Python and Julia in harmony.
Author cjdoris
69 Stars
Updated Last
1 Year Ago
Started In
November 2020

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Bringing Python® and Julia together in seamless harmony:

  • Call Python code from Julia and Julia code from Python via a symmetric interface.
  • Simple syntax, so the Python code looks like Python and the Julia code looks like Julia.
  • Intuitive and flexible conversions between Julia and Python: anything can be converted, you are in control.
  • Fast non-copying conversion of numeric arrays in either direction: modify Python arrays (e.g. bytes, array.array, numpy.ndarray) from Julia or Julia arrays from Python.
  • Helpful wrappers: interpret Python sequences, dictionaries, arrays, dataframes and IO streams as their Julia couterparts, and vice versa.
  • Beautiful stack-traces.
  • Works anywhere: tested on Windows, MacOS and Linux, 32- and 64-bit, Julia 1.0 upwards and Python 3.5 upwards.

If you like this, a GitHub star would be lovely thank you.

To get started, read the documentation.

Example 1: Calling Python from Julia

In this example, we use PythonCall.jl from an IJulia notebook to inspect the Iris dataset:

  • We load the Iris dataset as a Julia DataFrame using RDatasets.jl.
  • We use pypandasdataframe(df) to convert it to a Python pandas.DataFrame.
  • We use the Python package seaborn to produce a pair-plot, which is automatically displayed.

Seaborn example screenshot

Example 2: Calling Julia from Python

In this example we use the Python module juliacall from an IPython notebook to train a simple neural network:

  • We generate some random training data using Python's numpy.
  • We construct and train a neural network model using Julia's Flux.
  • We plot some sample output from the model using Python's matplotlib.pyplot.

Flux example screenshot

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