T2: Pydantic v2 — replace @dataclass with BaseModel

- All domain models now use pydantic.BaseModel
- Removed manual to_dict()/from_dict() — use model_dump(mode='json')/model_validate()
- Added field validators:
  - Account.balance >= 0
  - Transaction.amount != 0
  - RecurringCashflow.amount != 0, frequency in {daily, weekly, monthly, yearly}
  - Liability.interest, payment >= 0
  - ExchangeRate.rate > 0
  - ForecastScenario.multipliers >= 0
- pydantic v2 native UUID handling (auto str in JSON)
- Updated excel_sync.py to use model_validate()
- Updated tests/test_model.py and tests/test_currency.py
- Added pydantic>=2.0 to pyproject.toml

Tests: 63/63 pass.

domain/account.py

@@ -1,27 +1,17 @@
-from dataclasses import dataclass, field
 from uuid import UUID, uuid4
 
+from pydantic import BaseModel, Field, field_validator
 
-@dataclass
-class Account:
-    id: UUID = field(default_factory=uuid4)
+
+class Account(BaseModel):
+    id: UUID = Field(default_factory=uuid4)
     name: str = ""
     currency: str = "USD"
     balance: float = 0.0
 
-    def to_dict(self) -> dict:
-        return {
-            "id": str(self.id),
-            "name": self.name,
-            "currency": self.currency,
-            "balance": self.balance,
-        }
-
+    @field_validator("balance")
     @classmethod
-    def from_dict(cls, data: dict) -> "Account":
-        return cls(
-            id=UUID(data["id"]),
-            name=data["name"],
-            currency=data.get("currency", "USD"),
-            balance=data.get("balance", 0.0),
-        )
+    def _balance_non_negative(cls, v: float) -> float:
+        if v < 0:
+            raise ValueError("balance must be non-negative")
+        return v

domain/asset.py

@@ -1,27 +1,10 @@
-from dataclasses import dataclass, field
 from uuid import UUID, uuid4
 
+from pydantic import BaseModel, Field
 
-@dataclass
-class Asset:
-    id: UUID = field(default_factory=uuid4)
+
+class Asset(BaseModel):
+    id: UUID = Field(default_factory=uuid4)
     name: str = ""
     value: float = 0.0
     growth_rate: float = 0.0
-
-    def to_dict(self) -> dict:
-        return {
-            "id": str(self.id),
-            "name": self.name,
-            "value": self.value,
-            "growth_rate": self.growth_rate,
-        }
-
-    @classmethod
-    def from_dict(cls, data: dict) -> "Asset":
-        return cls(
-            id=UUID(data["id"]),
-            name=data["name"],
-            value=data.get("value", 0.0),
-            growth_rate=data.get("growth_rate", 0.0),
-        )

domain/currency.py

@@ -1,4 +1,4 @@
-from dataclasses import dataclass
+from pydantic import BaseModel, Field, field_validator
 
 CURRENCY_SYMBOLS = {
     "RUB": "₽",
@@ -12,26 +12,17 @@ CURRENCY_SYMBOLS = {
 }
 
 
-@dataclass
-class ExchangeRate:
+class ExchangeRate(BaseModel):
     from_currency: str = "USD"
     to_currency: str = "RUB"
     rate: float = 80.0
 
-    def to_dict(self) -> dict:
-        return {
-            "from_currency": self.from_currency,
-            "to_currency": self.to_currency,
-            "rate": self.rate,
-        }
-
+    @field_validator("rate")
     @classmethod
-    def from_dict(cls, data: dict) -> "ExchangeRate":
-        return cls(
-            from_currency=data.get("from_currency", "USD"),
-            to_currency=data.get("to_currency", "RUB"),
-            rate=data.get("rate", 80.0),
-        )
+    def _rate_positive(cls, v: float) -> float:
+        if v <= 0:
+            raise ValueError("rate must be positive")
+        return v
 
 
 DEFAULT_RATES: list[ExchangeRate] = [

domain/liability.py

@@ -1,30 +1,18 @@
-from dataclasses import dataclass, field
 from uuid import UUID, uuid4
 
+from pydantic import BaseModel, Field, field_validator
 
-@dataclass
-class Liability:
-    id: UUID = field(default_factory=uuid4)
+
+class Liability(BaseModel):
+    id: UUID = Field(default_factory=uuid4)
     name: str = ""
     balance: float = 0.0
     interest: float = 0.0
     payment: float = 0.0
 
-    def to_dict(self) -> dict:
-        return {
-            "id": str(self.id),
-            "name": self.name,
-            "balance": self.balance,
-            "interest": self.interest,
-            "payment": self.payment,
-        }
-
+    @field_validator("interest", "payment")
     @classmethod
-    def from_dict(cls, data: dict) -> "Liability":
-        return cls(
-            id=UUID(data["id"]),
-            name=data["name"],
-            balance=data.get("balance", 0.0),
-            interest=data.get("interest", 0.0),
-            payment=data.get("payment", 0.0),
-        )
+    def _non_negative(cls, v: float) -> float:
+        if v < 0:
+            raise ValueError("must be non-negative")
+        return v

domain/model.py

@@ -1,7 +1,8 @@
 import json
-from dataclasses import dataclass, field
 from pathlib import Path
 
