Conversion to Python

Conversion Rules

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 for an explanation of the juliacall.*Value wrapper types.

Custom rules

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 — Function

ispy(x)

True if x is a Python object.

This includes Py and Python wrapper types such as PyList.

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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 — Function

pyjltype(x)

The subtype of juliacall.AnyValue which the Julia object x is wrapped as by pyjl(x).

Overload pyjltype(::T) to define a custom conversion for your type T.

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