calculations.py

@@ -1,147 +0,0 @@
-"""
-Pure calculation functions for DCA transaction processing.
-
-These functions have no external dependencies (no lnbits, no database)
-and can be easily tested in isolation.
-"""
-
-from typing import Dict, Tuple
-
-
-def calculate_commission(
-    crypto_atoms: int,
-    commission_percentage: float,
-    discount: float = 0.0
-) -> Tuple[int, int, float]:
-    """
-    Calculate commission split from a Lamassu transaction.
-
-    The crypto_atoms from Lamassu already includes the commission baked in.
-    This function extracts the base amount (for DCA distribution) and
-    commission amount (for commission wallet).
-
-    Formula:
-        effective_commission = commission_percentage * (100 - discount) / 100
-        base_amount = round(crypto_atoms / (1 + effective_commission))
-        commission_amount = crypto_atoms - base_amount
-
-    Args:
-        crypto_atoms: Total sats from Lamassu (includes commission)
-        commission_percentage: Commission rate as decimal (e.g., 0.03 for 3%)
-        discount: Discount percentage on commission (e.g., 10.0 for 10% off)
-
-    Returns:
-        Tuple of (base_amount_sats, commission_amount_sats, effective_commission_rate)
-
-    Example:
-        >>> calculate_commission(266800, 0.03, 0.0)
-        (259029, 7771, 0.03)
-    """
-    if commission_percentage > 0:
-        effective_commission = commission_percentage * (100 - discount) / 100
-        base_crypto_atoms = round(crypto_atoms / (1 + effective_commission))
-        commission_amount_sats = crypto_atoms - base_crypto_atoms
-    else:
-        effective_commission = 0.0
-        base_crypto_atoms = crypto_atoms
-        commission_amount_sats = 0
-
-    return base_crypto_atoms, commission_amount_sats, effective_commission
-
-
-def calculate_distribution(
-    base_amount_sats: int,
-    client_balances: Dict[str, float],
-    min_balance_threshold: float = 0.01
-) -> Dict[str, int]:
-    """
-    Calculate proportional distribution of sats to clients based on their fiat balances.
-
-    Uses proportional allocation with remainder distribution to ensure
-    the total distributed equals exactly the base amount.
-
-    Args:
-        base_amount_sats: Total sats to distribute (after commission)
-        client_balances: Dict of {client_id: remaining_balance_fiat}
-        min_balance_threshold: Minimum balance to be included (default 0.01)
-
-    Returns:
-        Dict of {client_id: allocated_sats}
-
-    Example:
-        >>> calculate_distribution(100000, {"a": 500.0, "b": 500.0})
-        {"a": 50000, "b": 50000}
-    """
-    # Filter out clients with balance below threshold
-    active_balances = {
-        client_id: balance
-        for client_id, balance in client_balances.items()
-        if balance >= min_balance_threshold
-    }
-
-    if not active_balances:
-        return {}
-
-    total_balance = sum(active_balances.values())
-
-    if total_balance == 0:
-        return {}
-
-    # First pass: calculate base allocations and track for remainder distribution
-    client_calculations = []
-    distributed_sats = 0
-
-    for client_id, balance in active_balances.items():
-        proportion = balance / total_balance
-        exact_share = base_amount_sats * proportion
-        allocated_sats = round(exact_share)
-
-        client_calculations.append({
-            'client_id': client_id,
-            'proportion': proportion,
-            'exact_share': exact_share,
-            'allocated_sats': allocated_sats,
-        })
-        distributed_sats += allocated_sats
-
-    # Handle remainder due to rounding
-    remainder = base_amount_sats - distributed_sats
-
-    if remainder != 0:
-        # Sort by largest fractional remainder to distribute fairly
-        client_calculations.sort(
-            key=lambda x: x['exact_share'] - x['allocated_sats'],
-            reverse=True
-        )
-
-        # Distribute remainder one sat at a time
-        for i in range(abs(remainder)):
-            idx = i % len(client_calculations)
-            if remainder > 0:
-                client_calculations[idx]['allocated_sats'] += 1
-            else:
-                client_calculations[idx]['allocated_sats'] -= 1
-
-    # Build final distributions dict
-    distributions = {
-        calc['client_id']: calc['allocated_sats']
-        for calc in client_calculations
-    }
-
-    return distributions
-
-
-def calculate_exchange_rate(base_crypto_atoms: int, fiat_amount: float) -> float:
-    """
-    Calculate exchange rate in sats per fiat unit.
-
-    Args:
-        base_crypto_atoms: Base amount in sats (after commission)
-        fiat_amount: Fiat amount dispensed
-
-    Returns:
-        Exchange rate as sats per fiat unit
-    """
-    if fiat_amount <= 0:
-        return 0.0
-    return base_crypto_atoms / fiat_amount

