layout | toc_group | link_title | permalink |
---|---|---|---|
docs-experimental |
python |
Interoperability |
/reference-manual/python/Interoperability/ |
Besides being primarily recommended to use in your Java application, GraalPy can interoperate with other Graal languages (languages implemented on the Truffle framework). This means that you can use the objects and functions provided by those other languages directly from your Python scripts.
Java is the host language of the JVM and runs the GraalPy interpreter itself.
To interoperate with Java from Python scripts, use the java
module:
import java
BigInteger = java.type("java.math.BigInteger")
myBigInt = BigInteger.valueOf(42)
# a public Java methods can just be called
myBigInt.shiftLeft(128) # returns a <JavaObject[java.math.BigInteger] at ...>
# Java method names that are keywords in Python must be accessed using `getattr`
getattr(myBigInt, "not")() # returns a <JavaObject[java.math.BigInteger] at ...>
byteArray = myBigInt.toByteArray()
# Java arrays can act like Python lists
assert len(byteArray) == 1 and byteArray[0] == 42
To import packages from the java
namespace, you can also use the conventional Python import syntax:
import java.util.ArrayList
from java.util import ArrayList
assert java.util.ArrayList == ArrayList
al = ArrayList()
al.add(1)
al.add(12)
assert list(al) == [1, 12]
In addition to the type
built-in method, the java
module exposes the following methods:
Built-in | Specification |
---|---|
instanceof(obj, class) |
returns True if obj is an instance of class (class must be a foreign object class) |
is_function(obj) |
returns True if obj is a Java host language function wrapped using interop |
is_object(obj) |
returns True if obj if the argument is Java host language object wrapped using interop |
is_symbol(obj) |
returns True if obj if the argument is a Java host symbol, representing the constructor and static members of a Java class, as obtained by java.type |
ArrayList = java.type('java.util.ArrayList')
my_list = ArrayList()
assert java.is_symbol(ArrayList)
assert not java.is_symbol(my_list)
assert java.is_object(ArrayList)
assert java.is_function(my_list.add)
assert java.instanceof(my_list, ArrayList)
See Polyglot Programming and Embed Languages for more information about interoperability with other programming languages.
More general, non-JVM specific interactions with other languages from Python scripts are achieved via the polyglot API. This includes all interactions with dynamic languages supported via the Truffle framework, including JavaScript and Ruby.
Other languages can be included by using their respective Maven dependencies in the same manner as GraalPy. For example, if you have already configured a Maven project with GraalPy, add the following dependency to gain access to JavaScript:
<dependency>
<groupId>org.graalvm.polyglot</groupId>
<artifactId>js</artifactId>
<version>24.0.0</version>
</dependency>
-
Import the
polyglot
module to interact with other languages:import polyglot
-
Evaluate inlined code in another language:
assert polyglot.eval(string="1 + 1", language="js") == 2
-
Evaluate code from a file:
with open("./my_js_file.js", "w") as f: f.write("Polyglot.export('JSMath', Math)") polyglot.eval(path="./my_js_file.js", language="js")
-
Import a glocal value from the polyglot scope:
Math = polyglot.import_value("JSMath")
This global value should then work as expected:
-
Accessing attributes reads from the polyglot members namespace:
assert Math.E == 2.718281828459045
-
Calling a method on the result attempts to do a straight
invoke
and falls back to reading the member and trying to execute it.assert Math.toString() == "[object Math]"
-
Accessing items is supported both with strings and numbers.
assert Math["PI"] == 3.141592653589793
-
-
Use the JavaScript regular expression engine to match Python strings:
js_re = polyglot.eval(string="RegExp()", language="js") pattern = js_re.compile(".*(?:we have (?:a )?matching strings?(?:[!\\?] )?)(.*)") if pattern.exec("This string does not match"): raise SystemError("that shouldn't happen") md = pattern.exec("Look, we have matching strings! This string was matched by Graal.js") assert "Graal.js" in md[1]
This program matches Python strings using the JavaScript regular expression object. Python reads the captured group from the JavaScript result and checks for a substring in it.
The polyglot
module can be used to expose Python objects to JVM languages and other Graal languages (languages implemented on the Truffle framework).
-
You can export some object from Python to other languages so they can import it:
import ssl polyglot.export_value(value=ssl, name="python_ssl")
Then use it in (for example) from JavaScript code:
Polyglot.import('python_ssl).get_server_certificate(["oracle.com", 443])
-
You can decorate a Python function to export it by name:
@polyglot.export_value def python_method(): return "Hello from Python!"
