feat: Add code file support to file uploads (#2702)

tests/data/api_server.go

@@ -0,0 +1,371 @@
+package main
+
+import (
+	"context"
+	"encoding/json"
+	"fmt"
+	"log"
+	"net/http"
+	"strconv"
+	"strings"
+	"sync"
+	"time"
+
+	"github.com/gorilla/mux"
+)
+
+// User represents a user in the system
+type User struct {
+	ID        int       `json:"id"`
+	Name      string    `json:"name"`
+	Email     string    `json:"email"`
+	CreatedAt time.Time `json:"created_at"`
+	UpdatedAt time.Time `json:"updated_at"`
+}
+
+// UserService handles user-related operations
+type UserService struct {
+	users  map[int]*User
+	nextID int
+	mutex  sync.RWMutex
+}
+
+// NewUserService creates a new instance of UserService
+func NewUserService() *UserService {
+	return &UserService{
+		users:  make(map[int]*User),
+		nextID: 1,
+	}
+}
+
+// CreateUser adds a new user to the service
+func (us *UserService) CreateUser(name, email string) (*User, error) {
+	us.mutex.Lock()
+	defer us.mutex.Unlock()
+
+	if name == "" || email == "" {
+		return nil, fmt.Errorf("name and email are required")
+	}
+
+	// Check for duplicate email
+	for _, user := range us.users {
+		if user.Email == email {
+			return nil, fmt.Errorf("user with email %s already exists", email)
+		}
+	}
+
+	user := &User{
+		ID:        us.nextID,
+		Name:      name,
+		Email:     email,
+		CreatedAt: time.Now(),
+		UpdatedAt: time.Now(),
+	}
+
+	us.users[us.nextID] = user
+	us.nextID++
+
+	return user, nil
+}
+
+// GetUser retrieves a user by ID
+func (us *UserService) GetUser(id int) (*User, error) {
+	us.mutex.RLock()
+	defer us.mutex.RUnlock()
+
+	user, exists := us.users[id]
+	if !exists {
+		return nil, fmt.Errorf("user with ID %d not found", id)
+	}
+
+	return user, nil
+}
+
+// GetAllUsers returns all users
+func (us *UserService) GetAllUsers() []*User {
+	us.mutex.RLock()
+	defer us.mutex.RUnlock()
+
+	users := make([]*User, 0, len(us.users))
+	for _, user := range us.users {
+		users = append(users, user)
+	}
+
+	return users
+}
+
+// UpdateUser modifies an existing user
+func (us *UserService) UpdateUser(id int, name, email string) (*User, error) {
+	us.mutex.Lock()
+	defer us.mutex.Unlock()
+
+	user, exists := us.users[id]
+	if !exists {
+		return nil, fmt.Errorf("user with ID %d not found", id)
+	}
+
+	// Check for duplicate email (excluding current user)
+	if email != user.Email {
+		for _, u := range us.users {
+			if u.Email == email && u.ID != id {
+				return nil, fmt.Errorf("user with email %s already exists", email)
+			}
+		}
+	}
+
+	if name != "" {
+		user.Name = name
+	}
+	if email != "" {
+		user.Email = email
+	}
+	user.UpdatedAt = time.Now()
+
+	return user, nil
+}
+
+// DeleteUser removes a user from the service
+func (us *UserService) DeleteUser(id int) error {
+	us.mutex.Lock()
+	defer us.mutex.Unlock()
+
+	if _, exists := us.users[id]; !exists {
+		return fmt.Errorf("user with ID %d not found", id)
+	}
+
+	delete(us.users, id)
+	return nil
+}
+
+// APIServer represents the HTTP server
+type APIServer struct {
+	userService *UserService
+	router      *mux.Router
+}
+
+// NewAPIServer creates a new API server instance
+func NewAPIServer(userService *UserService) *APIServer {
+	server := &APIServer{
+		userService: userService,
+		router:      mux.NewRouter(),
+	}
+	server.setupRoutes()
+	return server
+}
+
+// setupRoutes configures the API routes
+func (s *APIServer) setupRoutes() {
+	api := s.router.PathPrefix("/api/v1").Subrouter()
+	
+	// User routes
+	api.HandleFunc("/users", s.handleGetUsers).Methods("GET")
+	api.HandleFunc("/users", s.handleCreateUser).Methods("POST")
+	api.HandleFunc("/users/{id:[0-9]+}", s.handleGetUser).Methods("GET")
+	api.HandleFunc("/users/{id:[0-9]+}", s.handleUpdateUser).Methods("PUT")
+	api.HandleFunc("/users/{id:[0-9]+}", s.handleDeleteUser).Methods("DELETE")
+	
+	// Health check
+	api.HandleFunc("/health", s.handleHealthCheck).Methods("GET")
+	
+	// Add CORS middleware
+	s.router.Use(s.corsMiddleware)
+	s.router.Use(s.loggingMiddleware)
+}
+
+// HTTP Handlers
+
+func (s *APIServer) handleGetUsers(w http.ResponseWriter, r *http.Request) {
+	users := s.userService.GetAllUsers()
+	s.writeJSON(w, http.StatusOK, map[string]interface{}{
+		"users": users,
+		"count": len(users),
+	})
+}
+
+func (s *APIServer) handleCreateUser(w http.ResponseWriter, r *http.Request) {