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "satmachineadmin"
-version = "0.0.4"
+version = "0.0.0"
 description = "Eightball is a simple API that allows you to create a random number generator."
 authors = ["benarc", "dni <dni@lnbits.com>"]
 

static/js/index.js

@@ -670,7 +670,7 @@ window.app = Vue.createApp({
       } catch (error) {
         LNbits.utils.notifyApiError(error)
       } finally {
-        this.processingSpecificTransaction = false
+        this.runningTestTransaction = false
       }
     },
 

tests/test_calculations.py

@@ -1,381 +0,0 @@
-"""
-Tests for DCA transaction calculations using empirical data.
-
-These tests verify commission and distribution calculations against
-real Lamassu transaction data to ensure the math is correct.
-"""
-
-import pytest
-from decimal import Decimal
-from typing import Dict, List, Tuple
-
-# Import from the parent package (following lnurlp pattern)
-from ..calculations import calculate_commission, calculate_distribution, calculate_exchange_rate
-
-
-# =============================================================================
-# COMMISSION CALCULATION TESTS
-# =============================================================================
-
-class TestCommissionCalculation:
-    """Tests for commission calculation logic."""
-
-    # Empirical test cases: (crypto_atoms, commission%, discount%, expected_base, expected_commission)
-    # Formula: base = round(crypto_atoms / (1 + effective_commission))
-    # Where: effective_commission = commission_percentage * (100 - discount) / 100
-    EMPIRICAL_COMMISSION_CASES = [
-        # =============================================================
-        # REAL LAMASSU TRANSACTIONS (extracted from production database)
-        # =============================================================
-
-        # 8.75% commission, no discount - small transaction
-        # 15600 / 1.0875 = 14344.827... → 14345
-        (15600, 0.0875, 0.0, 14345, 1255),
-
-        # 8.75% commission, no discount - large transaction
-        # 309200 / 1.0875 = 284322.298... → 284322
-        (309200, 0.0875, 0.0, 284322, 24878),
-
-        # 5.5% commission, no discount
-        # 309500 / 1.055 = 293364.928... → 293365
-        (309500, 0.055, 0.0, 293365, 16135),
-
-        # 5.5% commission with 100% discount (no commission charged)
-        # effective = 0.055 * (100-100)/100 = 0
-        (292400, 0.055, 100.0, 292400, 0),
-
-        # 5.5% commission with 90% discount
-        # effective = 0.055 * (100-90)/100 = 0.0055
-        # 115000 / 1.0055 = 114370.96... → 114371
-        (115000, 0.055, 90.0, 114371, 629),
-
-        # 5.5% commission, no discount - 1300 GTQ transaction
-        # 205600 / 1.055 = 194881.516... → 194882
-        # Note: This tx showed 0.01 GTQ rounding discrepancy in per-client fiat
-        (205600, 0.055, 0.0, 194882, 10718),
-
-        # =============================================================
-        # SYNTHETIC TEST CASES (edge cases)
-        # =============================================================
-
-        # Zero commission - all goes to base
-        (100000, 0.0, 0.0, 100000, 0),
-
-        # Small amount edge case (1 sat minimum)
-        (100, 0.03, 0.0, 97, 3),
-    ]
-
-    @pytest.mark.parametrize(
-        "crypto_atoms,commission_pct,discount,expected_base,expected_commission",
-        EMPIRICAL_COMMISSION_CASES,
-        ids=[
-            "lamassu_8.75pct_small",
-            "lamassu_8.75pct_large",
-            "lamassu_5.5pct_no_discount",
-            "lamassu_5.5pct_100pct_discount",
-            "lamassu_5.5pct_90pct_discount",
-            "lamassu_5.5pct_1300gtq",
-            "zero_commission",
-            "small_amount_100sats",
-        ]
-    )
-    def test_commission_calculation(
-        self,
-        crypto_atoms: int,
-        commission_pct: float,
-        discount: float,
-        expected_base: int,
-        expected_commission: int
-    ):
-        """Test commission calculation against empirical data."""
-        base, commission, _ = calculate_commission(crypto_atoms, commission_pct, discount)
-
-        assert base == expected_base, f"Base amount mismatch: got {base}, expected {expected_base}"
-        assert commission == expected_commission, f"Commission mismatch: got {commission}, expected {expected_commission}"
-
-        # Invariant: base + commission must equal total
-        assert base + commission == crypto_atoms, "Base + commission must equal total crypto_atoms"
-
-    def test_commission_invariant_always_sums_to_total(self):
-        """Commission + base must always equal the original amount."""
-        test_values = [1, 100, 1000, 10000, 100000, 266800, 1000000]
-        commission_rates = [0.0, 0.01, 0.03, 0.05, 0.10]
-        discounts = [0.0, 10.0, 25.0, 50.0]
-
-        for crypto_atoms in test_values:
-            for comm_rate in commission_rates:
-                for discount in discounts:
-                    base, commission, _ = calculate_commission(crypto_atoms, comm_rate, discount)
-                    assert base + commission == crypto_atoms, \
-                        f"Invariant failed: {base} + {commission} != {crypto_atoms} " \
-                        f"(rate={comm_rate}, discount={discount})"
-
-
