Advanced Code Listings and Minted

\documentclass{article}
\usepackage{listings}
\usepackage{xcolor}

% Basic configuration
\lstset{
  basicstyle=\ttfamily\footnotesize,
  breaklines=true,
  frame=single,
  numbers=left,
  numberstyle=\tiny,
  stepnumber=1,
  showstringspaces=false
}

\begin{document}

\section{Code Examples}

\begin{lstlisting}[language=Python]
def fibonacci(n):
    """Calculate the nth Fibonacci number."""
    if n <= 1:
        return n
    return fibonacci(n-1) + fibonacci(n-2)

# Example usage
for i in range(10):
    print(f"F({i}) = {fibonacci(i)}")
\end{lstlisting}

% Inline code
The function \lstinline|fibonacci(n)| calculates Fibonacci numbers.

\end{document}

\documentclass{article}
\usepackage{listings}
\usepackage{xcolor}

% Python style
\lstdefinestyle{pythonstyle}{
  language=Python,
  basicstyle=\ttfamily\small,
  keywordstyle=\color{blue}\bfseries,
  stringstyle=\color{red},
  commentstyle=\color{gray}\itshape,
  numberstyle=\tiny\color{gray},
  breaklines=true,
  showstringspaces=false,
  frame=leftline,
  framerule=2pt,
  rulecolor=\color{blue!30},
  backgroundcolor=\color{blue!5}
}

% Java style
\lstdefinestyle{javastyle}{
  language=Java,
  basicstyle=\ttfamily\small,
  keywordstyle=\color{purple}\bfseries,
  stringstyle=\color{orange},
  commentstyle=\color{green!60!black}\itshape,
  numberstyle=\tiny\color{gray},
  breaklines=true,
  showstringspaces=false,
  frame=tb,
  framerule=1pt
}

% C++ style
\lstdefinestyle{cppstyle}{
  language=C++,
  basicstyle=\ttfamily\small,
  keywordstyle=\color{blue}\bfseries,
  stringstyle=\color{red!80!black},
  commentstyle=\color{green!60!black}\itshape,
  numberstyle=\tiny\color{gray},
  breaklines=true,
  showstringspaces=false,
  frame=single,
  frameround=tttt
}

\begin{document}

\section{Python Example}
\begin{lstlisting}[style=pythonstyle]
class DataProcessor:
    def __init__(self, data):
        self.data = data
        
    def process(self):
        """Process the data using advanced algorithms."""
        result = []
        for item in self.data:
            if self.validate(item):
                result.append(self.transform(item))
        return result
\end{lstlisting}

\section{Java Example}
\begin{lstlisting}[style=javastyle]
public class Calculator {
    private double result;
    
    public Calculator() {
        this.result = 0.0;
    }
    
    public double add(double value) {
        result += value;
        return result;
    }
    
    public void reset() {
        result = 0.0;
    }
}
\end{lstlisting}

\section{C++ Example}
\begin{lstlisting}[style=cppstyle]
#include <iostream>
#include <vector>
#include <algorithm>

template<typename T>
class Container {
private:
    std::vector<T> data;
    
public:
    void add(const T& item) {
        data.push_back(item);
    }
    
    void sort() {
        std::sort(data.begin(), data.end());
    }
};
\end{lstlisting}

\end{document}

\documentclass{article}
\usepackage{listings}
\usepackage{xcolor}

% Define custom language (LaTeX commands)
\lstdefinelanguage{LaTeX}{
  morekeywords={
    documentclass, usepackage, begin, end, section, subsection,
    title, author, maketitle, textbf, textit, emph, label, ref,
    cite, bibliography, includegraphics, caption
  },
  morecomment=[l]{\%},
  morestring=[b]",
  morestring=[b]',
  sensitive=true
}

% Style for LaTeX
\lstdefinestyle{latexstyle}{
  language=LaTeX,
  basicstyle=\ttfamily\small,
  keywordstyle=\color{blue}\bfseries,
  stringstyle=\color{red},
  commentstyle=\color{green!60!black}\itshape,
  breaklines=true,
  showstringspaces=false,
  frame=single,
  backgroundcolor=\color{yellow!10},
  escapeinside={(*@}{@*)}  % Allow LaTeX commands inside
}

