Type translations#
In order to communicate between Python and JavaScript, we “translate” objects
between the two languages. Depending on the type of the object we either
translate the object by implicitly converting it or by proxying it. By
“converting” an object we mean producing a new object in the target language
which is the equivalent of the object from the source language, for example
converting a Python string to the equivalent a JavaScript string. By “proxying”
an object we mean producing a special object in the target language that
forwards requests to the source language. When we proxy a JavaScript object into
Python, the result is a JsProxy
object. When we proxy a
Python object into JavaScript, the result is a PyProxy
object. A proxied
object can be explicitly converted using the explicit conversion methods
JsProxy.to_py()
and
PyProxy.toJs()
.
Python to JavaScript translations occur:
when returning the final expression from a
pyodide.runPython()
call,when passing arguments to a JavaScript function called from Python,
when returning the results of a Python function called from JavaScript,
when accessing an attribute of a
PyProxy
JavaScript to Python translations occur:
when passing arguments to a Python function called from JavaScript
when returning the result of a JavaScript function called from Python
when accessing an attribute of a
JsProxy
Memory Leaks and Python to JavaScript translations
Any time a Python to JavaScript translation occurs, it may create a
PyProxy
. To avoid memory leaks, you must store the PyProxy
and
destroy()
it when you are done with it. See
Calling Python objects from JavaScript for more info.
Round trip conversions#
Translating an object from Python to JavaScript and then back to Python is
guaranteed to give an object that is equal to the original object. Furthermore,
if the object is proxied into JavaScript, then translation back unwraps the
proxy, and the result of the round trip conversion is
the original object (in
the sense that they live at the same memory address).
Translating an object from JavaScript to Python and then back to JavaScript
gives an object that is ===
to the original object. Furthermore, if the object
is proxied into Python, then translation back unwraps the proxy, and the result
of the round trip conversion is the original object (in the sense that they live
at the same memory address). There are a few exceptions:
NaN
is converted toNaN
after a round trip butNaN !== NaN
,a
BigInt
will be converted to aNumber
after a round trip unless its absolute value is greater thanNumber.MAX_SAFE_INTEGER
(i.e., 2^53).
Implicit conversions#
We implicitly convert immutable types but not mutable types. This ensures that
mutable Python objects can be modified from JavaScript and vice-versa. Python
has immutable types such as tuple
and bytes
that have no
equivalent in JavaScript. In order to ensure that round trip translations yield
an object of the same type as the original object, we proxy tuple
and bytes
objects.
Python to JavaScript#
The following immutable types are implicitly converted from Python to JavaScript:
Python |
JavaScript |
---|---|
* An int
is converted to a Number
if the absolute value
is less than or equal to Number.MAX_SAFE_INTEGER
otherwise it is
converted to a BigInt
. (If the browser does not support
BigInt
then a Number
will be used instead. In this case,
conversion of large integers from Python to JavaScript is lossy.)
JavaScript to Python#
The following immutable types are implicitly converted from JavaScript to Python:
JavaScript |
Python |
---|---|
* A Number
is converted to an int
if the absolute value
is less than or equal to Number.MAX_SAFE_INTEGER
and its fractional
part is zero. Otherwise, it is converted to a float
.
Proxying#
Any of the types not listed above are shared between languages using proxies that allow methods and some operations to be called on the object from the other language.
Proxying from JavaScript into Python#
When most JavaScript objects are translated into Python a JsProxy
is
returned. The following operations are currently supported on a JsProxy
:
Python |
JavaScript |
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Note that each of these operations is only supported if the proxied JavaScript
object supports the corresponding operation. See the JsProxy API docs
for the rest of the methods supported on
JsProxy
. Some other code snippets:
for v in proxy:
# do something
is equivalent to:
for (let v of x) {
// do something
}
The dir()
method has been overloaded to return all keys on the
prototype chain of x
, so dir(x)
roughly translates to:
function dir(x) {
let result = [];
do {
result.push(...Object.getOwnPropertyNames(x));
} while ((x = Object.getPrototypeOf(x)));
return result;
}
As a special case, JavaScript Array
, HTMLCollection
, and
NodeList
are container types, but instead of using array.get(7)
to
get the 7th element, JavaScript uses array[7]
. For these cases, we translate:
Python |
JavaScript |
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If you need to access the fields in a JavaScript object, you must use
obj.field_name
or if the name of the field is not a valid Python identifier,
getattr(obj, "field name")
. If you want to access the fields of the object
like obj["field name"]
you can use
as_object_map()
:
from pyodide.code import run_js
obj = run_js(
"""
({
a: 7,
b: 9,
$c: 11
})
"""
)
obj_map = obj.as_object_map()
assert obj_map["$c"] == 11
Another special case comes from the fact that Python reserved words cannot be
used as attributes. For instance, Array.from()
and
Promise.finally()
cannot be directly accessed because they are Python
SyntaxError
s. Instead we access these attributes with Array.from_
and
Promise.finally_
. Similarly, to access from Python, o.from_
you have to use
o.from__
with two underscores (since a single underscore is used for
o.from
). This is reflected in the dir
of a JsProxy
:
from pyodide.code import run_js
o = run_js("({finally: 1, return: 2, from: 3, from_: 4})")
assert set(dir(o)) == {"finally_", "return_", "from_", "from__"}
Proxying from Python into JavaScript#
When most Python objects are translated to JavaScript a
PyProxy
is produced.
