mirror of
https://github.com/kuhyx/steam-backlog-enforcer.git
synced 2026-11-11 14:07:33 +01:00
Krzysztof kuhy Rudnicki
07e6e15b6e
steam_api becomes a thin re-export over _steam_models (dataclasses) and _steam_api_client (HTTP). Inverting it that way rather than moving the client out and importing it back matters: _steam_api_client needs GameInfo, so a re-export from the old module would have been a cycle. 47 call sites import from steam_api and none of them change. _scanning_confidence sheds the poll backfill/reporting pair into _polls_reporting, and re-exports both. Test patch targets follow the code: the tests for _report_poll_confidence now patch _polls_reporting._echo, because that is where the name is bound. Patching the re-exporting module intercepts nothing, and the test then fails on an empty output list rather than an import error, which is why these are worth being careful about. 1347 tests pass. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_016A1EYiv7e7HGhET84oa9M3
109 lines
3.7 KiB
Python
109 lines
3.7 KiB
Python
"""Backfilling and reporting HLTB poll confidence for finished games.
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Split to keep both files under the 250-line cap.
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"""
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from __future__ import annotations
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import logging
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from typing import TYPE_CHECKING
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from steam_backlog_enforcer._echo import _echo
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from steam_backlog_enforcer._hltb_types import (
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load_hltb_cache,
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load_hltb_polls_cache,
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save_hltb_cache,
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)
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from steam_backlog_enforcer.hltb import fetch_hltb_confidence_cached
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if TYPE_CHECKING:
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from steam_backlog_enforcer._steam_models import GameInfo
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from steam_backlog_enforcer.config import State
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logger = logging.getLogger(__name__)
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def _backfill_polls_for_finished(
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state: State,
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games: list[GameInfo],
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) -> dict[int, int]:
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"""Lazily fetch poll counts for already-finished games missing them.
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Reads the polls cache, identifies finished games whose poll count is
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still ``0`` (typically because the cache predates the polls schema),
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and triggers a one-shot HLTB search to backfill them. Returns the
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refreshed polls cache.
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"""
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polls_cache = load_hltb_polls_cache()
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name_by_id = {g.app_id: g.name for g in games}
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missing = [
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(aid, name_by_id[aid])
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for aid in state.finished_app_ids
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if aid in name_by_id and polls_cache.get(aid, 0) == 0
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]
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if not missing:
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return polls_cache
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logger.info(
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"Backfilling HLTB poll counts for %d already-finished games...",
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len(missing),
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)
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# Force a fresh search by removing the hours entries we want to refetch.
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# (fetch_hltb_times_cached skips entries already in the hours cache.)
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cache = load_hltb_cache()
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preserved_hours = {aid: cache[aid] for aid, _ in missing if aid in cache}
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for aid, _name in missing:
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cache.pop(aid, None)
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save_hltb_cache(cache, polls_cache)
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fetch_hltb_confidence_cached(missing)
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# Restore any previously-known hours that the refetch may have replaced
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# with a worse match (we trust prior leisure+dlc estimates).
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refreshed_hours = load_hltb_cache()
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refreshed_polls = load_hltb_polls_cache()
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for aid, prior_hours in preserved_hours.items():
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if prior_hours > 0 and refreshed_hours.get(aid, -1) <= 0:
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refreshed_hours[aid] = prior_hours
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save_hltb_cache(refreshed_hours, refreshed_polls)
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return refreshed_polls
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def _report_poll_confidence(
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chosen: GameInfo,
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games: list[GameInfo],
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state: State,
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) -> None:
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"""Print HLTB poll-count confidence info for the just-assigned game.
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Shows the chosen game's ``comp_100_count`` (number of polled
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completionist times on HowLongToBeat) and the historical minimum
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among the user's previously-finished games. Marks a new historical
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low so the user can be skeptical of unreliable estimates.
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"""
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polls_cache = _backfill_polls_for_finished(state, games)
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chosen_polls = polls_cache.get(chosen.app_id, chosen.comp_100_count)
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chosen.comp_100_count = chosen_polls
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finished_polls = [
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(polls_cache[aid], aid)
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for aid in state.finished_app_ids
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if polls_cache.get(aid, 0) > 0
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]
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if not finished_polls:
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_echo(f" HLTB confidence: {chosen_polls} polled completionist times")
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return
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min_polls, min_aid = min(finished_polls)
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name_by_id = {g.app_id: g.name for g in games}
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min_name = name_by_id.get(min_aid, f"AppID={min_aid}")
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warning = ""
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if 0 < chosen_polls < min_polls:
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warning = " ⚠ NEW LOW — estimate may be unreliable"
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elif chosen_polls == 0:
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warning = " ⚠ no polls recorded — estimate may be unreliable"
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_echo(f" HLTB confidence: {chosen_polls} polled completionist times{warning}")
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_echo(f" Historical min among finished: {min_polls} ({min_name})")
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