% Define SQL language
\lstdefinelanguage{SQL}{
  morekeywords={
    SELECT, FROM, WHERE, INSERT, UPDATE, DELETE, CREATE, TABLE,
    INDEX, PRIMARY, KEY, FOREIGN, REFERENCES, JOIN, INNER, LEFT,
    RIGHT, OUTER, GROUP, BY, ORDER, HAVING, DISTINCT, COUNT, SUM,
    AVG, MAX, MIN, AND, OR, NOT, NULL, TRUE, FALSE
  },
  morecomment=[l]{--},
  morecomment=[s]{/*}{*/},
  morestring=[b]",
  morestring=[b]',
  sensitive=false
}

\begin{document}

\section{LaTeX Code Example}
\begin{lstlisting}[style=latexstyle]
\documentclass{article}
\usepackage{graphicx}
\usepackage{amsmath}

\title{My Document}
\author{John Doe}

\begin{document}
\maketitle

\section{Introduction}
This is an example of (*@\textbf{LaTeX}@*) code formatting.

\begin{equation}
E = mc^2
\end{equation}

\end{document}
\end{lstlisting}

\section{SQL Example}
\begin{lstlisting}[language=SQL, style=javastyle]
-- Create a table for user information
CREATE TABLE users (
    id INTEGER PRIMARY KEY,
    username VARCHAR(50) NOT NULL UNIQUE,
    email VARCHAR(100) NOT NULL,
    created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
);

-- Insert sample data
INSERT INTO users (username, email) VALUES
    ('john_doe', 'john_doe_mail'),
    ('jane_smith', 'jane_smith_mail');

-- Query with joins
SELECT u.username, p.title, p.created_at
FROM users u
INNER JOIN posts p ON u.id = p.user_id
WHERE p.published = TRUE
ORDER BY p.created_at DESC;
\end{lstlisting}

\end{document}

\documentclass{article}
\usepackage{minted}

% Global minted settings
\setminted{
  fontsize=\footnotesize,
  linenos,
  breaklines,
  frame=lines,
  framesep=2mm
}

\begin{document}

\section{Python with minted}

\begin{minted}{python}
import numpy as np
import matplotlib.pyplot as plt

def mandelbrot(c, max_iter):
    """Calculate the Mandelbrot set value for complex number c."""
    z = 0
    for n in range(max_iter):
        if abs(z) > 2:
            return n
        z = z*z + c
    return max_iter

# Generate Mandelbrot set
width, height = 800, 600
xmin, xmax = -2.0, 1.0
ymin, ymax = -1.5, 1.5

mandelbrot_set = np.zeros((height, width))
for i in range(height):
    for j in range(width):
        c = complex(xmin + (xmax - xmin) * j / width,
                   ymin + (ymax - ymin) * i / height)
        mandelbrot_set[i, j] = mandelbrot(c, 100)

plt.imshow(mandelbrot_set, extent=[xmin, xmax, ymin, ymax], 
           cmap='hot', origin='lower')
plt.colorbar()
plt.title('Mandelbrot Set')
plt.show()
\end{minted}

\end{document}

\documentclass{article}
\usepackage{minted}
\usepackage{mdframed}
\usepackage{xcolor}

% Define custom style
\definecolor{codegray}{rgb}{0.95,0.95,0.95}
\definecolor{codeframe}{rgb}{0.7,0.7,0.7}

% Custom environment for highlighted code
\newenvironment{mintedbox}[1]{%
  \begin{mdframed}[
    linecolor=codeframe,
    backgroundcolor=codegray,
    roundcorner=5pt,
    linewidth=1pt,
    innertopmargin=10pt,
    innerbottommargin=10pt,
    innerleftmargin=10pt,
    innerrightmargin=10pt
  ]
  \begin{minted}[
    fontsize=\small,
    linenos,
    breaklines,
    numbersep=5pt,
    gobble=2
  ]{#1}
}{%
  \end{minted}
  \end{mdframed}
}

\begin{document}

\section{Styled Code Blocks}

\begin{mintedbox}{javascript}
  // Advanced JavaScript example with ES6+ features
  class APIClient {
    constructor(baseURL) {
      this.baseURL = baseURL;
      this.headers = {
        'Content-Type': 'application/json',
        'Accept': 'application/json'
      };
    }
    
    async request(endpoint, options = {}) {
      const url = `${this.baseURL}${endpoint}`;
      const config = {
        ...options,
        headers: {
          ...this.headers,
          ...options.headers
        }
      };
      
      try {
        const response = await fetch(url, config);
        
        if (!response.ok) {
          throw new Error(`HTTP ${response.status}: ${response.statusText}`);
        }
        
        return await response.json();
      } catch (error) {
        console.error('API request failed:', error);
        throw error;
      }
    }
    
