simplified aggregation logic

This commit is contained in:
2025-11-02 00:01:48 +01:00
parent 3327bf8127
commit 30ddb76df7
3 changed files with 93 additions and 241 deletions

View File

@@ -16,118 +16,51 @@ class ProductInfo(BaseModel):
provider: str = ""
@staticmethod
def aggregate_multi_assets(products: dict[str, list['ProductInfo']]) -> list['ProductInfo']:
def aggregate(products: dict[str, list['ProductInfo']], filter_currency: str="USD") -> list['ProductInfo']:
"""
Aggregates a list of ProductInfo by symbol across different providers.
Aggregates a list of ProductInfo by symbol.
Args:
products (dict[str, list[ProductInfo]]): Map provider -> list of ProductInfo
filter_currency (str): If set, only products with this currency are considered. Defaults to "USD".
Returns:
list[ProductInfo]: List of ProductInfo aggregated by symbol, combining data from all providers
dict[ProductInfo, str]: Map of aggregated ProductInfo by symbol
"""
# Costruzione mappa symbol -> lista di ProductInfo (da tutti i provider)
symbols_infos: dict[str, list[ProductInfo]] = {}
for provider_name, product_list in products.items():
# Costruzione mappa id -> lista di ProductInfo + lista di provider
id_infos: dict[str, tuple[list[ProductInfo], list[str]]] = {}
for provider, product_list in products.items():
for product in product_list:
# Assicuriamo che il provider sia impostato
if not product.provider:
product.provider = provider_name
symbols_infos.setdefault(product.symbol, []).append(product)
if filter_currency and product.currency != filter_currency:
continue
id_value = product.id.upper().replace("-", "") # Normalizzazione id per compatibilità (es. BTC-USD -> btcusd)
product_list, provider_list = id_infos.setdefault(id_value, ([], []) )
product_list.append(product)
provider_list.append(provider)
# Aggregazione per ogni symbol usando aggregate_single_asset
# Aggregazione per ogni id
aggregated_products: list[ProductInfo] = []
for symbol, product_list in symbols_infos.items():
try:
# Usa aggregate_single_asset per aggregare ogni simbolo
aggregated = ProductInfo.aggregate_single_asset(product_list)
# aggregate_single_asset calcola il volume medio, ma per multi_assets
# vogliamo il volume totale. Ricalcoliamo il volume come somma dopo il filtro USD
# Dobbiamo rifare il filtro USD per contare correttamente
currencies = set(p.currency for p in product_list if p.currency)
if len(currencies) > 1:
product_list = [p for p in product_list if p.currency.upper() == "USD"]
# Volume totale
aggregated.volume_24h = sum(p.volume_24h for p in product_list if p.volume_24h > 0)
aggregated_products.append(aggregated)
except ValueError:
# Se aggregate_single_asset fallisce (es. no USD when currencies differ), salta
continue
return aggregated_products
@staticmethod
def aggregate_single_asset(assets: list['ProductInfo'] | dict[str, 'ProductInfo'] | dict[str, list['ProductInfo']]) -> 'ProductInfo':
"""
Aggregates an asset across different exchanges.
Args:
assets: Can be:
- list[ProductInfo]: Direct list of products
- dict[str, ProductInfo]: Map provider -> ProductInfo (from WrapperHandler.try_call_all)
- dict[str, list[ProductInfo]]: Map provider -> list of ProductInfo
Returns:
ProductInfo: Aggregated ProductInfo combining data from all exchanges
"""
for id_value, (product_list, provider_list) in id_infos.items():
product = ProductInfo()
# Defensive handling: normalize to a flat list of ProductInfo
if not assets:
raise ValueError("aggregate_single_asset requires at least one ProductInfo")
product.id = f"{id_value}_AGGREGATED"
product.symbol = next(p.symbol for p in product_list if p.symbol)
product.currency = next(p.currency for p in product_list if p.currency)
# Normalize to a flat list of ProductInfo
if isinstance(assets, dict):
# Check if dict values are ProductInfo or list[ProductInfo]
first_value = next(iter(assets.values())) if assets else None
if first_value and isinstance(first_value, list):
# dict[str, list[ProductInfo]] -> flatten
assets_list = [product for product_list in assets.values() for product in product_list]
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
if volume_sum > 0:
# Calcolo del prezzo pesato per volume (VWAP - Volume Weighted Average Price)
prices_weighted = sum(p.price * p.volume_24h for p in product_list if p.volume_24h > 0)
product.price = prices_weighted / volume_sum
else:
# dict[str, ProductInfo] -> extract values
assets_list = list(assets.values())
elif isinstance(assets, list) and assets and isinstance(assets[0], list):
# Flatten list[list[ProductInfo]] -> list[ProductInfo]
assets_list = [product for sublist in assets for product in sublist]
else:
# Already a flat list of ProductInfo
assets_list = list(assets)
if not assets_list:
raise ValueError("aggregate_single_asset requires at least one ProductInfo")
# Controllo valuta: se non sono tutte uguali, filtra solo USD
currencies = set(p.currency for p in assets_list if p.currency)
if len(currencies) > 1:
# Valute diverse: filtra solo USD
assets_list = [p for p in assets_list if p.currency.upper() == "USD"]
if not assets_list:
raise ValueError("aggregate_single_asset: no USD products available when currencies differ")
# Aggregazione per ogni Exchange
aggregated: ProductInfo = ProductInfo()
first = assets_list[0]
aggregated.id = f"{first.symbol}_AGGREGATED"
aggregated.symbol = first.symbol
aggregated.currency = next((p.currency for p in assets_list if p.currency), "")
# Raccogliamo i provider che hanno fornito dati
providers = [p.provider for p in assets_list if p.provider]
aggregated.provider = ", ".join(set(providers)) if providers else "AGGREGATED"
# Calcolo del volume medio
volume_sum = sum(p.volume_24h for p in assets_list if p.volume_24h > 0)
aggregated.volume_24h = volume_sum / len(assets_list) if assets_list else 0.0
# Calcolo del prezzo pesato per volume (VWAP - Volume Weighted Average Price)
if volume_sum > 0:
prices_weighted = sum(p.price * p.volume_24h for p in assets_list if p.volume_24h > 0)
aggregated.price = prices_weighted / volume_sum
else:
# Se non c'è volume, facciamo una media semplice dei prezzi
valid_prices = [p.price for p in assets_list if p.price > 0]
aggregated.price = sum(valid_prices) / len(valid_prices) if valid_prices else 0.0
return aggregated
# Se non c'è volume, facciamo una media semplice dei prezzi
valid_prices = [p.price for p in product_list if p.price > 0]
product.price = sum(valid_prices) / len(valid_prices) if valid_prices else 0.0
product.provider = ",".join(provider_list)
aggregated_products.append(product)
return aggregated_products
class Price(BaseModel):

View File

@@ -126,7 +126,7 @@ class MarketAPIsTool(MarketWrapper, Toolkit):
Exception: If all providers fail to return results.
"""
all_products = self.handler.try_call_all(lambda w: w.get_products(asset_ids))
return ProductInfo.aggregate_multi_assets(all_products)
return ProductInfo.aggregate(all_products)
def get_historical_prices_aggregated(self, asset_id: str = "BTC", limit: int = 100) -> list[Price]:
"""