+from pydantic import BaseModel, Field
+
 from domain.account import Account
 from domain.asset import Asset
 from domain.currency import DEFAULT_RATES, ExchangeRate
@@ -11,37 +12,41 @@ from domain.scenario import ForecastScenario
 from domain.transaction import Transaction
 
 
-@dataclass
-class FinancialModel:
-    base_currency: str = "RUB"
-    accounts: list[Account] = field(default_factory=list)
-    transactions: list[Transaction] = field(default_factory=list)
-    recurring: list[RecurringCashflow] = field(default_factory=list)
-    assets: list[Asset] = field(default_factory=list)
-    liabilities: list[Liability] = field(default_factory=list)
-    scenarios: list[ForecastScenario] = field(default_factory=list)
-    exchange_rates: list[ExchangeRate] = field(default_factory=lambda: DEFAULT_RATES.copy())
+class FinancialModel(BaseModel):
+    """Корневая модель финансового плана."""
 
-    SCHEMA_VERSION = 1
+    SCHEMA_VERSION: int = 1  # NB: не Field — это class-level metadata, не pydantic field
+
+    base_currency: str = "RUB"
+    accounts: list[Account] = Field(default_factory=list)
+    transactions: list[Transaction] = Field(default_factory=list)
+    recurring: list[RecurringCashflow] = Field(default_factory=list)
+    assets: list[Asset] = Field(default_factory=list)
+    liabilities: list[Liability] = Field(default_factory=list)
+    scenarios: list[ForecastScenario] = Field(default_factory=list)
+    exchange_rates: list[ExchangeRate] = Field(
+        default_factory=lambda: [r.model_copy() for r in DEFAULT_RATES]
+    )
 
     def to_dict(self) -> dict:
+        """Сериализация в dict с version и UUID-as-str (для JSON)."""
         return {
             "version": self.SCHEMA_VERSION,
             "base_currency": self.base_currency,
-            "accounts": [a.to_dict() for a in self.accounts],
-            "transactions": [t.to_dict() for t in self.transactions],
-            "recurring": [r.to_dict() for r in self.recurring],
-            "assets": [a.to_dict() for a in self.assets],
-            "liabilities": [li.to_dict() for li in self.liabilities],
-            "scenarios": [s.to_dict() for s in self.scenarios],
-            "exchange_rates": [r.to_dict() for r in self.exchange_rates],
+            "accounts": [a.model_dump(mode="json") for a in self.accounts],
+            "transactions": [t.model_dump(mode="json") for t in self.transactions],
+            "recurring": [r.model_dump(mode="json") for r in self.recurring],
+            "assets": [a.model_dump(mode="json") for a in self.assets],
+            "liabilities": [li.model_dump(mode="json") for li in self.liabilities],
+            "scenarios": [s.model_dump(mode="json") for s in self.scenarios],
+            "exchange_rates": [e.model_dump(mode="json") for e in self.exchange_rates],
         }
 
     @classmethod
     def from_dict(cls, data: dict) -> "FinancialModel":
         version = data.get("version", 0)
         if version == 0:
-            return cls._from_v0(data)
+            return cls._from_legacy(data)
         if version == 1:
             return cls._from_v1(data)
         raise ValueError(f"Unsupported FinancialModel version: {version}")
@@ -50,18 +55,18 @@ class FinancialModel:
     def _from_v1(cls, data: dict) -> "FinancialModel":
         return cls(
             base_currency=data.get("base_currency", "RUB"),
-            accounts=[Account.from_dict(a) for a in data.get("accounts", [])],
-            transactions=[Transaction.from_dict(t) for t in data.get("transactions", [])],
-            recurring=[RecurringCashflow.from_dict(r) for r in data.get("recurring", [])],
-            assets=[Asset.from_dict(a) for a in data.get("assets", [])],
-            liabilities=[Liability.from_dict(li) for li in data.get("liabilities", [])],
-            scenarios=[ForecastScenario.from_dict(s) for s in data.get("scenarios", [])],
-            exchange_rates=[ExchangeRate.from_dict(r) for r in data.get("exchange_rates", [])],
+            accounts=[Account.model_validate(a) for a in data.get("accounts", [])],
+            transactions=[Transaction.model_validate(t) for t in data.get("transactions", [])],
+            recurring=[RecurringCashflow.model_validate(r) for r in data.get("recurring", [])],
+            assets=[Asset.model_validate(a) for a in data.get("assets", [])],
+            liabilities=[Liability.model_validate(li) for li in data.get("liabilities", [])],
+            scenarios=[ForecastScenario.model_validate(s) for s in data.get("scenarios", [])],
+            exchange_rates=[ExchangeRate.model_validate(r) for r in data.get("exchange_rates", [])],
         )
 
