nbtoolbelt
Tools to work with Jupyter notebooks
Decision gist · record as of 2026-08-14
Yes. nbtoolbelt is a mature, actively maintained utility for Jupyter notebook automation with low install friction, no security vulnerabilities, and a permissive MIT license. Install it if you regularly work with multiple notebooks, need to validate or batch-process them, or want to automate notebook-based workflows (especially in education or research). It is not necessary for casual single-notebook use.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or later (supports up to 3.13).
- Low install friction with a pure-wheel distribution.
- Actively maintained as of 105 days ago with support for current Python versions (3.10–3.13).
License · maintenance · safety
permissive license (permissive) — MIT License permits unrestricted use, modification, and distribution with minimal obligations—suitable for both commercial and open-source projects.
last release 2026-05-01 (105 days)
0 known vulnerabilities (OSV.dev, 2026-08-14) · 201,848 downloads/mo, #9,660 on PyPI
Alternatives
Verify before relying
pip install nbtoolbelt
from nbtoolbelt import validate
validate('notebook.ipynb')
# Or via command line:
# nbtb validate notebook.ipynb- Whether the 'punch' tool for exercise creation integrates with existing learning management systems or grading workflows.
- Performance characteristics when processing very large notebooks or batch operations on hundreds of files.
- Availability and completeness of programmatic API documentation beyond the command-line interface.
What it is and what it does
nbtoolbelt is a suite of utilities for working with Jupyter notebooks at scale, available both as command-line scripts and as importable library functions. It wraps nbformat, nbconvert, jupyter-client, and data libraries (numpy, pandas) to provide operations like validation against the notebook schema, statistical summaries, content extraction, and execution with optional pre/post-processing. The package is particularly useful for educators and researchers who need to automate notebook workflows—validating student submissions, generating exercise templates with fill-in-the-blank sections (the 'punch' tool), or batch-processing collections of notebooks for analysis or transformation.
The tool is production-stable (Development Status 5) and has been maintained since 2017. It targets developers, educators, scientists, and system administrators. All operations are available through a single command-line entry point (nbtb) with per-tool options, or as library calls for integration into larger Python workflows.
Use it for
- Validate a batch of student-submitted notebooks against the Jupyter schema before grading or processing.
- Generate exercise notebooks by punching holes into template notebooks and distributing them for students to fill in.
- Extract and summarize statistics from a collection of notebooks (cell counts, execution time, output sizes).
- Concatenate multiple notebooks into a single document for report generation or archival.
- Clean notebooks by removing execution outputs, metadata, or specific cell types before version control or sharing.
- Execute a notebook with automatic pre-cleaning and post-processing as part of a data pipeline or CI workflow.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
nbtoolbelt is a mature, actively maintained utility for Jupyter notebook automation with low install friction, no security vulnerabilities, and a permissive MIT license. Install it if you regularly work with multiple notebooks, need to validate or batch-process them, or want to automate notebook-based workflows (especially in education or research). It is not necessary for casual single-notebook use.
Install
nbtoolbelt on PyPI
Before you install
Low install friction with a pure-wheel distribution. Actively maintained as of 105 days ago with support for current Python versions (3.10–3.13). Runtime dependencies are all well-established Jupyter ecosystem packages.
Requires Python 3.10 or later (supports up to 3.13).
License in practice
MIT License permits unrestricted use, modification, and distribution with minimal obligations—suitable for both commercial and open-source projects.
Quickstart
pip install nbtoolbelt
from nbtoolbelt import validate
validate('notebook.ipynb')
# Or via command line:
# nbtb validate notebook.ipynbVerify before relying
- Whether the 'punch' tool for exercise creation integrates with existing learning management systems or grading workflows.
- Performance characteristics when processing very large notebooks or batch operations on hundreds of files.
- Availability and completeness of programmatic API documentation beyond the command-line interface.
Package facts
| License | permissive license permissive |
| Python support | Supports the current Python release <3.14,>=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 5 packagesnbformatnbconvertjupyter-clientnumpypandas |
| Maintenance | Actively maintained 105 days since the last release |
| First released | |
| Downloads | 201,848 / month, #9,660 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableFramework :: JupyterIntended Audience :: DevelopersIntended Audience :: EducationIntended Audience :: Science/ResearchIntended Audience :: System AdministratorsLicense :: OSI Approved :: MIT LicenseOperating System :: OS IndependentProgramming Language :: PythonProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Topic :: EducationTopic :: Scientific/EngineeringTopic :: Software Development :: LibrariesTopic :: Utilities |
Evidence: nbtoolbelt-2026.4.1-py3-none-any.whl
Tags
Let your AI agent find packages like this
Example. Real query, live index.
You found this page by searching. An agent finds it by wishing: SkillFed indexes 14,416 PyPI packages by what they can do, searchable in plain language.
wish › “jupyter notebook command line tools”
- nbtoolbeltnbtoolbelt provides command-line and library tools for validating,…
- jupyter-consoleJupyter Console is a terminal-based frontend for Jupyter kernels,…
- jupyter-blackA Jupyter Notebook and JupyterLab extension that automatically…
Give your agent the search over MCP, or paste the wish link into any chat.
More Libraries packages
urllib3 is an HTTP client library that provides thread-safe connection pooling, SSL/TLS verification, multipart file uploads, request retries, compression support, and proxy handling for Python applications.
Requests is a Python HTTP library that simplifies sending HTTP/1.1 requests with automatic handling of headers, authentication, cookies, and response parsing.
Pluggy provides a plugin system that lets you define hook specifications and register implementations to be called in sequence, enabling extensible Python applications without tight coupling.
Install it if you're building an extensible application or framework.
Provides parsing, arithmetic, and recurrence rule computation for dates and times, with timezone support and iCalendar RFC compliance.
Install it if you need to parse flexible date strings, compute relative dates, handle timezones, or work with recurrence rules—it's the de facto choice for these tasks.
Six provides utility functions to write Python code that runs on both Python 2.7 and Python 3.3+, smoothing over language differences between the two versions.
pytest is a testing framework that lets you write test functions using plain assert statements and automatically discovers and runs them, with detailed failure reporting.
See also nb-clean · nbformat · pybatfish · nbconvert · nbdev · nbqa · nbmake · nbval · nbclient · pyct