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 |
None |
Bool |
bool |
Integer |
int |
Rational{<:Integer} |
fractions.Fraction |
Float64, Float32, Float16 |
float |
Complex{Float64}, Complex{Float32}, Complex{Float16} |
complex |
AbstractString, AbstractChar |
str |
Base.CodeUnits{UInt8} (e.g. b"example") |
bytes |
Tuple, Pair |
tuple |
AbstractRange{<:Integer} |
range |
Dates.Date |
datetime.date |
Dates.Time |
datetime.time |
Dates.DateTime |
datetime.datetime |
Dates.Second, Dates.Millisecond, Dates.Microsecond, Dates.Nanosecond |
datetime.timedelta |
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