本文目录导读：
基础Python脚本（使用列表）
# 简单的诗词数据库
poems = [
{"title": "静夜思", "author": "李白", "content": "床前明月光，疑是地上霜，举头望明月，低头思故乡。"},
{"title": "春晓", "author": "孟浩然", "content": "春眠不觉晓，处处闻啼鸟，夜来风雨声，花落知多少。"},
{"title": "登鹳雀楼", "author": "王之涣", "content": "白日依山尽，黄河入海流，欲穷千里目，更上一层楼。"}
]
def search_poems(keyword):
results = []
for poem in poems:
if keyword in poem["title"] or keyword in poem["content"] or keyword in poem["author"]:
results.append(poem)
return results
# 使用示例
keyword = "月"
results = search_poems(keyword)
for r in results:
print(f"{r['title']} - {r['author']}")
print(r['content'])
print("---")
使用JSON文件的完整检索系统
import json
import re
class PoemSearch:
def __init__(self, json_file="poems.json"):
self.poems = self.load_poems(json_file)
def load_poems(self, file_path):
with open(file_path, 'r', encoding='utf-8') as f:
return json.load(f)
def search_by_keyword(self, keyword, fields=None):
"""
关键词检索
:param keyword: 搜索关键词
:param fields: 搜索范围，如 ["title", "content", "author"]
"""
if fields is None:
fields = ["title", "content", "author", "dynasty"]
results = []
keyword_lower = keyword.lower()
for poem in self.poems:
for field in fields:
if field in poem and isinstance(poem[field], str):
if keyword_lower in poem[field].lower():
results.append(poem)
break
return results
def search_by_regex(self, pattern, fields=None):
"""
正则表达式检索
"""
if fields is None:
fields = ["title", "content"]
results = []
for poem in self.poems:
for field in fields:
if field in poem:
if re.search(pattern, poem[field]):
results.append(poem)
break
return results
def fuzzy_search(self, keyword, threshold=0.6):
"""
模糊检索（使用Levenshtein距离）
"""
from fuzzywuzzy import fuzz
results = []
for poem in self.poems:
score = 0
# 计算标题和内容的相似度
title_score = fuzz.partial_ratio(keyword, poem.get("title", ""))
content_score = fuzz.partial_ratio(keyword, poem.get("content", ""))
score = max(title_score, content_score) / 100
if score >= threshold:
poem["similarity"] = score
results.append(poem)
# 按相似度排序
results.sort(key=lambda x: x["similarity"], reverse=True)
return results
# 使用示例
search = PoemSearch()
# 普通搜索
results = search.search_by_keyword("明月")
# 正则搜索 - 搜索以"月"结尾的诗句
results = search.search_by_regex(r'月$')
# 模糊搜索
results = search.fuzzy_search("明朋光")
命令行版本
#!/usr/bin/env python3
# poem_search.py
import json
import sys
from colorama import init, Fore, Style
init(autoreset=True) # 初始化colorama
class PoemCLI:
def __init__(self):
self.poems = self.load_default_data()
def load_default_data(self):
# 这里可以加载JSON文件
return [
{
"title": "静夜思",
"author": "李白",
"dynasty": "唐",
"content": "床前明月光，疑是地上霜，举头望明月，低头思故乡。"
},
# ... 更多诗词
]
def search_and_display(self, keyword):
results = []
for poem in self.poems:
if (keyword in poem["title"] or
keyword in poem["content"] or
keyword in poem["author"]):
results.append(poem)
if not results:
print(f"{Fore.RED}未找到包含'{keyword}'的诗词")
return
print(f"{Fore.GREEN}找到 {len(results)} 首诗词：\n")
for i, poem in enumerate(results, 1):
print(f"{Fore.YELLOW}{i}. {poem['title']}")
print(f" {Fore.CYAN}作者：{poem['author']} | 朝代：{poem['dynasty']}")
print(f" {Fore.WHITE}{poem['content']}")
# 高亮关键字
highlighted = poem['content'].replace(
keyword,
f"{Fore.RED}{keyword}{Style.RESET_ALL}"
)
print(f" {highlighted}")
print()
def main():
if len(sys.argv) < 2:
print("使用方法：python poem_search.py <关键词>")
sys.exit(1)
keyword = sys.argv[1]
cli = PoemCLI()
cli.search_and_display(keyword)
if __name__ == "__main__":
main()
使用SQLite数据库的高级版本
import sqlite3
import jieba
class AdvancedPoemSearch:
def __init__(self, db_path="poems.db"):
self.conn = sqlite3.connect(db_path)
self.create_tables()
def create_tables(self):
cursor = self.conn.cursor()
cursor.execute('''
CREATE TABLE IF NOT EXISTS poems (
id INTEGER PRIMARY KEY,
title TEXT,
author TEXT,
dynasty TEXT,
content TEXT
)
''')
cursor.execute('''
CREATE INDEX IF NOT EXISTS idx_content
ON poems(content)
''')
self.conn.commit()
def fulltext_search(self, keyword):
"""全文搜索"""
cursor = self.conn.cursor()
cursor.execute('''
SELECT * FROM poems
WHERE content LIKE ? OR title LIKE ? OR author LIKE ?
