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#![cfg_attr(not(feature = "official-api"), allow(dead_code))]
use regex::Regex;
use std::sync::OnceLock;
use super::html_utils::{escape_html, unescape_basic_entities};
// Compiled regexes for performance (compiled once, reused across calls)
fn class_attr_regex() -> &'static Regex {
static REGEX: OnceLock<Regex> = OnceLock::new();
// Note: This pattern handles typical HTML class attributes but doesn't handle edge cases
// like escaped quotes within the class value. In practice, Tomato Novel API HTML doesn't
// use such complex patterns.
REGEX.get_or_init(|| Regex::new(r#"(?i)\bclass\s*=\s*["']([^"']*)["']"#).unwrap())
}
// Regex to match both paragraphs and headings (for skipping headings like clean_epub_body does)
fn para_and_heading_regex() -> &'static Regex {
static REGEX: OnceLock<Regex> = OnceLock::new();
REGEX.get_or_init(|| {
Regex::new(r"(?is)(<p\b[^>]*>)(.*?)(</p>)|(<h[1-6]\b[^>]*?>.*?</h[1-6]>)").unwrap()
})
}
fn id_attr_regex() -> &'static Regex {
static REGEX: OnceLock<Regex> = OnceLock::new();
REGEX.get_or_init(|| Regex::new(r"(?is)\bid\s*=").unwrap())
}
fn html_tags_regex() -> &'static Regex {
static REGEX: OnceLock<Regex> = OnceLock::new();
REGEX.get_or_init(|| Regex::new(r"<[^>]+>").unwrap())
}
fn bracket_emoji_regex() -> &'static Regex {
static REGEX: OnceLock<Regex> = OnceLock::new();
REGEX.get_or_init(|| Regex::new(r"\[([\u4e00-\u9fa5]{1,4})\]").unwrap())
}
/// 将 [笑] 形式的简单表情替换为 emoji。
pub fn convert_bracket_emojis(text: &str) -> String {
if !text.contains('[') {
return text.to_string();
}
let map = emoji_map();
bracket_emoji_regex()
.replace_all(text, |caps: ®ex::Captures| {
let key = caps.get(1).map(|m| m.as_str()).unwrap_or("");
map.get(key).cloned().unwrap_or_else(|| caps[0].to_string())
})
.to_string()
}
pub fn to_cjk_numeral(n: i32) -> String {
let digits = ["零", "一", "二", "三", "四", "五", "六", "七", "八", "九"];
if n <= 0 {
return n.to_string();
}
if n < 10 {
return digits[n as usize].to_string();
}
if n == 10 {
return "十".to_string();
}
if n < 20 {
return format!("十{}", digits[(n - 10) as usize]);
}
if n < 100 {
let shi = n / 10;
let ge = n % 10;
if ge == 0 {
format!("{}十", digits[shi as usize])
} else {
format!("{}十{}", digits[shi as usize], digits[ge as usize])
}
} else {
n.to_string()
}
}
/// 检查段落是否应该在段评计数时跳过(如图片包装段落、卷标题等)。
fn should_skip_para_for_comments(open_tag: &str) -> bool {
// List of class names that should be skipped when counting content paragraphs.
// Uses linear search which is efficient for small lists (9 items).
static SKIP_CLASSES: &[&str] = &[
"picture",
"volumetitle",
"volume-title",
"sectiontitle",
"section-title",
"catalogtitle",
"catalog-title",
"chaptertitle",
"chapter-title",
];
// Match class="..." or class='...' with exact class names or class lists
if let Some(caps) = class_attr_regex().captures(open_tag)
&& let Some(class_list) = caps.get(1)
{
let classes = class_list.as_str();
// Split by whitespace to get individual class names
for class in classes.split_whitespace() {
let lower = class.to_ascii_lowercase();
if SKIP_CLASSES.contains(&lower.as_str()) {
return true;
}
}
}
false
}
/// 提取指定段落的纯文本摘要(用于段评回链)。
pub fn extract_para_snippet(chapter_html: &str, target_idx: usize) -> String {
let mut content_idx = 0;
for cap in para_and_heading_regex().captures_iter(chapter_html) {
// Skip headings (group 4) - they're not content paragraphs
if cap.get(4).is_some() {
continue;
}
let open_tag = cap.get(1).map(|m| m.as_str()).unwrap_or("");
// Skip non-content paragraphs to match API's paragraph counting
if should_skip_para_for_comments(open_tag) {
continue;
}
if content_idx == target_idx {
let inner = cap.get(2).map(|m| m.as_str()).unwrap_or("");
let inner_text = strip_tags(inner);
let inner_text = unescape_basic_entities(&inner_text);
let inner_text = inner_text.trim().to_string();
if inner_text.is_empty() {
return String::new();
}
let cut = ["。", "!", "?", ".", "!", "?", ";", "…"]
.iter()
.filter_map(|sep| inner_text.find(sep).map(|p| p + sep.len()))
.min()
.unwrap_or_else(|| inner_text.len().min(20));
return inner_text[..cut].trim().to_string();
}
content_idx += 1;
}
String::new()
}
pub fn inject_segment_links(
content_html: &str,
comments_file: &str,
seg_counts: &serde_json::Map<String, serde_json::Value>,
) -> String {
// Mirror Python logic in `segment_utils.py`:
// - iterate <p> in-order with a monotonically increasing idx
// - SKIP non-content paragraphs (picture wrappers, volume titles, etc.) to match API counting
// - SKIP headings (EpubGenerator already injects <h1> for chapter title)
