jupyterlab-execute-time
Display cell timings in Jupyter Lab
Decision gist · record as of 2026-08-14
Yes. The extension is low-friction to install, actively maintained, carries no security vulnerabilities, and solves a concrete problem for notebook users who need execution timing visibility. The permissive BSD license and small dependency footprint make it safe to add to any JupyterLab environment. Install it if you regularly work with notebooks and want built-in performance insight.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires JupyterLab >= 3.0 and Python >= 3.7.
- Extension displays timing data that JupyterLab itself must record; manual metadata configuration may be needed if auto-setup fails.
- Low friction installation as a pure Python wheel with only jupyterlab as a runtime dependency.
License · maintenance · safety
permissive license (permissive) — BSD-3-Clause permissive license allows free use, modification, and distribution with minimal restrictions; suitable for most projects. Note that contributions require signing a CLA per the project's policy.
last release 2025-12-23 (234 days) · last repo commit 2026-06-01 · 403 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 98,796 downloads/mo, #13,059 on PyPI
Alternatives
Verify before relying
pip install jupyterlab_execute_time
Then launch JupyterLab. The extension auto-enables timing recording in notebook metadata on first load, or manually via Settings > Advanced Settings Editor > Notebook: {"recordTiming": true}- Whether the extension works with all JupyterLab 4.x versions or only specific releases
- Performance impact on notebooks with hundreds or thousands of cells
- Compatibility with JupyterLab plugins that modify cell execution or metadata handling
What it is and what it does
jupyterlab-execute-time is a JupyterLab extension that adds cell execution timing display to the notebook interface. When installed and enabled, it automatically configures JupyterLab to record execution duration in notebook metadata and renders that timing information visibly in the UI for each cell. The extension depends only on jupyterlab itself and installs as a prebuilt wheel, requiring no compilation or additional system dependencies.
The extension is designed for users who want to monitor cell performance during interactive development or data analysis work. It reads timing data that JupyterLab records natively and presents it in the notebook view. The project is actively maintained, supports Python 3.7 through 3.11, and is compatible with JupyterLab 3.0 and later, including version 4.
Use it for
- Identify slow-running cells in data analysis notebooks to optimize computation or queries
- Monitor performance of machine learning model training or inference cells during development
- Track execution time trends across notebook reruns to detect performance regressions
- Understand resource usage patterns in long-running computational workflows
- Debug performance issues in interactive data exploration by seeing which cells consume the most time
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
The extension is low-friction to install, actively maintained, carries no security vulnerabilities, and solves a concrete problem for notebook users who need execution timing visibility. The permissive BSD license and small dependency footprint make it safe to add to any JupyterLab environment. Install it if you regularly work with notebooks and want built-in performance insight.
Install
jupyterlab-execute-time on PyPI
Before you install
Low friction installation as a pure Python wheel with only jupyterlab as a runtime dependency. Active maintenance with a recent release (234 days ago) and 403 repository stars indicate ongoing support.
Requires JupyterLab >= 3.0 and Python >= 3.7. Extension displays timing data that JupyterLab itself must record; manual metadata configuration may be needed if auto-setup fails.
License in practice
BSD-3-Clause permissive license allows free use, modification, and distribution with minimal restrictions; suitable for most projects. Note that contributions require signing a CLA per the project's policy.
Quickstart
pip install jupyterlab_execute_time
Then launch JupyterLab. The extension auto-enables timing recording in notebook metadata on first load, or manually via Settings > Advanced Settings Editor > Notebook: {"recordTiming": true}Verify before relying
- Whether the extension works with all JupyterLab 4.x versions or only specific releases
- Performance impact on notebooks with hundreds or thousands of cells
- Compatibility with JupyterLab plugins that modify cell execution or metadata handling
Package facts
| License | permissive license permissive |
| Python support | Supports the current Python release >=3.7 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 1 packagejupyterlab |
| Maintenance | Actively maintained 234 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 98,796 / month, #13,059 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Framework :: JupyterFramework :: Jupyter :: JupyterLabFramework :: Jupyter :: JupyterLab :: 4Framework :: Jupyter :: JupyterLab :: ExtensionsFramework :: Jupyter :: JupyterLab :: Extensions :: PrebuiltLicense :: OSI Approved :: BSD LicenseProgramming Language :: PythonProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.7Programming Language :: Python :: 3.8Programming Language :: Python :: 3.9 |
Evidence: jupyterlab_execute_time-3.3.0-py3-none-any.whl
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See also jupyterlab_notebook_awareness · jupyter-black · ipython-autotime · jupyterlab-chat · jupyterlab-commands-toolkit · jupyter-server-documents · jupyter_bokeh · jupyter-server-fileid · jupyterlab-widgets · jupyter-builder