OpenClaw 使用指南

code --install-extension nickcoutsos.openclaw

{
  "openclaw.apiKey": "sk-...",
  "openclaw.model": "gpt-4o",
  "openclaw.temperature": 0.7,
  "openclaw.maxTokens": 4096
}

{
  "openclaw.apiKey": "your-api-key",
  "openclaw.provider": "openai",  // openai | anthropic | google
  "openclaw.model": "gpt-4o",
  "openclaw.temperature": 0.7,
  "openclaw.maxTokens": 4096,
  "openclaw.baseUrl": "https://api.openai.com/v1",  // 自定义端点
  "openclaw.streaming": true,
  "openclaw.autoScroll": true,
  "openclaw.promptPrefix": "You are a helpful coding assistant."
}

def fibonacci(n):
    """计算斐波那契数列第 n 项"""
    if n <= 0:
        return 0
    if n == 1:
        return 1
    
    a, b = 0, 1
    for _ in range(2, n + 1):
        a, b = b, a + b
    return b

{
  "openclaw.plugins": {
    "snippets": {
      "enabled": true,
      "languages": ["python", "javascript", "typescript"]
    },
    "refactor": {
      "enabled": true,
      "autoSuggest": true
    }
  }
}

import os
import glob

def rename_jpeg_to_jpg(directory="."):
    """将 .jpeg 文件重命名为 .jpg"""
    pattern = os.path.join(directory, "*.jpeg")
    files = glob.glob(pattern)
    
    renamed_count = 0
    for filepath in files:
        old_name = filepath
        new_name = filepath.replace(".jpeg", ".jpg")
        
        if not os.path.exists(new_name):
            os.rename(old_name, new_name)
            renamed_count += 1
            print(f"重命名: {old_name} -> {new_name}")
    
    print(f"\n完成！共重命名 {renamed_count} 个文件")

if __name__ == "__main__":
    rename_jpeg_to_jpg()

import csv
from collections import defaultdict

def analyze_csv(filepath):
    """分析 CSV 文件并生成统计报告"""
    with open(filepath, 'r', encoding='utf-8') as f:
        reader = csv.DictReader(f)
        data = defaultdict(list)
        
        for row in reader:
            for key, value in row.items():
                try:
                    data[key].append(float(value))
                except (ValueError, TypeError):
                    pass  # 跳过非数值列
    
    # 生成报告
    report = []
    report.append("=" * 50)
    report.append("CSV 统计分析报告")
    report.append("=" * 50)
    
    for column, values in data.items():
        if values:
            avg = sum(values) / len(values)
            max_val = max(values)
            min_val = min(values)
            
            report.append(f"\n列: {column}")
            report.append(f"  记录数: {len(values)}")
            report.append(f"  平均值: {avg:.2f}")
            report.append(f"  最大值: {max_val:.2f}")
            report.append(f"  最小值: {min_val:.2f}")
    
    report_text = "\n".join(report)
    print(report_text)
    
    # 保存报告
    with open("report.txt", "w", encoding="utf-8") as f:
        f.write(report_text)

if __name__ == "__main__":
    import sys
    if len(sys.argv) > 1:
        analyze_csv(sys.argv[1])
    else:
        print("用法: python analyze.py <csv文件路径>")

import pandas as pd

# 1. 创建 DataFrame
data = {
    'name': ['Alice', 'Bob', 'Charlie'],
    'age': [25, 30, 35],
    'score': [85, 92, 78]
}
df = pd.DataFrame(data)

# 2. 筛选数据
df[df['age'] > 25]  # 年龄大于25的记录
df[df['name'].str.startswith('A')]  # 名字以A开头的记录

# 3. 聚合统计
df['score'].mean()  # 平均分
df.groupby('age').count()  # 按年龄分组计数

import re

# 邮箱地址
email_pattern = r'^[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}$'

# 中国大陆手机号
phone_pattern = r'^1[3-9]\d{9}$'

# URL
url_pattern = r'^https?://[\w\-.]+(:\d+)?(/[\w\-./?%&=]*)?$'

# 测试
test_email = "user@example.com"
test_phone = "13812345678"
test_url = "https://example.com/path"

print(f"邮箱: {bool(re.match(email_pattern, test_email))}")
print(f"手机: {bool(re.match(phone_pattern, test_phone))}")
print(f"URL: {bool(re.match(url_pattern, test_url))}")

SELECT 
    DATE_FORMAT(order_date, '%Y-%m') AS month,
    COUNT(*) AS order_count,
    SUM(total_amount) AS total_revenue
FROM orders
WHERE status = '已完成'
GROUP BY DATE_FORMAT(order_date, '%Y-%m')
ORDER BY month;

# 设置环境变量
export OPENAI_API_KEY="sk-..."

{
  "openclaw.timeout": 120,
  "openclaw.retries": 3
}