ipynb
Package / Module importer for importing code from Jupyter Notebook files (.ipynb)
Decision gist · record as of 2026-08-14
Yes, if you need to import Jupyter Notebooks as modules and are working with a stable, older codebase. The low install friction and permissive license make it safe to try. However, the dormant maintenance status (no updates since 2017) means you should verify compatibility with your Jupyter and Python versions before relying on it in new projects. For modern notebook-to-module workflows, check whether newer alternatives exist.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Installation is frictionless with no runtime dependencies.
- The package is dormant—last release was 2017-10-23 and no commits since 2024-04-15—so expect no active maintenance or bug fixes, though the core functionality remains stable for straightforward use cases.
License · maintenance · safety
BSD (permissive) — BSD permissive license allows free use, modification, and distribution with minimal restrictions, making it safe to adopt in most projects without licensing concerns.
last release 2017-10-23 (3217 days) · last repo commit 2024-04-15 · 258 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 103,859 downloads/mo, #12,781 on PyPI
Alternatives
Verify before relying
pip install ipynb
import ipynb.fs.full.server # Import all code from server.ipynb
# Or import only definitions:
import ipynb.fs.defs.server # Import classes, functions, imports, and ALL_CAPS constants- Whether the package works reliably with modern Jupyter versions and recent Python releases (no version constraints specified in metadata).
- Whether relative imports work correctly in all contexts, particularly across different project structures.
What it is and what it does
ipynb lets you treat Jupyter Notebook files (.ipynb) as importable Python modules. Instead of manually copying code from notebooks or exporting to .py files, you can import them directly using standard Python import syntax. The package provides two modes: full import executes all code in the notebook and exposes top-level definitions, while definitions-only import skips computational work and brings in only function/class definitions, import statements, and ALL_CAPS constants—useful when a notebook contains analysis code you don't want to re-run.
The package has no runtime dependencies and installs cleanly. However, it has been dormant since late 2017 with no recent maintenance, so it may not be tested against current Jupyter or Python versions. It works well for simple notebook-to-module workflows but is not actively developed.
Use it for
- Reuse functions and classes defined in analysis notebooks across multiple projects without manual copying.
- Import utility notebooks as libraries in production code while keeping analysis and helper code in notebook form.
- Build modular notebook-based projects where some notebooks serve as reusable modules for others via relative imports.
- Extract only the definitions (functions, classes, constants) from a notebook without re-running exploratory or computational cells.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you need to import Jupyter Notebooks as modules and are working with a stable, older codebase.
The low install friction and permissive license make it safe to try. However, the dormant maintenance status (no updates since 2017) means you should verify compatibility with your Jupyter and Python versions before relying on it in new projects. For modern notebook-to-module workflows, check whether newer alternatives exist.
Install
ipynb on PyPI
Before you install
Installation is frictionless with no runtime dependencies. The package is dormant—last release was 2017-10-23 and no commits since 2024-04-15—so expect no active maintenance or bug fixes, though the core functionality remains stable for straightforward use cases.
License in practice
BSD permissive license allows free use, modification, and distribution with minimal restrictions, making it safe to adopt in most projects without licensing concerns.
Quickstart
pip install ipynb
import ipynb.fs.full.server # Import all code from server.ipynb
# Or import only definitions:
import ipynb.fs.defs.server # Import classes, functions, imports, and ALL_CAPS constantsVerify before relying
- Whether the package works reliably with modern Jupyter versions and recent Python releases (no version constraints specified in metadata).
- Whether relative imports work correctly in all contexts, particularly across different project structures.
Package facts
| License | BSD permissive |
| Python support | Not specified |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | None |
| Maintenance | Dormant 3,217 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 103,859 / month, #12,781 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
Evidence: ipynb-0.5.1-py3-none-any.whl
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