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This release is a pre-release and may not be stable for production use.

gofish-python

A Python wrapper for the GoFish graphics library. Both the mid-level chart API and the low-level mark/operator API are supported. (See notes/design.md and notes/implementation.md for more details.)

Installation

pip install --pre gofish-graphics

The latest stable release on PyPI is old and lags far behind development. The docs at gofish.graphics describe the current dev builds, which are published on every change to main. You must include the --pre flag, otherwise pip installs the outdated stable release.

The package is imported as gofish:

from gofish import chart

See the getting started docs for a full introduction.

Usage

from gofish import chart, spread, stack, rect

# Create a chart specification
data = [{"lake": "A", "species": "B", "count": 10}]
c = (
    chart(data, axes=True)
    .flow(
        spread("lake", dir="x", spacing=64),
        stack("species", dir="y", spacing=0),
    )
    .mark(rect(h="count", fill="species"))
)

# Convert to JSON IR
ir = c.to_ir()
print(ir)
# {
#     "data": None,
#     "operators": [
#         {"type": "spread", "field": "lake", "dir": "x", "spacing": 64},
#         {"type": "stack", "field": "species", "dir": "y", "spacing": 0}
#     ],
#     "mark": {"type": "rect", "h": "count", "fill": "species"},
#     "options": {"axes": True}
# }

IR Format

The JSON IR has the following structure:

{
  "data": null,
  "operators": [
    { "type": "spread", "field": "lake", "dir": "x", "spacing": 8 },
    { "type": "derive", "lambdaId": "uuid-here" },
    { "type": "stack", "field": "species", "dir": "y" }
  ],
  "mark": { "type": "rect", "h": "count", "fill": "species" },
  "options": {}
}

Development

Note: This package uses uv for fast package management and testing.

Prerequisites

  • Python 3.10+
  • uv - Fast Python package manager
  • Node.js (for building the widget bundle)
  • pnpm (for managing Node.js dependencies)

Development Install

cd packages/gofish-python
uv pip install -e .

Installing Node.js Dependencies

If you need to build the widget bundle, install Node.js dependencies:

pnpm install

Building the Widget Bundle

The widget bundle is a self-contained JavaScript module that includes all dependencies. Build it with:

# From the package directory
pnpm run build:widget

# Or directly with Node.js
node build-widget.mjs

This will:

  • Bundle the TypeScript widget source (widget-src/index.ts)
  • Include all dependencies (gofish-graphics, solid-js, apache-arrow)
  • Output to gofish/_static/widget.esm.js

Note: The build process will automatically use gofish-graphics/dist/index.js if available, otherwise it falls back to the package import. Make sure gofish-graphics is built first if you're developing locally.

Running Tests

Python Unit Tests

# Install with test dependencies
uv pip install -e ".[test]"

# Run all tests
uv run pytest

# Or run directly if installed
pytest

# Run specific test file
pytest tests/test_ast.py

# Run with verbose output
pytest -v

Jupyter Notebook Tests

The package includes Jupyter notebooks for interactive testing:

  • tests/test_ir.ipynb - Tests for IR generation
  • tests/test_rendering.ipynb - Tests for widget rendering

To run these:

# Start Jupyter
jupyter notebook

# Or use the provided script (if available)
./run_notebook.sh

Development Workflow

  1. Install dependencies:

    uv pip install -e ".[test]"
    pnpm install
    
  2. Make changes to Python code or widget TypeScript source

  3. Build widget (if you modified widget code):

    pnpm run build:widget
    
  4. Run tests:

    pytest
    
  5. Test in Jupyter (optional):

    jupyter notebook tests/test_rendering.ipynb
    

Metadata

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