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https://github.com/kuhyx/steam-backlog-enforcer.git
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steam_backlog_enforcer: fix library_hider crash on invalid AppIDs + improve HLTB hour extraction
- library_hider.py: add safeHide(ids) JS helper that binary-bisects on failure to skip problematic DLC/tool IDs without blocking the entire hide pass - library_hider.py: increase CDP timeout 30s -> 120s; extract richer CDP error details from exceptionDetails/exception.description - _hltb_detail.py: rewrite _extract_base_leisure_hours() to pick the maximum (slowest) time across all platform comp_high values and *_h fields; add _platform_comp_high_candidates() helper
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@ -56,8 +56,32 @@ def _as_positive_int(value: object) -> int:
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return 0
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def _platform_comp_high_candidates(game_data: dict[str, Any]) -> list[int]:
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"""Collect positive ``comp_high`` values from ``platformData`` entries."""
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platform_data = game_data.get("platformData", [])
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if not isinstance(platform_data, list):
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return []
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candidates = []
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for entry in platform_data:
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if isinstance(entry, dict):
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v = _as_positive_int(entry.get("comp_high", 0))
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if v > 0:
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candidates.append(v)
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return candidates
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def _extract_base_leisure_hours(game_data: dict[str, Any]) -> float:
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"""Extract base-game leisure hours from game detail data."""
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"""Extract base-game leisure hours from game detail data.
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Returns the highest (slowest) time to beat across all play styles.
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Candidates considered:
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1. ``comp_high`` from each entry in ``platformData`` — the per-platform
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slowest individual submission displayed on the HLTB page.
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2. The ``_h`` (leisure/high) fields from ``game[0]``:
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``comp_main_h``, ``comp_plus_h``, ``comp_100_h``, ``comp_all_h``.
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3. Falls back to average times: ``comp_main``, ``comp_plus``, ``comp_100``.
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"""
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games = game_data.get("game", [])
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if not isinstance(games, list) or not games:
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return -1
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@ -65,9 +89,25 @@ def _extract_base_leisure_hours(game_data: dict[str, Any]) -> float:
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return -1
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base = games[0]
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leisure_s = _as_positive_int(base.get("comp_100_h", 0))
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candidates = _platform_comp_high_candidates(game_data)
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# 2. Leisure/high fields from the game record
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for field in ("comp_main_h", "comp_plus_h", "comp_100_h", "comp_all_h"):
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v = _as_positive_int(base.get(field, 0))
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if v > 0:
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candidates.append(v)
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leisure_s = max(candidates) if candidates else 0
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# 3. Fallback: average completion times
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if leisure_s <= 0:
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leisure_s = _as_positive_int(base.get("comp_100", 0))
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avg_candidates = [
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_as_positive_int(base.get("comp_main", 0)),
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_as_positive_int(base.get("comp_plus", 0)),
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_as_positive_int(base.get("comp_100", 0)),
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]
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leisure_s = max(avg_candidates)
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if leisure_s <= 0:
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return -1
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@ -100,9 +140,9 @@ def _extract_dlc_relationships(game_data: dict[str, Any]) -> list[tuple[int, flo
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def _extract_leisure_hours(game_data: dict[str, Any]) -> float:
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"""Compute total leisure hours: base game + all DLCs.
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Uses ``comp_100_h`` (leisure completionist) from the game detail page.
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Falls back to ``comp_100`` (average completionist) if leisure unavailable.
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Also sums leisure time from any DLC listed in ``relationships``.
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Uses the highest (slowest) time across ``platformData comp_high`` and
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leisure ``_h`` fields from ``game[0]``. Falls back to average completion
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times. Also sums leisure time from any DLC listed in ``relationships``.
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"""
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base_hours = _extract_base_leisure_hours(game_data)
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if base_hours <= 0:
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@ -31,7 +31,7 @@ import websockets
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logger = logging.getLogger(__name__)
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_CDP_PORT = 8080
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_CDP_TIMEOUT = 30
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_CDP_TIMEOUT = 120
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_STEAM_STARTUP_WAIT = 45
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@ -85,9 +85,18 @@ def _evaluate_js(expression: str) -> dict:
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def _cdp_result_value(result: dict) -> str:
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"""Extract the return value from a CDP Runtime.evaluate response."""