+	var req struct {
+		Name  string `json:"name"`
+		Email string `json:"email"`
+	}
+
+	if err := json.NewDecoder(r.Body).Decode(&req); err != nil {
+		s.writeError(w, http.StatusBadRequest, "Invalid JSON payload")
+		return
+	}
+
+	user, err := s.userService.CreateUser(req.Name, req.Email)
+	if err != nil {
+		s.writeError(w, http.StatusBadRequest, err.Error())
+		return
+	}
+
+	s.writeJSON(w, http.StatusCreated, map[string]*User{"user": user})
+}
+
+func (s *APIServer) handleGetUser(w http.ResponseWriter, r *http.Request) {
+	vars := mux.Vars(r)
+	id, err := strconv.Atoi(vars["id"])
+	if err != nil {
+		s.writeError(w, http.StatusBadRequest, "Invalid user ID")
+		return
+	}
+
+	user, err := s.userService.GetUser(id)
+	if err != nil {
+		s.writeError(w, http.StatusNotFound, err.Error())
+		return
+	}
+
+	s.writeJSON(w, http.StatusOK, map[string]*User{"user": user})
+}
+
+func (s *APIServer) handleUpdateUser(w http.ResponseWriter, r *http.Request) {
+	vars := mux.Vars(r)
+	id, err := strconv.Atoi(vars["id"])
+	if err != nil {
+		s.writeError(w, http.StatusBadRequest, "Invalid user ID")
+		return
+	}
+
+	var req struct {
+		Name  string `json:"name"`
+		Email string `json:"email"`
+	}
+
+	if err := json.NewDecoder(r.Body).Decode(&req); err != nil {
+		s.writeError(w, http.StatusBadRequest, "Invalid JSON payload")
+		return
+	}
+
+	user, err := s.userService.UpdateUser(id, req.Name, req.Email)
+	if err != nil {
+		status := http.StatusBadRequest
+		if strings.Contains(err.Error(), "not found") {
+			status = http.StatusNotFound
+		}
+		s.writeError(w, status, err.Error())
+		return
+	}
+
+	s.writeJSON(w, http.StatusOK, map[string]*User{"user": user})
+}
+
+func (s *APIServer) handleDeleteUser(w http.ResponseWriter, r *http.Request) {
+	vars := mux.Vars(r)
+	id, err := strconv.Atoi(vars["id"])
+	if err != nil {
+		s.writeError(w, http.StatusBadRequest, "Invalid user ID")
+		return
+	}
+
+	if err := s.userService.DeleteUser(id); err != nil {
+		s.writeError(w, http.StatusNotFound, err.Error())
+		return
+	}
+
+	s.writeJSON(w, http.StatusOK, map[string]string{"message": "User deleted successfully"})
+}
+
+func (s *APIServer) handleHealthCheck(w http.ResponseWriter, r *http.Request) {
+	s.writeJSON(w, http.StatusOK, map[string]interface{}{
+		"status":    "healthy",
+		"timestamp": time.Now(),
+		"service":   "user-api",
+	})
+}
+
+// Middleware
+
+func (s *APIServer) corsMiddleware(next http.Handler) http.Handler {
+	return http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
+		w.Header().Set("Access-Control-Allow-Origin", "*")
+		w.Header().Set("Access-Control-Allow-Methods", "GET, POST, PUT, DELETE, OPTIONS")
+		w.Header().Set("Access-Control-Allow-Headers", "Content-Type, Authorization")
+
+		if r.Method == "OPTIONS" {
+			w.WriteHeader(http.StatusOK)
+			return
+		}
+
+		next.ServeHTTP(w, r)
+	})
+}
+
+func (s *APIServer) loggingMiddleware(next http.Handler) http.Handler {
+	return http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
+		start := time.Now()
+		
+		// Wrap ResponseWriter to capture status code
+		ww := &responseWriter{ResponseWriter: w, statusCode: http.StatusOK}
+		
+		next.ServeHTTP(ww, r)
+		
+		log.Printf("%s %s %d %v", r.Method, r.URL.Path, ww.statusCode, time.Since(start))
+	})
+}
+
+// Helper methods
+
+func (s *APIServer) writeJSON(w http.ResponseWriter, status int, data interface{}) {
+	w.Header().Set("Content-Type", "application/json")
+	w.WriteHeader(status)
+	json.NewEncoder(w).Encode(data)
+}
+
+func (s *APIServer) writeError(w http.ResponseWriter, status int, message string) {
+	s.writeJSON(w, status, map[string]string{"error": message})
+}
+
+// responseWriter wraps http.ResponseWriter to capture status code
+type responseWriter struct {
+	http.ResponseWriter
+	statusCode int
+}
+
+func (rw *responseWriter) WriteHeader(code int) {
+	rw.statusCode = code
+	rw.ResponseWriter.WriteHeader(code)
+}
+
+// Start starts the HTTP server
+func (s *APIServer) Start(ctx context.Context, addr string) error {
+	server := &http.Server{
+		Addr:         addr,
+		Handler:      s.router,
+		ReadTimeout:  15 * time.Second,
+		WriteTimeout: 15 * time.Second,
+		IdleTimeout:  60 * time.Second,
+	}
+
+	go func() {
+		<-ctx.Done()
+		log.Println("Shutting down server...")
