duckdb-sql
Analytical SQL engine for querying CSV, Parquet, and JSON files directly. No database setup required.
Source facts
- Repository
- malue-ai/dazee-small
- Last source activity
- March 7, 2026 at 06:41
- Detected SKILL.md language
- Chinese
- Stars
- 36
- Forks
- 2
Install options
The review-first prompt is selected by default. You can switch to a direct command or download a local copy.
Review the source files
Read SKILL.md and any companion files shown by SkillsMP before deciding whether to install.
Showing SKILL.md
SKILL.md
Source instructions · Read-only preview- name
- duckdb-sql
- description
- Analytical SQL engine for querying CSV, Parquet, and JSON files directly. No database setup required.
- metadata
- {"xiaodazi":{"dependency_level":"lightweight","os":["common"],"backend_type":"local","user_facing":true,"python_packages":["duckdb"]}}
- capabilities
- ["data_analysis","sql_query"]
# DuckDB SQL 分析引擎
用 SQL 直接查询 CSV、Parquet、JSON 文件，无需导入数据库。适合大数据集分析。
## 使用场景
- 用户说「用 SQL 分析这个 CSV 文件」「这个数据集有多少行」
- 数据量大（>10万行），excel-analyzer 处理较慢时
- 用户需要复杂聚合、JOIN、窗口函数等 SQL 功能
- 用户说「对比这两个 CSV 文件的差异」
## 与 excel-analyzer 的区别
| 工具 | 擅长 | 局限 |
|---|---|---|
| excel-analyzer | 小数据集、图表、格式化输出 | 大数据集慢 |
| **duckdb-sql** | **大数据集、复杂 SQL、多文件 JOIN** | 不做格式化输出 |
## 执行方式
### Python API
```python
import duckdb
con = duckdb.connect()
# 直接查询 CSV
result = con.sql("SELECT * FROM 'data.csv' LIMIT 10").fetchdf()
# 聚合分析
result = con.sql("""
SELECT category, COUNT(*) as count, AVG(price) as avg_price
FROM 'sales.csv'
GROUP BY category
ORDER BY count DESC
""").fetchdf()
# 多文件 JOIN
result = con.sql("""
SELECT o.order_id, c.name, o.total
FROM 'orders.csv' o
JOIN 'customers.csv' c ON o.customer_id = c.id
WHERE o.total > 1000
""").fetchdf()
# 查询 Parquet
result = con.sql("SELECT * FROM 'data.parquet' WHERE year = 2026").fetchdf()
# 通配符查询多文件
result = con.sql("SELECT * FROM 'logs/*.csv'").fetchdf()
```
### 命令行用法
```bash
# 安装
pip install duckdb
# 交互式
python3 -c "import duckdb; print(duckdb.sql(\"SELECT count(*) FROM 'data.csv'\").fetchone())"
```
### 常用分析模式
```sql
-- 数据概览
SUMMARIZE SELECT * FROM 'data.csv';
-- 去重计数
SELECT COUNT(DISTINCT user_id) FROM 'events.csv';
-- 窗口函数：排名
SELECT *, RANK() OVER (PARTITION BY department ORDER BY salary DESC) as rank
FROM 'employees.csv';
-- 导出结果
COPY (SELECT * FROM 'data.csv' WHERE status = 'active') TO 'output.csv';
```
## 输出规范
- 查询结果以表格格式展示（前 20 行 + 总行数）
- 大结果集自动截断，提示用户添加 LIMIT
- 查询耗时超过 5 秒时显示进度提示
View on GitHub