Skip to main content
Pre-release

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

Inklet

Scientific figures from Python, with measured layout and editable SVG/PDF output.

Combine plots, diagrams, images and native 3D artwork on a page sized in millimetres. Keep data and labels live, compile the figure, and inspect its layout and print diagnostics before exporting.

Get started · Documentation · Examples · API reference

Twenty-panel Inklet figure with 3D surfaces, architecture diagrams, dense scatter, statistical charts, polar plots and Sankey flows

This twenty-panel stress test includes 30,000 scatter points, 5,580 mesh triangles and 7,200 vector events. Its data are simulated. Only the dense scatter and scalar field are rasterized; the other artwork remains vector.

Start with plots from CSV, then combine them with measured diagrams, images and 3D in one figure. Shared scales keep panels comparable; physical dimensions keep type and strokes consistent when you change the page size. The plot guide helps choose a representation, while layout and export review cover the finished page.

4.0 development preview

4.0.0.dev16 adds compact dense-field PDF exports and reusable figure projects with verified input files, saved editor choices and shared entity identities.

python -m pip install "inklet==4.0.0.dev16"

Preview guide · Figure project tutorial · 4.0 roadmap · Release notes

This is an opt-in development release. Experimental APIs and saved-state schemas may change; 3.1.0 remains the stable release. General browser editing, depth-aware 3D selection and the remaining 4.0 release gates are still open. Animation and presentation authoring remain in the 5.0 direction.

Install

Python 3.11 or later is required. Install from PyPI:

python -m venv .venv
source .venv/bin/activate
python -m pip install inklet

SVG/PDF output and the built-in 3D renderer need no browser or external rendering engine. Text needs an installed font. For PNG output and visual review, install python -m pip install 'inklet[render]'. Poppler adds independent PDF previews; use compare_pdf=False or --no-pdf-preview for a review without it. See installation for system packages, Windows activation, optional dependencies and environment checks.

Your first figure

Save this as first_figure.py and run python first_figure.py:

import inklet as i


def make_document():
    data = i.dataset(
        {'time': [0, 1, 2, 3], 'signal': [1, 3, 2, 4]},
        name='response',
        source=i.Source('Quickstart demonstration', method='simulated'),
    )
    plot = i.plot_spec(x=(0, 3), y=(0, 5))
    plot.line(data.points('time', 'signal'), name='Signal', stroke='#176b9b')
    plot.axes(x='Time / s', y='Signal / mV').legend(side='bottom')

    doc = i.publication('single-column').document()
    doc.add('response', plot, min_height=55)
    return doc


if __name__ == '__main__':
    figure = make_document().compile()
    figure.save('response.svg', 'response.pdf')
    print(figure.report())

The document measures axis labels and the legend, fits the plot to an 89 mm page, and saves SVG and PDF with embedded text. It does not shrink the font to make the plot fit. The quickstart continues with live data edits, multiple panels and review exports.

Build, inspect, revise

With the preview dependencies installed:

inklet doctor
inklet build first_figure.py --output out/review
inklet watch first_figure.py --output out/review

build writes the vector files, PNG previews, diagnostics, a provenance manifest and a local HTML review page. watch serves a preview at http://127.0.0.1:8765/ and rebuilds when the authoring code changes. Review pages support diagnostic filters, SVG highlights and comparisons with a saved revision.

For an environment without preview tools, use inklet build first_figure.py --output out/review --vectors-only.

What you can build

Task Main tools Guide
Scientific, educational and branded styles preset, independent formats, live switching Presets
Multi-panel figures document, subfigure, weighted columns, spans, panel letters Layout
Scientific plots plot_spec, axes, bands, distributions, heatmaps, insets, polar plots Plotting
Data-driven revisions Dataset, Series, shared scales, categories, derive, source records Live data
Architecture and flow diagrams composition, module, named ports, measured connections, graph Diagrams
3D and image panels solid, model, scene, asset, explicit file dependencies 3D and images
Publication exports Physical presets, embedded or outlined text, SVG/PDF, review bundles Export and review

How Inklet works

A Document holds live definitions. compile() measures their contents, places them, routes connections and produces a snapshot used by both export backends. Updating a dataset or named instruction invalidates dependent components; unchanged definitions can reuse their cached geometry. Earlier snapshots remain unchanged.

