timedelta(days=i)
        stats = await sugar.get_daily_stats(target)

        net = stats.profit + stats.commission + stats.swap

        print(f"{target}: {stats.deals_count} trades, "
              f"${net:+.2f} net P&L")

# Output:
# Last 5 Days Performance:
# 2026-02-03: 12 trades, $+163.10 net P&L
# 2026-02-02: 8 trades, $-45.20 net P&L
# 2026-02-01: 15 trades, $+220.50 net P&L

Example 3: Cost Analysis

async def cost_analysis():
    account = MT5Account.create(
        user=591129415,
        password="your_password",
        grpc_server="mt5.mrpc.pro:443"
    )
    service = MT5Service(account)
    sugar = MT5Sugar(service)

    await sugar.quick_connect("FxPro-MT5 Demo")

    stats = await sugar.get_daily_stats()

    if stats.deals_count > 0:
        # Calculate costs per trade
        avg_commission = abs(stats.commission) / stats.deals_count
        total_costs = abs(stats.commission) + abs(stats.swap)
        costs_pct = (total_costs / abs(stats.profit)) * 100 if stats.profit != 0 else 0

        print(f"Cost Analysis:")
        print(f"  Average commission per trade: ${avg_commission:.2f}")
        print(f"  Total trading costs: ${total_costs:.2f}")
        print(f"  Costs as % of gross profit: {costs_pct:.1f}%")

---

Common Pitfalls

Pitfall 1: Forgetting commission is negative

stats = await sugar.get_daily_stats()

# ERROR: Commission is already negative, don't subtract again
net_profit = stats.profit - stats.commission  # WRONG!

# CORRECT: Commission is negative, so add it
net_profit = stats.profit + stats.commission  # RIGHT

Pitfall 2: Not checking deals_count

stats = await sugar.get_daily_stats()

# Calculating average without checking for zero
avg_profit = stats.profit / stats.deals_count  # ZeroDivisionError if no deals

Solution: Always check deals_count first

stats = await sugar.get_daily_stats()

if stats.deals_count > 0:
    avg_profit = stats.profit / stats.deals_count
else:
    avg_profit = 0.0

Pitfall 3: Expecting historical data to exist

# Asking for date before account existed
stats = await sugar.get_daily_stats(date(2020, 1, 1))
# Returns all zeros, not an error

Solution: Check if data exists

stats = await sugar.get_daily_stats(date(2020, 1, 1))

if stats.deals_count == 0:
    print("No trades on this date")

---

Pro Tips

Tip 1: Calculate net profit helper

def calculate_net(stats):
    """Calculate net profit from DailyStats."""
    return stats.profit + stats.commission + stats.swap

stats = await sugar.get_daily_stats()
net = calculate_net(stats)
print(f"Net profit: ${net:.2f}")

Tip 2: Weekly summary

from datetime import date, timedelta

async def weekly_summary():
    """Aggregate weekly statistics."""
    total_deals = 0
    total_profit = 0.0
    total_commission = 0.0
    total_swap = 0.0
    total_volume = 0.0

    # Get last 7 days
    for i in range(7):
        target = date.today() - timedelta(days=i)
        stats = await sugar.get_daily_stats(target)

        total_deals += stats.deals_count
        total_profit += stats.profit
        total_commission += stats.commission
        total_swap += stats.swap
        total_volume += stats.volume

    net_profit = total_profit + total_commission + total_swap

    print(f"Weekly Summary:")
    print(f"  Total trades: {total_deals}")
    print(f"  Total volume: {total_volume} lots")
    print(f"  Net profit: ${net_profit:.2f}")

Tip 3: Profit factor calculation

async def profit_factor():
    """Calculate profit factor (gross profit / gross loss)."""
    from datetime import date, timedelta

    gross_profit = 0.0
    gross_loss = 0.0

    # Get this month
    for i in range(30):
        target = date.today() - timedelta(days=i)
        deals = await sugar.get_deals(Period.CUSTOM, target, target)

        for deal in deals:
            if deal.profit > 0:
                gross_profit += deal.profit
            else:
                gross_loss += abs(deal.profit)

    if gross_loss > 0:
        pf = gross_profit / gross_loss
        print(f"Profit Factor: {pf:.2f}")
    else:
        print("No losing trades")

---

📚 See Also

• get_deals - Get historical deals
• get_profit - Get gross profit for period
• get_total_profit - Floating profit