### Start Headless Chrome for Examples Tests

Source: https://docs.bokeh.org/en/latest/docs/dev_guide/testing.html

Before running example tests locally, start a customized headless Chrome browser from the bokehjs directory. This is a prerequisite for the examples testing framework.

```bash
cd bokehjs
node make test:run:headless

```

--------------------------------

### Run Bokeh Server Example (Linux/macOS)

Source: https://docs.bokeh.org/en/latest/docs/dev_guide/setup.html

Start the Bokeh server with an example application on Linux or macOS. Set BOKEH_DEV=false to run in production mode.

```bash
BOKEH_DEV=false python -m bokeh serve --show examples/server/app/sliders.py
```

--------------------------------

### Run Bokeh Server Example (Windows CMD)

Source: https://docs.bokeh.org/en/latest/docs/dev_guide/setup.html

Start the Bokeh server with an example application on Windows using the Command Prompt. Set BOKEH_DEV=false to run in production mode.

```cmd
set BOKEH_DEV=false
python -m bokeh serve --show examples\server\app\sliders.py
```

--------------------------------

### Run Bokeh Server Example (Windows PowerShell)

Source: https://docs.bokeh.org/en/latest/docs/dev_guide/setup.html

Start the Bokeh server with an example application on Windows using PowerShell. Set BOKEH_DEV=false to run in production mode.

```powershell
$Env:BOKEH_DEV = "False"
python.exe -m bokeh serve --show .\examples\server\app\sliders.py
```

--------------------------------

### Run Bokeh Examples Tests with Pytest

Source: https://docs.bokeh.org/en/latest/docs/dev_guide/testing.html

After starting the headless Chrome tool, execute the examples tests from the top-level source directory using pytest. This command initiates the test suite and generates a report.

```bash
pytest tests/test_examples.py

```

--------------------------------

### Start Bokeh Server

Source: https://docs.bokeh.org/en/latest/docs/first_steps/first_steps_9.html

Use this command to start Bokeh in server mode from the command line.

```bash
bokeh serve
```

--------------------------------

### Start BokehJS Devtools Server

Source: https://docs.bokeh.org/en/latest/docs/dev_guide/debug_headless_chrome.html

Use this command to start a BokehJS devtools server for debugging.

```bash
node test/devtools server
```

--------------------------------

### Serve Documentation Locally (Linux/macOS)

Source: https://docs.bokeh.org/en/latest/docs/dev_guide/documentation.html

Starts a web server to display the built documentation and opens it in a web browser. This is necessary for documentation that relies on JavaScript.

```bash
make serve
```

--------------------------------

### Serve Documentation Locally (Windows CMD)

Source: https://docs.bokeh.org/en/latest/docs/dev_guide/documentation.html

Starts a web server to display the built documentation and opens it in a web browser using the make.bat script in the Command Prompt.

```batch
make.bat serve
```

--------------------------------

### Test Bokeh installation and environment

Source: https://docs.bokeh.org/en/latest/docs/dev_guide/setup.html

Run this command to verify that Bokeh is installed correctly and that your environment is properly configured. It displays detailed information about your Bokeh setup.

```python
python -m bokeh info
```

--------------------------------

### Serve Documentation Locally (Windows PowerShell)

Source: https://docs.bokeh.org/en/latest/docs/dev_guide/documentation.html

Starts a web server to display the built documentation and opens it in a web browser using the make.bat script in PowerShell.

```powershell
.\make.bat serve
```

--------------------------------

### Set up Data, Figure, and Renderer

Source: https://docs.bokeh.org/en/latest/docs/first_steps/first_steps_9.html

Prepare sample data and create a Bokeh figure with scatter plot points.

```python
x = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
y = [4, 5, 5, 7, 2, 6, 4, 9, 1, 3]

p = figure(x_range=(1,9), width=500, height=250)
points = p.scatter(x=x, y=y, size=30, fill_color="#21a7df")
```

--------------------------------

### Setting Model Properties Individually

Source: https://docs.bokeh.org/en/latest/docs/reference/models/plots.html

Example of initializing a `Range1d` model and setting its `start` and `end` properties individually.

```python
from bokeh.models import Range1d

r = Range1d

# set properties individually:
r.start = 10
r.end = 20

```

--------------------------------

### Run Standalone Example (Windows CMD)

Source: https://docs.bokeh.org/en/latest/docs/dev_guide/setup.html

Execute a standalone Bokeh example on Windows using the Command Prompt. Ensure the BOKEH_RESOURCES environment variable is set to 'inline' or 'absolute-dev'.

```cmd
set BOKEH_RESOURCES=inline
python examples\basic\data\transform_markers.py
```