+		
+		shutdownCtx, cancel := context.WithTimeout(context.Background(), 10*time.Second)
+		defer cancel()
+		
+		if err := server.Shutdown(shutdownCtx); err != nil {
+			log.Printf("Server shutdown error: %v", err)
+		}
+	}()
+
+	log.Printf("Server starting on %s", addr)
+	return server.ListenAndServe()
+}
+
+func main() {
+	userService := NewUserService()
+	
+	// Add some sample data
+	userService.CreateUser("John Doe", "john@example.com")
+	userService.CreateUser("Jane Smith", "jane@example.com")
+	
+	server := NewAPIServer(userService)
+	
+	ctx, cancel := context.WithCancel(context.Background())
+	defer cancel()
+	
+	if err := server.Start(ctx, ":8080"); err != nil && err != http.ErrServerClosed {
+		log.Fatalf("Server failed to start: %v", err)
+	}
+}

tests/data/data_analysis.py

@@ -0,0 +1,402 @@
+#!/usr/bin/env python3
+"""
+Data Analysis Module - Advanced statistical and machine learning operations
+Contains various data processing and analysis functions for research purposes.
+"""
+
+import warnings
+from dataclasses import dataclass
+from datetime import datetime
+from enum import Enum
+from typing import Dict, Optional
+
+import numpy as np
+import pandas as pd
+
+
+class AnalysisType(Enum):
+    """Enumeration of different analysis types."""
+
+    DESCRIPTIVE = "descriptive"
+    CORRELATION = "correlation"
+    REGRESSION = "regression"
+    CLUSTERING = "clustering"
+    TIME_SERIES = "time_series"
+
+
+@dataclass
+class AnalysisResult:
+    """Container for analysis results."""
+
+    analysis_type: AnalysisType
+    timestamp: datetime
+    metrics: Dict[str, float]
+    metadata: Dict[str, any]
+    success: bool = True
+    error_message: Optional[str] = None
+
+
+class DataPreprocessor:
+    """
+    Advanced data preprocessing utility class.
+    Handles cleaning, transformation, and feature engineering.
+    """
+
+    def __init__(self, missing_threshold: float = 0.5):
+        self.missing_threshold = missing_threshold
+        self.transformations_applied = []
+
+    def clean_data(self, df: pd.DataFrame) -> pd.DataFrame:
+        """
+        Comprehensive data cleaning pipeline.
+
+        Args:
+            df: Input DataFrame to clean
+
+        Returns:
+            Cleaned DataFrame
+        """
+        original_shape = df.shape
+
+        # Remove columns with excessive missing values
+        missing_ratios = df.isnull().sum() / len(df)
+        cols_to_drop = missing_ratios[missing_ratios > self.missing_threshold].index
+        df_cleaned = df.drop(columns=cols_to_drop)
+
+        if len(cols_to_drop) > 0:
+            self.transformations_applied.append(f"Dropped {len(cols_to_drop)} columns")
+
+        # Handle remaining missing values
+        numeric_cols = df_cleaned.select_dtypes(include=[np.number]).columns
+        categorical_cols = df_cleaned.select_dtypes(include=["object"]).columns
+
+        # Fill numeric missing values with median
+        for col in numeric_cols:
+            if df_cleaned[col].isnull().any():
+                median_value = df_cleaned[col].median()
+                df_cleaned[col].fillna(median_value, inplace=True)
+                self.transformations_applied.append(f"Filled {col} with median")
+
+        # Fill categorical missing values with mode
+        for col in categorical_cols:
+            if df_cleaned[col].isnull().any():
+                mode_value = df_cleaned[col].mode().iloc[0] if not df_cleaned[col].mode().empty else "Unknown"
+                df_cleaned[col].fillna(mode_value, inplace=True)
+                self.transformations_applied.append(f"Filled {col} with mode")
+
+        # Remove duplicates
+        initial_rows = len(df_cleaned)
+        df_cleaned = df_cleaned.drop_duplicates()
+        duplicates_removed = initial_rows - len(df_cleaned)
+
+        if duplicates_removed > 0:
+            self.transformations_applied.append(f"Removed {duplicates_removed} duplicate rows")
+
+        print(f"Data cleaning complete: {original_shape} -> {df_cleaned.shape}")
+        return df_cleaned
+
+    def engineer_features(self, df: pd.DataFrame) -> pd.DataFrame:
+        """
+        Create new features from existing data.
+
+        Args:
+            df: Input DataFrame
+
+        Returns:
+            DataFrame with engineered features
+        """
+        df_featured = df.copy()
+
+        # Numeric feature engineering
+        numeric_cols = df_featured.select_dtypes(include=[np.number]).columns
+
+        if len(numeric_cols) >= 2:
+            # Create interaction features
+            for i, col1 in enumerate(numeric_cols):
+                for col2 in numeric_cols[i + 1 :]:
+                    df_featured[f"{col1}_{col2}_ratio"] = df_featured[col1] / (df_featured[col2] + 1e-8)
+                    df_featured[f"{col1}_{col2}_sum"] = df_featured[col1] + df_featured[col2]
+
+            self.transformations_applied.append("Created interaction features")
+
+        # Binning continuous variables
+        for col in numeric_cols:
+            if df_featured[col].nunique() > 10:  # Only bin if many unique values
+                df_featured[f"{col}_binned"] = pd.qcut(df_featured[col], q=5, labels=False, duplicates="drop")
+                self.transformations_applied.append(f"Binned {col}")
+
+        return df_featured
+
+
+class StatisticalAnalyzer:
+    """
+    Statistical analysis and hypothesis testing utilities.
