Bokeh 2.3.3 is a specific maintenance release of the Bokeh Python library, launched in July 2021 to resolve critical layout and extension-related bugs. As part of the broader 2.3.x release cycle, it represents a stable point for developers who require high-performance, interactive data visualizations in modern web browsers without writing JavaScript. Key Bug Fixes in Version 2.3.3
As a patch release, Bokeh 2.3.3 focused on stability. Significant fixes included:
Layout Consistency: Resolved an issue where Column layouts ignored the scrollable CSS class and fixed a layout regression specifically affecting Panel dashboards.
Visual Refinements: Fixed bad formatting of y-axis labels when using themes and corrected a bug where a plot's height could not go below 600px.
Widget Behavior: Addressed a bug in the MultiChoice widget where the dropdown menu would remain hidden and ensured the active tab is correctly in view upon rendering.
CDN Integration: Updated extensions to fetch exact versions from the CDN to prevent version mismatch issues. Major Features from the 2.3.x Series
While 2.3.3 provided stability, it inherited powerful features introduced in the 2.3.0 minor release:
Multi-line Labels: Users can split long axis and tick labels across multiple lines for better readability in tight layouts.
Improved Log Axes: Rendered exponents as proper superscripts by default, enhancing the scientific quality of plots.
Hatch Patterns: Added support for hatch patterns (textures) across all fillable glyphs and annotations.
New Marker Types: Introduced "star" markers and vectorized support for arrowheads and line-dash patterns.
DataModel Class: A new base class allowed developers to define "properties-only" Bokeh subclasses more easily, simplifying the creation of custom models. Core Capabilities of Bokeh
Regardless of the specific patch version, Bokeh continues to be a staple in the PyData ecosystem for several reasons:
Interactivity: Built-in tools for zooming, panning, and hovering allow users to explore data dynamically.
Flexibility: It offers three layers of abstraction: the low-level bokeh.models for full control, the mid-level bokeh.plotting for standard glyphs, and high-level integration with tools like HoloViews.
Scalability: Through the Bokeh server, it supports real-time streaming data and server-side downsampling for massive datasets.
Integration: Plots can be seamlessly embedded into Flask or Django web applications, as well as Jupyter Notebooks. Migration and Legacy Support bokeh 2.3.3
Bokeh at a Glance * Flexible. Bokeh makes it simple to create common plots, but also can handle custom or specialized use-cases. * Bokeh plots Building Charts in Bokeh - Pluralsight
Bokeh 2.3.3 , you are working with a legacy release of the powerful Python interactive visualization library. While newer versions exist, 2.3.3 is often maintained for specific dependency environments. 🛠️ Official Documentation & Installation The most authoritative "deep guide" is the archived Bokeh 2.3.3 User Guide
, which covers everything from basic glyphs to server deployment. Bokeh documentation Installation : Use pip to target this specific version: pip install bokeh==2.3.3 Sample Data
: To follow many tutorial examples, you may need to download the companion datasets using: bokeh sampledata Bokeh documentation 💡 Core Architecture: How 2.3.3 Works Bokeh operates on a two-part system: Python Library
: You define your plots, widgets, and logic in Python. It generates a declarative JSON object graph.
: A client-side JavaScript library that takes that JSON and renders the actual interactive visualization in the browser. Bokeh documentation 🗝️ Key Features in 2.3.3
Version 2.3.3 introduced or refined several critical features that were major updates at the time: Hatch Patterns
: Support for textured fills (dots, stripes, etc.) on all fill-able glyphs and annotations. Multi-line Labels : The ability to have multi-line axis and tick labels. WebGL Acceleration
: Enhanced performance for large datasets (thousands of points) by offloading rendering to the GPU. SVG Export
: While PNG was standard, 2.3.3 documentation provides specific paths for exporting layouts as SVGs Bokeh documentation 🏗️ Building a Basic Plot In Bokeh 2.3.3, the bokeh.plotting interface is the most common entry point: # Create a figure with specific tools = figure(title= Basic Line Plot , x_axis_label= , y_axis_label= pan,wheel_zoom,box_zoom,reset # Add a renderer ], line_width= # Display the result Use code with caution. Copied to clipboard 🚀 Advanced Usage Bokeh Server
: Use this to build applications where Python code reacts to browser events (like sliders or selections). You run these apps via the bokeh serve Interactions CustomJS callbacks
for interactions that don't require a Python server, allowing your plots to remain interactive even as standalone HTML files. Integration : Seamlessly works with Jupyter Notebooks by calling output_notebook() Bokeh documentation ⚠️ Version-Specific Warnings Python Compatibility
: This version is typically used with Python 3.6 through 3.9. Check your environment if you encounter installation errors. Documentation Warning : Ensure you are looking at the /en/2.3.3/ path in the docs; the
documentation contains breaking changes and new syntax (like the bokeh.models overhaul) not present in 2.3.3. Bokeh documentation specific code example
(like a real-time dashboard or a complex map) to build with Bokeh 2.3.3? User guide — Bokeh 2.3.3 Documentation
The phrase " bokeh 2.3.3 " refers to a specific version of the interactive visualization library, released in Bokeh 2
. Depending on your context, "full piece" likely refers to one of the following: Bokeh documentation 1. The Bokeh Software Documentation Version 2.3.3 is a stable release of the Bokeh Python library . The "full piece" might refer to the complete source code full documentation for setting up a development environment, which includes: Bokeh documentation Bokeh (Python): The package source code. BokehJS (TypeScript): The client-side library that handles browser rendering. Bokeh documentation 2. Standalone Code Examples In technical forums, "full piece" often refers to a Minimal Reproducible Example (MRE)
—a complete, self-contained script used to demonstrate a feature or bug. For example, version 2.3.3 users often share "full pieces" of code to troubleshoot layout regressions in the model or panels. Bokeh documentation 3. Misleading "Apk" or Video Content
You may encounter searches or TikTok videos mentioning "Download Bokeh 2.3.3 Apk" or "full piece" videos. Be cautious: Getting Set Up — Bokeh 2.3.3 Documentation 2 Jun 2020 —
Bokeh 2.3.3 is a patch release from July 2021 that primarily addresses layout bugs and extension-related regressions . Below are helpful resources and posts categorized by their utility. Key Technical Updates & Fixes
The Official Release Notes for 2.3.3 detail several critical bug fixes :
Layout Fixes: Resolved issues where columns ignored scrollable CSS classes and panel layout regressions .