    // Convenience methods
    get(endpoint) {
      return this.request(endpoint, { method: 'GET' });
    }
    
    post(endpoint, data) {
      return this.request(endpoint, {
        method: 'POST',
        body: JSON.stringify(data)
      });
    }
  }
  
  // Usage example
  const client = new APIClient('https://api.example.com');
  
  client.get('/users')
    .then(users => console.log('Users:', users))
    .catch(error => console.error('Failed to fetch users:', error));
\end{mintedbox}

\section{Rust Example}

\begin{minted}[
  bgcolor=codegray,
  fontsize=\footnotesize,
  linenos,
  breaklines,
  frame=single,
  framerule=0.5pt,
  framesep=3mm
]{rust}
use std::collections::HashMap;
use std::fs::File;
use std::io::{BufRead, BufReader, Result};

#[derive(Debug, Clone)]
pub struct WordCounter {
    counts: HashMap<String, usize>,
    total_words: usize,
}

impl WordCounter {
    pub fn new() -> Self {
        Self {
            counts: HashMap::new(),
            total_words: 0,
        }
    }
    
    pub fn add_word(&mut self, word: &str) {
        let normalized = word.to_lowercase();
        *self.counts.entry(normalized).or_insert(0) += 1;
        self.total_words += 1;
    }
    
    pub fn count_from_file(&mut self, filename: &str) -> Result<()> {
        let file = File::open(filename)?;
        let reader = BufReader::new(file);
        
        for line in reader.lines() {
            let line = line?;
            for word in line.split_whitespace() {
                // Remove punctuation
                let clean_word: String = word
                    .chars()
                    .filter(|c| c.is_alphabetic())
                    .collect();
                
                if !clean_word.is_empty() {
                    self.add_word(&clean_word);
                }
            }
        }
        
        Ok(())
    }
    
    pub fn most_frequent(&self, n: usize) -> Vec<(&String, &usize)> {
        let mut pairs: Vec<_> = self.counts.iter().collect();
        pairs.sort_by(|a, b| b.1.cmp(a.1));
        pairs.into_iter().take(n).collect()
    }
}
\end{minted}

\end{document}

\documentclass{article}
\usepackage{minted}
\usepackage{xcolor}

% Define highlight colors
\definecolor{highlightgray}{rgb}{0.9,0.9,0.9}
\definecolor{highlightyellow}{rgb}{1.0,1.0,0.8}

\begin{document}

\section{Line Highlighting Examples}

\subsection{Highlighting Specific Lines}
\begin{minted}[
  linenos,
  highlightlines={3,7-9},
  highlightcolor=highlightyellow
]{python}
def binary_search(arr, target):
    left, right = 0, len(arr) - 1
    
    while left <= right:  # Main loop condition
        mid = (left + right) // 2
        
        if arr[mid] == target:    # Found target
            return mid            # Return index
        elif arr[mid] < target:   # Target in right half
            left = mid + 1
        else:                     # Target in left half
            right = mid - 1
    
    return -1  # Target not found
\end{minted}

\subsection{Multiple Highlight Ranges}
\begin{minted}[
  linenos,
  highlightlines={1-2,8-10},
  highlightcolor=highlightgray
]{cpp}
#include <iostream>
#include <vector>
#include <algorithm>

int main() {
    std::vector<int> numbers = {64, 34, 25, 12, 22, 11, 90};
    
    std::cout << "Original array: ";
    for (int num : numbers) {
        std::cout << num << " ";
    }
    std::cout << std::endl;
    
    std::sort(numbers.begin(), numbers.end());
    
    std::cout << "Sorted array: ";
    for (int num : numbers) {
        std::cout << num << " ";
    }
    std::cout << std::endl;
    
    return 0;
}
\end{minted}

\end{document}

\documentclass{article}
\usepackage{minted}
\usepackage{caption}
\usepackage{float}

% Define new float type for code
\newfloat{listing}{tbp}{lol}
\floatname{listing}{Listing}

% Caption setup for listings
\captionsetup[listing]{position=below}

\begin{document}

\section{Algorithm Examples}

Listing~\ref{lst:quicksort} shows an implementation of the quicksort algorithm.

\begin{listing}[H]
\begin{minted}[
  fontsize=\footnotesize,
  linenos,
  frame=single,
  framesep=2mm
]{python}
def quicksort(arr):
    """
    Sorts an array using the quicksort algorithm.
    