Then use it (for example) from Java code:
import org.graalvm.polyglot.*; class Main { public static void main(String[] args) { try (var context = Context.create()) { context.eval(Source.newBuilder("python", "file:///python_script.py").build()); String result = context. getPolyglotBindings(). getMember("python_method"). execute(). asString(); assert result.equals("Hello from Python!"); } } }
The interop protocol defines different "types" which can overlap in all kinds of ways and have restrictions on how they can interact with Python.
Most importantly and upfront: all foreign objects passed into Python have the Python type foreign
.
There is no emulation of (for example) objects that are of interop type "boolean" to have the Python type bool
.
This is because interop types can overlap in ways that the Python built-in types cannot, and we have yet to define which type should take precedence and such situations.
We do expect to change this in the future, however.
For now, the foreign
type defines all of the Python special methods for type conversion that are used throughout the interpreter (methods such as __add__
, __int__
, __str__
, __getitem__
, and so on)
and these try to "do the right thing" based on the interop type (or raise an exception).
Types not listed in the table below have no special interpretation in Python.
Interop Type | Python Interpretation |
---|---|
null |
null is like None . Important to know: interop null values are all identical to None . JavaScript defines two "null-like" values; undefined and null , which are not identical, but when passed to Python, they are treated so. |
boolean |
boolean behaves like Python booleans, including the fact that in Python, all booleans are also integers (1 and 0 for true and false, respectively). |
number |
number Behaves like Python numbers. Python only has one integer and one floating point type, but ranges are imported in some places such as typed arrays. |
string |
Behaves in the same way as a Python string. |
buffer |
Buffers are also a concept in Python's native API (albeit slightly different). Interop buffers are treated in the same was as Python buffers in some places (such as memoryview ) to avoid copies of data. |
array |
An array can be used with subscript access in the same way as Python lists, with integers and slices as indices. |
hash |
A hash can be used with subscript access in the same way as Python dictionaries, with any "hashable" object as a key. "Hashable" follows Python semantics: generally every interop type with an identity is deemed "hashable". Note that if an interop object is of type Array and Hash , the behavior of subscript access is undefined. |
members |
An object of type members can be read using conventional Python . notation or getattr and related functions. |
iterable |
An iterable is treated in the same way as any Python object with an __iter__ method. That is, it can be used in a loop and other places that accept Python iterables. |
iterator |
An iterator is treated in the same way as any Python object with a __next__ method. |
exception |
An exception can be caught in a generic except clause. |
MetaObject |
Meta objects can be used in subtype and isinstance checks. |
executable |
An executable object can be executed as a function, but never with keyword arguments. |
instantiable |
An instantiable object can be called just like a Python type, but never with keyword arguments. |
Interop Type | Python Interpretation |
---|---|
null |
Only None . |
boolean |
Only subtypes of Python bool . Note that in contrast to Python semantics, Python bool is never also an interop number. |
number |
Only subtypes of int and float . |
string |
Only subtypes of str . |
array |
Any object with __getitem__ and __len__ methods, but not if it also has keys , values , and items methods (in the same way that dict does.) |
hash |
Only subtypes of dict . |
members |
Any Python object. Note that the rules for readable/writable are a bit ad-hoc, since checking that is not part of the Python MOP. |
iterable |
Any Python object that has __iter__ or a __getitem__ methods. |
iterator |
Any Python object with a __next__ method. |
exception |
Any Python BaseException subtype. |
MetaObject |
Any Python type . |
executable |
Any Python object with a __call__ method. |
instantiable |
Any Python type . |
It is possible to extend the interoperability protocol directly from Python via a simple API defined in the polyglot
module.
The purpose of this API is to enable custom / user defined types to take part in the interop ecosystem.
This is particularly useful for external types which are not compatible by default with the interop protocol.
An example in this sense are the numpy
numeric types (for example, numpy.int32
) which are not supported by default by the interop protocol.
Function | Description |
---|---|
register_interop_behavior | Takes the receiver type as first argument. The remainder keyword arguments correspond to the respective interop messages. Not All interop messages are supported. |
get_registered_interop_behavior | Takes the receiver type as first argument. Returns the list of extended interop messages for the given type. |
@interop_behavior | Class decorator, takes the receiver type as only argument. The interop messages are extended via static methods defined in the decorated class (supplier). |
The majority (with some exceptions) of the interop messages are supported by the interop behavior extension API, as shown in the table below.
