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https://github.com/elisiariocouto/leggen.git
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fbb3eb9e64
Introduces a DataProcessor layer to separate transformation logic from orchestration and persistence concerns: - Created data_processors/ directory with AccountEnricher, BalanceTransformer, AnalyticsProcessor, and moved TransactionProcessor - Refactored SyncService to pure orchestrator, removing account/balance enrichment logic - Refactored DatabaseService to pure CRUD, removing analytics and transformation logic - Extracted 90+ lines of analytics SQL from DatabaseService to AnalyticsProcessor - Extracted 80+ lines of balance transformation logic to BalanceTransformer - Maintained backward compatibility - all 109 tests pass - No API contract changes This improves code clarity, testability, and maintainability while maintaining the existing API surface. 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Haiku 4.5 <noreply@anthropic.com>
91 lines
3.3 KiB
Python
91 lines
3.3 KiB
Python
from datetime import datetime
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from typing import Any, Dict, List
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class TransactionProcessor:
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"""Handles processing and transformation of raw transaction data"""
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def process_transactions(
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self,
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account_id: str,
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account_info: Dict[str, Any],
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transaction_data: Dict[str, Any],
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) -> List[Dict[str, Any]]:
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"""Process raw transaction data into standardized format"""
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transactions = []
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# Process booked transactions
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for transaction in transaction_data.get("transactions", {}).get("booked", []):
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processed = self._process_single_transaction(
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account_id, account_info, transaction, "booked"
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)
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transactions.append(processed)
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# Process pending transactions
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for transaction in transaction_data.get("transactions", {}).get("pending", []):
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processed = self._process_single_transaction(
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account_id, account_info, transaction, "pending"
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)
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transactions.append(processed)
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return transactions
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def _process_single_transaction(
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self,
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account_id: str,
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account_info: Dict[str, Any],
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transaction: Dict[str, Any],
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status: str,
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) -> Dict[str, Any]:
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"""Process a single transaction into standardized format"""
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# Extract dates
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booked_date = transaction.get("bookingDateTime") or transaction.get(
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"bookingDate"
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)
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value_date = transaction.get("valueDateTime") or transaction.get("valueDate")
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if booked_date and value_date:
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min_date = min(
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datetime.fromisoformat(booked_date), datetime.fromisoformat(value_date)
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)
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else:
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date_str = booked_date or value_date
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if not date_str:
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raise ValueError("No valid date found in transaction")
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min_date = datetime.fromisoformat(date_str)
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# Extract amount and currency
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transaction_amount = transaction.get("transactionAmount", {})
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amount = float(transaction_amount.get("amount", 0))
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currency = transaction_amount.get("currency", "")
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# Extract description
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description = transaction.get(
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"remittanceInformationUnstructured",
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",".join(transaction.get("remittanceInformationUnstructuredArray", [])),
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)
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# Extract transaction IDs - transactionId is now primary, internalTransactionId is reference
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transaction_id = transaction.get("transactionId")
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internal_transaction_id = transaction.get("internalTransactionId")
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if not transaction_id:
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if internal_transaction_id:
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transaction_id = internal_transaction_id
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else:
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raise ValueError("Transaction missing required transactionId field")
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return {
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"accountId": account_id,
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"transactionId": transaction_id,
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"internalTransactionId": internal_transaction_id,
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"institutionId": account_info["institution_id"],
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"iban": account_info.get("iban", "N/A"),
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"transactionDate": min_date,
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"description": description,
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"transactionValue": amount,
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"transactionCurrency": currency,
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"transactionStatus": status,
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"rawTransaction": transaction,
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}
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