+    """
+
+    @staticmethod
+    def descriptive_statistics(df: pd.DataFrame) -> AnalysisResult:
+        """
+        Calculate comprehensive descriptive statistics.
+
+        Args:
+            df: Input DataFrame
+
+        Returns:
+            AnalysisResult with descriptive metrics
+        """
+        try:
+            numeric_df = df.select_dtypes(include=[np.number])
+
+            if numeric_df.empty:
+                return AnalysisResult(
+                    analysis_type=AnalysisType.DESCRIPTIVE,
+                    timestamp=datetime.now(),
+                    metrics={},
+                    metadata={},
+                    success=False,
+                    error_message="No numeric columns found",
+                )
+
+            metrics = {
+                "mean_values": numeric_df.mean().to_dict(),
+                "std_values": numeric_df.std().to_dict(),
+                "median_values": numeric_df.median().to_dict(),
+                "skewness": numeric_df.skew().to_dict(),
+                "kurtosis": numeric_df.kurtosis().to_dict(),
+                "correlation_with_target": None,  # Would need target column
+            }
+
+            metadata = {
+                "total_rows": len(df),
+                "total_columns": len(df.columns),
+                "numeric_columns": len(numeric_df.columns),
+                "missing_values": df.isnull().sum().to_dict(),
+            }
+
+            return AnalysisResult(analysis_type=AnalysisType.DESCRIPTIVE, timestamp=datetime.now(), metrics=metrics, metadata=metadata)
+
+        except Exception as e:
+            return AnalysisResult(
+                analysis_type=AnalysisType.DESCRIPTIVE,
+                timestamp=datetime.now(),
+                metrics={},
+                metadata={},
+                success=False,
+                error_message=str(e),
+            )
+
+    @staticmethod
+    def correlation_analysis(df: pd.DataFrame, method: str = "pearson") -> AnalysisResult:
+        """
+        Perform correlation analysis between variables.
+
+        Args:
+            df: Input DataFrame
+            method: Correlation method ('pearson', 'spearman', 'kendall')
+
+        Returns:
+            AnalysisResult with correlation metrics
+        """
+        try:
+            numeric_df = df.select_dtypes(include=[np.number])
+
+            if len(numeric_df.columns) < 2:
+                return AnalysisResult(
+                    analysis_type=AnalysisType.CORRELATION,
+                    timestamp=datetime.now(),
+                    metrics={},
+                    metadata={},
+                    success=False,
+                    error_message="Need at least 2 numeric columns for correlation",
+                )
+
+            corr_matrix = numeric_df.corr(method=method)
+
+            # Find highest correlations (excluding diagonal)
+            corr_pairs = []
+            for i in range(len(corr_matrix.columns)):
+                for j in range(i + 1, len(corr_matrix.columns)):
+                    col1, col2 = corr_matrix.columns[i], corr_matrix.columns[j]
+                    corr_value = corr_matrix.iloc[i, j]
+                    if not np.isnan(corr_value):
+                        corr_pairs.append((col1, col2, abs(corr_value)))
+
+            # Sort by correlation strength
+            corr_pairs.sort(key=lambda x: x[2], reverse=True)
+
+            metrics = {
+                "correlation_matrix": corr_matrix.to_dict(),
+                "highest_correlations": corr_pairs[:10],  # Top 10
+                "method_used": method,
+            }
+
+            metadata = {"variables_analyzed": list(numeric_df.columns), "total_pairs": len(corr_pairs)}
+
+            return AnalysisResult(analysis_type=AnalysisType.CORRELATION, timestamp=datetime.now(), metrics=metrics, metadata=metadata)
+
+        except Exception as e:
+            return AnalysisResult(
+                analysis_type=AnalysisType.CORRELATION,
+                timestamp=datetime.now(),
+                metrics={},
+                metadata={},
+                success=False,
+                error_message=str(e),
+            )
+
+
+class TimeSeriesAnalyzer:
+    """
+    Time series analysis and forecasting utilities.
+    """
+
+    def __init__(self, frequency: str = "D"):
+        self.frequency = frequency
+        self.models_fitted = {}
+
+    def detect_seasonality(self, series: pd.Series) -> Dict[str, any]:
+        """
+        Detect seasonal patterns in time series data.
+
+        Args:
+            series: Time series data
+
+        Returns:
+            Dictionary with seasonality information
+        """
+        try:
+            # Simple seasonality detection using autocorrelation
+            autocorr_values = []
+            for lag in range(1, min(len(series) // 2, 365)):
+                if len(series) > lag:
+                    autocorr = series.autocorr(lag=lag)
+                    if not np.isnan(autocorr):
+                        autocorr_values.append((lag, autocorr))
+
+            # Find peaks in autocorrelation
+            significant_lags = [(lag, corr) for lag, corr in autocorr_values if abs(corr) > 0.5]
+            significant_lags.sort(key=lambda x: abs(x[1]), reverse=True)
+
+            return {
+                "seasonal_lags": significant_lags[:5],
+                "strongest_seasonality": significant_lags[0] if significant_lags else None,
+                "autocorrelation_values": autocorr_values,
+            }
+
+        except Exception as e:
+            warnings.warn(f"Seasonality detection failed: {e}")
+            return {"error": str(e)}
+
+    def trend_analysis(self, series: pd.Series, window: int = 30) -> Dict[str, any]:
+        """
+        Analyze trend patterns in time series.
