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 1.0.6

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 1.0.6
File	Size	Uploaded
ai_parrot_visualizations-1.0.6.tar.gz	749.3 kB	Sep 23, 2026	Details

Built distribution (wheel)

Table of built distributions (wheels) for ai-parrot-visualizations 1.0.6
File	Interpreter	ABI	Platform	Reset
ai_parrot_visualizations-1.0.6-py3-none-any.whl 777.9 kB Sep 23, 2026	Python 3	none	any	Details

Total release size: 1.5 MB

Release files / ai_parrot_visualizations-1.0.6.tar.gz

Download URL	ai_parrot_visualizations-1.0.6.tar.gz
Size	749.3 kB
Tags	Source
SHA-256 checksum How to use checksums	`07c38edf928806acb26a156aae89da1324c1fdacb70c24f24618013f2da39abd`
BLAKE2b-256 checksum How to use checksums	`aff61dfdb0f10240dedb459161de0e040f5bad2ffc4ae4b1cc85197120e44085`
Upload date	Sep 23, 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/ccf5a2b6b260f015fa6b02603b230b2aa4bf9077

Workflow

Publishing configuration: github.com/phenobarbital/ai-parrot/blob/ccf5a2b6b260f015fa6b02603b230b2aa4bf9077/.github/workflows/release.yml
Publishing logs: github.com/phenobarbital/ai-parrot/actions/runs/35932114525/attempts/1

Artifact

Subject: ai_parrot_visualizations-1.0.6.tar.gz
SHA-256 checksum: 07c38edf928806acb26a156aae89da1324c1fdacb70c24f24618013f2da39abd Verifying attestations

Release files / ai_parrot_visualizations-1.0.6-py3-none-any.whl

Download URL	ai_parrot_visualizations-1.0.6-py3-none-any.whl
Size	777.9 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`6fa7701d96e56ca8fb34fbd16ef0b8981804f1cec8c82cfd2c80398e5ca4a501`
BLAKE2b-256 checksum How to use checksums	`705ed8931a817a7f9b2faebaa5c52d152ca25581b423c1896f8d7d69e46179d0`
Upload date	Sep 23, 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/ccf5a2b6b260f015fa6b02603b230b2aa4bf9077

Workflow

Publishing configuration: github.com/phenobarbital/ai-parrot/blob/ccf5a2b6b260f015fa6b02603b230b2aa4bf9077/.github/workflows/release.yml
Publishing logs: github.com/phenobarbital/ai-parrot/actions/runs/35932114525/attempts/1

Artifact

Subject: ai_parrot_visualizations-1.0.6-py3-none-any.whl
SHA-256 checksum: 6fa7701d96e56ca8fb34fbd16ef0b8981804f1cec8c82cfd2c80398e5ca4a501 Verifying attestations