// - if cnt>0 and <p> has no id=, add id="p-{idx}" while preserving other attrs
// - append a badge link to the segment comment page
let mut out = String::new();
let mut last_end = 0usize;
let mut content_idx = 0usize; // Index for content paragraphs only
for m in para_and_heading_regex().find_iter(content_html) {
out.push_str(&content_html[last_end..m.start()]);
let caps = para_and_heading_regex().captures(m.as_str()).unwrap();
// Check if this is a heading (group 4)
if caps.get(4).is_some() {
// Skip headings entirely (like clean_epub_body does) since wrap_chapter_html adds <h1>
last_end = m.end();
continue;
}
// This is a paragraph (groups 1-3)
let mut open_tag = caps.get(1).map(|m| m.as_str()).unwrap_or("").to_string();
let mut inner = caps.get(2).map(|m| m.as_str()).unwrap_or("").to_string();
inner = normalize_html_text_nodes(&inner);
let close_tag = caps.get(3).map(|m| m.as_str()).unwrap_or("");
// Skip non-content paragraphs to match API's paragraph counting
if should_skip_para_for_comments(&open_tag) {
out.push_str(&open_tag);
out.push_str(&inner);
out.push_str(close_tag);
last_end = m.end();
continue;
}
let cnt = seg_counts
.get(&content_idx.to_string())
.and_then(|v| v.as_u64())
.unwrap_or(0);
if cnt > 0 {
if !id_attr_regex().is_match(&open_tag) && open_tag.ends_with('>') {
open_tag.pop();
open_tag.push_str(&format!(" id=\"p-{}\">", content_idx));
}
inner.push_str(&format!(
" <a class=\"seg-count\" href=\"{}#para-{}\" title=\"查看本段评论\">({})</a>",
html_escape_attr(comments_file),
content_idx,
cnt
));
}
out.push_str(&open_tag);
out.push_str(&inner);
out.push_str(close_tag);
last_end = m.end();
content_idx += 1; // Only increment for content paragraphs
}
out.push_str(&content_html[last_end..]);
out
}
fn html_escape_attr(input: &str) -> String {
// Sufficient for EPUB internal href attr.
input
.replace('&', "&")
.replace('<', "<")
.replace('>', ">")
.replace('"', """)
.replace('\'', "'")
}
fn strip_tags(raw: &str) -> String {
html_tags_regex().replace_all(raw, "").to_string()
}
fn normalize_html_text_nodes(fragment: &str) -> String {
if !fragment.contains('&') {
return fragment.to_string();
}
let mut out = String::with_capacity(fragment.len());
let mut text_buf = String::new();
let mut in_tag = false;
for ch in fragment.chars() {
match ch {
'<' if !in_tag => {
if !text_buf.is_empty() {
out.push_str(&normalize_text_segment(&text_buf));
text_buf.clear();
}
in_tag = true;
out.push(ch);
}
'>' if in_tag => {
in_tag = false;
out.push(ch);
}
_ if in_tag => out.push(ch),
_ => text_buf.push(ch),
}
}
if !text_buf.is_empty() {
out.push_str(&normalize_text_segment(&text_buf));
}
out
}
fn normalize_text_segment(text: &str) -> String {
let decoded = unescape_basic_entities(text);
escape_html(decoded.as_ref())
}
fn emoji_map() -> std::collections::HashMap<&'static str, String> {
use std::collections::HashMap;
let mut m = HashMap::new();
m.insert("笑", "😄".to_string());
m.insert("哭", "😭".to_string());
m.insert("汗", "😅".to_string());
m.insert("怒", "😡".to_string());
m.insert("痛", "😣".to_string());
m.insert("赞", "👍".to_string());
m.insert("踩", "👎".to_string());
m.insert("惊", "😲".to_string());
m.insert("疑", "🤔".to_string());
m.insert("色", "😍".to_string());
m.insert("呆", "😐".to_string());
m.insert("坏", "😈".to_string());
m.insert("奸笑", "😏".to_string());
m.insert("舔屏", "🤤".to_string());
m.insert("委屈", "🥺".to_string());
m.insert("飞吻", "😘".to_string());
m.insert("酷", "😎".to_string());
m.insert("送心", "💖".to_string());
m.insert("我也强推", "💯".to_string());
m.insert("惊呆", "😲".to_string());
m.insert("偷笑", "🤭".to_string());
m.insert("翻白眼", "🙄".to_string());
m.insert("石化", "🗿".to_string());
m
}
#[cfg(test)]
mod tests {
use super::{extract_para_snippet, inject_segment_links};
use serde_json::json;
#[test]
fn extract_para_snippet_decodes_html_entities() {
let html = "<p>她说&#34;你好&#34;。</p>";
assert_eq!(extract_para_snippet(html, 0), "她说\"你好\"。");
}
#[test]
fn inject_segment_links_normalizes_text_nodes_but_preserves_attrs() {
let mut seg_counts = serde_json::Map::new();
seg_counts.insert("0".to_string(), json!(3));
let out = inject_segment_links(
r#"<p class="content" data-ref="a&b">她说&#34;你好&#34;<span>It&#39;s me</span></p>"#,
"aux_00001.xhtml",
&seg_counts,
);
assert!(out.contains(r#"data-ref="a&b""#));
assert!(out.contains("她说"你好"<span>It's me</span>"));
assert!(out.contains(r#"id="p-0""#));
assert!(out.contains(r#"href="aux_00001.xhtml#para-0""#));
assert!(!out.contains("&#34;"));
assert!(!out.contains("&#39;"));
}
}
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