    Args:
        arr: List of comparable elements
        
    Returns:
        Sorted list
    """
    if len(arr) <= 1:
        return arr
    
    pivot = arr[len(arr) // 2]
    left = [x for x in arr if x < pivot]
    middle = [x for x in arr if x == pivot]
    right = [x for x in arr if x > pivot]
    
    return quicksort(left) + middle + quicksort(right)

# Example usage
if __name__ == "__main__":
    test_array = [3, 6, 8, 10, 1, 2, 1]
    print(f"Original: {test_array}")
    print(f"Sorted: {quicksort(test_array)}")
\end{minted}
\caption{Quicksort algorithm implementation in Python}
\label{lst:quicksort}
\end{listing}

The algorithm shown in Listing~\ref{lst:quicksort} has an average time complexity of O(n log n).

\begin{listing}[t]
\begin{minted}[
  fontsize=\small,
  linenos,
  frame=leftline,
  framerule=2pt,
  rulecolor=blue
]{java}
public class BinaryTree<T extends Comparable<T>> {
    private Node<T> root;
    
    private static class Node<T> {
        T data;
        Node<T> left, right;
        
        Node(T data) {
            this.data = data;
            this.left = this.right = null;
        }
    }
    
    public void insert(T data) {
        root = insertRec(root, data);
    }
    
    private Node<T> insertRec(Node<T> root, T data) {
        if (root == null) {
            root = new Node<>(data);
            return root;
        }
        
        if (data.compareTo(root.data) < 0) {
            root.left = insertRec(root.left, data);
        } else if (data.compareTo(root.data) > 0) {
            root.right = insertRec(root.right, data);
        }
        
        return root;
    }
    
    public boolean search(T data) {
        return searchRec(root, data);
    }
    
    private boolean searchRec(Node<T> root, T data) {
        if (root == null) {
            return false;
        }
        
        if (data.compareTo(root.data) == 0) {
            return true;
        }
        
        return data.compareTo(root.data) < 0 
            ? searchRec(root.left, data)
            : searchRec(root.right, data);
    }
}
\end{minted}
\caption{Generic binary search tree implementation in Java}
\label{lst:bst}
\end{listing}

\end{document}

\documentclass{article}
\usepackage{minted}
\usepackage{subcaption}
\usepackage{caption}

\begin{document}

\section{Algorithm Comparison}

Figure~\ref{fig:sorting-algorithms} compares different sorting algorithm implementations.

\begin{figure}[htbp]
\centering

\begin{subfigure}[t]{0.45\textwidth}
\begin{minted}[
  fontsize=\tiny,
  linenos,
  frame=single,
  framesep=1mm
]{python}
def bubble_sort(arr):
    """Bubble sort - O(n²)"""
    n = len(arr)
    for i in range(n):
        for j in range(0, n - i - 1):
            if arr[j] > arr[j + 1]:
                arr[j], arr[j + 1] = arr[j + 1], arr[j]
    return arr

# Example
numbers = [64, 34, 25, 12, 22, 11, 90]
print("Bubble sort:", bubble_sort(numbers.copy()))
\end{minted}
\caption{Bubble sort algorithm}
\label{fig:bubble-sort}
\end{subfigure}
\hfill
\begin{subfigure}[t]{0.45\textwidth}
\begin{minted}[
  fontsize=\tiny,
  linenos,
  frame=single,
  framesep=1mm
]{python}
def merge_sort(arr):
    """Merge sort - O(n log n)"""
    if len(arr) <= 1:
        return arr
    
    mid = len(arr) // 2
    left = merge_sort(arr[:mid])
    right = merge_sort(arr[mid:])
    
    return merge(left, right)

def merge(left, right):
    result = []
    i = j = 0
    
    while i < len(left) and j < len(right):
        if left[i] <= right[j]:
            result.append(left[i])
            i += 1
        else:
            result.append(right[j])
            j += 1
    
    result.extend(left[i:])
    result.extend(right[j:])
    return result

# Example
numbers = [64, 34, 25, 12, 22, 11, 90]
print("Merge sort:", merge_sort(numbers.copy()))
\end{minted}
\caption{Merge sort algorithm}
\label{fig:merge-sort}
\end{subfigure}

\caption{Comparison of sorting algorithms with different time complexities}
\label{fig:sorting-algorithms}
\end{figure}

\end{document}

\documentclass{article}
\usepackage{minted}
\usepackage{listings}

% Configure listings for inline code
\lstset{
  basicstyle=\ttfamily,
  breaklines=true
}

\begin{document}

\section{Inline Code Examples}

% Simple inline code
The \lstinline|print()| function outputs text to the console.