+
+        Args:
+            series: Time series data
+            window: Rolling window size for trend calculation
+
+        Returns:
+            Dictionary with trend information
+        """
+        try:
+            # Calculate rolling statistics
+            rolling_mean = series.rolling(window=window).mean()
+            rolling_std = series.rolling(window=window).std()
+
+            # Simple trend detection
+            first_third = rolling_mean.iloc[: len(rolling_mean) // 3].mean()
+            last_third = rolling_mean.iloc[-len(rolling_mean) // 3 :].mean()
+
+            trend_direction = "increasing" if last_third > first_third else "decreasing"
+            trend_strength = abs(last_third - first_third) / first_third if first_third != 0 else 0
+
+            return {
+                "trend_direction": trend_direction,
+                "trend_strength": trend_strength,
+                "rolling_mean": rolling_mean.to_dict(),
+                "rolling_std": rolling_std.to_dict(),
+                "volatility": rolling_std.mean(),
+            }
+
+        except Exception as e:
+            warnings.warn(f"Trend analysis failed: {e}")
+            return {"error": str(e)}
+
+
+def generate_sample_data(n_samples: int = 1000) -> pd.DataFrame:
+    """
+    Generate sample dataset for testing analysis functions.
+
+    Args:
+        n_samples: Number of samples to generate
+
+    Returns:
+        Sample DataFrame
+    """
+    np.random.seed(42)
+
+    data = {
+        "feature_1": np.random.normal(100, 15, n_samples),
+        "feature_2": np.random.exponential(2, n_samples),
+        "feature_3": np.random.uniform(0, 100, n_samples),
+        "category": np.random.choice(["A", "B", "C"], n_samples),
+        "timestamp": pd.date_range("2023-01-01", periods=n_samples, freq="D"),
+    }
+
+    # Add some correlation
+    data["feature_4"] = data["feature_1"] * 0.7 + np.random.normal(0, 10, n_samples)
+
+    # Add missing values
+    missing_indices = np.random.choice(n_samples, size=int(0.05 * n_samples), replace=False)
+    for idx in missing_indices:
+        col = np.random.choice(["feature_1", "feature_2", "feature_3"])
+        data[col][idx] = np.nan
+
+    return pd.DataFrame(data)
+
+
+def main():
+    """
+    Demonstration of the data analysis pipeline.
+    """
+    print("=== Data Analysis Pipeline Demo ===")
+
+    # Generate sample data
+    df = generate_sample_data(1000)
+    print(f"Generated dataset with shape: {df.shape}")
+
+    # Data preprocessing
+    preprocessor = DataPreprocessor(missing_threshold=0.1)
+    df_clean = preprocessor.clean_data(df)
+    df_featured = preprocessor.engineer_features(df_clean)
+
+    print(f"Applied transformations: {preprocessor.transformations_applied}")
+
+    # Statistical analysis
+    analyzer = StatisticalAnalyzer()
+
+    # Descriptive statistics
+    desc_result = analyzer.descriptive_statistics(df_featured)
+    if desc_result.success:
+        print(f"Descriptive analysis completed at {desc_result.timestamp}")
+        print(f"Analyzed {desc_result.metadata['numeric_columns']} numeric columns")
+
+    # Correlation analysis
+    corr_result = analyzer.correlation_analysis(df_featured)
+    if corr_result.success:
+        print(f"Correlation analysis completed")
+        print(f"Found {len(corr_result.metrics['highest_correlations'])} significant correlations")
+
+    # Time series analysis
+    ts_analyzer = TimeSeriesAnalyzer()
+    time_series = df_clean.set_index("timestamp")["feature_1"]
+
+    ts_analyzer.detect_seasonality(time_series)
+    trend = ts_analyzer.trend_analysis(time_series)
+
+    print(f"Time series trend: {trend.get('trend_direction', 'unknown')}")
+    print(f"Volatility: {trend.get('volatility', 0):.2f}")
+
+
+if __name__ == "__main__":
+    main()

tests/data/data_structures.cpp

@@ -0,0 +1,286 @@
+#include <iostream>
+#include <vector>
+#include <memory>
+#include <algorithm>
+#include <stdexcept>
+
+/**
+ * Binary Search Tree implementation with smart pointers
+ * Template class supporting any comparable type
+ */
+template<typename T>
+class BinarySearchTree {
+private:
+    struct Node {
+        T data;
+        std::unique_ptr<Node> left;
+        std::unique_ptr<Node> right;
+        
+        Node(const T& value) : data(value), left(nullptr), right(nullptr) {}
+    };
+    
+    std::unique_ptr<Node> root;
+    size_t size_;
+
+    void insertHelper(std::unique_ptr<Node>& node, const T& value) {
+        if (!node) {
+            node = std::make_unique<Node>(value);
+            ++size_;
+            return;
+        }
+        
+        if (value < node->data) {
+            insertHelper(node->left, value);
+        } else if (value > node->data) {
+            insertHelper(node->right, value);
+        }
+        // Ignore duplicates
+    }
+    
+    bool searchHelper(const std::unique_ptr<Node>& node, const T& value) const {
+        if (!node) return false;
+        
+        if (value == node->data) return true;
+        else if (value < node->data) return searchHelper(node->left, value);
+        else return searchHelper(node->right, value);
+    }
+    
+    void inorderHelper(const std::unique_ptr<Node>& node, std::vector<T>& result) const {
+        if (!node) return;
+        
+        inorderHelper(node->left, result);
