Compatibility Tools
Some packages require a little extra help to work nicely with PythonCall.
Some of these are "fixes" that are silently applied for you, and some are just extra functions to bridge a gap. We aim to keep these as minimal as possible.
Python standard library
Whenever a Python exception is displayed by Julia, sys.last_traceback
and friends are set. This allows the post-mortem debugger pdb.pm()
to work. Disable by setting PythonCall.CONFIG.auto_sys_last_traceback = false
.
Tabular data / Pandas
The abstract type PyTable
is for wrapper types around Python tables, providing the Tables.jl interface. PyTable(x)
is shorthand for pyconvert(PyTable, x)
.
The subtype PyPandasDataFrame
wraps a pandas.DataFrame
.
For example, if x
is a pandas.DataFrame
then PyTable(x)
is a PyPandasDataFrame
and DataFrame(PyTable(x))
is a DataFrame
.
In the other direction, the following functions can be used to convert any Tables.jl
-compatible table to a Python table.
Missing docstring for pytable
. Check Documenter's build log for details.
MatPlotLib / PyPlot / Seaborn
MatPlotLib figures can be shown with Julia's display mechanism, like display(fig)
or display(mime, fig)
.
This means that if you return a figure from a Jupyter or Pluto notebook cell, it will be shown. You can call display(plt.gcf())
to display the current figure.
We also provide a simple MatPlotLib backend: mpl.use("module://juliacall.matplotlib")
. Now you can call plt.show()
to display the figure with Julia's display mechanism. You can specify the format like plt.show(format="png")
.
Python GUIs (including MatPlotLib)
Event loops
If for example you wish to use PyPlot in interactive mode (matplotlib.pyplot.ion()
) then activating the correct event loop will allow it to work.
Missing docstring for PythonCall.event_loop_on
. Check Documenter's build log for details.
Missing docstring for PythonCall.event_loop_off
. Check Documenter's build log for details.
Qt path fix
Missing docstring for PythonCall.fix_qt_plugin_path
. Check Documenter's build log for details.
IPython
The juliacall
IPython extension adds these features to your IPython session:
- The line magic
%julia code
executes the given Julia code in-line. - The cell magic
%%julia
executes a cell of Julia code. - Julia's
stdout
andstderr
are redirected to IPython. - Calling
display(x)
from Julia will displayx
in IPython.
The extension is experimental and unstable - the API can change at any time.
Enable the extension with %load_ext juliacall
. See the IPython docs.
The %%julia
cell magic can synchronise variables between Julia and Python by listing them on the first line:
In [1]: %load_ext juliacall
In [2]: x = 2
In [3]: y = 8
In [4]: %%julia x y z
...: z = "$x^$y = $(x^y)";
...:
...:
In [5]: z
Out[5]: '2^8 = 256'
Asynchronous Julia code (including Makie)
Asynchronous Julia code will not normally run while Python is executing, unless it is in a separate thread.
This can be fixed by calling jl.yield()
periodically from Python code, allowing the Julia scheduler to run.
When working at the Python REPL, you may call juliacall.interactive()
which will allow Julia async code to run while the prompt is showing. This will allow interactive plots such as Makie to work.