Scrapbox Syntax Comprehensive Test File

[* Heading Level 1]
[** Heading Level 2]
[*** Heading Level 3]
[**** Heading Level 4]
[***** Heading Level 5]

Text Formatting
[/ italic text]
[- strikethrough text]
Inline [* bold text] within a sentence
[*/ bold italic text]
[*- bold strikethrough text]
[/- italic strikethrough text]

Math Notation
[$ E = mc^2]
[$ \sum_{i=1}^{n} x_i]

Links and Media
[Link Title https://example.com]
[https://example.com Reverse Link Title]
[img https://example.com/image.jpg]
[https://example.com/picture.png]
[YouTube https://www.youtube.com/watch?v=dQw4w9WgXcQ]
[Twitter https://twitter.com/user/status/123456789]

URL Auto-linking
Normal URL: https://example.com
Non-HTTPS URL: http://legacy.example.com

Blockquotes
> This is a blockquote
>Multiple lines of
>blockquote text

List Structure
 List item 1
  Nested list item 1-1
   Further nested item 1-1-1
    4th level nested item
  Nested list item 1-2
 List item 2
	Tab indented item
　Full-width space indented item
 List item 3

Code Blocks (Programming Languages)
code:python
 def hello_world():
     print("Hello, World!")
     return 42

code:javascript
 const greeting = "Hello, World!";
 console.log(greeting);

code:typescript
 interface User {
     name: string;
     age: number;
 }

code:bash
 #!/bin/bash
 echo "Hello, World!"
 ls -la

code:json
 {
     "name": "example",
     "version": "1.0.0",
     "dependencies": {}
 }

LaTeX Math Blocks
Mathematical expression test
code:tex
 V(X) = E((X-μ)^2)
 σ = √V(X)
 E(X) = μ

Complex formulas
code:tex
 \sum_{i=1}^{n} x_i = x_1 + x_2 + ... + x_n
 \int_{-\infty}^{\infty} e^{-x^2} dx = \sqrt{\pi}

Code Blocks in Lists
 Programming examples
  Python
   code:python
    import numpy as np
    def variance(x):
        return np.var(x)
  JavaScript
   code:js
    const mean = arr => arr.reduce((a, b) => a + b) / arr.length;

LaTeX in Lists
 Statistics
  Variance definition
   code:tex
    V(X) = E((X-μ)^2)
  Standard deviation
   code:tex
    σ = √V(X)

Table Notation
table:User Information
 Name	Age	Occupation
 John	25	Engineer
 Jane	30	Designer
 Bob	28	Manager

table:Statistical Data
 Item	Value	Note
 Mean	75.2	Score
 Variance	12.8	Spread
 StdDev	3.58	Standard deviation

Mixed Content
[** Data Analysis Procedure]
 Data Collection
  CSV file loading
   code:python
    import pandas as pd
    df = pd.read_csv('data.csv')
 Statistical Calculation
  Variance calculation formula
   code:tex
    V(X) = \frac{1}{n}\sum_{i=1}^{n}(x_i - \bar{x})^2
  Implementation example
   code:python
    variance = df['column'].var()
 Result Visualization
  Chart creation
   code:python
    import matplotlib.pyplot as plt
    plt.hist(df['column'])
    plt.show()

Special Characters and Escaping
{ curly braces }
[ square brackets ]
Normal text with [mixed] brackets

Image Embedding
[img https://example.com/chart.png]
![Existing Markdown image](https://example.com/existing.jpg)

Multi-line Code Blocks (with empty lines)
code:python
 def complex_function():
     # Comment
     x = 1

     # Code with empty lines
     y = 2

     return x + y

LaTeX with Non-Math Text (content preserved verbatim)
code:tex
 E(X) = μ
 This is the definition of expected value
 V(X) = σ^2

End of test file
