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
.
Julia standard library
Python objects can be serialised with the Serialization
stdlib. This uses pickle
library under the hood. You can opt into using dill
instead by setting the environment variable JULIA_PYTHONCALL_PICKLE="dill"
.
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.
PythonCall.Compat.pytable
— Functionpytable(src, format=:pandas; ...)
Construct a Python table from the Tables.jl-compatible table src
.
The format
controls the type of the resulting table, and is one of:
:pandas
: Apandas.DataFrame
. Keyword arguments are passed to theDataFrame
constructor.:columns
: Adict
mapping column names to columns.:rows
: Alist
of rows, which arenamedtuple
s.:rowdicts
: Alist
of rows, which aredict
s.
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.
PythonCall.Compat.event_loop_on
— Functionevent_loop_on(g::Symbol; interval=0.04, fix=false)
Activate an event loop for the GUI framework g
, so that the framework can run in the background of a Julia session.
The event loop runs every interval
seconds. If fix
is true and g
is a Qt framework, then fix_qt_plugin_path
is called.
Supported values of g
(and the Python module they relate to) are: :pyqt4
(PyQt4), :pyqt5
(PyQt5), :pyside
(PySide), :pyside2
(PySide2), :gtk
(gtk), :gtk3
(gi), :wx
(wx), :tkinter
(tkinter).
PythonCall.Compat.event_loop_off
— Functionevent_loop_off(g::Symbol)
Terminate the event loop g
if it is running.
Qt path fix
PythonCall.Compat.fix_qt_plugin_path
— Functionfix_qt_plugin_path()
Try to set the QT_PLUGIN_PATH
environment variable in Python, if not already set.
This fixes the problem that Qt does not know where to find its qt.conf
file, because it always looks relative to sys.executable
, which can be the Julia executable not the Python one when using this package.
If CONFIG.auto_fix_qt_plugin_path
is true, then this is run automatically before PyQt4
, PyQt5
, PySide
or PySide2
are imported.
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.
You can explicitly enable the extension with %load_ext juliacall
, but it will automatically be loaded if juliacall
is imported and IPython is detected. You can disable this behavior with an environment variable.
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'
Also see the IPython docs for more information on extensions.
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.