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https://github.com/denizsafak/abogen.git
synced 2026-07-18 05:40:26 +02:00
feat: Enhance CalibreOPDSClient with improved search scoring and OpenSearch template fetching
This commit is contained in:
@@ -4,12 +4,12 @@ import dataclasses
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import html
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import re
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import unicodedata
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import xml.etree.ElementTree as ET
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from collections import deque
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from dataclasses import dataclass, field
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from pathlib import PurePosixPath
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from typing import Any, Deque, Dict, Iterable, Iterator, List, Mapping, Optional, Set, Tuple
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from typing import Any, Deque, Dict, Iterable, Iterator, List, Mapping, Optional, Set, Tuple, Union
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from urllib.parse import quote, urljoin, urlparse
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from xml.etree import ElementTree as ET
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import httpx
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@@ -43,6 +43,12 @@ _EPUB_MIME_TYPES = {
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}
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_SUPPORTED_DOWNLOAD_MIME_TYPES = set(_EPUB_MIME_TYPES) | {"application/pdf"}
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_SUPPORTED_DOWNLOAD_EXTENSIONS = {".epub", ".pdf"}
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_STOP_WORDS = {
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"a", "an", "the", "and", "or", "but", "if", "then", "else", "when",
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"at", "by", "for", "from", "in", "into", "of", "off", "on", "onto",
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"to", "with", "is", "are", "was", "were", "be", "been", "being",
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"that", "this", "these", "those", "it", "its"
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}
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class CalibreOPDSError(RuntimeError):
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@@ -199,6 +205,59 @@ class CalibreOPDSClient:
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return self._parse_feed(response.text, base_url=target)
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def _fetch_opensearch_template(self, href: str) -> Optional[str]:
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target = self._make_url(href)
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try:
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with self._open_client() as client:
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response = client.get(target, follow_redirects=True)
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response.raise_for_status()
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# Simple XML parsing to find the Url template
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# We avoid full namespace handling for robustness
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root = ET.fromstring(response.text)
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for node in root.iter():
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if node.tag.endswith("Url"):
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template = node.attrib.get("template")
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if template and "{searchTerms}" in template:
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mime = node.attrib.get("type", "")
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# Prefer atom/xml feeds
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if "atom" in mime or "xml" in mime:
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return template
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return None
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except Exception:
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return None
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def _find_best_seed_feed(self, root_feed: OPDSFeed) -> OPDSFeed:
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# If the root feed already has books, use it
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for entry in root_feed.entries:
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if any("acquisition" in (link.rel or "") for link in entry.links):
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return root_feed
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# Otherwise, look for a "By Title" or "All" navigation entry
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candidates = ["title", "all", "books", "catalog"]
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best_href = None
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for entry in root_feed.entries:
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title_lower = (entry.title or "").lower()
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if any(c in title_lower for c in candidates):
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# Check if it has a navigation link
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for link in entry.links:
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if self._is_navigation_link(link):
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best_href = link.href
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# Prefer "By Title" explicitly
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if "title" in title_lower:
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break
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if best_href and "title" in title_lower:
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break
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if best_href:
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try:
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return self.fetch_feed(best_href)
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except CalibreOPDSError:
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pass
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return root_feed
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def search(self, query: str, start_href: Optional[str] = None) -> OPDSFeed:
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cleaned = (query or "").strip()
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if not cleaned:
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@@ -210,37 +269,62 @@ class CalibreOPDSClient:
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except CalibreOPDSError:
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pass
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candidates: List[Tuple[Optional[str], Optional[Mapping[str, Any]]]] = []
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# 1. Try explicit search link from feed
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if base_feed:
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# Check for OpenSearch description first
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search_link = self._resolve_link(base_feed.links, "search")
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if search_link and search_link.type == "application/opensearchdescription+xml":
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template = self._fetch_opensearch_template(search_link.href)
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if template:
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search_url = template.replace("{searchTerms}", quote(cleaned))
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try:
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feed = self.fetch_feed(search_url)
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if feed.entries:
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filtered = self._filter_feed_entries(feed, cleaned)
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if filtered.entries:
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return filtered
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except CalibreOPDSError:
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pass
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# Check for direct template
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search_url = self._resolve_search_url(base_feed, cleaned)
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if search_url:
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candidates.append((search_url, None))
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try:
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feed = self.fetch_feed(search_url)
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if feed.entries:
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filtered = self._filter_feed_entries(feed, cleaned)
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if filtered.entries:
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return filtered
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except CalibreOPDSError:
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pass
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candidates.extend([
