# retoor <retoor@molodetz.nl>
import math
import re
from collections import Counter
from functools import lru_cache

from bs4 import BeautifulSoup

from molodetz.docs_api import ordered_groups
from molodetz.docs_prose import DOCS_PAGES, render_page

TOKEN = re.compile(r"[a-z0-9_]+")
K1 = 1.5
B = 0.75


def tokenize(text):
    return TOKEN.findall((text or "").lower())


@lru_cache(maxsize=1)
def build_index():
    documents = []
    for page in DOCS_PAGES:
        text = BeautifulSoup(render_page(page["slug"]), "html.parser").get_text(" ")
        documents.append({"title": page["title"], "url": f"/docs/{page['slug']}", "text": text, "admin": bool(page.get("admin"))})
    for group in ordered_groups():
        lines = [group["title"], group["description"]]
        for item in group["endpoints"]:
            lines.append(f"{item['method']} {item['path']} {item['title']} {item['description']}")
        documents.append(
            {"title": f"API: {group['title']}", "url": f"/docs/api/{group['slug']}", "text": " ".join(lines), "admin": group["slug"] == "beheer"}
        )
    tokens = [Counter(tokenize(doc["title"] + " " + doc["text"])) for doc in documents]
    lengths = [sum(counter.values()) for counter in tokens]
    average = sum(lengths) / max(1, len(lengths))
    frequency = Counter()
    for counter in tokens:
        frequency.update(counter.keys())
    return documents, tokens, lengths, average, frequency


def _snippet(text, terms, width=160):
    lowered = text.lower()
    position = min((lowered.find(term) for term in terms if lowered.find(term) >= 0), default=0)
    start = max(0, position - width // 3)
    snippet = text[start : start + width].strip()
    for term in terms:
        snippet = re.sub(f"({re.escape(term)})", r"[[\1]]", snippet, flags=re.IGNORECASE)
    return snippet


def search(query, viewer_is_admin=False, limit=20):
    terms = tokenize(query)
    if not terms:
        return []
    documents, tokens, lengths, average, frequency = build_index()
    total = len(documents)
    results = []
    for index, doc in enumerate(documents):
        if doc["admin"] and not viewer_is_admin:
            continue
        score = 0.0
        for term in terms:
            tf = tokens[index].get(term, 0)
            if not tf:
                continue
            idf = math.log(1 + (total - frequency[term] + 0.5) / (frequency[term] + 0.5))
            score += idf * tf * (K1 + 1) / (tf + K1 * (1 - B + B * lengths[index] / average))
        if score > 0:
            results.append({"title": doc["title"], "url": doc["url"], "score": round(score, 3), "snippet": _snippet(doc["text"], terms)})
    results.sort(key=lambda item: item["score"], reverse=True)
    return results[:limit]