Conversion to Julia

Conversion Rules

The following table specifies the conversion rules used whenever converting a Python object to a Julia object. If the initial Python type matches the "From" column and the desired type T intersects with the "To" column, then that conversion is attempted. Conversions are tried in priority order, then in specificity order.

From Julia, one can convert Python objects to a desired type using pyconvert(T, x) for example.

From Python, the arguments to a Julia function will be converted according to these rules with T=Any.

From	To
Top priority (wrapped values).
`juliacall.AnyValue`	`Any`
Very high priority (arrays).
Objects satisfying the buffer or array interface (inc. `bytes`, `bytearray`, `array.array`, `numpy.ndarray`)	`PyArray`
High priority (canonical conversions).
`None`	`Nothing`
`bool`	`Bool`
`numbers.Integral` (inc. `int`)	`Integer` (prefers `Int`, or `BigInt` on overflow)
`float`	`Float64`
`complex`	`Complex{Float64}`
`range`	`StepRange`
`str`	`String`
`tuple`	`Tuple`
`collections.abc.Mapping` (inc. `dict`)	`PyDict`
`collections.abc.Sequence` (inc. `list`)	`PyList`
`collections.abc.Set` (inc. `set`, `frozenset`)	`PySet`
`io.IOBase` (includes open files)	`PyIO`
`BaseException`	`PyException`
`datetime.date`/`datetime.time`/`datetime.datetime`	`Date`/`Time`/`DateTime`
`datetime.timedelta`	`Microsecond` (or `Millisecond` or `Second` on overflow)
`numpy.intXX`/`numpy.uintXX`/`numpy.floatXX`	`IntXX`/`UIntXX`/`FloatXX`
Standard priority (other reasonable conversions).
`None`	`Missing`
`bytes`	`Vector{UInt8}`, `Vector{Int8}`, `String`
`str`	`String`, `Symbol`, `Char`, `Vector{UInt8}`, `Vector{Int8}`
`range`	`UnitRange`
`collections.abc.Mapping`	`Dict`
`collections.abc.Iterable`	`Vector`, `Set`, `Tuple`, `NamedTuple`, `Pair`
`datetime.timedelta`	`Dates.CompoundPeriod`
`numbers.Integral`	`Integer`, `Rational`, `Real`, `Number`
`numbers.Real`	`AbstractFloat`, `Number`, `Missing`/`Nothing` (if NaN)
`numbers.Complex`	`Complex`, `Number`
`ctypes.c_int` and other integers	`Integer`, `Rational`, `Real`, `Number`
`ctypes.c_float`/`ctypes.c_double`	`Cfloat`/`Cdouble`, `AbstractFloat`, `Real`, `Number`
`ctypes.c_voidp`	`Ptr{Cvoid}`, `Ptr`
`ctypes.c_char_p`	`Cstring`, `Ptr{Cchar}`, `Ptr`
`ctypes.c_wchar_p`	`Cwstring`, `Ptr{Cwchar}`, `Ptr`
`numpy.intXX`/`numpy.uintXX`/`numpy.floatXX`	`Integer`, `Rational`, `Real`, `Number`
Objects satisfying the buffer or array interface	`Array`, `AbstractArray`
Low priority (fallback to `Py`).
Anything	`Py`
Bottom priority (must be explicitly specified by excluding `Py`).
Objects satisfying the buffer interface	`PyBuffer`
Anything	`PyRef`

See here for an explanation of the Py* wrapper types (PyList, PyIO, etc).

Custom rules

To add a custom conversion rule, you must define a function to do the conversion and call pyconvert_add_rule to register it.

You must not do this while precompiling, so these calls will normally be in the __init__ function of your module.

PythonCall.pyconvert_add_rule — Function

pyconvert_add_rule(tname::String, T::Type, func::Function, priority::PyConvertPriority=PYCONVERT_PRIORITY_NORMAL)

Add a new conversion rule for pyconvert.

Arguments

tname is a string of the form "__module__:__qualname__" identifying a Python type t, such as "builtins:dict". This rule only applies to Python objects of this type.
T is a Julia type, such that this rule only applies when the target type intersects with T.
func is the function implementing the rule.
priority determines whether to prioritise this rule above others.

When pyconvert(R, x) is called, all rules such that typeintersect(T, R) != Union{} and pyisinstance(x, t) are considered. These rules are sorted first by priority, then by the specificity of t (e.g. bool is more specific than int is more specific than object) then by the order they were added. The rules are tried in turn until one succeeds.

Implemeting func

func is called as func(S, x::Py) for some S <: T.

It must return one of:

pyconvert_return(ans) where ans is the result of the conversion (and must be an S).
pyconvert_unconverted() if the conversion was not possible (e.g. converting a list to Vector{Int} might fail if some of the list items are not integers).

The target type S is never a union or the empty type, i.e. it is always a data type or union-all.

Priority

Most rules should have priority PYCONVERT_PRIORITY_NORMAL (the default) which is for any reasonable conversion rule.

Use priority PYCONVERT_PRIORITY_CANONICAL for canonical conversion rules. Immutable objects may be canonically converted to their corresponding Julia type, such as int to Integer. Mutable objects must be converted to a wrapper type, such that the original Python object can be retrieved. For example a list is canonically converted to PyList and not to a Vector. There should not be more than one canonical conversion rule for a given Python type.

Other priorities are reserved for internal use.