What input does the tool accept?

It accepts pasted .ipynb JSON or a notebook file using supported JSON or plain-text MIME types.

How are notebook cells ordered?

Cells can be ordered by execution count or by their document order.

Does the output include Markdown cells?

Yes, Markdown can be included as comments when the option is enabled.

What does the tool produce?

It produces text containing a reproducibility report and a linearized Python script with # %% markers.

Elysia Tools

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Data Processing

Jupyter Notebook to Reproducible Script Linearizer

Turn .ipynb into a # %% Python script and detect out-of-order, hidden, and deleted state

Details

What this tool helps you do

Linearizes code by execution_count or document order and statically checks use-before-definition, mutable cross-cell state, references after deletion, random seeds, file paths, environment dependencies, and notebook magics.

Execution

Run this tool

Fill in the form, run the tool, and review the result in one place.

Prepared example runs

Click an example to fill the form automatically. File inputs still need an upload.

1 examples

Diagnose an out-of-order analysis notebook

Linearize a notebook that only worked because a later cell had been run first.

Jupyter reproducibility report and linearized Python

Inputs

Set the required fields, then run the tool.

4 options

FilesUpload source files for this workflow.1

Notebook FilefileOptional

Single file max size: 10 MBSupported types: application/x-ipynb+json, application/json, text/json, text/plain

ContentPaste or type the main input values.1

Notebook InputtextareaOptional

SettingsAdjust formats, ranges, numbers, and modes.1

Cell OrderselectOptional

TogglesEnable or disable optional behavior.1

Include Markdown as commentscheckboxOptionalEnabled when checked

Result

Ready for a run

Run the tool to preview files, text, structured data, or streamed output here.

Samples

Jupyter Notebook to Reproducible Script Linearizer

What this tool helps you do

Run this tool

Prepared example runs

Inputs

Result

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Prepared example runs

Inputs

Result

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Key facts

Overview

When to use

How it works

Use cases

Examples

1. Diagnose an out-of-order analysis notebook

2. Review a notebook before converting it into a script

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