     @classmethod
-    def _from_v0(cls, data: dict) -> "FinancialModel":
-        # Legacy: файлы, сохранённые до введения version. Совпадает по структуре с v1.
+    def _from_legacy(cls, data: dict) -> "FinancialModel":
+        # Legacy: файлы без version. Структура совпадает с v1.
         return cls._from_v1(data)
 
     def save(self, path: str | Path) -> None:

domain/recurring.py

@@ -1,33 +1,26 @@
-from dataclasses import dataclass, field
 from uuid import UUID, uuid4
 
+from pydantic import BaseModel, Field, field_validator
 
-@dataclass
-class RecurringCashflow:
-    id: UUID = field(default_factory=uuid4)
+
+class RecurringCashflow(BaseModel):
+    id: UUID = Field(default_factory=uuid4)
     start_date: str = ""
     end_date: str = ""
     frequency: str = "monthly"
     amount: float = 0.0
     category: str = ""
 
-    def to_dict(self) -> dict:
-        return {
-            "id": str(self.id),
-            "start_date": self.start_date,
-            "end_date": self.end_date,
-            "frequency": self.frequency,
-            "amount": self.amount,
-            "category": self.category,
-        }
-
+    @field_validator("frequency")
     @classmethod
-    def from_dict(cls, data: dict) -> "RecurringCashflow":
-        return cls(
-            id=UUID(data["id"]),
-            start_date=data.get("start_date", ""),
-            end_date=data.get("end_date", ""),
-            frequency=data.get("frequency", "monthly"),
-            amount=data.get("amount", 0.0),
-            category=data.get("category", ""),
-        )
+    def _frequency_known(cls, v: str) -> str:
+        if v not in {"daily", "weekly", "monthly", "yearly"}:
+            raise ValueError(f"unknown frequency: {v}")
+        return v
+
+    @field_validator("amount")
+    @classmethod
+    def _amount_nonzero(cls, v: float) -> float:
+        if v == 0:
+            raise ValueError("amount must be non-zero")
+        return v

domain/scenario.py

@@ -1,33 +1,19 @@
-from dataclasses import dataclass, field
 from uuid import UUID, uuid4
 
+from pydantic import BaseModel, Field, field_validator
 
-@dataclass
-class ForecastScenario:
-    id: UUID = field(default_factory=uuid4)
+
+class ForecastScenario(BaseModel):
+    id: UUID = Field(default_factory=uuid4)
     name: str = "baseline"
     income_multiplier: float = 1.0
     expense_multiplier: float = 1.0
     growth_multiplier: float = 1.0
     description: str = ""
 
-    def to_dict(self) -> dict:
-        return {
-            "id": str(self.id),
-            "name": self.name,
-            "income_multiplier": self.income_multiplier,
-            "expense_multiplier": self.expense_multiplier,
-            "growth_multiplier": self.growth_multiplier,
-            "description": self.description,
-        }
-
+    @field_validator("income_multiplier", "expense_multiplier", "growth_multiplier")
     @classmethod
-    def from_dict(cls, data: dict) -> "ForecastScenario":
-        return cls(
-            id=UUID(data["id"]),
-            name=data["name"],
-            income_multiplier=data.get("income_multiplier", 1.0),
-            expense_multiplier=data.get("expense_multiplier", 1.0),
-            growth_multiplier=data.get("growth_multiplier", 1.0),
-            description=data.get("description", ""),
-        )
+    def _non_negative(cls, v: float) -> float:
+        if v < 0:
+            raise ValueError("multiplier must be non-negative")
+        return v

domain/transaction.py

@@ -1,33 +1,19 @@
-from dataclasses import dataclass, field
 from uuid import UUID, uuid4
 
+from pydantic import BaseModel, Field, field_validator
 
-@dataclass
-class Transaction:
-    id: UUID = field(default_factory=uuid4)
+
+class Transaction(BaseModel):
+    id: UUID = Field(default_factory=uuid4)
     date: str = ""
     account: str = ""
     category: str = ""
     amount: float = 0.0
     description: str = ""
 
-    def to_dict(self) -> dict:
-        return {
-            "id": str(self.id),
-            "date": self.date,
-            "account": self.account,
-            "category": self.category,
-            "amount": self.amount,
-            "description": self.description,
-        }
-
+    @field_validator("amount")
     @classmethod
-    def from_dict(cls, data: dict) -> "Transaction":
-        return cls(
-            id=UUID(data["id"]),
-            date=data["date"],
-            account=data.get("account", ""),
-            category=data.get("category", ""),
-            amount=data.get("amount", 0.0),
-            description=data.get("description", ""),
-        )
+    def _amount_nonzero(cls, v: float) -> float:
+        if v == 0:
+            raise ValueError("amount must be non-zero")
+        return v