-# =============================================================================
-# DISTRIBUTION CALCULATION TESTS
-# =============================================================================
-
-class TestDistributionCalculation:
-    """Tests for proportional distribution logic."""
-
-    def test_single_client_gets_all(self):
-        """Single client should receive entire distribution."""
-        distributions = calculate_distribution(
-            base_amount_sats=100000,
-            client_balances={"client_a": 500.00}
-        )
-
-        assert distributions == {"client_a": 100000}
-
-    def test_two_clients_equal_balance(self):
-        """Two clients with equal balance should split evenly."""
-        distributions = calculate_distribution(
-            base_amount_sats=100000,
-            client_balances={
-                "client_a": 500.00,
-                "client_b": 500.00
-            }
-        )
-
-        assert distributions["client_a"] == 50000
-        assert distributions["client_b"] == 50000
-        assert sum(distributions.values()) == 100000
-
-    def test_two_clients_unequal_balance(self):
-        """Two clients with 75/25 balance split."""
-        distributions = calculate_distribution(
-            base_amount_sats=100000,
-            client_balances={
-                "client_a": 750.00,
-                "client_b": 250.00
-            }
-        )
-
-        assert distributions["client_a"] == 75000
-        assert distributions["client_b"] == 25000
-        assert sum(distributions.values()) == 100000
-
-    def test_distribution_invariant_sums_to_total(self):
-        """Total distributed sats must always equal base amount."""
-        # Test with various client configurations
-        test_cases = [
-            {"a": 100.0},
-            {"a": 100.0, "b": 100.0},
-            {"a": 100.0, "b": 200.0, "c": 300.0},
-            {"a": 33.33, "b": 33.33, "c": 33.34},  # Tricky rounding case
-            {"a": 1000.0, "b": 1.0},  # Large imbalance
-        ]
-
-        for client_balances in test_cases:
-            for base_amount in [100, 1000, 10000, 100000, 258835]:
-                distributions = calculate_distribution(base_amount, client_balances)
-                total_distributed = sum(distributions.values())
-
-                assert total_distributed == base_amount, \
-                    f"Distribution sum {total_distributed} != base {base_amount} " \
-                    f"for balances {client_balances}"
-
-    def test_zero_balance_client_excluded(self):
-        """Clients with zero balance should be excluded."""
-        distributions = calculate_distribution(
-            base_amount_sats=100000,
-            client_balances={
-                "client_a": 500.00,
-                "client_b": 0.0,
-                "client_c": 500.00
-            }
-        )
-
-        assert "client_b" not in distributions
-        assert distributions["client_a"] == 50000
-        assert distributions["client_c"] == 50000
-
-    def test_tiny_balance_excluded(self):
-        """Clients with balance < 0.01 should be excluded."""
-        distributions = calculate_distribution(
-            base_amount_sats=100000,
-            client_balances={
-                "client_a": 500.00,
-                "client_b": 0.005,  # Less than threshold
-            }
-        )
-
-        assert "client_b" not in distributions
-        assert distributions["client_a"] == 100000
-
-    def test_no_eligible_clients_returns_empty(self):
-        """If no clients have balance, return empty distribution."""
-        distributions = calculate_distribution(
-            base_amount_sats=100000,
-            client_balances={
-                "client_a": 0.0,
-                "client_b": 0.0,
-            }
-        )
-
-        assert distributions == {}
-
-    def test_fiat_round_trip_invariant(self):
-        """
-        Verify that distributed sats convert back to original fiat amount.
-
-        The sum of each client's fiat equivalent should equal the original
-        fiat amount (within rounding tolerance).
-        """
-        # Use real Lamassu transaction data
-        test_cases = [
-            # (crypto_atoms, fiat_amount, commission_pct, discount, client_balances)
-            (309200, 2000.0, 0.0875, 0.0, {"a": 1000.0, "b": 1000.0}),
-            (309500, 2000.0, 0.055, 0.0, {"a": 500.0, "b": 1000.0, "c": 500.0}),
-            (292400, 2000.0, 0.055, 100.0, {"a": 800.0, "b": 1200.0}),
-            (115000, 800.0, 0.055, 90.0, {"a": 400.0, "b": 400.0}),
-            # Transaction that showed 0.01 GTQ rounding discrepancy with 4 clients
-            (205600, 1300.0, 0.055, 0.0, {"a": 1.0, "b": 986.0, "c": 14.0, "d": 4.0}),
-        ]
-
-        for crypto_atoms, fiat_amount, comm_pct, discount, client_balances in test_cases:
-            # Calculate commission and base amount
-            base_sats, _, _ = calculate_commission(crypto_atoms, comm_pct, discount)
-
-            # Calculate exchange rate
-            exchange_rate = calculate_exchange_rate(base_sats, fiat_amount)
-
-            # Distribute sats to clients
-            distributions = calculate_distribution(base_sats, client_balances)
-
-            # Convert each client's sats back to fiat
-            total_fiat_distributed = sum(
