📊 Dynamic View Alignment - A Guide to Data Display in Telegram

A professional solution for monospaced font data alignment and formatting

📑 Table of Contents

Core Principles
Implementation Code
Formatting System
Application Examples
Best Practices

Core Principles

Problem Scenario

When displaying leaderboards or data tables in a Telegram Bot, perfect alignment is required in a monospaced font environment (code block):

❌ Unaligned:

1. BTC $1.23B $45000 +5.23%
10. DOGE $123.4M $0.0789 -1.45%

✅ Dynamically Aligned:

1.   BTC      $1.23B    $45,000   +5.23%
10.  DOGE   $123.4M   $0.0789   -1.45%

Three-Step Alignment Algorithm

Step 1: Scan the data to calculate the maximum width of each column
Step 2: Apply alignment rules based on the column type (text left-aligned, numbers right-aligned)
Step 3: Concatenate into the final text

Alignment Rules

Column Index	Data Type	Alignment	Example
Column 0	Sequence No.	Left-aligned	`1.`, `10.`
Column 1	Symbol	Left-aligned	`BTC`, `DOGE`
Column 2+	Numeric Value	Right-aligned	`$1.23B`, `$123.4M`

Implementation Code

Core Function

def dynamic_align_format(data_rows):
    """
    Dynamically aligns and formats the view.

    Args:
        data_rows: A 2D list [["1.", "BTC", "$1.23B", ...], ...]

    Returns:
        An aligned text string.
    """
    if not data_rows:
        return "No data available"

    # ========== Step 1: Calculate the maximum width of each column ==========
    max_widths = []
    for row in data_rows:
        for i, cell in enumerate(row):
            # Dynamically expand the list
            if i >= len(max_widths):
                max_widths.append(0)
            # Update the maximum width
            max_widths[i] = max(max_widths[i], len(str(cell)))

    # ========== Step 2: Format each row ==========
    formatted_rows = []
    for row in data_rows:
        formatted_cells = []
        for i, cell in enumerate(row):
            cell_str = str(cell)

            if i == 0 or i == 1:
                # Sequence number and symbol columns - left-aligned
                formatted_cells.append(cell_str.ljust(max_widths[i]))
            else:
                # Numeric columns - right-aligned
                formatted_cells.append(cell_str.rjust(max_widths[i]))

        # Join all cells with a space
        formatted_line = ' '.join(formatted_cells)
        formatted_rows.append(formatted_line)

    # ========== Step 3: Concatenate into the final text ==========
    return '\n'.join(formatted_rows)

Usage Example

# Prepare the data
data_rows = [
    ["1.", "BTC", "$1.23B", "$45,000", "+5.23%"],
    ["2.", "ETH", "$890.5M", "$2,500", "+3.12%"],
    ["10.", "DOGE", "$123.4M", "$0.0789", "-1.45%"]
]

# Call the alignment function
aligned_text = dynamic_align_format(data_rows)

# Output to Telegram
text = f"""
📊 Leaderboard

{aligned_text}

💡 Explanatory text"""

Formatting System

1. Smart Abbreviation for Trading Volume

def format_volume(volume: float) -> str:
    """Intelligently formats trading volume."""
    if volume >= 1e9:
        return f"${volume/1e9:.2f}B"    # Billions → $1.23B
    elif volume >= 1e6:
        return f"${volume/1e6:.2f}M"    # Millions → $890.5M
    elif volume >= 1e3:
        return f"${volume/1e3:.2f}K"    # Thousands → $123.4K
    else:
        return f"${volume:.2f}"          # Decimals → $45.67

Example:

format_volume(1234567890)  # → "$1.23B"
format_volume(890500000)   # → "$890.5M"
format_volume(123400)      # → "$123.4K"

2. Smart Precision for Price

def format_price(price: float) -> str:
    """Intelligently formats price - automatically adjusts decimal places based on value."""
    if price >= 1000:
        return f"${price:,.0f}"      # Above 1000 → $45,000
    elif price >= 1:
        return f"${price:.3f}"       # 1-1000 → $2.500
    elif price >= 0.01:
        return f"${price:.4f}"       # 0.01-1 → $0.0789
    else:
        return f"${price:.6f}"       # <0.01 → $0.000123

