What is Dear ImGui Bundle?

Dear ImGui Bundle is a “batteries included” framework built on Dear ImGui. It bundles 20+ libraries for plotting, markdown, node editors, 3D gizmos, and more - all working seamlessly in C++ and Python, on all major platforms (Windows, Linux, macOS, iOS, Android, WebAssembly).

If you are building scientific tools, game tools, visualization applications, developer tools, or creative apps, give it a try. You’ll soon see that GUI code can be clear, readable, and easy to maintain. The immediate mode paradigm makes it a joy to reason about your app logic.

Key highlights:

• Immediate mode: Your code reads like a book. No widget trees, no callbacks, no synchronization headaches.

• Cross-platform: Same code runs on desktop, mobile, and web (via Emscripten or Pyodide).

• Python-first: Full Python bindings with type hints and IDE autocompletion.

• Always up-to-date: Tracks Dear ImGui upstream closely; Python bindings are auto-generated.

Code That Reads Like a Book¶

The immediate mode paradigm means your UI code is simple and direct: the app below can be coded with just 9 readable lines of Python:

from imgui_bundle import imgui, hello_imgui

selected_idx = 0
items = ["Apple", "Banana", "Cherry"]

def gui():
    global selected_idx
    imgui.text("Choose a fruit:")
    _, selected_idx = imgui.list_box("##fruits", selected_idx, items)
    imgui.text(f"You selected: {items[selected_idx]}")

hello_imgui.run(gui, window_title="Fruit Picker")

The relation between code and behavior is direct: what you write is what runs. There are no hidden widget trees, no callback chains, and no implicit state synchronization. This makes it easier to reason about your app’s logic and flow.

Easy to understand for humans

Being able to work with readable code is getting more and more important as LLMs are now widely used to generate code: You, the human, still need to understand, review, and maintain that code. Immediate mode makes this easier.

Easy to understand for AI

And the same clarity that helps humans also helps AI: with no implicit state to get wrong, LLMs can read and generate ImGui code reliably. The full PDF manuals give an AI assistant all the context it needs.

How Does It Compare?¶

Not sure if Dear ImGui Bundle is right for you? Compare the code styles with other popular GUI libraries:

from imgui_bundle import imgui, hello_imgui

selected_idx = 0
items = ["Apple", "Banana", "Cherry"]

def gui():
    global selected_idx
    imgui.text("Choose a fruit:")
    _changed, selected_idx = imgui.list_box("##fruits", selected_idx, items)
    imgui.text(f"You selected: {items[selected_idx]}")

hello_imgui.run(gui, window_title="Fruit Picker")

from PyQt6.QtWidgets import QApplication, QWidget, QVBoxLayout, QLabel, QListWidget

items = ["Apple", "Banana", "Cherry"]

class FruitPicker(QWidget):
    def __init__(self):
        super().__init__()
        layout = QVBoxLayout()
        self.label = QLabel("Choose a fruit:")
        self.list_widget = QListWidget()
        self.list_widget.addItems(items)
        self.result_label = QLabel(f"You selected: {items[0]}")
        self.list_widget.currentRowChanged.connect(self.on_selection_changed)
        layout.addWidget(self.label)
        layout.addWidget(self.list_widget)
        layout.addWidget(self.result_label)
        self.setLayout(layout)

    def on_selection_changed(self, index):
        self.result_label.setText(f"You selected: {items[index]}")

app = QApplication([])
window = FruitPicker()
window.show()
app.exec()

import dearpygui.dearpygui as dpg

items = ["Apple", "Banana", "Cherry"]
dpg.create_context()

def on_selection_changed(sender, app_data):
    dpg.set_value("result_label", f"You selected: {app_data}")

with dpg.window(tag="Primary Window", label="Fruit Picker"):
    dpg.add_text("Choose a fruit:")
    dpg.add_listbox(items=items, callback=on_selection_changed, num_items=len(items))
    dpg.add_text("You selected: ", tag="result_label")

dpg.create_viewport(title='Fruit Picker', width=400, height=300)
dpg.setup_dearpygui()
dpg.show_viewport()
dpg.set_primary_window("Primary Window", True)
dpg.start_dearpygui()
dpg.destroy_context()

from nicegui import ui

selected_idx = -1
items = ["Apple", "Banana", "Cherry"]

def on_selection_change(e):
    global selected_idx
    selected_idx = items.index(e.value)
    selection_label.text = f"You selected: {e.value}"

ui.label("Choose a fruit:")
dropdown = ui.select(options=items, value=items[0], on_change=on_selection_change)
selection_label = ui.label(f"You selected: {items[0]}")

ui.run(title="Fruit Picker")

import gradio as gr

items = ["Apple", "Banana", "Cherry"]
selected_item = items[0]

def on_selection_change(choice):
    global selected_item
    selected_item = choice
    return f"You selected: {choice}"

with gr.Blocks() as demo:
    gr.Markdown("# Fruit Picker")
    gr.Markdown("Choose a fruit:")
    dropdown = gr.Dropdown(choices=items, value=items[0], label="Choose a fruit")
    output = gr.Textbox(value=f"You selected: {items[0]}", label="Selection", interactive=False)
    dropdown.change(fn=on_selection_change, inputs=dropdown, outputs=output)

demo.launch()

Who is it for?¶

• beginners and developers: go from idea to GUI prototype in minutes, without learning a complex framework. Deploy to almost any platform.

• ML/AI researchers: visualize training in real time, tune hyperparameters mid-run, inside Jupyter

• Computer vision engineers: inspect images and tensors at the pixel level with ImmVision

• Robotics developers: fast, readable debug UIs in Python or C++

• Scientific instrument builders: cross-platform GUIs that deploy to desktop and web from the same code

• Technical tool makers: build node editors, gizmos, code editors without a web stack

Who is this project not for

You should prefer a more complete framework (such as Qt for example) if your intent is to build a fully fledged application, with support for accessibility, internationalization, advanced styling, etc.

Learn More¶

• Key Features — Library list, FAQ, and more details.

• Immediate Mode Explained — Understand the paradigm that makes ImGui different.

• Interactive Manuals & Demos — Try the demos in your browser.

• Jupyter Notebooks — Interactive GUIs inside Jupyter. Your training loop keeps running while you tune hyperparameters.