% Inline code with special characters
Use \lstinline|arr[i] = arr[j]| to swap array elements.

% Different delimiters for special characters
The regular expression \lstinline/[a-zA-Z0-9]+/ matches alphanumeric strings.

% Minted inline code
The \mintinline{python}|lambda x: x**2| function squares its input.

% Inline code with highlighting
The key function is \mintinline[bgcolor=yellow!30]{python}|process_data()|.

\section{Code with LaTeX Escapes}

\begin{lstlisting}[language=Python, escapeinside={(*@}{@*)}]
def calculate_(*@\textbf{mean}@*)(values):
    """Calculate the arithmetic (*@\emph{mean}@*) of a list."""
    if not values:
        return 0
    return sum(values) / len(values)  # (*@$\frac{\sum x_i}{n}$@*)

# Example: (*@\textcolor{red}{Important note}@*)
result = calculate_mean([1, 2, 3, 4, 5])
print(f"Mean: {result}")  # Output: (*@\texttt{Mean: 3.0}@*)
\end{lstlisting}

\end{document}

\documentclass{article}
\usepackage{minted}
\usepackage{xcolor}

% Define custom color scheme
\definecolor{darkblue}{rgb}{0.0,0.2,0.4}
\definecolor{darkgreen}{rgb}{0.0,0.4,0.2}
\definecolor{darkred}{rgb}{0.4,0.0,0.2}
\definecolor{darkorange}{rgb}{0.8,0.4,0.0}
\definecolor{codebg}{rgb}{0.98,0.98,0.98}

% Custom minted style
\newminted{python}{
  bgcolor=codebg,
  fontsize=\footnotesize,
  linenos,
  numbersep=8pt,
  frame=leftline,
  framerule=2pt,
  rulecolor=darkblue,
  breaklines,
  breaksymbolleft=\raisebox{0.8ex}{\small\reflectbox{\carriagereturn}},
  breaksymbolindentleft=0pt,
  breaksymbolsepleft=0pt,
  breaksymbolright=\small\carriagereturn,
  breaksymbolindentright=0pt,
  breaksymbolsepright=0pt
}

% Custom environment
\newenvironment{darkcode}
{%
  \begin{tcolorbox}[
    colback=black!95,
    coltext=white,
    colframe=gray!50,
    arc=2mm,
    boxrule=0.5pt
  ]
  \begin{minted}[
    bgcolor={},
    fontsize=\small,
    style=monokai
  ]{python}
}{%
  \end{minted}
  \end{tcolorbox}
}

\begin{document}

\section{Custom Styled Code}

\begin{pythoncode}
import asyncio
import aiohttp
from typing import List, Dict, Optional

class AsyncWebScraper:
    def __init__(self, max_concurrent: int = 10):
        self.max_concurrent = max_concurrent
        self.session: Optional[aiohttp.ClientSession] = None
        
    async def __aenter__(self):
        connector = aiohttp.TCPConnector(limit=self.max_concurrent)
        self.session = aiohttp.ClientSession(connector=connector)
        return self
        
    async def __aexit__(self, exc_type, exc_val, exc_tb):
        if self.session:
            await self.session.close()
            
    async def fetch_url(self, url: str) -> Dict[str, str]:
        """Fetch content from a single URL."""
        try:
            async with self.session.get(url) as response:
                content = await response.text()
                return {
                    'url': url,
                    'status': response.status,
                    'content': content[:1000],  # First 1000 chars
                    'headers': dict(response.headers)
                }
        except Exception as e:
            return {
                'url': url,
                'error': str(e),
                'status': None,
                'content': None
            }
    
    async def scrape_urls(self, urls: List[str]) -> List[Dict[str, str]]:
        """Scrape multiple URLs concurrently."""
        tasks = [self.fetch_url(url) for url in urls]
        results = await asyncio.gather(*tasks, return_exceptions=True)
        return [r for r in results if not isinstance(r, Exception)]