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inner = result.get("result", {}).get("result", {})
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if "exceptionDetails" in result.get("result", {}):
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desc = inner.get("description", "Unknown JS error")
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outer = result.get("result", {})
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inner = outer.get("result", {})
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if "exceptionDetails" in outer:
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exc_details = outer["exceptionDetails"]
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exc = exc_details.get("exception", {})
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desc = (
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inner.get("description")
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or exc.get("description")
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or exc_details.get("text")
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or repr(exc_details)
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)
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logger.debug("CDP exception details: %s", exc_details)
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msg = f"JS evaluation error: {desc}"
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raise RuntimeError(msg)
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value: str = inner.get("value", "")
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@ -251,6 +260,19 @@ def hide_other_games(
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const maxPasses = {_MAX_HIDE_PASSES};
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const batchSize = {_HIDE_BATCH_SIZE};
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async function safeHide(ids) {{
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if (ids.length === 0) return 0;
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try {{
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await collectionStore.SetAppsAsHidden(ids, true);
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return ids.length;
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}} catch(e) {{
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if (ids.length === 1) return 0;
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const mid = Math.floor(ids.length / 2);
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return (await safeHide(ids.slice(0, mid))) +
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(await safeHide(ids.slice(mid)));
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}}
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}}
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for (let pass = 0; pass < maxPasses; pass++) {{
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let visible = coll && coll.visibleApps
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? coll.visibleApps.map(a => a.appid).filter(id => id !== allowed)
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@ -267,8 +289,7 @@ def hide_other_games(
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for (let i = 0; i < visible.length; i += batchSize) {{
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const batch = visible.slice(i, i + batchSize);
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await collectionStore.SetAppsAsHidden(batch, true);
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totalHidden += batch.length;
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totalHidden += await safeHide(batch);
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}}
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await new Promise(r => setTimeout(r, {_SETTLE_DELAY_MS}));
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@ -36,6 +36,70 @@ class TestInternalHelpers:
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data: dict[str, Any] = {"game": [123]}
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assert _extract_base_leisure_hours(data) == -1
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def test_extract_base_leisure_platform_data_comp_high_is_max(self) -> None:
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data: dict[str, Any] = {
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"game": [{"comp_100_h": 16063}],
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"platformData": [{"platform": "PC", "comp_high": 23760}],
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}
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assert _extract_base_leisure_hours(data) == round(23760 / 3600, 2)
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def test_extract_base_leisure_h_field_exceeds_platform_comp_high(self) -> None:
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data: dict[str, Any] = {
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"game": [{"comp_100_h": 25000}],
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"platformData": [{"platform": "PC", "comp_high": 23760}],
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}
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assert _extract_base_leisure_hours(data) == round(25000 / 3600, 2)
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def test_extract_base_leisure_max_of_multiple_platforms(self) -> None:
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data: dict[str, Any] = {
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"game": [{}],
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"platformData": [
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{"platform": "PC", "comp_high": 23760},
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{"platform": "Switch", "comp_high": 18000},
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],
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}
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assert _extract_base_leisure_hours(data) == round(23760 / 3600, 2)
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def test_extract_base_leisure_platform_data_not_list(self) -> None:
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data: dict[str, Any] = {
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"game": [{"comp_100_h": 16063}],
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"platformData": "not_a_list",
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}
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assert _extract_base_leisure_hours(data) == round(16063 / 3600, 2)
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def test_extract_base_leisure_platform_non_dict_entry_skipped(self) -> None:
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data: dict[str, Any] = {
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"game": [{"comp_100_h": 16063}],
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"platformData": ["bad", {"platform": "PC", "comp_high": 23760}],
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}
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assert _extract_base_leisure_hours(data) == round(23760 / 3600, 2)
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def test_extract_base_leisure_platform_comp_high_zero_skipped(self) -> None:
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data: dict[str, Any] = {
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"game": [{"comp_100_h": 16063}],
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"platformData": [{"platform": "PC", "comp_high": 0}],
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}
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assert _extract_base_leisure_hours(data) == round(16063 / 3600, 2)
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def test_extract_base_leisure_max_of_h_fields(self) -> None:
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data: dict[str, Any] = {
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"game": [
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{
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"comp_main_h": 14951,
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"comp_plus_h": 17957,
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"comp_100_h": 16063,
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"comp_all_h": 17959,
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}
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],
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}
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assert _extract_base_leisure_hours(data) == round(17959 / 3600, 2)
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def test_extract_base_leisure_fallback_to_avg_comp_main(self) -> None:
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data: dict[str, Any] = {
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"game": [{"comp_main": 10800, "comp_plus": 0, "comp_100": 0}],
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}
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assert _extract_base_leisure_hours(data) == round(10800 / 3600, 2)
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def test_extract_dlc_relationships_skips_non_dict(self) -> None:
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data: dict[str, Any] = {
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"relationships": [
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@ -376,3 +440,29 @@ class TestFetchLeisureTimes:
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expected = round((21243 + 4075) / 3600, 2)
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assert cache[1289310] == expected
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assert results[0].completionist_hours == expected
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def test_with_explicit_count_comp(self) -> None:
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"""Pass a non-None count_comp to cover the False branch of the None check."""
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results = [
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HLTBResult(
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app_id=440,
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game_name="TF2",
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completionist_hours=50.0,
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similarity=1.0,
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hltb_game_id=12345,
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),
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]
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game_data: dict[str, Any] = {
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"game": [{"comp_100_h": 3600}],
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"relationships": [],
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}
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cache: dict[int, float] = {}
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with patch(
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"python_pkg.steam_backlog_enforcer._hltb_detail._fetch_detail_one",
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new_callable=AsyncMock,
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return_value=game_data,
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):
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asyncio.run(
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_fetch_leisure_times(results, cache, {}, None, count_comp={440: 5})
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)
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assert cache[440] == 1.0
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