feat: 初始化 ProStock 项目基础结构和配置

- 添加项目规则文档（开发规范、安全规则、配置管理）
- 实现数据模块核心功能（API 客户端、限流器、存储管理、配置加载）
- 添加 .gitignore 和 .kilocodeignore 配置
- 配置环境变量模板
- 编写 daily 模块单元测试

src/data/client.py

@@ -0,0 +1,89 @@
+"""Simplified Tushare client with rate limiting and retry logic."""
+import time
+import pandas as pd
+from typing import Optional
+from src.data.config import get_config
+from src.data.rate_limiter import TokenBucketRateLimiter
+
+
+class TushareClient:
+    """Tushare API client with rate limiting and retry."""
+
+    def __init__(self, token: Optional[str] = None):
+        """Initialize client.
+
+        Args:
+            token: Tushare API token (auto-loaded from config if not provided)
+        """
+        cfg = get_config()
+        token = token or cfg.tushare_token
+
+        if not token:
+            raise ValueError("Tushare token is required")
+
+        self.token = token
+        self.config = cfg
+
+        # Initialize rate limiter: capacity = rate_limit, refill_rate = rate_limit/60 per second
+        rate_per_second = cfg.rate_limit / 60.0
+        self.rate_limiter = TokenBucketRateLimiter(
+            capacity=cfg.rate_limit,
+            refill_rate_per_second=rate_per_second,
+        )
+
+        self._api = None
+
+    def _get_api(self):
+        """Get Tushare API instance."""
+        if self._api is None:
+            import tushare as ts
+            self._api = ts.pro_api(self.token)
+        return self._api
+
+    def query(self, api_name: str, timeout: float = 30.0, **params) -> pd.DataFrame:
+        """Execute API query with rate limiting and retry.
+
+        Args:
+            api_name: API name (e.g., 'daily')
+            timeout: Timeout for rate limiting
+            **params: API parameters
+
+        Returns:
+            DataFrame with query results
+        """
+        # Acquire rate limit token
+        success, wait_time = self.rate_limiter.acquire(timeout=timeout)
+
+        if not success:
+            raise RuntimeError(f"Rate limit exceeded after {timeout}s timeout")
+
+        if wait_time > 0:
+            print(f"[RateLimit] Waited {wait_time:.2f}s for token")
+
+        # Execute with retry
+        max_retries = 3
+        retry_delays = [1, 3, 10]
+
+        for attempt in range(max_retries):
+            try:
+                api = self._get_api()
+                data = api.query(api_name, **params)
+
+                available = self.rate_limiter.get_available_tokens()
+                print(f"[Tushare] {api_name} | tokens: {available:.0f}/{self.rate_limiter.capacity}")
+
+                return data
+
+            except Exception as e:
+                if attempt < max_retries - 1:
+                    delay = retry_delays[attempt]
+                    print(f"[Retry] {api_name} failed (attempt {attempt + 1}): {e}, retry in {delay}s")
+                    time.sleep(delay)
+                else:
+                    raise RuntimeError(f"API call failed after {max_retries} attempts: {e}")
+
+        return pd.DataFrame()
+
+    def close(self):
+        """Close client."""
+        pass