The naming convention for the register_interop_behavior
keyword arguments follows the snake_case naming convention, i.e. the interop fitsInLong
message
becomes fits_in_long
and so on. Each message can be extended with a pure python function (default keyword arguments, free vars and cell vars are not allowed) or a boolean constant.
The table below describes the supported interop messages:
Message | Extension argument name | Expected return type |
---|---|---|
isBoolean | is_boolean | bool |
isDate | is_date | bool |
isDuration | is_duration | bool |
isIterator | is_iterator | bool |
isNumber | is_number | bool |
isString | is_string | bool |
isTime | is_time | bool |
isTimeZone | is_time_zone | bool |
isExecutable | is_executable | bool |
fitsInBigInteger | fits_in_big_integer | bool |
fitsInByte | fits_in_byte | bool |
fitsInDouble | fits_in_double | bool |
fitsInFloat | fits_in_float | bool |
fitsInInt | fits_in_int | bool |
fitsInLong | fits_in_long | bool |
fitsInShort | fits_in_short | bool |
asBigInteger | as_big_integer | int |
asBoolean | as_boolean | bool |
asByte | as_byte | int |
asDate | as_date | 3-tuple with the following elements: (year : int, month : int, day : int) |
asDouble | as_double | float |
asDuration | as_duration | 2-tuple with the following elements: (seconds : long, nano_adjustment : long) |
asFloat | as_float | float |
asInt | as_int | int |
asLong | as_long | int |
asShort | as_short | int |
asString | as_string | str |
asTime | as_time | 4-tuple with the following elements: (hour : int, minute : int, second : int, microsecond : int) |
asTimeZone | as_time_zone | a string (the timezone) or int (utc delta in seconds) |
execute | execute | object |
readArrayElement | read_array_element | object |
getArraySize | get_array_size | int |
hasArrayElements | has_array_elements | bool |
isArrayElementReadable | is_array_element_readable | bool |
isArrayElementModifiable | is_array_element_modifiable | bool |
isArrayElementInsertable | is_array_element_insertable | bool |
isArrayElementRemovable | is_array_element_removable | bool |
removeArrayElement | remove_array_element | NoneType |
writeArrayElement | write_array_element | NoneType |
hasIterator | has_iterator | bool |
hasIteratorNextElement | has_iterator_next_element | bool |
getIterator | get_iterator | a python iterator |
getIteratorNextElement | get_iterator_next_element | object |
hasHashEntries | has_hash_entries | bool |
getHashEntriesIterator | get_hash_entries_iterator | a python iterator |
getHashKeysIterator | get_hash_keys_iterator | a python iterator |
getHashSize | get_hash_size | int |
getHashValuesIterator | get_hash_values_iterator | a python iterator |
isHashEntryReadable | is_hash_entry_readable | bool |
isHashEntryModifiable | is_hash_entry_modifiable | bool |
isHashEntryInsertable | is_hash_entry_insertable | bool |
isHashEntryRemovable | is_hash_entry_removable | bool |
readHashValue | read_hash_value | object |
writeHashEntry | write_hash_entry | NoneType |
removeHashEntry | remove_hash_entry | NoneType |
A simple register_interop_behavior
API is available to register interop behaviors for existing types:
import polyglot
import numpy
polyglot.register_interop_behavior(numpy.int32,
is_number=True,
fitsInByte=lambda v: -128 <= v < 128,
fitsInShort=lambda v: -0x8000 <= v < 0x8000
fitsInInt=True,
fitsInLong=True,
fitsInBigInteger=True,
asByte=int,
asShort=int,
asInt=int,
asLong=int,
asBigInteger=int,
)
The @interop_behavior
decorator may be more convenient when declaring more behaviors.
Interop message extension is achieved via static methods of the decorated class.
The names of the static methods are identical to the keyword names expected by register_interop_behavior
.
from polyglot import interop_behavior
import numpy
@interop_behavior(numpy.float64)
class Int8InteropBehaviorSupplier:
@staticmethod
def is_number(_):
return True
@staticmethod
def fitsInDouble(_):
return True
@staticmethod
def asDouble(v):
return float(v)
Both classes can then behave as expected when embedded:
import java.nio.file.Files;
import java.nio.file.Path;
import org.graalvm.polyglot.Context;
class Main {
public static void main(String[] args) {
try (var context = Context.create()) {
context.eval("python", Files.readString(Path.of("path/to/interop/behavior/script.py")));
assert context.eval("python", "numpy.float64(12)").asDouble() == 12.0;
assert context.eval("python", "numpy.int32(12)").asByte() == 12;
}
}
}