PyScript Examples

packages = ["bokeh", "pandas", "numpy", "networkx", "diagrams", "scikit-learn", "pillow", "matplotlib", "plotly"] [[fetch]] files = ["diagrams_base.py"] from = "../python/diagrams/" [[fetch]] files = ["pyscript_manager.py", "data.py"] to_folder = "lib" from = "../python/lib/" [[fetch]] files = ["bokeh_utils.py"] from = "../python/bokeh/" [[fetch]] files = ["matplotlib_utils.py", "plotly_utils.py"] from = "../python/matplotlib/" [[fetch]] files = ["agent.py", "trainer.py", "utils.py", "metrics_chart.py", "crossover.py", "__init__.py"] to_folder = "ml/neuro" from = "../python/ml/neuro/" [[fetch]] files = ["trainer.py"] to_folder = "ml/grokking" from = "../python/ml/grokking/"

🐍 Loading Python chart...

Bokeh

🎨 What is Bokeh?

Bokeh is a powerful Python library...

⚙️ How Does Bokeh Generate Charts?

1. Python API: You write Python code... 2. JSON Serialization... 3. BokehJS Rendering... 4. Interactivity...

🐍 Why Use Bokeh with Python Instead of Pure JavaScript?

Even though Bokeh ultimately renders using JavaScript:

Data Processing Power: Python excels at data manipulation...
Scientific Ecosystem: Leverage Python's rich scientific libraries...
High-Level API: Bokeh's Python API is more intuitive...
Code Reusability: Same Python code works...
Complexity Abstraction: Bokeh handles the tedious...
With PyScript: Run this Python code directly...

🔄 The PyScript + Bokeh Workflow

In this example, PyScript runs the Python code...

💡 Interactive Features

Try interacting with the chart above!...