-                sats / exchange_rate for sats in distributions.values()
-            )
-
-            # Should equal original fiat amount (within small rounding tolerance)
-            assert abs(total_fiat_distributed - fiat_amount) < 0.01, \
-                f"Fiat round-trip failed: {total_fiat_distributed:.2f} != {fiat_amount:.2f} " \
-                f"(crypto={crypto_atoms}, comm={comm_pct}, discount={discount})"
-
-
-# =============================================================================
-# EMPIRICAL END-TO-END TESTS
-# =============================================================================
-
-class TestEmpiricalTransactions:
-    """
-    End-to-end tests using real Lamassu transaction data.
-
-    Add your empirical test cases here! Each case should include:
-    - Transaction details (crypto_atoms, fiat, commission, discount)
-    - Client balances at time of transaction
-    - Expected distribution outcome
-    """
-
-    # TODO: Add your empirical data here
-    # Example structure:
-    EMPIRICAL_SCENARIOS = [
-        {
-            "name": "real_tx_266800sats_two_equal_clients",
-            "transaction": {
-                "crypto_atoms": 266800,
-                "fiat_amount": 2000,
-                "commission_percentage": 0.03,
-                "discount": 0.0,
-            },
-            "client_balances": {
-                "client_a": 1000.00,  # 50% of total
-                "client_b": 1000.00,  # 50% of total
-            },
-            # 266800 / 1.03 = 259029
-            "expected_base_sats": 259029,
-            "expected_commission_sats": 7771,
-            "expected_distributions": {
-                # 259029 / 2 = 129514.5 → both get 129514 or 129515
-                # With banker's rounding: 129514.5 → 129514 (even)
-                # Remainder of 1 sat goes to first client by fractional sort
-                "client_a": 129515,
-                "client_b": 129514,
-            },
-        },
-        # Add more scenarios from your real data!
-    ]
-
-    @pytest.mark.parametrize(
-        "scenario",
-        EMPIRICAL_SCENARIOS,
-        ids=[s["name"] for s in EMPIRICAL_SCENARIOS]
-    )
-    def test_empirical_scenario(self, scenario):
-        """Test full transaction flow against empirical data."""
-        tx = scenario["transaction"]
-
-        # Calculate commission
-        base, commission, _ = calculate_commission(
-            tx["crypto_atoms"],
-            tx["commission_percentage"],
-            tx["discount"]
-        )
-
-        assert base == scenario["expected_base_sats"], \
-            f"Base amount mismatch in {scenario['name']}"
-        assert commission == scenario["expected_commission_sats"], \
-            f"Commission mismatch in {scenario['name']}"
-
-        # Calculate distribution
-        distributions = calculate_distribution(
-            base,
-            scenario["client_balances"]
-        )
-
-        # Verify each client's allocation
-        for client_id, expected_sats in scenario["expected_distributions"].items():
-            actual_sats = distributions.get(client_id, 0)
-            assert actual_sats == expected_sats, \
-                f"Distribution mismatch for {client_id} in {scenario['name']}: " \
-                f"got {actual_sats}, expected {expected_sats}"
-
-        # Verify total distribution equals base
-        assert sum(distributions.values()) == base, \
-            f"Total distribution doesn't match base in {scenario['name']}"
-
-
-# =============================================================================
-# EDGE CASE TESTS
-# =============================================================================
-
-class TestEdgeCases:
-    """Tests for edge cases and boundary conditions."""
-
-    def test_minimum_amount_1_sat(self):
-        """Test with minimum possible amount (1 sat)."""
-        base, commission, _ = calculate_commission(1, 0.03, 0.0)
-        # With 3% commission on 1 sat, base rounds to 1, commission to 0
-        assert base + commission == 1
-
-    def test_large_transaction(self):
-        """Test with large transaction (100 BTC worth of sats)."""
-        crypto_atoms = 10_000_000_000  # 100 BTC in sats
-        base, commission, _ = calculate_commission(crypto_atoms, 0.03, 0.0)
-
-        assert base + commission == crypto_atoms
-        assert commission > 0
-
-    def test_100_percent_discount(self):
-        """100% discount should result in zero commission."""
-        base, commission, effective = calculate_commission(100000, 0.03, 100.0)
-
-        assert effective == 0.0
-        assert commission == 0
-        assert base == 100000
-
-    def test_many_clients_distribution(self):
-        """Test distribution with many clients."""
-        # 10 clients with varying balances
-        client_balances = {f"client_{i}": float(i * 100) for i in range(1, 11)}
-
-        distributions = calculate_distribution(1000000, client_balances)
-
-        assert len(distributions) == 10
-        assert sum(distributions.values()) == 1000000
-
-        # Verify proportionality (client_10 should get ~18% with balance 1000)
-        # Total balance = 100+200+...+1000 = 5500
-        # client_10 proportion = 1000/5500 ≈ 18.18%
-        assert distributions["client_10"] > distributions["client_1"]