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# 2. Try common guesses if explicit link failed
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candidates: List[Tuple[Optional[str], Optional[Mapping[str, Any]]]] = [
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("search", {"query": cleaned}),
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("search", {"q": cleaned}),
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(None, {"search": cleaned}),
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])
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]
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last_error: Optional[Exception] = None
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base_combined: Optional[OPDSFeed] = None
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# Try server-side search first (global search)
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for path, params in candidates:
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try:
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feed = self.fetch_feed(path, params=params)
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if feed.entries:
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# Check if the server ignored the query and returned the default feed
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if base_feed and feed.title == base_feed.title:
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# Compare first entry ID to see if it's the same feed
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if feed.entries[0].id == base_feed.entries[0].id:
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continue
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filtered = self._filter_feed_entries(feed, cleaned)
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if filtered.entries:
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return filtered
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except CalibreOPDSError as exc:
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last_error = exc
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continue
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# If we got results from server search, use them
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if feed.entries:
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return feed
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# Fallback to local search (crawling)
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# If start_href is provided, we search from there (contextual search)
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# Otherwise we search from root (which might be empty if root has no books)
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# 3. Fallback to local search (crawling)
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seed_feed: Optional[OPDSFeed] = None
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if start_href:
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try:
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@@ -249,7 +333,8 @@ class CalibreOPDSClient:
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pass
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if not seed_feed and base_feed:
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seed_feed = base_feed
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# If we are falling back to base_feed (Root), try to find a better seed
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seed_feed = self._find_best_seed_feed(base_feed)
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if not seed_feed:
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try:
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@@ -259,7 +344,22 @@ class CalibreOPDSClient:
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raise last_error
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raise exc
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return self._local_search(cleaned, seed_feed=seed_feed)
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# Heuristic: If the seed feed has acquisition links, use linear scan.
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# Otherwise, use BFS to find content.
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has_books = False
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if seed_feed and seed_feed.entries:
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for entry in seed_feed.entries[:5]:
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for link in entry.links:
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if "acquisition" in (link.rel or ""):
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has_books = True
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break
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if has_books:
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break
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if has_books:
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return self._collect_search_results(seed_feed, cleaned)
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else:
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return self._local_search(cleaned, seed_feed=seed_feed)
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def _collect_search_results(
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self,
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@@ -484,7 +584,8 @@ class CalibreOPDSClient:
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feed_id = root.findtext("atom:id", default=None, namespaces=NS)
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feed_title = root.findtext("atom:title", default=None, namespaces=NS)
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links = self._parse_links(root.findall("atom:link", NS), base_url)
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links_list = self._extract_links(root.findall("atom:link", NS), base_url)
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links = self._links_to_dict(links_list)
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parsed_entries = [self._parse_entry(node, base_url) for node in root.findall("atom:entry", NS)]
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entries: List[OPDSEntry] = []
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for entry in parsed_entries:
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@@ -531,10 +632,11 @@ class CalibreOPDSClient:
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authors.append(value)
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links = node.findall("atom:link", NS)
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parsed_links = self._parse_links(links, base_url)
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download_link = self._select_download_link(parsed_links.values())
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alternate_link = parsed_links.get("alternate")
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thumb_link = parsed_links.get("http://opds-spec.org/image/thumbnail") or parsed_links.get(
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all_links = self._extract_links(links, base_url)
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link_dict = self._links_to_dict(all_links)
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download_link = self._select_download_link(all_links)
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alternate_link = link_dict.get("alternate")
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thumb_link = link_dict.get("http://opds-spec.org/image/thumbnail") or link_dict.get(
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"thumbnail"
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)
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@@ -595,7 +697,7 @@ class CalibreOPDSClient:
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download=download_link,
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alternate=alternate_link,
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thumbnail=thumb_link,
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links=list(parsed_links.values()),
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links=all_links,
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series=series_name,
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series_index=series_index,
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tags=tags,
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@@ -782,8 +884,8 @@ class CalibreOPDSClient:
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continue
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return None
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def _parse_links(self, link_nodes: List[ET.Element], base_url: str) -> Dict[str, OPDSLink]:
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results: Dict[str, OPDSLink] = {}
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def _extract_links(self, link_nodes: List[ET.Element], base_url: str) -> List[OPDSLink]:
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links: List[OPDSLink] = []
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for link in link_nodes:
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href = link.attrib.get("href")
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if not href:
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@@ -793,15 +895,22 @@ class CalibreOPDSClient:
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title = link.attrib.get("title")
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base_for_join = base_url or self._base_url