+        result.push_back(node->data);
+        inorderHelper(node->right, result);
+    }
+    
+    std::unique_ptr<Node> removeHelper(std::unique_ptr<Node> node, const T& value) {
+        if (!node) return nullptr;
+        
+        if (value < node->data) {
+            node->left = removeHelper(std::move(node->left), value);
+        } else if (value > node->data) {
+            node->right = removeHelper(std::move(node->right), value);
+        } else {
+            // Node to delete found
+            --size_;
+            
+            if (!node->left) return std::move(node->right);
+            if (!node->right) return std::move(node->left);
+            
+            // Node has two children
+            Node* successor = findMin(node->right.get());
+            node->data = successor->data;
+            node->right = removeHelper(std::move(node->right), successor->data);
+            ++size_; // Compensate for decrement in recursive call
+        }
+        
+        return node;
+    }
+    
+    Node* findMin(Node* node) const {
+        while (node->left) {
+            node = node->left.get();
+        }
+        return node;
+    }
+
+public:
+    BinarySearchTree() : root(nullptr), size_(0) {}
+    
+    void insert(const T& value) {
+        insertHelper(root, value);
+    }
+    
+    bool search(const T& value) const {
+        return searchHelper(root, value);
+    }
+    
+    void remove(const T& value) {
+        root = removeHelper(std::move(root), value);
+    }
+    
+    std::vector<T> inorderTraversal() const {
+        std::vector<T> result;
+        inorderHelper(root, result);
+        return result;
+    }
+    
+    size_t size() const { return size_; }
+    bool empty() const { return size_ == 0; }
+    
+    void clear() {
+        root.reset();
+        size_ = 0;
+    }
+};
+
+/**
+ * Dynamic Array implementation with automatic resizing
+ */
+template<typename T>
+class DynamicArray {
+private:
+    std::unique_ptr<T[]> data;
+    size_t capacity_;
+    size_t size_;
+    
+    void resize() {
+        size_t newCapacity = capacity_ == 0 ? 1 : capacity_ * 2;
+        auto newData = std::make_unique<T[]>(newCapacity);
+        
+        for (size_t i = 0; i < size_; ++i) {
+            newData[i] = std::move(data[i]);
+        }
+        
+        data = std::move(newData);
+        capacity_ = newCapacity;
+    }
+
+public:
+    DynamicArray() : data(nullptr), capacity_(0), size_(0) {}
+    
+    explicit DynamicArray(size_t initialCapacity) 
+        : data(std::make_unique<T[]>(initialCapacity)), 
+          capacity_(initialCapacity), 
+          size_(0) {}
+    
+    void pushBack(const T& value) {
+        if (size_ >= capacity_) {
+            resize();
+        }
+        data[size_++] = value;
+    }
+    
+    void pushBack(T&& value) {
+        if (size_ >= capacity_) {
+            resize();
+        }
+        data[size_++] = std::move(value);
+    }
+    
+    T& operator[](size_t index) {
+        if (index >= size_) {
+            throw std::out_of_range("Index out of bounds");
+        }
+        return data[index];
+    }
+    
+    const T& operator[](size_t index) const {
+        if (index >= size_) {
+            throw std::out_of_range("Index out of bounds");
+        }
+        return data[index];
+    }
+    
+    void popBack() {
+        if (size_ > 0) {
+            --size_;
+        }
+    }
+    
+    size_t size() const { return size_; }
+    size_t capacity() const { return capacity_; }
+    bool empty() const { return size_ == 0; }
+    
+    void clear() { size_ = 0; }
+    
+    // Iterator support
+    T* begin() { return data.get(); }
+    T* end() { return data.get() + size_; }
+    const T* begin() const { return data.get(); }
+    const T* end() const { return data.get() + size_; }
+};
+
+/**
+ * Stack implementation using dynamic array
+ */
+template<typename T>
+class Stack {
+private:
+    DynamicArray<T> container;
+
+public:
+    void push(const T& value) {
+        container.pushBack(value);
+    }
+    
+    void push(T&& value) {
+        container.pushBack(std::move(value));
+    }
+    
+    void pop() {
+        if (empty()) {
+            throw std::runtime_error("Stack underflow");
+        }
+        container.popBack();
+    }
+    
+    T& top() {
+        if (empty()) {
+            throw std::runtime_error("Stack is empty");
+        }
+        return container[container.size() - 1];
+    }
+    
+    const T& top() const {
+        if (empty()) {
+            throw std::runtime_error("Stack is empty");
+        }
+        return container[container.size() - 1];
+    }
+    
+    bool empty() const { return container.empty(); }
+    size_t size() const { return container.size(); }
+};
+
+// Demonstration and testing
+int main() {
+    std::cout << "=== Binary Search Tree Demo ===" << std::endl;
+    
+    BinarySearchTree<int> bst;
+    std::vector<int> values = {50, 30, 70, 20, 40, 60, 80, 10, 25, 35};
+    
+    for (int val : values) {
+        bst.insert(val);
+    }
+    
+    std::cout << "Tree size: " << bst.size() << std::endl;
+    std::cout << "Inorder traversal: ";
+    auto inorder = bst.inorderTraversal();
+    for (size_t i = 0; i < inorder.size(); ++i) {
+        std::cout << inorder[i];
+        if (i < inorder.size() - 1) std::cout << ", ";
+    }