--------------------------------

### Complete Scale Bar Example with Custom Units

Source: https://docs.bokeh.org/en/latest/docs/user_guide/basic/annotations.html

A full example demonstrating a plot with a vertical scale bar configured for custom metric units (MeV based on eV). Includes data generation, plot setup, and layout.

```python
import numpy as np

from bokeh.layouts import column
from bokeh.models import ColumnDataSource, Metric, RangeTool, ScaleBar
from bokeh.plotting import figure, show

n_points = 3000
x_values = np.linspace(0, 100, n_points)
y_values = np.random.randn(n_points).cumsum()

source = ColumnDataSource(data=dict(x=x_values, y=y_values))

detailed_plot = figure(
    width=800,
    height=300,
    tools=["xpan", "xzoom_in", "xzoom_out", "reset", "wheel_zoom"],
    toolbar_location="above",
    active_scroll="wheel_zoom",
    background_fill_color="#efefef",
    x_range=(22, 30),
    y_axis_location=None,
)

detailed_plot.line("x", "y", source=source)

scale_bar = ScaleBar(
    range=detailed_plot.y_range,
    unit="MeV",
    dimensional=Metric(base_unit="eV"),
    orientation="vertical",
    location="top_left",
    background_fill_color=None,
    border_line_color=None,
)
detail_plot.add_layout(scale_bar)

select_plot = figure(
    width=detailed_plot.width,
    height=150,
    y_range=detailed_plot.y_range,
    y_axis_location=None,
    tools="",
    toolbar_location=None,
    background_fill_color=detailed_plot.background_fill_color,
)

select_plot.line("x", "y", source=source)
select_plot.x_range.range_padding = 0
select_plot.ygrid.grid_line_color = None

range_tool = RangeTool(x_range=detailed_plot.x_range)
range_tool.overlay.fill_color = "navy"
range_tool.overlay.fill_alpha = 0.2
select_plot.add_tools(range_tool)

show(column(detailed_plot, select_plot))
```

--------------------------------

### Wedge Glyph Example

Source: https://docs.bokeh.org/en/latest/docs/reference/models/glyphs/wedge.html

Renders wedges with specified x, y, radius, start and end angles, and fill color. Requires numpy and bokeh.io imports.

```python
import numpy as np

from bokeh.io import curdoc, show
from bokeh.models import ColumnDataSource, Grid, LinearAxis, Plot, Wedge

N = 9
x = np.linspace(-2, 2, N)
y = x**2
r = x/15.0+0.3

source = ColumnDataSource(dict(x=x, y=y, r=r))

plot = Plot(
    title=None, width=300, height=300,
    min_border=0, toolbar_location=None)

glyph = Wedge(x="x", y="y", radius="r", start_angle=0.6, end_angle=4.1, fill_color="#b3de69")
plot.add_glyph(source, glyph)

xaxis = LinearAxis()
plot.add_layout(xaxis, 'below')

yaxis = LinearAxis()
plot.add_layout(yaxis, 'left')

plot.add_layout(Grid(dimension=0, ticker=xaxis.ticker))
plot.add_layout(Grid(dimension=1, ticker=yaxis.ticker))

curdoc().add_root(plot)

show(plot)

```

--------------------------------

### Initialize a new Bokeh extension interactively

Source: https://docs.bokeh.org/en/latest/docs/user_guide/advanced/extensions.html

Run this command to create and customize a new pre-built Bokeh extension step by step through an interactive process.

```bash
bokeh init --interactive
```

--------------------------------

### Define Range Class with Float Properties

Source: https://docs.bokeh.org/en/latest/docs/reference/core/property/descriptors.html

This example shows how to define a simple Range class inheriting from Model and using Float descriptors for 'start' and 'end' properties.

```python
from bokeh.model import Model
from bokeh.core.properties import Float

class Range(Model):
    start = Float(help="start point")
    end   = Float(help="end point")

```

--------------------------------

### WSHandler.open

Source: https://docs.bokeh.org/en/latest/docs/reference/server/views.html

Initialize a connection to a client.

```APIDOC
## WSHandler.open

### Description
Initialize a connection to a client.

### Parameters
None

### Response
None
```

