juliacall
Julia and Python in seamless harmony
Decision gist · record as of 2026-08-14
Yes, if you need to call Julia from Python. The package is actively maintained, has low install friction, carries no known vulnerabilities, and uses a permissive MIT license. It is well-suited for workflows that leverage Julia's computational strengths while staying in a Python environment. Not necessary if you work exclusively in one language.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Julia 1.10 or later and Python 3.10 or later to be installed on the system.
- Low friction: pure Python wheel with a single runtime dependency (juliapkg).
- Actively maintained with recent releases.
License · maintenance · safety
permissive license (permissive) — MIT license permits commercial and private use with minimal restrictions.
last release 2026-06-08 (67 days)
0 known vulnerabilities (OSV.dev, 2026-08-14) · 199,356 downloads/mo, #9,708 on PyPI
Alternatives
Verify before relying
pip install juliacall
from juliacall import Main as jl
# Call Julia code from Python
result = jl.sqrt(2.0)- Whether the package handles all edge cases in bidirectional array conversion without data loss or unexpected behavior.
- Performance characteristics of non-copying array conversions in practice for large datasets.
- Stability and completeness of the symmetric interface across different Julia and Python versions.
What it is and what it does
JuliaCall is a Python module that enables calling Julia code directly from Python, complementing PythonCall which does the reverse. It provides a symmetric interface so that Python code looks like Python and Julia code looks like Julia, with automatic conversions between the two languages' types and data structures.
The package handles numeric array conversion without copying—you can modify Python arrays like numpy.ndarray from Julia or Julia arrays from Python, with changes reflected in the original objects. It wraps Python sequences, dictionaries, dataframes, and IO streams as their Julia equivalents, and vice versa. It requires Julia 1.10 or later and Python 3.10 or later, and manages Python dependencies per Julia project using a separate Conda environment.
Use it for
- Train machine learning models in Julia (e.g. Flux) using data prepared in Python (NumPy) and visualize results with Matplotlib.
- Perform numerical computations in Julia while keeping data processing and visualization workflows in Python.
- Access Julia's scientific libraries (statistics, optimization, differential equations) from a Python notebook without rewriting code.
- Share mutable arrays between Julia and Python for in-place modifications without copying overhead.
- Combine Julia's performance for compute-heavy tasks with Python's ecosystem for data manipulation and plotting.
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.
The package is actively maintained, has low install friction, carries no known vulnerabilities, and uses a permissive MIT license. It is well-suited for workflows that leverage Julia's computational strengths while staying in a Python environment. Not necessary if you work exclusively in one language.
Install
juliacall on PyPI
Before you install
Low friction: pure Python wheel with a single runtime dependency (juliapkg). Actively maintained with recent releases.
Requires Julia 1.10 or later and Python 3.10 or later to be installed on the system.
License in practice
MIT license permits commercial and private use with minimal restrictions.
Quickstart
pip install juliacall
from juliacall import Main as jl
# Call Julia code from Python
result = jl.sqrt(2.0)Verify before relying
- Whether the package handles all edge cases in bidirectional array conversion without data loss or unexpected behavior.
- Performance characteristics of non-copying array conversions in practice for large datasets.
- Stability and completeness of the symmetric interface across different Julia and Python versions.
Package facts
| License | permissive license permissive |
| Python support | Supports the current Python release <4,>=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 1 packagejuliapkg |
| Maintenance | Actively maintained 67 days since the last release |
| First released | |
| Downloads | 199,356 / month, #9,708 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 LicenseOperating System :: OS IndependentProgramming Language :: Python :: 3 |
Evidence: juliacall-0.9.35-py3-none-any.whl
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