165 lines
5.2 KiB
Python
165 lines
5.2 KiB
Python
from datetime import datetime
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from unittest.mock import MagicMock, patch
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import pytest
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from tradingagents.agents.discovery import NewsArticle
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from tradingagents.dataflows.alpha_vantage_common import AlphaVantageRateLimitError
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class TestGetBulkNewsReturnsNewsArticles:
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def test_get_bulk_news_returns_list_of_news_article_objects(self):
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mock_raw_news = [
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{
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"title": "Market Update: Tech stocks rally",
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"source": "Reuters",
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"url": "https://reuters.com/market-update",
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"published_at": datetime.now().isoformat(),
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"content_snippet": "Technology stocks led gains in early trading...",
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},
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{
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"title": "Fed signals rate decision",
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"source": "Bloomberg",
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"url": "https://bloomberg.com/fed-rates",
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"published_at": datetime.now().isoformat(),
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"content_snippet": "Federal Reserve officials indicated...",
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},
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]
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from tradingagents.dataflows.interface import (
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_bulk_news_cache,
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get_bulk_news,
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)
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_bulk_news_cache.clear()
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with patch(
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"tradingagents.dataflows.interface._fetch_bulk_news_from_vendor"
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) as mock_fetch:
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mock_fetch.return_value = mock_raw_news
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result = get_bulk_news(lookback_period="24h")
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assert isinstance(result, list)
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assert len(result) == 2
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for article in result:
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assert isinstance(article, NewsArticle)
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assert article.title is not None
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assert article.source is not None
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assert article.url is not None
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class TestLookbackPeriodParsing:
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@pytest.mark.parametrize(
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"lookback,expected_hours",
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[
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("1h", 1),
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("6h", 6),
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("24h", 24),
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("7d", 168),
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],
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)
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def test_lookback_period_parsing(self, lookback, expected_hours):
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from tradingagents.dataflows.interface import parse_lookback_period
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hours = parse_lookback_period(lookback)
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assert hours == expected_hours
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def test_invalid_lookback_period_raises_error(self):
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from tradingagents.dataflows.interface import parse_lookback_period
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with pytest.raises(ValueError):
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parse_lookback_period("invalid")
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class TestVendorFallback:
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def test_vendor_fallback_when_primary_rate_limited(self):
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mock_openai_news = [
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{
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"title": "Fallback news from OpenAI",
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"source": "Web Search",
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"url": "https://example.com/fallback",
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"published_at": datetime.now().isoformat(),
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"content_snippet": "This is fallback content...",
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},
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]
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from tradingagents.dataflows.interface import (
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_bulk_news_cache,
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)
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_bulk_news_cache.clear()
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with patch(
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"tradingagents.dataflows.interface.VENDOR_METHODS",
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{
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"get_bulk_news": {
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"alpha_vantage": MagicMock(
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side_effect=AlphaVantageRateLimitError("Rate limit")
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),
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"openai": MagicMock(return_value=mock_openai_news),
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"google": MagicMock(return_value=[]),
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}
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},
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):
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from tradingagents.dataflows.interface import _fetch_bulk_news_from_vendor
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result = _fetch_bulk_news_from_vendor("24h")
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assert isinstance(result, list)
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assert len(result) == 1
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assert result[0]["title"] == "Fallback news from OpenAI"
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class TestBulkNewsCache:
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def test_cache_returns_same_results_within_ttl(self):
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from tradingagents.dataflows.interface import (
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_bulk_news_cache,
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_get_cached_bulk_news,
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_set_cached_bulk_news,
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)
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_bulk_news_cache.clear()
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test_articles = [
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NewsArticle(
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title="Cached article",
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source="Test Source",
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url="https://test.com/cached",
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published_at=datetime.now(),
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content_snippet="Cached content...",
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ticker_mentions=[],
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)
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]
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_set_cached_bulk_news("24h", test_articles)
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cached_result = _get_cached_bulk_news("24h")
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assert cached_result is not None
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assert len(cached_result) == 1
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assert cached_result[0].title == "Cached article"
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cached_result_again = _get_cached_bulk_news("24h")
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assert cached_result_again is not None
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assert cached_result_again[0].title == cached_result[0].title
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class TestEmptyResultHandling:
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def test_empty_result_handling(self):
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from tradingagents.dataflows.interface import (
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_bulk_news_cache,
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get_bulk_news,
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)
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_bulk_news_cache.clear()
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with patch(
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"tradingagents.dataflows.interface._fetch_bulk_news_from_vendor"
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) as mock_fetch:
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mock_fetch.return_value = []
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result = get_bulk_news(lookback_period="1h")
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assert isinstance(result, list)
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assert len(result) == 0
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