How to size TradingView labels with a Pine Script input?

How to size TradingView labels with a Pine Script input?

TL;DR
Offer a dropdown with the supported label sizes, translate the selection into a label.size_* constant, and reuse that value whenever you create or update labels.

At a Glance

Difficulty	Beginner
Time to implement	10-15 min
Category	Visual Effects

Quick Actions

• Open in AI Editor
• Browse PineScript Examples
• Connect to Live Trading

Quick Start

//@version=5
indicator("Resizable labels", overlay=true, max_labels_count=500)

labelSizeInput = input.string("default", "Label size", options=["very small", "small", "default", "large", "very large"])

labelSizeFromInput(string value) =>
    switch value
        "very small" => label.size_tiny
        "small"      => label.size_small
        "large"      => label.size_large
        "very large" => label.size_huge
        => label.size_normal

sizeSetting = labelSizeFromInput(labelSizeInput)

if barstate.islast
    label.new(bar_index, high, text="Size: " + labelSizeInput, style=label.style_label_down, textcolor=color.white, bgcolor=color.new(color.blue, 65), size=sizeSetting)

Tip. Keep the dropdown values human-friendly, but always map them back to the built-in `label.size_*` constants before you pass them to `label.new()` or `label.set_size()`.

Why It Matters

Charts rarely ship with one-size-fits-all annotations. Allowing traders to resize labels helps them fit more (or less) text, align with branding, or keep overlays readable on different monitors. Inputs provide the control; a small helper function keeps the sizing logic consistent everywhere labels are used.

What You’ll Learn

• Capture label-size preferences with input.string().
• Translate human-readable dropdown values into Pine’s label.size_* enum.
• Apply the selected size when creating new labels or updating existing ones.
• Reuse the helper across multiple label types (signals, stats, tooltips).

Quick Reference

Call	Purpose
input.string(defval, title, options=[])	Renders a dropdown for label size choices.
label.size_*	Enum constants Pine expects when sizing labels.
label.new(x, y, text, size=...)	Creates an annotation with the chosen size.
label.set_size(id, size)	Updates an existing label when preferences change.
switch	Cleanly maps input strings to size constants.

Implementation Blueprint

1. Collect the size preference
   Use a dropdown with descriptive options so users recognise each size.

   sizeChoice = input.string("default", "Label size", options=["very small", "small", "default", "large", "very large"], tooltip="Controls label.size_* constant")

2. Map strings to label.size_* constants
   Convert the selection once and reuse the result throughout the script.

   labelSize(string value) =>
       switch value
           "very small" => label.size_tiny
           "small"      => label.size_small
           "large"      => label.size_large
           "very large" => label.size_huge
           => label.size_normal

3. Apply the size to labels
   Pass the mapped constant to label.new() or label.set_size() whenever you render annotations.

   sizeSetting = labelSize(sizeChoice)
   tradeLabel = label.new(bar_index, high, text="Signal", size=sizeSetting)

Example Playbook

//@version=5
indicator("Signal labels with sizing", overlay=true, max_labels_count=500)

sizeChoice = input.string("default", "Label size", options=["very small", "small", "default", "large", "very large"], tooltip="Pick how big signal labels should render")
textColour = input.color(color.white, "Text colour")
bgColour   = input.color(color.new(color.blue, 70), "Background colour")

labelSize(string value) =>
    switch value
        "very small" => label.size_tiny
        "small"      => label.size_small
        "large"      => label.size_large
        "very large" => label.size_huge
        => label.size_normal

sizeSetting = labelSize(sizeChoice)

fast = ta.ema(close, 12)
slow = ta.ema(close, 26)

bullish = ta.crossover(fast, slow)
bearish = ta.crossunder(fast, slow)

if bullish
    label.new(bar_index, low, "Bull", style=label.style_label_up, size=sizeSetting, textcolor=textColour, bgcolor=bgColour)

if bearish
    id = label.new(bar_index, high, "Bear", style=label.style_label_down, textcolor=textColour, bgcolor=bgColour)
    label.set_size(id, sizeSetting)

Why this works.

• A single helper translates user-friendly text into Pine’s enum values.
• Both new labels and post-creation adjustments respect the same preference.
• Separating colour inputs from size keeps the settings panel tidy but flexible.

Pro Tips & Pitfalls

• label.size_auto is available if you’d rather Pine adapt the size to text, but users often prefer explicit control.
• When you allow emojis or icons in labels, bump the default size to keep them legible.
• Reapply label.set_size() after clearing/recreating labels so they stay in sync with updated input values.
• If you manage dozens of labels, cache the size constant in a global variable to avoid recomputing inside loops.

Troubleshooting & FAQ

The dropdown shows values I didn’t provide

Each option must be unique. Double-check the options array and make sure the default exists inside it.

Changing the input doesn’t resize existing labels

Labels retain their original size until you call label.set_size() with the new constant. Re-run updates on the next bar or when detecting an input change (if barstate.isnew and sizeChoice != sizeChoice[1]).

Can I expose different sizes for different label types?

Absolutely—duplicate the input (e.g., “Signal label size”, “Stats label size”) and keep separate helper calls for each context.

Key Takeaways

• Collect label-size preferences via input.string() so users can resize annotations quickly.
• Translate those strings to label.size_* constants with a small helper before applying them.
• Use the mapped size for both new labels and any adjustments you make later via label.set_size().
• Consistent sizing inputs improve readability while keeping scripts flexible for different chart setups.

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Keep Going

• Open AI Editor to apply the pattern with guided assistance
• Browse Strategy Examples for ready-to-run templates
• Connect to Live Trading when you are ready to automate

Adapted from tradingcode.net, optimised for Algo Trade Analytics users.