--------------------------------

### Create and Show an Arc Glyph

Source: https://docs.bokeh.org/en/latest/docs/reference/models/glyphs/arc.html

This example demonstrates how to create an Arc glyph with specified radius, start and end angles, and line properties, then add it to a Bokeh plot and display it.

```python
import numpy as np

from bokeh.io import curdoc, show
from bokeh.models import Arc, ColumnDataSource, Grid, LinearAxis, Plot

N = 9
x = np.linspace(-2, 2, N)
y = x**2
r = x/15.0+0.3

source = ColumnDataSource(dict(x=x, y=y, r=r))

plot = Plot(
    title=None, width=300, height=300,
    min_border=0, toolbar_location=None)

glyph = Arc(x="x", y="y", radius="r", start_angle=0.6, end_angle=4.1, line_color="#beaed4", line_width=3)
plot.add_glyph(source, glyph)

xaxis = LinearAxis()
plot.add_layout(xaxis, 'below')

yaxis = LinearAxis()
plot.add_layout(yaxis, 'left')

plot.add_layout(Grid(dimension=0, ticker=xaxis.ticker))
plot.add_layout(Grid(dimension=1, ticker=yaxis.ticker))

curdoc().add_root(plot)

show(plot)

```

--------------------------------

### Customize Grid Band Fill

Source: https://docs.bokeh.org/en/latest/docs/examples/styling/plots/grid_band_fill.html

This example shows how to customize the fill color and alpha of y-grid bands. It also demonstrates removing x-grid lines. Ensure Bokeh is installed and imported.

```python
from bokeh.plotting import figure, show

p = figure(width=400, height=400)
p.scatter([1,2,3,4,5], [2,5,8,2,7], size=10)

# change just some things about the x-grid
p.xgrid.grid_line_color = None

# change just some things about the y-grid
p.ygrid.band_fill_alpha = 0.1
p.ygrid.band_fill_color = "navy"

show(p)

```

--------------------------------

### Build with Local BokehJS (Windows CMD)

Source: https://docs.bokeh.org/en/latest/docs/dev_guide/documentation.html

Builds the documentation using a local version of BokehJS. Sets the BOKEH_DOCS_CDN environment variable and then builds HTML and serves.

```batch
set BOKEH_DOCS_CDN=local
make.bat html
make.bat serve
```

--------------------------------

### CumSum Expression Example

Source: https://docs.bokeh.org/en/latest/docs/reference/models/expressions.html

Illustrates the usage of the `CumSum` expression to cumulatively sum values from a single column in a `ColumnDataSource`. The `include_zero` parameter controls whether zero is included at the start of the result.

```python
source = ColumnDataSource(data=dict(foo=[1, 2, 3, 4]))

CumSum(field='foo')
# -> [1, 3, 6, 10]

CumSum(field='foo', include_zero=True)

```

--------------------------------

### Start Bokeh static server for development (Linux/macOS)

Source: https://docs.bokeh.org/en/latest/docs/dev_guide/setup.html

Initiate a local Bokeh server to serve development resources. This is the first step when using the 'server-dev' option for BOKEH_RESOURCES.

```bash
BOKEH_DEV=true bokeh static
```

--------------------------------

### Basic Vertical Bar Chart Example

Source: https://docs.bokeh.org/en/latest/docs/user_guide/basic/bars.html

Generates a basic vertical bar chart displaying fruit counts. It configures the plot with a categorical x-axis, removes grid lines, and sets the y-axis start to zero.

```python
from bokeh.plotting import figure, show

fruits = ['Apples', 'Pears', 'Nectarines', 'Plums', 'Grapes', 'Strawberries']
counts = [5, 3, 4, 2, 4, 6]

p = figure(x_range=fruits, height=350, title="Fruit Counts",
           toolbar_location=None, tools="")

p.vbar(x=fruits, top=counts, width=0.9)

p.xgrid.grid_line_color = None
p.y_range.start = 0

show(p)

```

--------------------------------

### Equivalent CustomJS for Range Slider js_link

Source: https://docs.bokeh.org/en/latest/docs/reference/models/expressions.html

This shows the `CustomJS` callback equivalent to the `js_link` example for a range slider and plot x-range. It explicitly sets the 'start' property of the x-range using the first value from the slider.

```python
from bokeh.models import CustomJS
range_slider.js_on_change('value', CustomJS(args=dict(other=plot.x_range), code='other.start = this.value[0]'))
```

--------------------------------

### Start Bokeh static server for development (Windows CMD)

Source: https://docs.bokeh.org/en/latest/docs/dev_guide/setup.html

Initiate a local Bokeh server to serve development resources. This is the first step when using the 'server-dev' option for BOKEH_RESOURCES.

```cmd
set BOKEH_DEV=true
bokeh static
```