# Usage example
async def main():
    urls = [
        'https://httpbin.org/json',
        'https://httpbin.org/xml',
        'https://httpbin.org/html'
    ]
    
    async with AsyncWebScraper(max_concurrent=5) as scraper:
        results = await scraper.scrape_urls(urls)
        
    for result in results:
        print(f"URL: {result['url']}")
        print(f"Status: {result.get('status', 'Error')}")
        print("-" * 50)

if __name__ == "__main__":
    asyncio.run(main())
\end{pythoncode}

\end{document}

\documentclass{article}
\usepackage{minted}

\begin{document}

\section{Importing Code from Files}

% Import entire file
\inputminted{python}{example_script.py}

% Import specific lines from file
\inputminted[firstline=10,lastline=25]{python}{large_script.py}

% Import with custom styling
\inputminted[
  fontsize=\footnotesize,
  linenos,
  numbersep=5pt,
  frame=lines,
  framesep=2mm,
  bgcolor=gray!10
]{python}{algorithm.py}

\section{Code Snippets}

% You can also use external command to include processed code
\immediate\write18{pygmentize -l python -f latex example.py > example_highlighted.tex}
\input{example_highlighted.tex}

\end{document}

\documentclass{article}
\usepackage{minted}
\usepackage{tcolorbox}
\usepackage{caption}

% Global minted configuration
\setminted{
  fontsize=\footnotesize,
  linenos=true,
  numbersep=8pt,
  frame=leftline,
  framerule=1pt,
  breaklines=true,
  breaksymbolleft=\raisebox{0.8ex}{\small\reflectbox{\carriagereturn}},
  autogobble=true
}

% Professional code environment
\newtcolorbox{codebox}[2][]{
  colback=blue!5!white,
  colframe=blue!50!black,
  title=#2,
  fonttitle=\bfseries,
  #1
}

% Language-specific environments
\newenvironment{pythoncode}[1][]
{%
  \begin{codebox}[#1]{Python Code}
  \begin{minted}{python}
}{%
  \end{minted}
  \end{codebox}
}

\newenvironment{javacode}[1][]
{%
  \begin{codebox}[colback=orange!5!white,colframe=orange!50!black,#1]{Java Code}
  \begin{minted}{java}
}{%
  \end{minted}
  \end{codebox}
}

\begin{document}

\section{Professional Code Presentation}

\begin{pythoncode}[title=Data Analysis Pipeline]
import pandas as pd
import numpy as np
from sklearn.preprocessing import StandardScaler
from sklearn.model_selection import train_test_split
from sklearn.ensemble import RandomForestClassifier
from sklearn.metrics import classification_report, confusion_matrix

class DataAnalysisPipeline:
    """A complete data analysis pipeline for machine learning."""
    
    def __init__(self, random_state=42):
        self.random_state = random_state
        self.scaler = StandardScaler()
        self.model = RandomForestClassifier(
            n_estimators=100,
            random_state=self.random_state
        )
        self.is_fitted = False
        
    def preprocess_data(self, X, y=None, fit_transform=True):
        """Preprocess the input data."""
        if fit_transform:
            X_scaled = self.scaler.fit_transform(X)
        else:
            X_scaled = self.scaler.transform(X)
            
        return X_scaled
        
    def train(self, X, y, test_size=0.2):
        """Train the model with the provided data."""
        # Split the data
        X_train, X_test, y_train, y_test = train_test_split(
            X, y, test_size=test_size, random_state=self.random_state
        )
        
        # Preprocess
        X_train_scaled = self.preprocess_data(X_train, fit_transform=True)
        X_test_scaled = self.preprocess_data(X_test, fit_transform=False)
        
        # Train model
        self.model.fit(X_train_scaled, y_train)
        self.is_fitted = True
        
        # Evaluate
        train_score = self.model.score(X_train_scaled, y_train)
        test_score = self.model.score(X_test_scaled, y_test)
        
        return {
            'train_score': train_score,
            'test_score': test_score,
            'X_test': X_test_scaled,
            'y_test': y_test
        }
        
    def predict(self, X):
        """Make predictions on new data."""
        if not self.is_fitted:
            raise ValueError("Model must be trained before making predictions")
            
        X_scaled = self.preprocess_data(X, fit_transform=False)
        return self.model.predict(X_scaled)
        
    def feature_importance(self):
        """Get feature importance scores."""
        if not self.is_fitted:
            raise ValueError("Model must be trained first")
            
        return self.model.feature_importances_

# Example usage
if __name__ == "__main__":
    # Load your dataset here
    # X, y = load_your_data()
    
    pipeline = DataAnalysisPipeline()
    results = pipeline.train(X, y)
    
    print(f"Training accuracy: {results['train_score']:.3f}")
    print(f"Testing accuracy: {results['test_score']:.3f}")
\end{pythoncode}

\end{document}