517842c834
* Aggiorna gli agenti e il modello del team per utilizzare OLLAMA_QWEN_1B * Riorganizza e rinomina funzioni di estrazione in moduli di mercato e notizie; migliora la gestione delle importazioni * Spostato main nel corretto file __main__ e aggiornato il README.md * Aggiunta cartella per i modelli, agenti e team * Aggiornata la posizione delle istruzioni * Rimossi TODO e Aggiunto documentazione per metodi aggregated * Aggiornate le istruzioni del coordinatore del team * utils type checks * Rinominato BaseWrapper in MarketWrapper e fix type check markets * fix type checks di notizie e social. * Aggiunti type hints finali * Riorganizzati gli import * Refactoring architetturale e spostamento classi base - Eliminazione del file __init__.py obsoleto che importava ChatManager e Pipeline - Spostamento della classe Pipeline in agents/pipeline.py - Spostamento della classe ChatManager in utils/chat_manager.py - Aggiornamento di __main__.py per importare da app.utils e app.agents, e modifica della logica per utilizzare Pipeline invece di chat per la selezione di provider e stile - Creazione della cartella base con classi base comuni: markets.py (ProductInfo, Price, MarketWrapper), news.py (Article, NewsWrapper), social.py (SocialPost, SocialComment, SocialWrapper) - Aggiornamento di tutti gli import nel progetto (markets/, news/, social/, utils/, tests/) per utilizzare la nuova struttura base/ * Aggiornato Readme * Corretto il valore predefinito della valuta in BinanceWrapper da "USDT" a "USD" * fix type in tests * fix type per models * Rinominato 'quote_currency' in 'currency' e aggiornato il trattamento del timestamp in Price * fix errors found by Copilot * WrapperHandler: semplificata la logica di chiamata delle funzioni sui wrapper * fix docs * fix demos, semplificata logica lista ollama
131 lines
5.4 KiB
Python
131 lines
5.4 KiB
Python
import pytest
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from datetime import datetime
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from app.base.markets import ProductInfo, Price
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from app.utils.market_aggregation import aggregate_history_prices, aggregate_product_info
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@pytest.mark.aggregator
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@pytest.mark.market
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class TestMarketDataAggregator:
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def __product(self, symbol: str, price: float, volume: float, currency: str) -> ProductInfo:
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prod = ProductInfo()
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prod.id=f"{symbol}-{currency}"
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prod.symbol=symbol
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prod.price=price
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prod.volume_24h=volume
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prod.currency=currency
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return prod
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def __price(self, timestamp_s: int, high: float, low: float, open: float, close: float, volume: float) -> Price:
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price = Price()
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price.set_timestamp(timestamp_s=timestamp_s)
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price.high = high
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price.low = low
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price.open = open
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price.close = close
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price.volume = volume
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return price
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def test_aggregate_product_info(self):
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products: dict[str, list[ProductInfo]] = {
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"Provider1": [self.__product("BTC", 50000.0, 1000.0, "USD")],
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"Provider2": [self.__product("BTC", 50100.0, 1100.0, "USD")],
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"Provider3": [self.__product("BTC", 49900.0, 900.0, "USD")],
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}
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aggregated = aggregate_product_info(products)
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assert len(aggregated) == 1
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info = aggregated[0]
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assert info is not None
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assert info.symbol == "BTC"
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avg_weighted_price = (50000.0 * 1000.0 + 50100.0 * 1100.0 + 49900.0 * 900.0) / (1000.0 + 1100.0 + 900.0)
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assert info.price == pytest.approx(avg_weighted_price, rel=1e-3) # type: ignore
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assert info.volume_24h == pytest.approx(1000.0, rel=1e-3) # type: ignore
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assert info.currency == "USD"
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def test_aggregate_product_info_multiple_symbols(self):
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products = {
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"Provider1": [
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self.__product("BTC", 50000.0, 1000.0, "USD"),
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self.__product("ETH", 4000.0, 2000.0, "USD"),
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],
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"Provider2": [
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self.__product("BTC", 50100.0, 1100.0, "USD"),
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self.__product("ETH", 4050.0, 2100.0, "USD"),
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],