--------------------------------

### Creating and Displaying HStrip Glyphs

Source: https://docs.bokeh.org/en/latest/docs/reference/models/glyphs/hstrip.html

This example demonstrates how to create a ColumnDataSource with y-coordinates, instantiate an HStrip glyph with specified fill color and y-coordinates, add it to a plot, configure axes and grids, and finally display the plot. Ensure Bokeh is installed and configured for display.

```python
import numpy as np

from bokeh.core.properties import field
from bokeh.io import curdoc, show
from bokeh.models import ColumnDataSource, Grid, HStrip, LinearAxis, Plot, Range1d

N = 9
y0 = np.linspace(-9, 9, N)
y1 = [y + 0.2*(i + 1) for i, y in enumerate(y0)]

source = ColumnDataSource(dict(y0=y0, y1=y1))

plot = Plot(
    x_range=Range1d(start=-10, end=10),
    title=None, width=300, height=300,
    min_border=0, toolbar_location=None,
)

glyph = HStrip(y0=field("y0"), y1=field("y1"), fill_color="#7fc97f")
plot.add_glyph(source, glyph)

xaxis = LinearAxis()
plot.add_layout(xaxis, "below")

yaxis = LinearAxis()
plot.add_layout(yaxis, "left")

plot.add_layout(Grid(dimension=0, ticker=xaxis.ticker))
plot.add_layout(Grid(dimension=1, ticker=yaxis.ticker))

curdoc().add_root(plot)

show(plot)


```

--------------------------------

### Run Standalone Example (Linux/macOS)

Source: https://docs.bokeh.org/en/latest/docs/dev_guide/setup.html

Execute a standalone Bokeh example on Linux or macOS. Ensure the BOKEH_RESOURCES environment variable is set to 'inline' or 'absolute-dev'.

```bash
BOKEH_RESOURCES=inline python examples/basic/data/transform_markers.py
```

--------------------------------

### Build HTML Documentation (Linux/macOS)

Source: https://docs.bokeh.org/en/latest/docs/dev_guide/documentation.html

Builds the HTML output for Bokeh's documentation using the standard make command.

```bash
make html
```

--------------------------------

### Python Setup for Custom DrawTool

Source: https://docs.bokeh.org/en/latest/docs/user_guide/advanced/extensions/tool.html

This Python code sets up a Bokeh plot and integrates the custom DrawTool. It initializes a ColumnDataSource, creates a figure, adds the custom tool, and renders a line using the data from the source. This is the main entry point for running the example.

```python
from bokeh.core.properties import Instance
from bokeh.models import ColumnDataSource, Tool
from bokeh.plotting import figure, show
from bokeh.util.compiler import TypeScript

CODE = """
import {GestureTool, GestureToolView} from "models/tools/gestures/gesture_tool"
import {ColumnDataSource} from "models/sources/column_data_source"
import {PanEvent} from "core/ui_events"
import * as p from "core/properties"

export class DrawToolView extends GestureToolView {
  declare model: DrawTool

  // this is executed when the pan/drag event starts
  _pan_start(_e: PanEvent): void {
    this.model.source.data = {x: [], y: []}
  }

  // this is executed on subsequent mouse/touch moves
  _pan(e: PanEvent): void {
    const {frame} = this.plot_view
    const {sx, sy} = e

    if (!frame.bbox.contains(sx, sy))
      return

    const x = frame.x_scale.invert(sx)
    const y = frame.y_scale.invert(sy)

    const {source} = this.model
    source.get_array("x").push(x)
    source.get_array("y").push(y)
    source.change.emit()
  }

  // this is executed then the pan/drag ends
  _pan_end(_e: PanEvent): void {}
}

export namespace DrawTool {
  export type Attrs = p.AttrsOf<Props>

  export type Props = GestureTool.Props & {
    source: p.Property<ColumnDataSource>
  }
}

export interface DrawTool extends DrawTool.Attrs {}

export class DrawTool extends GestureTool {
  declare properties: DrawTool.Props
  declare __view_type__: DrawToolView

  constructor(attrs?: Partial<DrawTool.Attrs>) {
    super(attrs)
  }

  tool_name = "Draw Tool"
  tool_icon = "bk-tool-icon-lasso-select"
  event_type = "pan" as "pan"
  default_order = 12

  static {
    this.prototype.default_view = DrawToolView

    this.define<DrawTool.Props>(({Ref}) => ({
      source: [ Ref(ColumnDataSource) ],
    }))
  }
}
"

class DrawTool(Tool):
    __implementation__ = TypeScript(CODE)
    source = Instance(ColumnDataSource)

source = ColumnDataSource(data=dict(x=[], y=[]))

plot = figure(x_range=(0,10), y_range=(0,10), title="Click and drag to draw",
              background_fill_color="#efefef", tools="")

plot.add_tools(DrawTool(source=source))

plot.line('x', 'y', line_width=3, source=source)

show(plot)

