177 lines
7.1 KiB
Python
177 lines
7.1 KiB
Python
from __future__ import annotations
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import random
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from typing import Any
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try:
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from . import item_axis_policy
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from .hardcore_role_anal import build_anal_or_double_role_graph
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from .hardcore_role_climax import build_climax_role_graph
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from .hardcore_role_fallback import (
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build_men_only_role_graph,
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build_mixed_group_fallback_role_graph,
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build_solo_role_graph,
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build_support_sentence,
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build_women_only_role_graph,
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)
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from .hardcore_role_interaction import (
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build_foreplay_role_graph,
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build_group_coordination_role_graph,
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build_interaction_role_graph,
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build_manual_role_graph,
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)
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from .hardcore_role_oral import build_oral_role_graph
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from .hardcore_role_outercourse import build_outercourse_role_graph
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from .hardcore_role_penetration import build_penetration_role_graph
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except ImportError: # Allows local smoke tests with `python -c`.
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import item_axis_policy
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from hardcore_role_anal import build_anal_or_double_role_graph
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from hardcore_role_climax import build_climax_role_graph
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from hardcore_role_fallback import (
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build_men_only_role_graph,
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build_mixed_group_fallback_role_graph,
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build_solo_role_graph,
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build_support_sentence,
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build_women_only_role_graph,
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)
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from hardcore_role_interaction import (
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build_foreplay_role_graph,
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build_group_coordination_role_graph,
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build_interaction_role_graph,
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build_manual_role_graph,
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)
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from hardcore_role_oral import build_oral_role_graph
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from hardcore_role_outercourse import build_outercourse_role_graph
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from hardcore_role_penetration import build_penetration_role_graph
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def _lettered(prefix: str, count: int) -> list[str]:
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letters = "ABCDEFGHIJKLMNOPQRSTUVWXYZ"
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return [f"{prefix.capitalize()} {letters[index]}" for index in range(max(0, count))]
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def _pick_distinct(rng: random.Random, items: list[str], count: int) -> list[str]:
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if not items:
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return []
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if len(items) >= count:
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return rng.sample(items, count)
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picked = list(items)
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while len(picked) < count:
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picked.append(items[rng.randrange(len(items))])
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return picked
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def _participant_context(women_count: int, men_count: int) -> dict[str, list[str]]:
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women = _lettered("woman", women_count)
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men = _lettered("man", men_count)
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return {"women": women, "men": men, "people": women + men}
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def build_hardcore_role_graph(
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rng: random.Random,
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subcategory: dict[str, Any],
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context: dict[str, Any],
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item_axis_values: dict[str, Any] | None = None,
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pov_labels: list[str] | None = None,
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) -> str:
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if context.get("subject_type") != "configured_cast":
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return ""
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women_count = int(context.get("women_count") or 0)
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men_count = int(context.get("men_count") or 0)
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people_count = women_count + men_count
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if people_count <= 0:
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return ""
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participants = _participant_context(women_count, men_count)
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women = participants["women"]
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men = participants["men"]
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people = participants["people"]
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slug = str(subcategory.get("slug") or subcategory.get("name") or "").lower()
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item_text = item_axis_policy.context_text(axis_values=item_axis_values)
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def any_person(exclude: set[str] | None = None) -> str:
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exclude = exclude or set()
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pool = [person for person in people if person not in exclude] or people
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return rng.choice(pool)
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def any_woman(exclude: set[str] | None = None) -> str:
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exclude = exclude or set()
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pool = [person for person in women if person not in exclude] or [person for person in people if person not in exclude] or people
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return rng.choice(pool)
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def any_man(exclude: set[str] | None = None) -> str:
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exclude = exclude or set()
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pool = [person for person in men if person not in exclude] or [person for person in people if person not in exclude] or people
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return rng.choice(pool)
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if people_count == 1:
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return build_solo_role_graph(people[0], women_count, slug, item_text, item_axis_values)
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if women_count > 0 and men_count == 0:
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a, b = _pick_distinct(rng, women, 2)
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c = any_woman({a, b}) if len(women) >= 3 else ""
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used = {a, b}
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if any(token in slug for token in ("foreplay", "body_worship", "clothing_position", "dominant_guidance", "camera_performance", "aftercare")):
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graph = build_interaction_role_graph(a, b, c, slug, item_text, item_axis_values)
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if c and "camera_performance" in slug:
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used.add(c)
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elif "foreplay" in slug:
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graph = build_foreplay_role_graph(a, b, item_text, item_axis_values)
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else:
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graph, used = build_women_only_role_graph(
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slug,
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a,
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b,
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c,
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c or any_woman({a}),
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item_text,
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item_axis_values,
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)
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return graph + build_support_sentence(rng, people, used)
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if men_count > 0 and women_count == 0:
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a, b = _pick_distinct(rng, men, 2)
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c = any_man({a, b}) if len(men) >= 3 else ""
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graph, used = build_men_only_role_graph(
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slug,
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a,
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b,
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c,
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c or any_man({a}),
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item_text,
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item_axis_values,
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)
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return graph + build_support_sentence(rng, people, used)
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woman = any_woman()
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man = any_man()
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third = any_person({woman, man}) if people_count >= 3 else ""
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if "manual_stimulation" in slug:
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graph = build_manual_role_graph(woman, man, item_text, item_axis_values)
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elif "group_coordination" in slug:
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graph = build_group_coordination_role_graph(
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woman,
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man,
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third,
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any_person({woman, man}) if not third else "",
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item_text,
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item_axis_values,
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)
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elif any(token in slug for token in ("foreplay", "body_worship", "clothing_position", "dominant_guidance", "camera_performance", "aftercare")):
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graph = build_interaction_role_graph(woman, man, third, slug, item_text, item_axis_values)
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elif "foreplay" in slug:
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graph = build_foreplay_role_graph(woman, man, item_text, item_axis_values)
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elif "outercourse" in slug:
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graph = build_outercourse_role_graph(woman, man, item_text, item_axis_values, pov_labels)
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elif "oral" in slug:
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graph = build_oral_role_graph(woman, man, item_text, item_axis_values, pov_labels)
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elif "anal" in slug or "double" in slug:
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graph = build_anal_or_double_role_graph(woman, man, third, people_count, item_text, item_axis_values)
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elif "threesome" in slug or "group" in slug or "orgy" in slug:
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graph = build_mixed_group_fallback_role_graph(woman, man, third, any_person({woman, man}), slug)
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elif "cumshot" in slug or "climax" in slug:
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graph = build_climax_role_graph(woman, man, third, item_text, item_axis_values)
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else:
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graph = build_penetration_role_graph(woman, man, item_text, item_axis_values)
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return graph + build_support_sentence(rng, people, {woman, man, third} if third else {woman, man})
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