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 |
numpy.datetime64 | NumpyDates.DateTime64 |
numpy.timedelta64 | NumpyDates.TimeDelta64 |
| 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.bool_/numpy.intXX/numpy.uintXX/numpy.floatXX | Bool, Integer, Rational, Real, Number |
numpy.datetime64 | NumpyDates.InlineDateTime64, Dates.DateTime |
numpy.timedelta64 | NumpyDates.InlineTimeDelta64, Dates.Period |
| 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 — Functionpyconvert_add_rule(tname::String, T::Type, func::Function, priority::PyConvertPriority=PYCONVERT_PRIORITY_NORMAL)Add a new conversion rule for pyconvert.
Arguments
tnameis a string of the form"__module__:__qualname__"identifying a Python typet, such as"builtins:dict"or"sympy.core.symbol:Symbol". This rule only applies to Python objects of this type.Tis a Julia type, such that this rule only applies when the target type intersects withT.funcis the function implementing the rule.prioritydetermines 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.
Implementing func
func is called as func(S, x::Py) for some S <: T.
It must return one of:
pyconvert_return(ans)whereansis the result of the conversion (and must be anS).pyconvert_unconverted()if the conversion was not possible (e.g. converting alisttoVector{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.