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signal-platform/tests/unit/test_scheduler.py
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dennisthiessen ebff19940b
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feat: add standalone AI/Tech regime-change monitor tab
A new /regime tab scoring how far the AI/Tech bull regime has deteriorated
toward a re-rating as a single 0-100 index with per-signal breakdown and a
7/30-day trend. Intentionally decoupled: nothing reads its output to gate or
score trades — the daily-pipeline membership is scheduling only.

- regime_monitor_service: price sub-scores (P1-P6 via Alpaca, like
  market_regime), VIX + HY credit spreads via a small FRED helper, weighted
  aggregation over available signals (missing source -> n/a, dropped from the
  denominator), one snapshot row/day, and a ~90-day history backfill by
  replaying the already-fetched series as-of each past day.
- F1/F3 fundamentals proposed by the configured grounded LLM (reuses
  sentiment_provider_service config resolution), with a manual override + lock.
- regime_snapshots table (migration 011); endpoints on the existing market
  router; admin-editable weights/threshold; standalone /regime page.

Data needs: prices via Alpaca, VIX/credit via FRED (optional key — signals show
n/a without it). No LLM needed for history.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-06-26 11:51:45 +02:00

117 lines
3.6 KiB
Python

"""Unit tests for app.scheduler module."""
import pytest
from app.scheduler import (
_is_job_enabled,
_parse_frequency,
_resume_tickers,
_last_successful,
configure_scheduler,
scheduler,
)
class TestParseFrequency:
def test_hourly(self):
assert _parse_frequency("hourly") == {"hours": 1}
def test_daily(self):
assert _parse_frequency("daily") == {"hours": 24}
def test_case_insensitive(self):
assert _parse_frequency("Hourly") == {"hours": 1}
assert _parse_frequency("DAILY") == {"hours": 24}
def test_weekly_maps_to_one_week(self):
assert _parse_frequency("weekly") == {"weeks": 1}
def test_unknown_defaults_to_daily(self):
assert _parse_frequency("monthly") == {"hours": 24}
assert _parse_frequency("") == {"hours": 24}
class TestResumeTickers:
def test_no_previous_returns_full_list(self):
symbols = ["AAPL", "GOOG", "MSFT"]
_last_successful["test_job"] = None
result = _resume_tickers(symbols, "test_job")
assert result == ["AAPL", "GOOG", "MSFT"]
def test_resume_after_first(self):
symbols = ["AAPL", "GOOG", "MSFT"]
_last_successful["test_job"] = "AAPL"
result = _resume_tickers(symbols, "test_job")
# Should start from GOOG, then wrap around
assert result == ["GOOG", "MSFT", "AAPL"]
def test_resume_after_middle(self):
symbols = ["AAPL", "GOOG", "MSFT", "TSLA"]
_last_successful["test_job"] = "GOOG"
result = _resume_tickers(symbols, "test_job")
assert result == ["MSFT", "TSLA", "AAPL", "GOOG"]
def test_resume_after_last(self):
symbols = ["AAPL", "GOOG", "MSFT"]
_last_successful["test_job"] = "MSFT"
result = _resume_tickers(symbols, "test_job")
# All already processed, wraps to full list
assert result == ["AAPL", "GOOG", "MSFT"]
def test_unknown_last_returns_full_list(self):
symbols = ["AAPL", "GOOG", "MSFT"]
_last_successful["test_job"] = "NVDA"
result = _resume_tickers(symbols, "test_job")
assert result == ["AAPL", "GOOG", "MSFT"]
def test_empty_list(self):
_last_successful["test_job"] = "AAPL"
result = _resume_tickers([], "test_job")
assert result == []
class TestConfigureScheduler:
def test_configure_adds_all_jobs(self):
# Remove any existing jobs first
scheduler.remove_all_jobs()
configure_scheduler()
jobs = scheduler.get_jobs()
job_ids = {j.id for j in jobs}
assert job_ids == {
"data_collector",
"data_backfill",
"sentiment_collector",
"fundamental_collector",
"rr_scanner",
"ticker_universe_sync",
"outcome_evaluator",
"alerts",
"market_regime",
"regime_monitor",
"backtest",
"daily_pipeline",
"intraday_pipeline",
}
def test_configure_is_idempotent(self):
scheduler.remove_all_jobs()
configure_scheduler()
configure_scheduler() # Should replace, not duplicate
job_ids = [j.id for j in scheduler.get_jobs()]
# Each ID should appear exactly once
assert sorted(job_ids) == sorted([
"alerts",
"backtest",
"daily_pipeline",
"intraday_pipeline",
"data_collector",
"data_backfill",
"fundamental_collector",
"market_regime",
"regime_monitor",
"outcome_evaluator",
"rr_scanner",
"sentiment_collector",
"ticker_universe_sync",
])