Numeric lengths, including low-level text sizes, are millimetres. Use i.pt(8) for an 8-point text size; publication profile options such as font_pt=8 take points explicitly. Plot coordinates follow their data scales.

The direct Figure, Panel and Diagram APIs remain supported for fixed drawings. See the authoring model for when to use each layer.

Scope and limits

  • Layout respects physical constraints. Impossible fits raise LayoutError; changing page width does not automatically rearrange the number of columns.
  • Diagnostics help find collisions, small type and other print issues. Review the rendered figure as well; a clean report does not establish scientific accuracy.
  • Rasterization keeps dense exports compact, but dense-scatter rebuilds can still be expensive. The stress report records the workload, timings and remaining limitations.
  • Reproducible appearance requires consistent inputs, fonts and dependencies. The export manifest records dataset and font hashes for comparison.

Scene rendering

Inklet combines complete Blender scenes with vector plots, labels and measurements. Cycles uses an available GPU and falls back to CPU when none is found. Render queues provide progress, cancellation and bounded concurrency. Saved camera projection and numeric passes support depth-tested paths, object masks and world-space dimensions without rerendering an annotation change.

Three editable templates cover laboratory apparatus, product presentation and architecture. The annotated laboratory combines 265 objects, twelve callouts, a measured footprint, two detail views and an analytic response plot.

An annotated laboratory cutaway with detail views and a response plot

PNG export uses resvg and needs no browser. Gradients, hatching and group blending remain vector in SVG/PDF. Masks and explicit rasterization create image layers; keep editable text outside them. Blender is installed separately and remains optional for ordinary plots and native vector 3D.

Rendering guide · Scene templates · Showcase library · Upgrade from 2.6 · Compatibility

Documentation and development

Read the documentation on Read the Docs. The latest documentation follows the development branch. The source Markdown is also readable on GitHub, and contributors can serve the site from a checkout:

python -m pip install -e '.[docs]'
python -m mkdocs serve

See contributing for tests, documentation checks and visual regressions. Existing users can consult migration, historical guides and the changelog.

License

Inklet code is available under the MIT license. Included third-party meshes and structural data retain their own terms; see third-party notices.

Release files for inklet 4.0.0.dev16

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

Source distribution (sdist)

Source distribution for inklet 4.0.0.dev16
File Size Uploaded
inklet-4.0.0.dev16.tar.gz 82.3 MB Details

Built distribution (wheel)

Table of built distributions (wheels) for inklet 4.0.0.dev16
File Interpreter ABI Platform
inklet-4.0.0.dev16-py3-none-any.whl Python 3 none any Details

Total release size: 83.4 MB

Release files / inklet-4.0.0.dev16.tar.gz

Download URL inklet-4.0.0.dev16.tar.gz
Size 82.3 MB
Tags Source
SHA-256 checksum
How to use checksums
86af2ee9acd422e97acb703025254858d25742afb68bc06d11603becc99577ab
BLAKE2b-256 checksum
How to use checksums
4782f618ca47d56a630f34b9fe12dcefe977e5a5e0406b5c2524f04c09fe219c
Upload date
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.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Sep 14, 2026.

Transparency log

Release files / inklet-4.0.0.dev16-py3-none-any.whl

Download URL inklet-4.0.0.dev16-py3-none-any.whl
Size 1.1 MB
Tags Python 3
SHA-256 checksum
How to use checksums
2bb45d09861ee03f41796e4784667055c3aef19e4197cc500e15ad7cbab47930
BLAKE2b-256 checksum
How to use checksums
e62b80c180162059e65370459c1df8d8b2eacd6814de35645c146d1e7eb43d0a
Upload date
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.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Sep 14, 2026.

Transparency log
Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page