+    std::cout << std::endl;
+    
+    std::cout << "\n=== Dynamic Array Demo ===" << std::endl;
+    
+    DynamicArray<std::string> arr;
+    arr.pushBack("Hello");
+    arr.pushBack("World");
+    arr.pushBack("C++");
+    arr.pushBack("Templates");
+    
+    std::cout << "Array contents: ";
+    for (size_t i = 0; i < arr.size(); ++i) {
+        std::cout << arr[i];
+        if (i < arr.size() - 1) std::cout << ", ";
+    }
+    std::cout << std::endl;
+    
+    std::cout << "\n=== Stack Demo ===" << std::endl;
+    
+    Stack<int> stack;
+    for (int i = 1; i <= 5; ++i) {
+        stack.push(i * 10);
+    }
+    
+    std::cout << "Stack contents (top to bottom): ";
+    while (!stack.empty()) {
+        std::cout << stack.top() << " ";
+        stack.pop();
+    }
+    std::cout << std::endl;
+    
+    return 0;
+}

tests/data/react_component.jsx

@@ -0,0 +1,123 @@
+import React, { useState, useEffect } from 'react';
+import PropTypes from 'prop-types';
+
+/**
+ * UserProfile component for displaying user information
+ * @param {Object} props - Component props
+ * @param {Object} props.user - User object
+ * @param {Function} props.onEdit - Edit callback function
+ */
+const UserProfile = ({ user, onEdit }) => {
+  const [isEditing, setIsEditing] = useState(false);
+  const [userData, setUserData] = useState(user);
+  const [loading, setLoading] = useState(false);
+
+  useEffect(() => {
+    setUserData(user);
+  }, [user]);
+
+  const handleSave = async () => {
+    setLoading(true);
+    try {
+      await onEdit(userData);
+      setIsEditing(false);
+    } catch (error) {
+      console.error('Failed to save user data:', error);
+    } finally {
+      setLoading(false);
+    }
+  };
+
+  const handleCancel = () => {
+    setUserData(user);
+    setIsEditing(false);
+  };
+
+  const handleInputChange = (field, value) => {
+    setUserData(prev => ({
+      ...prev,
+      [field]: value
+    }));
+  };
+
+  if (loading) {
+    return <div className="loading-spinner">Saving...</div>;
+  }
+
+  return (
+    <div className="user-profile">
+      <div className="profile-header">
+        <h2>{userData.name}</h2>
+        {!isEditing && (
+          <button onClick={() => setIsEditing(true)} className="edit-btn">
+            Edit Profile
+          </button>
+        )}
+      </div>
+
+      <div className="profile-content">
+        {isEditing ? (
+          <form onSubmit={(e) => { e.preventDefault(); handleSave(); }}>
+            <div className="form-group">
+              <label htmlFor="name">Name:</label>
+              <input
+                id="name"
+                type="text"
+                value={userData.name}
+                onChange={(e) => handleInputChange('name', e.target.value)}
+                required
+              />
+            </div>
+
+            <div className="form-group">
+              <label htmlFor="email">Email:</label>
+              <input
+                id="email"
+                type="email"
+                value={userData.email}
+                onChange={(e) => handleInputChange('email', e.target.value)}
+                required
+              />
+            </div>
+
+            <div className="form-group">
+              <label htmlFor="bio">Bio:</label>
+              <textarea
+                id="bio"
+                value={userData.bio || ''}
+                onChange={(e) => handleInputChange('bio', e.target.value)}
+                rows={4}
+              />
+            </div>
+
+            <div className="form-actions">
+              <button type="submit" className="save-btn">Save</button>
+              <button type="button" onClick={handleCancel} className="cancel-btn">
+                Cancel
+              </button>
+            </div>
+          </form>
+        ) : (
+          <div className="profile-display">
+            <p><strong>Email:</strong> {userData.email}</p>
+            <p><strong>Bio:</strong> {userData.bio || 'No bio provided'}</p>
+            <p><strong>Member since:</strong> {new Date(userData.joinDate).toLocaleDateString()}</p>
+          </div>
+        )}
+      </div>
+    </div>
+  );
+};
+
+UserProfile.propTypes = {
+  user: PropTypes.shape({
+    id: PropTypes.number.isRequired,
+    name: PropTypes.string.isRequired,
+    email: PropTypes.string.isRequired,
+    bio: PropTypes.string,
+    joinDate: PropTypes.string.isRequired,
+  }).isRequired,
+  onEdit: PropTypes.func.isRequired,
+};
+
+export default UserProfile;

tests/data/task_manager.java

@@ -0,0 +1,177 @@
+package com.example.taskmanager;
+
+import java.util.*;
+import java.time.LocalDateTime;
+
+/**
+ * TaskManager class for managing tasks and their lifecycle
+ * 
+ * @author Development Team
+ * @version 1.0
+ */
+public class TaskManager {
+    private Map<String, Task> tasks;
+    private List<TaskObserver> observers;
+    private static final int MAX_TASKS = 1000;
+
+    public TaskManager() {
+        this.tasks = new HashMap<>();
+        this.observers = new ArrayList<>();
+    }
+
+    /**
+     * Adds a new task to the manager
+     * 
+     * @param id Unique task identifier
+     * @param title Task title
+     * @param description Task description
+     * @param priority Task priority level
+     * @return true if task was added successfully
+     * @throws IllegalArgumentException if task ID already exists