```

--------------------------------

### Build HTML Documentation (Windows CMD)

Source: https://docs.bokeh.org/en/latest/docs/dev_guide/documentation.html

Builds the HTML output for Bokeh's documentation using the make.bat script in the Command Prompt.

```batch
make.bat html
```

--------------------------------

### Create and Display Tabs with Multiple Figures

Source: https://docs.bokeh.org/en/latest/docs/reference/models/layouts.html

This example demonstrates how to create two Tabs widgets, each containing different Bokeh figures. It shows how to add tooltips to individual tab panels and display them side-by-side using a Row layout. Ensure Bokeh is installed and run this script to see the interactive output.

```python
from bokeh.models import TabPanel, Tabs, Tooltip
from bokeh.models.layouts import Row
from bokeh.plotting import figure, show

p1 = figure(width=300, height=300)
p1.scatter([1, 2, 3, 4, 5], [6, 7, 2, 4, 5], size=20, color="navy", alpha=0.5)

p2 = figure(width=300, height=300)
p2.line([1, 2, 3, 4, 5], [6, 7, 2, 4, 5], line_width=3, color="navy", alpha=0.5)

p3 = figure(width=300, height=300)
p3.scatter([1, 2, 3, 4, 5], [6, 7, 2, 4, 5], size=20, color="navy", alpha=0.5)

p4 = figure(width=300, height=300)
p4.line([1, 2, 3, 4, 5], [6, 7, 2, 4, 5], line_width=3, color="navy", alpha=0.5)

tabs0 = Tabs(tabs=[
    TabPanel(child=p1, title="circle"),
    TabPanel(child=p2, title="line"),
])

tabs1 = Tabs(tabs=[
    TabPanel(child=p1, title="circle", tooltip=Tooltip(content="This is the first tab.", position="bottom_center")),
    TabPanel(child=p2, title="line", tooltip=Tooltip(content="This is the second tab.", position="bottom_center")),
])

show(Row(tabs0, tabs1))

```

--------------------------------

### Install Bokeh with Conda

Source: https://docs.bokeh.org/en/latest/docs/first_steps.html

Use this command to install Bokeh using conda. This requires Anaconda or Miniconda to be installed.

```bash
conda install bokeh

```

--------------------------------

### Serve a Bokeh App Directory

Source: https://docs.bokeh.org/en/latest/docs/user_guide/server/app.html

Command to start a Bokeh server application from a specified directory.

```bash
bokeh serve --show myapp
```

--------------------------------

### Navigate to Documentation Directory

Source: https://docs.bokeh.org/en/latest/docs/dev_guide/documentation.html

Changes the current directory to the Bokeh documentation source files.

```bash
cd docs/bokeh/
```

--------------------------------

### Install Bokeh with Pip

Source: https://docs.bokeh.org/en/latest/docs/first_steps.html

Use this command to install Bokeh using pip. Ensure you have Python 3.10 or above installed.

```bash
pip install bokeh

```

--------------------------------

### Install Selenium and geckodriver with conda

Source: https://docs.bokeh.org/en/latest/docs/user_guide/output/export.html

Installs Selenium and geckodriver using conda for Firefox compatibility. Ensure Firefox is also installed.

```bash
conda install selenium geckodriver -c conda-forge

