juliapkg
Julia version manager and package manager
Decision gist · record as of 2026-08-14
Yes, if you need to call Julia from Python and want automated dependency and version management. The low install friction, active maintenance, permissive license, and zero known vulnerabilities make it safe to adopt. Install it only if your project actually requires Julia; it adds a runtime dependency on Julia itself, which is non-trivial to acquire and maintain.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python ≥3.9 and a system capable of downloading/installing Julia (or Julia already present in PATH or via juliaup).
- Low friction: pure Python wheel with only four lightweight runtime dependencies (filelock, semver, tomli, tomlkit).
- Actively maintained as of 2026-08-14 with no known vulnerabilities.
License · maintenance · safety
permissive license (permissive) — MIT license (permissive) — you can use this in commercial and proprietary projects without restriction or obligation to share modifications.
last release 2026-08-14 (0 days) · last repo commit 2026-08-14 · 65 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 196,412 downloads/mo, #9,788 on PyPI
Alternatives
Verify before relying
pip install juliapkg
import juliapkg
juliapkg.require_julia('1.5')
juliapkg.add('Example', version='0.5')
julia_exe = juliapkg.executable()
project_dir = juliapkg.project()- Whether offline mode works reliably when Julia is pre-installed in non-standard locations.
- Performance characteristics when managing large numbers of Julia package dependencies.
- Compatibility with Julia versions newer than the latest tested in the repository.
What it is and what it does
JuliaPkg is a version and package manager for Julia that runs from Python. It lets you declare Julia version requirements and Julia package dependencies in a `juliapkg.json` file, then automatically resolves and installs them. The package handles the mechanics of finding or downloading a compatible Julia executable, managing isolated Julia project directories per Python environment (virtual env, Conda, etc.), and keeping dependencies separate across different Python contexts.
You interact with it through a functional API (require_julia, add, rm, resolve), direct JSON editing, or a command-line interface. It automatically discovers `juliapkg.json` files in installed Python packages, so you can embed Julia dependencies in your own package distributions. The tool supports multiple strategies for locating Julia (PATH, juliaup, or automatic download) and respects standard Julia configuration like JULIA_DEPOT.
Use it for
- Embed Julia computations in a Python package by declaring Julia dependencies in juliapkg.json and letting users' installations resolve them automatically.
- Run Julia scripts from Python with guaranteed version compatibility, avoiding manual Julia setup or version conflicts across team members.
- Isolate Julia environments per Python virtual environment so different projects can require different Julia versions without interference.
- Prototype numerical or scientific algorithms in Julia while keeping the Python project as the entry point, managing both runtimes together.
- Use juliaup or download Julia on-demand in CI/CD pipelines without pre-installing Julia system-wide.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you need to call Julia from Python and want automated dependency and version management.
The low install friction, active maintenance, permissive license, and zero known vulnerabilities make it safe to adopt. Install it only if your project actually requires Julia; it adds a runtime dependency on Julia itself, which is non-trivial to acquire and maintain.
Install
juliapkg on PyPI
Before you install
Low friction: pure Python wheel with only four lightweight runtime dependencies (filelock, semver, tomli, tomlkit). Actively maintained as of 2026-08-14 with no known vulnerabilities.
Requires Python ≥3.9 and a system capable of downloading/installing Julia (or Julia already present in PATH or via juliaup).
License in practice
MIT license (permissive) — you can use this in commercial and proprietary projects without restriction or obligation to share modifications.
Quickstart
pip install juliapkg
import juliapkg
juliapkg.require_julia('1.5')
juliapkg.add('Example', version='0.5')
julia_exe = juliapkg.executable()
project_dir = juliapkg.project()Verify before relying
- Whether offline mode works reliably when Julia is pre-installed in non-standard locations.
- Performance characteristics when managing large numbers of Julia package dependencies.
- Compatibility with Julia versions newer than the latest tested in the repository.
Package facts
| License | permissive license permissive |
| Python support | Supports the current Python release >=3.9 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 4 packagesfilelocksemvertomlitomlkit |
| Maintenance | Actively maintained 0 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 196,412 / month, #9,788 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | License :: OSI Approved :: MIT LicenseProgramming Language :: Python :: 3 |
Evidence: juliapkg-0.1.26-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 › “julia package manager python”
- juliapkgManages Julia language installation and package dependencies from…
- juliacallCall Julia code from Python and Python code from Julia with automatic…
- tree-sitter-juliaProvides incremental parsing of Julia source code using tree-sitter,…
Give your agent the search over MCP, or paste the wish link into any chat.
More Build Tools packages
Provides reusable utilities for Python packaging interoperability, including version handling, specifiers, markers, requirements, tags, and metadata parsing according to standards like PEP 440 and PEP 425.
Wraps any iterable to display a real-time progress bar in the terminal or Jupyter notebook, showing iteration count, elapsed time, and estimated time remaining.
pip is the standard installer for Python packages, enabling you to download and install packages from the Python Package Index and other indexes into your Python environment.
Hatchling is a standards-compliant Python build backend that handles packaging, metadata, and distribution of Python projects when configured in a project's pyproject.toml file.
Generates Python gRPC service stubs and message classes from Protocol Buffer definitions, enabling developers to build gRPC clients and servers.
pre-commit is a framework for installing and running git hooks written in any language before commits are made, automating code quality and validation checks across multi-language projects.
Install it if your team needs consistent, automated validation at commit time.
See also pdm · juliacall · tree-sitter-julia · dependency-groups · pbs-installer · conda-inject · dependencies · dparse2 · poetry-multiproject-plugin · pipupgrade