+     * @throws IllegalStateException if maximum tasks exceeded
+     */
+    public boolean addTask(String id, String title, String description, Priority priority) {
+        if (tasks.containsKey(id)) {
+            throw new IllegalArgumentException("Task with ID " + id + " already exists");
+        }
+        
+        if (tasks.size() >= MAX_TASKS) {
+            throw new IllegalStateException("Maximum number of tasks reached");
+        }
+
+        Task newTask = new Task(id, title, description, priority);
+        tasks.put(id, newTask);
+        notifyObservers(TaskEvent.TASK_ADDED, newTask);
+        return true;
+    }
+
+    /**
+     * Updates an existing task status
+     */
+    public void updateTaskStatus(String id, TaskStatus newStatus) {
+        Task task = tasks.get(id);
+        if (task == null) {
+            throw new NoSuchElementException("Task not found: " + id);
+        }
+
+        TaskStatus oldStatus = task.getStatus();
+        task.setStatus(newStatus);
+        task.setLastModified(LocalDateTime.now());
+        
+        notifyObservers(TaskEvent.TASK_UPDATED, task);
+        
+        if (newStatus == TaskStatus.COMPLETED) {
+            handleTaskCompletion(task);
+        }
+    }
+
+    /**
+     * Retrieves tasks by status
+     */
+    public List<Task> getTasksByStatus(TaskStatus status) {
+        return tasks.values()
+                   .stream()
+                   .filter(task -> task.getStatus() == status)
+                   .sorted(Comparator.comparing(Task::getPriority))
+                   .toList();
+    }
+
+    /**
+     * Handles task completion logic
+     */
+    private void handleTaskCompletion(Task task) {
+        task.setCompletedAt(LocalDateTime.now());
+        System.out.println("Task completed: " + task.getTitle());
+        
+        // Check for dependent tasks
+        tasks.values().stream()
+             .filter(t -> t.getDependencies().contains(task.getId()))
+             .forEach(this::checkDependenciesResolved);
+    }
+
+    private void checkDependenciesResolved(Task task) {
+        boolean allResolved = task.getDependencies()
+                                 .stream()
+                                 .allMatch(depId -> {
+                                     Task dep = tasks.get(depId);
+                                     return dep != null && dep.getStatus() == TaskStatus.COMPLETED;
+                                 });
+        
+        if (allResolved && task.getStatus() == TaskStatus.BLOCKED) {
+            updateTaskStatus(task.getId(), TaskStatus.TODO);
+        }
+    }
+
+    public void addObserver(TaskObserver observer) {
+        observers.add(observer);
+    }
+
+    private void notifyObservers(TaskEvent event, Task task) {
+        observers.forEach(observer -> observer.onTaskEvent(event, task));
+    }
+
+    // Inner classes and enums
+    public enum Priority {
+        LOW(1), MEDIUM(2), HIGH(3), CRITICAL(4);
+        
+        private final int value;
+        Priority(int value) { this.value = value; }
+        public int getValue() { return value; }
+    }
+
+    public enum TaskStatus {
+        TODO, IN_PROGRESS, BLOCKED, COMPLETED, CANCELLED
+    }
+
+    public enum TaskEvent {
+        TASK_ADDED, TASK_UPDATED, TASK_DELETED
+    }
+
+    public static class Task {
+        private String id;
+        private String title;
+        private String description;
+        private Priority priority;
+        private TaskStatus status;
+        private LocalDateTime createdAt;
+        private LocalDateTime lastModified;
+        private LocalDateTime completedAt;
+        private Set<String> dependencies;
+
+        public Task(String id, String title, String description, Priority priority) {
+            this.id = id;
+            this.title = title;
+            this.description = description;
+            this.priority = priority;
+            this.status = TaskStatus.TODO;
+            this.createdAt = LocalDateTime.now();
+            this.lastModified = LocalDateTime.now();
+            this.dependencies = new HashSet<>();
+        }
+
+        // Getters and setters
+        public String getId() { return id; }
+        public String getTitle() { return title; }
+        public String getDescription() { return description; }
+        public Priority getPriority() { return priority; }
+        public TaskStatus getStatus() { return status; }
+        public LocalDateTime getCreatedAt() { return createdAt; }
+        public LocalDateTime getLastModified() { return lastModified; }
+        public LocalDateTime getCompletedAt() { return completedAt; }
+        public Set<String> getDependencies() { return dependencies; }
+
+        public void setStatus(TaskStatus status) { this.status = status; }
+        public void setLastModified(LocalDateTime lastModified) { this.lastModified = lastModified; }
+        public void setCompletedAt(LocalDateTime completedAt) { this.completedAt = completedAt; }
+
+        @Override
+        public String toString() {
+            return String.format("Task{id='%s', title='%s', status=%s, priority=%s}", 
+                               id, title, status, priority);
+        }
+    }
+
+    public interface TaskObserver {
+        void onTaskEvent(TaskEvent event, Task task);
+    }
+}