transaction_processor.py

@@ -26,7 +26,6 @@ from lnbits.core.crud.wallets import get_wallet
 from lnbits.core.services import update_wallet_balance
 from lnbits.settings import settings
 
-from .calculations import calculate_commission, calculate_distribution, calculate_exchange_rate
 from .crud import (
     get_flow_mode_clients,
     get_payments_by_lamassu_transaction,
@@ -669,21 +668,15 @@ class LamassuTransactionProcessor:
             logger.error(f"Error fetching transactions from Lamassu database: {e}")
             return []
     
-    async def calculate_distribution_amounts(self, transaction: Dict[str, Any]) -> tuple[Dict[str, Any], int]:
-        """Calculate how much each Flow Mode client should receive.
-
-        Returns:
-            tuple: (distributions dict, orphan_sats int)
-            - distributions: {client_id: {fiat_amount, sats_amount, exchange_rate}}
-            - orphan_sats: sats that couldn't be distributed due to sync mismatch
-        """
+    async def calculate_distribution_amounts(self, transaction: Dict[str, Any]) -> Dict[str, int]:
+        """Calculate how much each Flow Mode client should receive"""
         try:
             # Get all active Flow Mode clients
             flow_clients = await get_flow_mode_clients()
-
+            
             if not flow_clients:
                 logger.info("No Flow Mode clients found - skipping distribution")
-                return {}, 0
+                return {}
             
             # Extract transaction details - guaranteed clean from data ingestion
             crypto_atoms = transaction.get("crypto_amount", 0)  # Total sats with commission baked in
@@ -707,10 +700,10 @@ class LamassuTransactionProcessor:
             # Validate required fields
             if crypto_atoms is None:
                 logger.error(f"Missing crypto_amount in transaction: {transaction}")
-                return {}, 0
+                return {}
             if fiat_amount is None:
                 logger.error(f"Missing fiat_amount in transaction: {transaction}")
-                return {}, 0
+                return {}
             if commission_percentage is None:
                 logger.warning(f"Missing commission_percentage in transaction: {transaction}, defaulting to 0")
                 commission_percentage = 0.0
@@ -722,13 +715,21 @@ class LamassuTransactionProcessor:
                 # Could use current time as fallback, but this indicates a data issue
                 # transaction_time = datetime.now(timezone.utc)
             
