The following table specifies the conversion rules used whenever converting a Julia object to a Python object.
From Julia, this occurs explicitly with Py(x) or implicitly when passing Julia objects as the argument to a Python function.
To avoid this automatic conversion, the user can convert objects explicitly, such as by calling pylist or pydict.
From Python, this occurs when converting the return value of a Julia function.
| From | To |
|---|---|
Any Python object type (Py, PyList, etc.) |
itself |
Nothing, Missing |
None |
Bool |
bool |
Standard integer (IntXX, UIntXX, BigInt) |
int |
Standard rational (Rational{T}, T a standard integer) |
fractions.Fraction |
Standard float (FloatXX) |
float |
Standard complex (Complex{T}, T a standard float) |
complex |
Standard string/char (String and SubString{String}, Char) |
str |
Tuple |
tuple |
Standard integer range (AbstractRange{T}, T a standard integer) |
range |
Date, Time, DateTime (from Dates) |
date, time, datetime (from datetime) |
Second, Millisecond, Microsecond, Nanosecond (from Dates) |
timedelta (from datetime) |
Number |
juliacall.NumberValue, juliacall.ComplexValue, etc. |
AbstractArray |
juliacall.ArrayValue, juliacall.VectorValue |
AbstractDict |
juliacall.DictValue |
AbstractSet |
juliacall.SetValue |
IO |
juliacall.BufferedIOValue |
Module |
juliacall.ModuleValue |
Type |
juliacall.TypeValue |
| Anything else | juliacall.AnyValue |
See [here](@ref julia-wrappers) for an explanation of the juliacall.*Value wrapper types.
You may define a new conversion rule for your new type T by overloading Py(::T).
If T is a wrapper type (such as PyList) where Py(x) simply returns the stored Python
object, then also define ispy(::T) = true.
PythonCall.ispy
Alternatively, if you define a wrapper type (a subtype of
juliacall.AnyValue) then you may instead define pyjltype(::T) to
be that type.
PythonCall.pyjltype