```

--------------------------------

### Basic BokehJS Plot Setup and Interactivity

Source: https://docs.bokeh.org/en/latest/docs/user_guide/advanced/bokehjs.html

Demonstrates importing BokehJS libraries, creating a plot with tools, adding a line glyph, and dynamically adding data points via a button click.

```javascript
<script src="https://cdn.bokeh.org/bokeh/release/bokeh-3.9.1.min.js"></script>
<script src="https://cdn.bokeh.org/bokeh/release/bokeh-gl-3.9.1.min.js"></script>
<script src="https://cdn.bokeh.org/bokeh/release/bokeh-widgets-3.9.1.min.js"></script>
<script src="https://cdn.bokeh.org/bokeh/release/bokeh-tables-3.9.1.min.js"></script>
<script src="https://cdn.bokeh.org/bokeh/release/bokeh-mathjax-3.9.1.min.js"></script>
<script src="https://cdn.bokeh.org/bokeh/release/bokeh-api-3.9.1.min.js"></script>
<script>// create a data source to hold data
const source = new Bokeh.ColumnDataSource({
    data: { x: [], y: [] }
});

// make a plot with some tools
const plot = Bokeh.Plotting.figure({
    title: 'Example of random data',
    tools: "pan,wheel_zoom,box_zoom,reset,save",
    height: 300,
    width: 300
});

// add a line with data from the source
plot.line({ field: "x" }, { field: "y" }, {
    source: source,
    line_width: 2
});

// show the plot, appending it to the end of the current section
Bokeh.Plotting.show(plot);

function addPoint() {
    // add data --- all fields must be the same length.
    source.data.x.push(Math.random())
    source.data.y.push(Math.random())

    // update the data source with local changes
    source.change.emit()
}

const addDataButton = document.createElement("Button");
addDataButton.appendChild(document.createTextNode("Some data."));
document.currentScript.parentElement.appendChild(addDataButton);
addDataButton.addEventListener("click", addPoint);

addPoint();
addPoint();</script>
```

--------------------------------

### Install Selenium with pip

Source: https://docs.bokeh.org/en/latest/docs/user_guide/output/export.html

Installs the Selenium library using pip. You will need to manually download and install geckodriver and ensure it's in your PATH.

```bash
pip install selenium

```

--------------------------------

### Create and Show PreText Model

Source: https://docs.bokeh.org/en/latest/docs/reference/models/widgets/markups.html

This example demonstrates how to create a PreText model with specified text content, width, and height, and then display it using bokeh.io.show. Ensure bokeh.io is imported.

```python
from bokeh.io import show
from bokeh.models import PreText

pre = PreText(text="""Your text is initialized with the 'text' argument.

The remaining Paragraph arguments are 'width' and 'height'. For this example,
those values are 500 and 100, respectively.""",
width=500,
height=100)

show(pre)
```

--------------------------------

### Build with Local BokehJS (Windows PowerShell)

Source: https://docs.bokeh.org/en/latest/docs/dev_guide/documentation.html

Builds the documentation using a local version of BokehJS. Sets the BOKEH_DOCS_CDN environment variable and then builds HTML and serves.

```powershell
$Env:BOKEH_DOCS_CDN = "local"
.\make.bat html
.\make.bat serve
```

--------------------------------

### StartEnd Enumeration

Source: https://docs.bokeh.org/en/latest/docs/reference/core/enums.html

Specifies a start or end value. Options are start and end.

```python
StartEnd _ = Enumeration(start, end)_#
```

--------------------------------

### Install and Enable jupyter-server-proxy

Source: https://docs.bokeh.org/en/latest/docs/user_guide/output/jupyter.html

Install the jupyter-server-proxy package and enable its server extension for JupyterLab.

```bash
pip install jupyter-server-proxy && jupyter server extension enable --py jupyter-server-proxy

```

--------------------------------

### Initialize a new Bokeh extension

Source: https://docs.bokeh.org/en/latest/docs/user_guide/advanced/extensions.html

Use this command to create the necessary files for a new pre-built Bokeh extension, including configuration files like `bokeh.ext.json`, `package.json`, and `tsconfig.json`.

```bash
bokeh init
```

--------------------------------

### Install jupyter_bokeh with Pip

Source: https://docs.bokeh.org/en/latest/docs/user_guide/output/jupyter.html

Install the jupyter_bokeh extension using pip for use with JupyterLab.

```bash
pip install jupyter_bokeh

```

--------------------------------

### Clone Bokeh Tutorial Repository

Source: https://docs.bokeh.org/en/latest/docs/user_guide/output/jupyter.html

Clone the bokeh-tutorial repository to access example notebooks for various Bokeh features, including notebook integration.

```git
git clone https://github.com/bokeh/tutorial.git
```

--------------------------------

### DirectoryHandler.__init__()

Source: https://docs.bokeh.org/en/latest/docs/reference/application/handlers/directory.html

Initializes the DirectoryHandler with a path to the application directory and optional command-line arguments.

```APIDOC
## DirectoryHandler.__init__()

### Description
Initializes the handler for a given application directory.

### Parameters
#### filename (str)
    A path to an application directory with either "main.py" or "main.ipynb".
#### argv (list[str], optional)
    A list of string arguments to make available as sys.argv to main.py. Defaults to []
```