3. Formatting for Price Change Percentage

def format_change(change_percent: float) -> str:
    """Formats price change percentage - adds a '+' sign for positive numbers."""
    if change_percent >= 0:
        return f"+{change_percent:.2f}%"
    else:
        return f"{change_percent:.2f}%"

Example:

format_change(5.234)   # → "+5.23%"
format_change(-1.456)  # → "-1.46%"
format_change(0)       # → "+0.00%"

4. Smart Display for Fund Flow

def format_flow(net_flow: float) -> str:
    """Formats net fund flow."""
    sign = "+" if net_flow >= 0 else ""
    abs_flow = abs(net_flow)

    if abs_flow >= 1e9:
        return f"{sign}{net_flow/1e9:.2f}B"
    elif abs_flow >= 1e6:
        return f"{sign}{net_flow/1e6:.2f}M"
    elif abs_flow >= 1e3:
        return f"{sign}{net_flow/1e3:.2f}K"
    else:
        return f"{sign}{net_flow:.0f}"

Application Examples

Complete Leaderboard Implementation

def get_volume_ranking(data, limit=10):
    """Gets the trading volume leaderboard."""

    # 1. Data processing and sorting
    sorted_data = sorted(data, key=lambda x: x['volume'], reverse=True)[:limit]

    # 2. Prepare data rows
    data_rows = []
    for i, item in enumerate(sorted_data, 1):
        symbol = item['symbol']
        volume = item['volume']
        price = item['price']
        change = item['change_percent']

        # Format each column
        volume_str = format_volume(volume)
        price_str = format_price(price)
        change_str = format_change(change)

        # Add to data rows
        data_rows.append([
            f"{i}.",      # Sequence No.
            symbol,       # Coin
            volume_str,   # Volume
            price_str,    # Price
            change_str    # Change %
        ])

    # 3. Dynamic alignment and formatting
    aligned_data = dynamic_align_format(data_rows)

    # 4. Build the final message
    text = f"""
🎪 Hot Coins - Volume Ranking 🎪
⏰ Updated {datetime.now().strftime('%Y-%m-%d %H:%M')}
📊 Sorted by 24h Volume (USDT) / Descending
Rank/Coin/24h Vol/Price/24h Change

{aligned_data}

💡 Volume reflects market activity and liquidity."""

    return text

Output Effect

🎪 Hot Coins - Volume Ranking 🎪
⏰ Updated 2025-10-29 14:30
📊 Sorted by 24h Volume (USDT) / Descending
Rank/Coin/24h Vol/Price/24h Change

1.   BTC      $1.23B    $45,000   +5.23%
2.   ETH    $890.5M     $2,500   +3.12%
3.   SOL    $567.8M       $101   +8.45%
4.   BNB    $432.1M       $315   +2.67%
5.   XRP    $345.6M     $0.589   -1.23%

💡 Volume reflects market activity and liquidity.

Best Practices

1. Data Preparation Standards

# ✅ Recommended: Use a nested list structure
data_rows = [
    ["1.", "BTC", "$1.23B", "$45,000", "+5.23%"],
    ["2.", "ETH", "$890.5M", "$2,500", "+3.12%"]
]

# ❌ Not recommended: Use a dictionary (requires extra conversion)
data_rows = [
    {"rank": 1, "symbol": "BTC", ...},
]

2. Formatting Order

# ✅ Recommended: Format first, then align
for i, item in enumerate(data, 1):
    volume_str = format_volume(item['volume'])      # Format
    price_str = format_price(item['price'])         # Format
    change_str = format_change(item['change'])      # Format

    data_rows.append([f"{i}.", symbol, volume_str, price_str, change_str])

aligned_data = dynamic_align_format(data_rows)  # Align

3. Embedding in Telegram Messages

# ✅ Recommended: Wrap aligned data in a code block
text = f"""
📊 Leaderboard Title
⏰ Update Time {time}