Formatting: Fixed bad formatting of y-axis labels when using themes .
UI Tweaks: Active tabs now correctly stay in view on render, and a bug preventing plot heights from going below 600px was fixed .
Extensions: Fixed a bug where extensions did not fetch the exact version from the CDN . Helpful Community Discussions
Working with Tabs and Panels: A discussion on Bokeh Discourse confirms that Bokeh 2.3.3 works well with Panel 0.12.1 to resolve common layout warning messages (like W-1002 EMPTY_LAYOUT) .
DataTable Formatting: Users on Bokeh Discourse share solutions for combining NumberFormatter and HTMLTemplateFormatter in 2.3.3 to style specific cells based on value (e.g., coloring negative numbers red) .
Embedding in Private Networks: If you're having trouble with plots not rendering on a private network, this post explains how to manually configure a Resources object to load BokehJS components without relying on external CDNs . Common Troubleshooting
WebGL Issues: If you experience bugs with WebGL in 2.3.3, such as legend interactions not working properly, community experts on Stack Overflow suggest upgrading to Bokeh 2.4.3+, which included significant WebGL refactoring .
Memory Management: There are noted reports of increasing memory consumption when using bokeh serve with multiple browser sessions; if your application is long-running, monitoring memory usage is recommended .
Step Cast Warning: Be aware that the default step value for numeric inputs is 1, which may unexpectedly cast float inputs to integers. You must explicitly set step to a float (e.g., 0.1) to avoid this . Plots Not Rendering on Private Network - Bokeh Discourse
Bokeh 2.3.3 is a maintenance patch release for the Bokeh interactive visualization library, published in July 2021. As a minor update within the 2.3 series, it focused on stabilization rather than introducing new features, specifically addressing layout and extension bugs that emerged in previous 2.x versions. Key Improvements and Bug Fixes Technical Write-Up: Bokeh 2
This version resolved several regressions and formatting issues critical for consistent dashboard layouts:
Layout Fixes: Addressed an issue where a Column would ignore the "scrollable" CSS class and fixed height constraints where plots could not go below 600px.
UI Components: Fixed a bug where dropdown menus were hidden in multi-choice components and ensured active tabs were correctly in view upon rendering.
Axis Labeling: Corrected bad formatting of y-axis labels when specific themes were applied.
Extensions: Improved how extensions fetch exact versions from CDNs to prevent compatibility mismatches. Overview of Bokeh (Library Context)
Bokeh remains a premier choice for Python developers needing web-ready interactivity without writing JavaScript.
Architecture: Built on a "layered glyph" system similar to ggplot's geoms, allowing users to build complex plots one layer at a time.
Interactivity: Unlike Matplotlib, Bokeh is designed for large or streaming datasets and supports complex interactive elements like linked brushing and hover tools.
Dashboards: It is highly suited for data applications and dashboards, with a dedicated server component for real-time updates. Recommendations
While 2.3.3 was an essential update for stability in its time, it has since been succeeded by the 3.x branch, which introduced major architectural changes, including improved CSS-based theming and performance upgrades. Releases — Bokeh 2.3.3 Documentation
Here’s a helpful reference paper for Bokeh 2.3.3 — structured as a quick-start + cheat sheet for users who need to work with this specific version.
Release Date: July 9, 2021
Type: Patch Release
Previous Version: 2.3.2
Next Version: 2.3.4
Working with categorical axes (e.g., bar charts with string categories) became more intuitive. The factor_cmap and factor_mark functions saw internal fixes, ensuring that color mapping and marker shapes apply correctly even when categories have long names or special characters.
Some users complain that hover tooltips show ??? for special characters. Fix: Explicitly set a css_classes property and define font-family in your own CSS file.
The team collected decibel levels from three key games in June 2021. They wanted to compare the noise levels against the previous "normal" season (2019).