-            # Calculate commission split using the extracted pure function
-            base_crypto_atoms, commission_amount_sats, effective_commission = calculate_commission(
-                crypto_atoms, commission_percentage, discount
-            )
-
+            # Calculate effective commission percentage after discount (following the reference logic)
+            if commission_percentage > 0:
+                effective_commission = commission_percentage * (100 - discount) / 100
+                # Since crypto_atoms already includes commission, we need to extract the base amount
+                # Formula: crypto_atoms = base_amount * (1 + effective_commission)
+                # Therefore: base_amount = crypto_atoms / (1 + effective_commission)
+                base_crypto_atoms = round(crypto_atoms / (1 + effective_commission))
+                commission_amount_sats = crypto_atoms - base_crypto_atoms
+            else:
+                effective_commission = 0.0
+                base_crypto_atoms = crypto_atoms
+                commission_amount_sats = 0
+            
             # Calculate exchange rate based on base amounts
-            exchange_rate = calculate_exchange_rate(base_crypto_atoms, fiat_amount)
+            exchange_rate = base_crypto_atoms / fiat_amount if fiat_amount > 0 else 0  # sats per fiat unit
             
             logger.info(f"Transaction - Total crypto: {crypto_atoms} sats")
             logger.info(f"Commission: {commission_percentage*100:.1f}% - {discount:.1f}% discount = {effective_commission*100:.1f}% effective ({commission_amount_sats} sats)")
@@ -756,76 +757,75 @@ class LamassuTransactionProcessor:
             
             if total_confirmed_deposits == 0:
                 logger.info("No clients with remaining DCA balance - skipping distribution")
-                return {}, 0
-
-            # Detect sync mismatch: more money in ATM than tracked client balances
-            sync_mismatch = total_confirmed_deposits < fiat_amount
-            if sync_mismatch:
-                orphan_fiat = fiat_amount - total_confirmed_deposits
-                logger.warning(
-                    f"Sync mismatch detected: tracked balances ({total_confirmed_deposits:.2f} GTQ) "
-                    f"< transaction ({fiat_amount} GTQ). Orphan amount: {orphan_fiat:.2f} GTQ"
-                )
-
-            # Calculate distribution amounts
+                return {}
+            
+            # Calculate proportional distribution with remainder allocation
             distributions = {}
-
-            if sync_mismatch:
-                # SYNC MISMATCH MODE: Cap each client's allocation to their remaining fiat balance
-                # Each client gets sats equivalent to their full remaining balance
-                for client_id, client_balance in client_balances.items():
-                    # Calculate sats equivalent to this client's remaining fiat balance
-                    client_sats_amount = round(client_balance * exchange_rate)
-                    proportion = client_balance / total_confirmed_deposits
-
-                    # Calculate equivalent fiat value in GTQ for tracking purposes
-                    client_fiat_amount = round(client_sats_amount / exchange_rate, 2) if exchange_rate > 0 else 0.0
-
-                    distributions[client_id] = {
-                        "fiat_amount": client_fiat_amount,
-                        "sats_amount": client_sats_amount,
-                        "exchange_rate": exchange_rate
-                    }
-
-                    logger.info(f"Client {client_id[:8]}... gets {client_sats_amount} sats (≈{client_fiat_amount:.2f} GTQ, {proportion:.2%} share)")
-
-                # Calculate orphan sats (difference between base amount and distributed)
-                total_distributed = sum(dist["sats_amount"] for dist in distributions.values())
-                orphan_sats = base_crypto_atoms - total_distributed
-                logger.info(
-                    f"Sync mismatch distribution: {total_distributed} sats to clients, "
-                    f"{orphan_sats} sats orphaned (staying in source wallet)"
+            distributed_sats = 0
+            client_calculations = []
+            
+            # First pass: calculate base amounts and track remainders
+            for client_id, client_balance in client_balances.items():
+                # Calculate this client's proportion of the total DCA pool
+                proportion = client_balance / total_confirmed_deposits
+                
+                # Calculate exact share (with decimals)
+                exact_share = base_crypto_atoms * proportion
+                
+                # Use banker's rounding for base allocation
+                client_sats_amount = round(exact_share)
+                
+                client_calculations.append({
+                    'client_id': client_id,
+                    'proportion': proportion,
+                    'exact_share': exact_share,
+                    'allocated_sats': client_sats_amount,
+                    'client_balance': client_balance
+                })
+                
+                distributed_sats += client_sats_amount
+            
+            # Handle any remainder due to rounding (should be small)
+            remainder = base_crypto_atoms - distributed_sats
+            
+            if remainder != 0:
+                logger.info(f"Distributing remainder: {remainder} sats among {len(client_calculations)} clients")
+                
+                # Sort clients by largest fractional remainder to distribute fairly
+                client_calculations.sort(
+                    key=lambda x: x['exact_share'] - x['allocated_sats'], 
+                    reverse=True
                 )
-            else:
-                # NORMAL MODE: Proportional distribution based on transaction amount
-                sat_allocations = calculate_distribution(base_crypto_atoms, client_balances)
-
-                if not sat_allocations:
-                    logger.info("No allocations calculated - skipping distribution")
-                    return {}, 0
-
-                # Build final distributions dict with additional tracking fields
-                for client_id, client_sats_amount in sat_allocations.items():
-                    # Calculate proportion for logging
-                    proportion = client_balances[client_id] / total_confirmed_deposits
-
-                    # Calculate equivalent fiat value in GTQ for tracking purposes
-                    client_fiat_amount = round(client_sats_amount / exchange_rate, 2) if exchange_rate > 0 else 0.0
-
-                    distributions[client_id] = {
-                        "fiat_amount": client_fiat_amount,
-                        "sats_amount": client_sats_amount,
-                        "exchange_rate": exchange_rate
-                    }
-
-                    logger.info(f"Client {client_id[:8]}... gets {client_sats_amount} sats (≈{client_fiat_amount:.2f} GTQ, {proportion:.2%} share)")
-
-                # Verification: ensure total distribution equals base amount
-                total_distributed = sum(dist["sats_amount"] for dist in distributions.values())
-                if total_distributed != base_crypto_atoms:
-                    logger.error(f"Distribution mismatch! Expected: {base_crypto_atoms} sats, Distributed: {total_distributed} sats")
-                    raise ValueError(f"Satoshi distribution calculation error: {base_crypto_atoms} != {total_distributed}")
-                orphan_sats = 0
+                
+                # Distribute remainder one sat at a time to clients with largest fractional parts
+                for i in range(abs(remainder)):
+                    if remainder > 0:
+                        client_calculations[i % len(client_calculations)]['allocated_sats'] += 1
+                    else:
+                        client_calculations[i % len(client_calculations)]['allocated_sats'] -= 1
+            
+            # Second pass: create distributions with final amounts
+            for calc in client_calculations:
+                client_id = calc['client_id']
+                client_sats_amount = calc['allocated_sats']
+                proportion = calc['proportion']
+                
+                # Calculate equivalent fiat value in GTQ for tracking purposes
+                client_fiat_amount = round(client_sats_amount / exchange_rate, 2) if exchange_rate > 0 else 0.0
+                
+                distributions[client_id] = {
+                    "fiat_amount": client_fiat_amount,
+                    "sats_amount": client_sats_amount,
+                    "exchange_rate": exchange_rate
+                }
+                
+                logger.info(f"Client {client_id[:8]}... gets {client_sats_amount} sats (≈{client_fiat_amount:.2f} GTQ, {proportion:.2%} share)")
+            
+            # Verification: ensure total distribution equals base amount
+            total_distributed = sum(dist["sats_amount"] for dist in distributions.values())
+            if total_distributed != base_crypto_atoms:
+                logger.error(f"Distribution mismatch! Expected: {base_crypto_atoms} sats, Distributed: {total_distributed} sats")
+                raise ValueError(f"Satoshi distribution calculation error: {base_crypto_atoms} != {total_distributed}")
             
