Statements (55)
| Predicate | Object |
|---|---|
| gptkbp:instance_of |
gptkb:software
|
| gptkbp:bfsLayer |
5
|
| gptkbp:bfsParent |
gptkb:Py_Call.jl
|
| gptkbp:community |
Open-source community
|
| gptkbp:dependency |
gptkb:Julia
Py Call |
| gptkbp:developed_by |
gptkb:Julia_Computing
|
| gptkbp:example |
Data manipulation using Julia's Data Frames in Python
Accessing Julia's scientific libraries from Python Building hybrid applications with Python and Julia Calling Julia functions from Python scripts Creating Julia-based AP Is for Python applications Integrating Julia with Python data pipelines Integrating Julia with Python web frameworks Running Julia code in Python interactive sessions Running Julia scripts from Python environments Using Julia's machine learning libraries in Python Using Julia's optimization packages in Python Using Julia's plotting libraries in Python Using Julia's statistics libraries in Python Using Julia's symbolic computation capabilities in Python Using Julia's differential equations libraries in Python Creating interactive applications with Python and Julia Combining Python and Julia for high-performance computing Creating visualizations with Julia's Plots.jl in Python Using Julia's parallel computing features in Python |
| gptkbp:features |
Call Julia functions from Python
Data exchange between Python and Julia Interactive use in Jupyter notebooks Support for Julia's type system Support for multiple Julia versions Use Julia libraries in Python |
| gptkbp:has_documentation |
https://pyjulia.readthedocs.io/
|
| https://www.w3.org/2000/01/rdf-schema#label |
Py Julia
|
| gptkbp:installation |
pip install julia
|
| gptkbp:language |
gptkb:Julia
gptkb:Library |
| gptkbp:latest_version |
0.5.0
|
| gptkbp:license |
MIT License
|
| gptkbp:platform |
Cross-platform
|
| gptkbp:purpose |
Interface between Python and Julia
|
| gptkbp:related_to |
gptkb:Jupyter
Data science Machine learning Scientific computing Numerical analysis |
| gptkbp:release_date |
gptkb:2015
|
| gptkbp:repository |
https://github.com/ Julia Py/pyjulia
|
| gptkbp:uses |
Used in optimization problems
Used in academic research Used in data analysis Used in financial modeling Used in machine learning projects Used in numerical simulations Used in visualization tasks |