summaryrefslogtreecommitdiff
path: root/shared/tests/test_news_events.py
blob: f748d8a5b43df0f00546ff1cf0372dd33f9aab0d (plain)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
"""Tests for NewsEvent."""

from datetime import UTC, datetime

from shared.events import Event, EventType, NewsEvent
from shared.models import NewsCategory, NewsItem


def test_news_event_to_dict():
    item = NewsItem(
        source="finnhub",
        headline="Test",
        published_at=datetime(2026, 4, 2, tzinfo=UTC),
        sentiment=0.5,
        category=NewsCategory.MACRO,
    )
    event = NewsEvent(data=item)
    d = event.to_dict()
    assert d["type"] == EventType.NEWS
    assert d["data"]["source"] == "finnhub"


def test_news_event_from_raw():
    raw = {
        "type": "NEWS",
        "data": {
            "id": "abc",
            "source": "rss",
            "headline": "Test headline",
            "published_at": "2026-04-02T00:00:00+00:00",
            "sentiment": 0.3,
            "category": "earnings",
            "symbols": ["AAPL"],
            "raw_data": {},
        },
    }
    event = NewsEvent.from_raw(raw)
    assert event.data.source == "rss"
    assert event.data.symbols == ["AAPL"]


def test_event_dispatcher_news():
    raw = {
        "type": "NEWS",
        "data": {
            "id": "abc",
            "source": "finnhub",
            "headline": "Test",
            "published_at": "2026-04-02T00:00:00+00:00",
            "sentiment": 0.0,
            "category": "macro",
            "raw_data": {},
        },
    }
    event = Event.from_dict(raw)
    assert isinstance(event, NewsEvent)