''', (f'%{keyword}%', f'%{keyword}%', f'%{keyword}%'))
return cursor.fetchall()
def keyword_analysis(self, text):
"""中文分词和关键词提取"""
words = jieba.lcut(text)
# 去除停用词
stop_words = set(['的', '了', '是', '在', '我', '有', '和', '就', '不', '人'])
keywords = [w for w in words if w not in stop_words and len(w) > 1]
return keywords
def advanced_search(self, keywords):
"""多关键词组合搜索"""
results = []
keywords_list = keywords.split()
for poem in self.get_all_poems():
score = 0
for kw in keywords_list:
if kw in poem['content']:
score += 1
if kw in poem['title']:
score += 2 # 标题匹配权重更高
if score > 0:
poem['score'] = score
results.append(poem)
# 按相关性排序
results.sort(key=lambda x: x['score'], reverse=True)
return results
# 使用示例
searcher = AdvancedPoemSearch()
results = searcher.fulltext_search("明月")
results = searcher.advanced_search("明月 思乡") # 多关键词搜索
PHP版本（Web接口）
<?php
// poem_search.php
class PoemSearch {
private $poems = [];
public function __construct() {
$this->loadPoems();
}
private function loadPoems() {
// 从文件加载诗词数据
$json = file_get_contents('poems.json');
$this->poems = json_decode($json, true);
}
public function search($keyword, $fields = ['title', 'content', 'author']) {
$results = [];
foreach ($this->poems as $poem) {
foreach ($fields as $field) {
if (isset($poem[$field]) &&
mb_stripos($poem[$field], $keyword) !== false) {
$results[] = $poem;
break;
}
}
}
return $results;
}
public function ajaxResponse($keyword) {
header('Content-Type: application/json; charset=utf-8');
$results = $this->search($keyword);
echo json_encode([
'status' => 'success',
'count' => count($results),
'data' => $results
]);
}
}
// HTML前端界面
?>
<!DOCTYPE html>
<html>
<head>诗词检索</title>
<style>
.search-box { margin: 20px; }
.result-item {
border: 1px solid #ddd;
margin: 10px 0;
padding: 10px;
}
.highlight {
background-color: yellow;
font-weight: bold;
}
</style>
</head>
<body>
<div class="search-box">
<input type="text" id="keyword" placeholder="输入关键词">
<button onclick="searchPoems()">搜索</button>
</div>
<div id="results"></div>
<script>
function searchPoems() {
const keyword = document.getElementById('keyword').value;
fetch(`poem_search.php?keyword=${encodeURIComponent(keyword)}`)
.then(response => response.json())
.then(data => {
displayResults(data);
});
}
function displayResults(data) {
const container = document.getElementById('results');
container.innerHTML = `<h3>找到 ${data.count} 首诗词</h3>`;
data.data.forEach(poem => {
const div = document.createElement('div');
div.className = 'result-item';
div.innerHTML = `
<h4>${poem.title}</h4>
<p>作者：${poem.author} | 朝代：${poem.dynasty}</p>
<p>${highlightKeyword(poem.content, keyword)}</p>
`;
container.appendChild(div);
});
}
function highlightKeyword(text, keyword) {
const regex = new RegExp(keyword, 'gi');
return text.replace(regex, `<span class="highlight">$&</span>`);
}
</script>
</body>
</html>
使用建议
- 小规模数据：使用Python列表或JSON文件
- 大规模数据：使用数据库（SQLite、MySQL）
- 需要高性能：使用Elasticsearch或Whoosh
- Web应用：使用PHP/Node.js配合前端框架
- 需要考虑：
- 中文分词（jieba）
- 同义词扩展
- 拼音搜索
- 模糊匹配
这些脚本可以根据你的具体需求进行调整和扩展,需要我详细解释某个特定部分吗？