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absolute_href = urljoin(base_for_join, href)
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entry = OPDSLink(href=absolute_href, rel=rel, type=link_type, title=title)
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key = rel or absolute_href
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links.append(OPDSLink(href=absolute_href, rel=rel, type=link_type, title=title))
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return links
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def _links_to_dict(self, links: List[OPDSLink]) -> Dict[str, OPDSLink]:
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results: Dict[str, OPDSLink] = {}
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for entry in links:
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key = entry.rel or entry.href
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if not key:
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continue
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# Prioritize search links with template parameters
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if key == "search" and key in results:
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existing = results[key]
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if "{searchTerms}" in (existing.href or ""):
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continue
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if "{searchTerms}" in absolute_href:
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if "{searchTerms}" in (entry.href or ""):
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results[key] = entry
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continue
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@@ -988,7 +1097,18 @@ class CalibreOPDSClient:
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tokens = [token for token in re.split(r"\s+", normalized_query) if token]
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if not tokens:
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return feed
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filtered = [entry for entry in feed.entries if self._entry_matches_query(entry, tokens)]
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scored_entries = []
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for entry in feed.entries:
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score = self._calculate_match_score(entry, tokens)
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# Require a minimum score to avoid weak matches (e.g. single word in summary)
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if score >= 10:
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scored_entries.append((score, entry))
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# Sort by score descending
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scored_entries.sort(key=lambda x: x[0], reverse=True)
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filtered = [e for s, e in scored_entries]
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return dataclasses.replace(feed, entries=filtered)
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def browse_letter(
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@@ -1094,8 +1214,89 @@ class CalibreOPDSClient:
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return href
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def _calculate_match_score(self, entry: OPDSEntry, tokens: List[str]) -> int:
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if not tokens:
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return 0
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score = 0
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# Prepare normalized text
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title = self._normalize_text(entry.title)
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authors = [self._normalize_text(a) for a in entry.authors]
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series = self._normalize_text(entry.series) if entry.series else ""
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summary = self._normalize_text(entry.summary) if entry.summary else ""
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tags = [self._normalize_text(t) for t in entry.tags]
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# 1. Exact/Phrase matches
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query_phrase = " ".join(tokens)
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if query_phrase == title:
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score += 1000
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elif query_phrase in title:
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score += 500
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for author in authors:
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if query_phrase in author:
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score += 300
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if query_phrase in series:
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score += 200
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for tag in tags:
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if query_phrase == tag:
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score += 100
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elif query_phrase in tag:
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score += 50
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def feed_to_dict(feed: OPDSFeed) -> Dict[str, Any]:
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"""Helper used by APIs to convert a feed into JSON-serialisable payloads."""
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# 2. Token matches
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# Filter out stop words unless the query is only stop words
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significant_tokens = [t for t in tokens if t not in _STOP_WORDS]
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if not significant_tokens:
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significant_tokens = tokens
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return feed.to_dict()
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for token in significant_tokens:
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token_score = 0
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# Use regex for word boundary matching
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# Escape token to handle special chars
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token_regex = r"\b" + re.escape(token) + r"\b"
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# Title: High weight
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if re.search(token_regex, title):
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token_score = max(token_score, 50)
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elif token in title:
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token_score = max(token_score, 5)
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# Author: Medium-High weight
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for author in authors:
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if re.search(token_regex, author):
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token_score = max(token_score, 40)
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elif token in author:
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token_score = max(token_score, 5)
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# Series: Medium weight
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if token in series:
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if re.search(token_regex, series):
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token_score = max(token_score, 30)
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else:
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token_score = max(token_score, 5)
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# Tags: Medium weight
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for tag in tags:
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if re.search(token_regex, tag):
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token_score = max(token_score, 30)
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elif token in tag:
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token_score = max(token_score, 5)
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# Summary: Low weight
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if token in summary:
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if re.search(token_regex, summary):
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# Only add if not found elsewhere? Or just add small amount?
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if token_score == 0:
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token_score = 15
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else:
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token_score += 5 # Small boost if also in description
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elif token_score == 0:
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token_score = 2 # Very low for substring in summary
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score += token_score
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return score
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