Jupyter Server Dependency Graph

Jupyter Server is used in Python projects. The backend—i.e. core services, APIs, and REST endpoints—to Jupyter web applications. It has 19 direct runtime dependencies. Check its dependency graph on PyDeps to understand the full transitive dependency tree, reverse dependents, known CVEs, and license compatibility before installing.

What is Jupyter Server used for?

The backend—i.e. core services, APIs, and REST endpoints—to Jupyter web applications.

Direct dependencies

Jupyter Server declares 19 direct runtime dependencies, each of which is resolved and rendered as an expandable node in the graph:

Transitive dependencies

Beyond its direct dependencies, Jupyter Server pulls in further packages through its dependency tree. PyDeps walks the entire chain from PyPI and deps.dev so you can see every transitive (nested) dependency, expand any node on demand, and understand the full set of code that ships when you install Jupyter Server.

Dependency risk and maintenance

Jupyter Server is distributed under the BSD License license. Use the vulnerability panel, powered by the OSV database, to check whether Jupyter Server or anything in its dependency tree has known CVEs before you ship, and review the license of every dependency to confirm compatibility with your project.

How to read the dependency graph

In the interactive graph each node is a package and each edge is a version constraint. Expand a node to load its subdependencies, switch to the dependents view to see which packages rely on Jupyter Server, and download Jupyter Server together with all of its dependencies as wheels for offline or air-gapped installs.

Related packages

PyDeps