             # Safety check: Re-verify all clients still have positive balances before finalizing distributions
             # This prevents race conditions where balances changed during calculation
@@ -845,18 +845,18 @@ class LamassuTransactionProcessor:
                 # Recalculate proportions if some clients were rejected
                 if len(final_distributions) == 0:
                     logger.info("All clients rejected due to negative balances - no distributions")
-                    return {}, orphan_sats
-
+                    return {}
+                
                 # For simplicity, we'll still return the original distributions but log the warning
                 # In a production system, you might want to recalculate the entire distribution
                 logger.warning("Proceeding with original distribution despite balance warnings - manual review recommended")
-
+            
             logger.info(f"Distribution verified: {total_distributed} sats distributed across {len(distributions)} clients (clients with positive allocations only)")
-            return distributions, orphan_sats
-
+            return distributions
+            
         except Exception as e:
             logger.error(f"Error calculating distribution amounts: {e}")
-            return {}, 0
+            return {}
     
     async def distribute_to_clients(self, transaction: Dict[str, Any], distributions: Dict[str, Dict[str, int]]) -> None:
         """Send Bitcoin payments to DCA clients"""
@@ -965,7 +965,7 @@ class LamassuTransactionProcessor:
             }
             new_payment = await create_invoice(
                 wallet_id=target_wallet.id,
-                amount=float(amount_sats),  # LNBits create_invoice expects float
+                amount=amount_sats,  # LNBits create_invoice expects sats
                 internal=True,  # Internal transfer within LNBits
                 memo=memo,
                 extra=extra
@@ -1062,13 +1062,18 @@ class LamassuTransactionProcessor:
                 elif transaction_time.tzinfo != timezone.utc:
                     transaction_time = transaction_time.astimezone(timezone.utc)
             
