Rinominato 'quote_currency' in 'currency' e aggiornato il trattamento del timestamp in Price

src/app/base/markets.py

@@ -1,3 +1,4 @@
+from datetime import datetime
 from pydantic import BaseModel
 
 
@@ -10,7 +11,7 @@ class ProductInfo(BaseModel):
     symbol: str = ""
     price: float = 0.0
     volume_24h: float = 0.0
-    quote_currency: str = ""
+    currency: str = ""
 
 class Price(BaseModel):
     """
@@ -22,7 +23,24 @@ class Price(BaseModel):
     open: float = 0.0
     close: float = 0.0
     volume: float = 0.0
-    timestamp_ms: int = 0  # Timestamp in milliseconds
+    timestamp: str = ""
+    """Timestamp con formato YYYY-MM-DD HH:MM"""
+
+    def set_timestamp(self, timestamp_ms: int | None = None, timestamp_s: int | None = None) -> None:
+        """
+        Imposta il timestamp in millisecondi.
+        Args:
+            timestamp (int | datetime): Il timestamp in millisecondi o come oggetto datetime.
+        """
+        if timestamp_ms is not None:
+            timestamp = timestamp_ms // 1000
+        elif timestamp_s is not None:
+            timestamp = timestamp_s
+        else:
+            raise ValueError("Either timestamp_ms or timestamp_s must be provided")
+        assert timestamp > 0, "Invalid timestamp data received"
+
+        self.timestamp = datetime.fromtimestamp(timestamp).strftime('%Y-%m-%d %H:%M')
 
 class MarketWrapper:
     """

src/app/markets/binance.py

@@ -10,17 +10,19 @@ def extract_product(currency: str, ticker_data: dict[str, Any]) -> ProductInfo:
     product.symbol = ticker_data.get('symbol', '').replace(currency, '')
     product.price = float(ticker_data.get('price', 0))
     product.volume_24h = float(ticker_data.get('volume', 0))
-    product.quote_currency = currency
+    product.currency = currency
     return product
 
 def extract_price(kline_data: list[Any]) -> Price:
+    timestamp = kline_data[0]
+
     price = Price()
     price.open = float(kline_data[1])
     price.high = float(kline_data[2])
     price.low = float(kline_data[3])
     price.close = float(kline_data[4])
     price.volume = float(kline_data[5])
-    price.timestamp_ms = kline_data[0]
+    price.set_timestamp(timestamp_ms=timestamp)
     return price
 
 class BinanceWrapper(MarketWrapper):

src/app/markets/coinbase.py

@@ -15,13 +15,15 @@ def extract_product(product_data: GetProductResponse | Product) -> ProductInfo:
     return product
 
 def extract_price(candle_data: Candle) -> Price:
+    timestamp = int(candle_data.start) if candle_data.start else 0
+
     price = Price()
     price.high = float(candle_data.high) if candle_data.high else 0.0
     price.low = float(candle_data.low) if candle_data.low else 0.0
     price.open = float(candle_data.open) if candle_data.open else 0.0
     price.close = float(candle_data.close) if candle_data.close else 0.0
     price.volume = float(candle_data.volume) if candle_data.volume else 0.0
-    price.timestamp_ms = int(candle_data.start) * 1000 if candle_data.start else 0
+    price.set_timestamp(timestamp_s=timestamp)
     return price
 
 

src/app/markets/cryptocompare.py

@@ -14,14 +14,15 @@ def extract_product(asset_data: dict[str, Any]) -> ProductInfo:
     return product
 
 def extract_price(price_data: dict[str, Any]) -> Price:
+    timestamp = price_data.get('time', 0)
+
     price = Price()
     price.high = float(price_data.get('high', 0))
     price.low = float(price_data.get('low', 0))
     price.open = float(price_data.get('open', 0))
     price.close = float(price_data.get('close', 0))
     price.volume = float(price_data.get('volumeto', 0))
-    price.timestamp_ms = price_data.get('time', 0) * 1000
-    assert price.timestamp_ms > 0, "Invalid timestamp data received from CryptoCompare"
+    price.set_timestamp(timestamp_s=timestamp)
     return price
 
 

src/app/markets/yfinance.py

@@ -12,20 +12,22 @@ def extract_product(stock_data: dict[str, str]) -> ProductInfo:
     product.symbol = product.id.split('-')[0]  # Rimuovi il suffisso della valuta per le crypto
     product.price = float(stock_data.get('Current Stock Price', f"0.0 USD").split(" ")[0]) # prende solo il numero
     product.volume_24h = 0.0 # YFinance non fornisce il volume 24h direttamente
-    product.quote_currency = product.id.split('-')[1]  # La valuta è la parte dopo il '-'
+    product.currency = product.id.split('-')[1]  # La valuta è la parte dopo il '-'
     return product
 
 def extract_price(hist_data: dict[str, str]) -> Price:
     """
     Converte i dati storici di YFinanceTools in Price.
     """
+    timestamp = int(hist_data.get('Timestamp', '0'))
+
     price = Price()
     price.high = float(hist_data.get('High', 0.0))
     price.low = float(hist_data.get('Low', 0.0))
     price.open = float(hist_data.get('Open', 0.0))
     price.close = float(hist_data.get('Close', 0.0))
     price.volume = float(hist_data.get('Volume', 0.0))
-    price.timestamp_ms = int(hist_data.get('Timestamp', '0'))
+    price.set_timestamp(timestamp_ms=timestamp)
     return price
 
 

src/app/utils/market_aggregation.py

@@ -4,25 +4,24 @@ from app.base.markets import ProductInfo, Price
 
 def aggregate_history_prices(prices: dict[str, list[Price]]) -> list[Price]:
     """
-    Aggrega i prezzi storici per symbol calcolando la media oraria.
+    Aggrega i prezzi storici per symbol calcolando la media.
     Args:
         prices (dict[str, list[Price]]): Mappa provider -> lista di Price
     Returns:
-        list[Price]: Lista di Price aggregati per ora
+        list[Price]: Lista di Price aggregati per timestamp
     """
 
-    # Costruiamo una mappa timestamp_h -> lista di Price
-    timestamped_prices: dict[int, list[Price]] = {}
+    # Costruiamo una mappa timestamp -> lista di Price
+    timestamped_prices: dict[str, list[Price]] = {}
     for _, price_list in prices.items():
         for price in price_list:
-            time = price.timestamp_ms - (price.timestamp_ms % 3600000)  # arrotonda all'ora (non dovrebbe essere necessario)
-            timestamped_prices.setdefault(time, []).append(price)
+            timestamped_prices.setdefault(price.timestamp, []).append(price)
 
-    # Ora aggregiamo i prezzi per ogni ora
+    # Ora aggregiamo i prezzi per ogni timestamp
     aggregated_prices: list[Price] = []
     for time, price_list in timestamped_prices.items():
         price = Price()
-        price.timestamp_ms = time
+        price.timestamp = time
         price.high = statistics.mean([p.high for p in price_list])
         price.low = statistics.mean([p.low for p in price_list])
         price.open = statistics.mean([p.open for p in price_list])
@@ -53,7 +52,7 @@ def aggregate_product_info(products: dict[str, list[ProductInfo]]) -> list[Produ
 
         product.id = f"{symbol}_AGGREGATED"
         product.symbol = symbol
-        product.quote_currency = next(p.quote_currency for p in product_list if p.quote_currency)
+        product.currency = next(p.currency for p in product_list if p.currency)
 
         volume_sum = sum(p.volume_24h for p in product_list)
         product.volume_24h = volume_sum / len(product_list) if product_list else 0.0