{"categories":[{"label":"Scientific/Engineering","url":"https://skillfed.io/packages/category/scientific-engineering/6"}],"enrichment":{"capability":"Call Julia code from Python and Python code from Julia with automatic type conversion, array wrapping, and a symmetric interface between the two languages.","skillfed_tags":["language-interop","scientific-computing"],"use_cases":["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."],"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.\n\nThe package handles numeric array conversion without copying\u2014you 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.","worth_installing":"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."},"id":"juliacall","links":{"html":"https://skillfed.io/packages/juliacall","md":"https://skillfed.io/packages/juliacall.md","pypi":"https://pypi.org/project/juliacall/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-06-08","license_spdx":null,"license_treatment":"permissive","name":"juliacall","python_support":"supports_current","summary":"Julia and Python in seamless harmony"},"popularity":{"monthly_downloads":199356,"position":9708,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.9.35"}