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}
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aggregated = aggregate_product_info(products)
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assert len(aggregated) == 2
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btc_info = next((p for p in aggregated if p.symbol == "BTC"), None)
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eth_info = next((p for p in aggregated if p.symbol == "ETH"), None)
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assert btc_info is not None
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avg_weighted_price_btc = (50000.0 * 1000.0 + 50100.0 * 1100.0) / (1000.0 + 1100.0)
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assert btc_info.price == pytest.approx(avg_weighted_price_btc, rel=1e-3) # type: ignore
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assert btc_info.volume_24h == pytest.approx(1050.0, rel=1e-3) # type: ignore
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assert btc_info.currency == "USD"
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assert eth_info is not None
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avg_weighted_price_eth = (4000.0 * 2000.0 + 4050.0 * 2100.0) / (2000.0 + 2100.0)
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assert eth_info.price == pytest.approx(avg_weighted_price_eth, rel=1e-3) # type: ignore
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assert eth_info.volume_24h == pytest.approx(2050.0, rel=1e-3) # type: ignore
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assert eth_info.currency == "USD"
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def test_aggregate_product_info_with_no_data(self):
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products: dict[str, list[ProductInfo]] = {
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"Provider1": [],
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"Provider2": [],
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}
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aggregated = aggregate_product_info(products)
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assert len(aggregated) == 0
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def test_aggregate_product_info_with_partial_data(self):
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products: dict[str, list[ProductInfo]] = {
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"Provider1": [self.__product("BTC", 50000.0, 1000.0, "USD")],
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"Provider2": [],
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}
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aggregated = aggregate_product_info(products)
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assert len(aggregated) == 1
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info = aggregated[0]
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assert info.symbol == "BTC"
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assert info.price == pytest.approx(50000.0, rel=1e-3) # type: ignore
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assert info.volume_24h == pytest.approx(1000.0, rel=1e-3) # type: ignore
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assert info.currency == "USD"
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def test_aggregate_history_prices(self):
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"""Test aggregazione di prezzi storici usando aggregate_history_prices"""
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timestamp_now = datetime.now()
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timestamp_1h_ago = int(timestamp_now.replace(hour=timestamp_now.hour - 1).timestamp())
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timestamp_2h_ago = int(timestamp_now.replace(hour=timestamp_now.hour - 2).timestamp())
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prices = {
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"Provider1": [
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self.__price(timestamp_1h_ago, 50000.0, 49500.0, 49600.0, 49900.0, 150.0),
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self.__price(timestamp_2h_ago, 50200.0, 49800.0, 50000.0, 50100.0, 200.0),
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],
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"Provider2": [
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self.__price(timestamp_1h_ago, 50100.0, 49600.0, 49700.0, 50000.0, 180.0),
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self.__price(timestamp_2h_ago, 50300.0, 49900.0, 50100.0, 50200.0, 220.0),
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],
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}
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price = Price()
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price.set_timestamp(timestamp_s=timestamp_1h_ago)
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timestamp_1h_ago = price.timestamp
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price.set_timestamp(timestamp_s=timestamp_2h_ago)
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timestamp_2h_ago = price.timestamp
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aggregated = aggregate_history_prices(prices)
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assert len(aggregated) == 2
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assert aggregated[0].timestamp == timestamp_1h_ago
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assert aggregated[0].high == pytest.approx(50050.0, rel=1e-3) # type: ignore
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assert aggregated[0].low == pytest.approx(49550.0, rel=1e-3) # type: ignore
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assert aggregated[1].timestamp == timestamp_2h_ago
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assert aggregated[1].high == pytest.approx(50250.0, rel=1e-3) # type: ignore
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assert aggregated[1].low == pytest.approx(49850.0, rel=1e-3) # type: ignore
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