-            # Calculate commission metrics using the extracted pure function
-            base_crypto_atoms, commission_amount_sats, effective_commission = calculate_commission(
-                crypto_atoms, commission_percentage, discount
-            )
-
+            # Calculate commission metrics
+            if commission_percentage > 0:
+                effective_commission = commission_percentage * (100 - discount) / 100
+                base_crypto_atoms = round(crypto_atoms / (1 + effective_commission))
+                commission_amount_sats = crypto_atoms - base_crypto_atoms
+            else:
+                effective_commission = 0.0
+                base_crypto_atoms = crypto_atoms
+                commission_amount_sats = 0
+            
             # Calculate exchange rate
-            exchange_rate = calculate_exchange_rate(base_crypto_atoms, fiat_amount)
+            exchange_rate = base_crypto_atoms / fiat_amount if fiat_amount > 0 else 0
             
             # Create transaction data with GTQ amounts
             transaction_data = CreateLamassuTransactionData(
@@ -1130,7 +1135,7 @@ class LamassuTransactionProcessor:
             
             commission_payment = await create_invoice(
                 wallet_id=admin_config.commission_wallet_id,
-                amount=float(commission_amount_sats),  # LNbits create_invoice expects float
+                amount=commission_amount_sats,
                 internal=True,
                 memo=commission_memo,
                 extra={
@@ -1185,16 +1190,10 @@ class LamassuTransactionProcessor:
             stored_transaction = await self.store_lamassu_transaction(transaction)
             
             # Calculate distribution amounts
-            distributions, orphan_sats = await self.calculate_distribution_amounts(transaction)
-
+            distributions = await self.calculate_distribution_amounts(transaction)
+            
             if not distributions:
-                if orphan_sats > 0:
-                    logger.warning(
-                        f"No client distributions for transaction {transaction_id}, "
-                        f"but {orphan_sats} orphan sats remain in source wallet"
-                    )
-                else:
-                    logger.info(f"No distributions calculated for transaction {transaction_id}")
+                logger.info(f"No distributions calculated for transaction {transaction_id}")
                 return
             
             # Calculate commission amount for sending to commission wallet
@@ -1202,10 +1201,12 @@ class LamassuTransactionProcessor:
             commission_percentage = transaction.get("commission_percentage", 0.0)
             discount = transaction.get("discount", 0.0)
             
-            # Calculate commission amount using the extracted pure function
-            _, commission_amount_sats, _ = calculate_commission(
-                crypto_atoms, commission_percentage, discount
-            )
+            if commission_percentage and commission_percentage > 0:
+                effective_commission = commission_percentage * (100 - discount) / 100
+                base_crypto_atoms = round(crypto_atoms / (1 + effective_commission))
+                commission_amount_sats = crypto_atoms - base_crypto_atoms
+            else:
+                commission_amount_sats = 0
             
             # Distribute to clients
             await self.distribute_to_clients(transaction, distributions)

views.py

@@ -1,11 +1,9 @@
 # Description: DCA Admin page endpoints.
 
-from http import HTTPStatus
-
-from fastapi import APIRouter, Depends, HTTPException, Request
+from fastapi import APIRouter, Depends, Request
 from fastapi.responses import HTMLResponse
 from lnbits.core.models import User
-from lnbits.decorators import check_user_exists
+from lnbits.decorators import check_super_user
 from lnbits.helpers import template_renderer
 
 satmachineadmin_generic_router = APIRouter()
@@ -17,11 +15,7 @@ def satmachineadmin_renderer():
 
 # DCA Admin page - Requires superuser access
 @satmachineadmin_generic_router.get("/", response_class=HTMLResponse)
-async def index(req: Request, user: User = Depends(check_user_exists)):
-    if not user.super_user:
-        raise HTTPException(
-            HTTPStatus.FORBIDDEN, "User not authorized. No super user privileges."
-        )
+async def index(req: Request, user: User = Depends(check_super_user)):
     return satmachineadmin_renderer().TemplateResponse(
         "satmachineadmin/index.html", {"request": req, "user": user.json()}
     )