ai-parrot-visualizations

Visualization renderer backends for the AI-Parrot framework.

Provides heavy visualization renderers (matplotlib, seaborn, plotly, altair, bokeh, holoviews, echarts, d3, folium, infographic) as a separate installable package, keeping the core ai-parrot package lightweight.

Installation

# Install all renderers
pip install "ai-parrot-visualizations[all]"

# Install specific renderer groups
pip install "ai-parrot-visualizations[matplotlib,seaborn]"
pip install "ai-parrot-visualizations[plotly,altair]"
pip install "ai-parrot-visualizations[charts]"      # all chart renderers
pip install "ai-parrot-visualizations[infographic]"  # infographic renderers
pip install "ai-parrot-visualizations[messaging]"    # card/slack/whatsapp

Usage

Import paths are unchanged — the PEP 420 namespace merging makes satellite renderers transparent to the consumer:

from parrot.outputs.formats import get_renderer
from parrot.models.outputs import OutputMode

# Works the same whether renderer is in core or satellite
renderer_cls = get_renderer(OutputMode.MATPLOTLIB)
result = renderer_cls.render(data)

Available Extras

Extra	Renderers	Dependencies
`matplotlib`	MatplotlibRenderer	matplotlib>=3.7
`seaborn`	SeabornRenderer	seaborn>=0.13, matplotlib>=3.7
`plotly`	PlotlyRenderer	plotly>=5.0
`altair`	AltairRenderer	altair>=5.0
`bokeh`	BokehRenderer	bokeh>=3.0, pandas-bokeh>=0.5
`holoviews`	HoloviewsRenderer	holoviews>=1.18
`echarts`	EChartsRenderer	(JS-based, no Python deps)
`d3`	D3Renderer	(JS-based, no Python deps)
`map`	MapRenderer	folium>=0.14
`infographic`	InfographicRenderer, InfographicHTMLRenderer	cairosvg, svglib, reportlab
`jinja2`	Jinja2Renderer, TemplateReportRenderer	jinja2>=3.0
`streamlit`	StreamlitGenerator	streamlit>=1.30
`panel`	PanelGenerator	panel>=1.0
`messaging`	CardRenderer, SlackRenderer, WhatsAppRenderer	(no heavy deps)
`charts`	All chart renderers	(all chart deps above)
`all`	Everything	(all deps above)

Architecture

This package uses PEP 420 implicit namespace packages to contribute to the parrot.outputs.formats namespace without requiring entry-points. When both ai-parrot and ai-parrot-visualizations are installed, Python merges their parrot/outputs/formats/ directories via extend_path().

License

MIT — see the LICENSE file.

Metadata

Release files for ai-parrot-visualizations 1.2.3

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for ai-parrot-visualizations 1.2.3
File	Size	Uploaded
ai_parrot_visualizations-1.2.3.tar.gz	750.7 kB	Oct 16, 2026	Details

Built distribution (wheel)

Table of built distributions (wheels) for ai-parrot-visualizations 1.2.3
File	Interpreter	ABI	Platform	Reset
ai_parrot_visualizations-1.2.3-py3-none-any.whl 779.3 kB Oct 16, 2026	Python 3	none	any	Details

Total release size: 1.5 MB

Release files / ai_parrot_visualizations-1.2.3.tar.gz

Download URL	ai_parrot_visualizations-1.2.3.tar.gz
Size	750.7 kB
Tags	Source
SHA-256 checksum How to use checksums	`0edd3a6dc8a832cb1dcd56b862235ab2b95472f4d641b8a90703c2b8c3f50ff0`
BLAKE2b-256 checksum How to use checksums	`7f4bee3080ae668e325269f139e2f190c253e30712c46eb6c151ca20991253d2`
Upload date	Oct 16, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	Yes
Uploaded via	`twine/7.0.0 CPython/3.13.14`

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

Identity

Publishing platform: GitHub Actions
Publishing repository: github.com/phenobarbital/ai-parrot
Publishing commit: github.com/phenobarbital/ai-parrot/tree/22b0c4ed75a07105a3a8c12d09dbb056ba94c9b1

Workflow

Publishing configuration: github.com/phenobarbital/ai-parrot/blob/22b0c4ed75a07105a3a8c12d09dbb056ba94c9b1/.github/workflows/release.yml
Publishing logs: github.com/phenobarbital/ai-parrot/actions/runs/38831313265/attempts/1

Artifact

Subject: ai_parrot_visualizations-1.2.3.tar.gz
SHA-256 checksum: 0edd3a6dc8a832cb1dcd56b862235ab2b95472f4d641b8a90703c2b8c3f50ff0 Verifying attestations

Release files / ai_parrot_visualizations-1.2.3-py3-none-any.whl

Download URL	ai_parrot_visualizations-1.2.3-py3-none-any.whl
Size	779.3 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`c3525ab3e3ed52586c49701015efd71bdc4d68c15f68597ed6afb1b402329244`
BLAKE2b-256 checksum How to use checksums	`64dd7feb01389d8055dc9637ec2d62c737d483fe31e10ee2e4b54d9efc1fd490`
Upload date	Oct 16, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	Yes
Uploaded via	`twine/7.0.0 CPython/3.13.14`

Provenance

Identity

Publishing platform: GitHub Actions
Publishing repository: github.com/phenobarbital/ai-parrot
Publishing commit: github.com/phenobarbital/ai-parrot/tree/22b0c4ed75a07105a3a8c12d09dbb056ba94c9b1

Workflow

Publishing configuration: github.com/phenobarbital/ai-parrot/blob/22b0c4ed75a07105a3a8c12d09dbb056ba94c9b1/.github/workflows/release.yml
Publishing logs: github.com/phenobarbital/ai-parrot/actions/runs/38831313265/attempts/1

Artifact

Subject: ai_parrot_visualizations-1.2.3-py3-none-any.whl
SHA-256 checksum: c3525ab3e3ed52586c49701015efd71bdc4d68c15f68597ed6afb1b402329244 Verifying attestations