shellviz 0.4.3

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Shellviz Python Library

Shellviz is a zero-hassle Python tool that transforms your data into dynamic, real-time visualizations you can explore right in your browser. It's lightweight, free, and has no dependencies — just install and start visualizing!

🛠️ Installation

Install Shellviz with pip:

pip install shellviz

🔧 Getting Started

Basic Usage

from shellviz import log, table, json

log('my first shellviz command')
# Shellviz serving on http://127.0.0.1:5544

table([("Alice", 25, 5.6), ("Bob", 30, 5.9)])
json({"name": "Alice", "age": 25, "height": 5.6})

Open the generated URL in your browser, and you'll see your data visualized instantly.

Advanced Usage

Update Existing Values

from shellviz import progress
progress(0.0, id='migration')
progress(1.0, id='migration') # Update data dynamically

Django Integration

Querysets and Models

Shellviz can encode Queryset and Model instances, so you can visualize ORM queries without having to serialize them

from shellviz import json, card
json(request.user)
card(User.objects.all())

Django Logging

Shellviz has an optional drop-in logging handler that can automatically initialize a Shellviz instance and forward all logging calls to it

LOGGING = {
    'handlers': {
        'shellviz': {
            'class': 'shellviz.django_logging.ShellvizHandler',
            #...
        },
    }
}

Django Debug Toolbar

Shellviz can be configured to launch as a tab in the Django Debug Toolbar

DEBUG_TOOLBAR_PANELS = [
    #...
    'shellviz.django_debug_toolbar.ShellvizPanel'
    #...
]

Build

Bundling and deploying Shellviz is straightforward. To automate the process of building the client, copying the necessary files, and compiling the Python package, use the provided build_with_latest_client.py script:

# From the libraries/python directory:
python build_with_latest_client.py

This script will:

1. Build the Shellviz client (runs npm install and npm run build in the client directory)
2. Copy the built client files into the Python package
3. Build the Python package using Poetry

Once this is done, you can publish the package to PyPI:

poetry publish

To install into a local python environment, run the following command:

poetry add --no-cache ~/[path-to-repo]/dist/shellviz-0.x.x-py3-none-any.whl