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signal-platform/tests/unit/test_scheduler.py
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dennisthiessen 30effa89b7
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feat: ticker search, watchlist momentum column, alpha vs S&P 500
Three usability fixes:

1. Global ticker search in the sidebar (TickerSearch) — typeahead over the
   tracked universe that opens a ticker's detail page without adding it to the
   watchlist. Also wired into the mobile nav.

2. Watchlist table shows the ticker's 12-1 momentum percentile (the top-pick
   selector) instead of the noisy full S/R-level list. Enriched from the setup
   already loaded in watchlist_service._enrich_entry — no extra query.

3. Alpha vs the S&P 500 on paper trades (open + closed). New benchmark_prices
   table + benchmark_service store SPY daily closes (a standalone series, not a
   Ticker, so it never enters the scanner / momentum ranking / rankings) via a
   new daily-pipeline step. paper_trade_service computes per-trade
   benchmark_return / alpha_pct / alpha_usd over each holding period; the open-
   trades table, dashboard, and closed-trades panel surface per-trade and total
   alpha. The list read path never makes a provider call.

Deploy: alembic upgrade head, then run the benchmark/daily job once to populate
SPY closes (alpha shows "—" until then).

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-06-28 08:44:40 +02:00

121 lines
3.8 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",
"benchmark_collector",
"sentiment_collector",
"fundamental_collector",
"rr_scanner",
"ticker_universe_sync",
"outcome_evaluator",
"alerts",
"market_regime",
"regime_monitor",
"event_study",
"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",
"benchmark_collector",
"daily_pipeline",
"intraday_pipeline",
"data_collector",
"data_backfill",
"fundamental_collector",
"market_regime",
"regime_monitor",
"event_study",
"outcome_evaluator",
"rr_scanner",
"sentiment_collector",
"ticker_universe_sync",
])