Fewer operations can be overloaded in JavaScript than in Python, so some
operations are more cumbersome on a PyProxy
than on a
JsProxy
. The following operations are supported:
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Python |
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Memory Leaks and PyProxy
Make sure to destroy PyProxies when you are done with them to avoid memory leaks.
let foo = pyodide.globals.get('foo');
foo();
foo.destroy();
foo(); // throws Error: Object has already been destroyed
Explicit Conversion of Proxies#
Python to JavaScript#
Explicit conversion of a PyProxy
into a native
JavaScript object is done with the toJs()
method.
You can also perform such a conversion in Python using
to_js()
which behaves in much the same way. By default,
the toJs()
method does a recursive “deep”
conversion, to do a shallow conversion use proxy.toJs({depth : 1})
. In
addition to the normal type conversion, the
toJs()
method performs the following explicit
conversions:
Python |
JavaScript |
---|---|
* Examples of buffers include bytes
objects and numpy
Array objects.
If you need to convert dict
instead to Object
, you can
pass Object.fromEntries()
as the dict_converter
argument:
proxy.toJs({dict_converter : Object.fromEntries})
.
In JavaScript, Map
and Set
keys are compared using
object identity unless the key is an immutable type (meaning a
String
, a Number
, a BigInt
, a
Boolean
, undefined
, or null
). On the other
hand, in Python, dict
and set
keys are compared using
deep equality. If a key is encountered in a dict
or set
that would have different semantics in JavaScript than in Python, then a
ConversionError
will be thrown.
See Using Python Buffer objects from JavaScript for the behavior of toJs()
on buffers.
Memory Leaks and toJs
The toJs()
method can create many proxies at arbitrary
depth. It is your responsibility to manually destroy()
these proxies if you wish to avoid memory leaks. The pyproxies
argument to
toJs()
is designed to help with this:
let pyproxies = [];
proxy.toJs({pyproxies});
// Do stuff
// pyproxies contains the list of proxies created by `toJs`. We can destroy them
// when we are done with them
for(let px of pyproxies){
px.destroy();
}
proxy.destroy();
As an alternative, if you wish to assert that the object should be fully
converted and no proxies should be created, you can use
proxy.toJs({create_proxies : false})
. If a proxy would be created, a
ConversionError
is raised instead.
JavaScript to Python#
Explicit conversion of a JsProxy
into a native Python
object is done with the JsProxy.to_py()
method. By default, the to_py()
method does a
recursive “deep” conversion, to do a shallow conversion use
proxy.to_py(depth=1)
. The to_py()
method
performs the following explicit conversions:
JavaScript |
Python |
---|---|
* to_py()
will only convert an Object
into a dictionary if its constructor is Object
, otherwise the object
will be left alone. Example:
class Test {};
window.x = { "a" : 7, "b" : 2};
window.y = { "a" : 7, "b" : 2};
Object.setPrototypeOf(y, Test.prototype);
pyodide.runPython(`
from js import x, y
# x is converted to a dictionary
assert x.to_py() == { "a" : 7, "b" : 2}
# y is not a "Plain Old JavaScript Object", it's an instance of type Test so it's not converted
assert y.to_py() == y
`);
In JavaScript, Map
and Set
keys are compared using
object identity unless the key is an immutable type (meaning a
String
, a Number
, a BigInt
, a
Boolean
, undefined
, or null
). On the other
hand, in Python, dict
and set
keys are compared using
deep equality. If a key is encountered in a Map
or Set
that would have different semantics in Python than in JavaScript, then a
ConversionError
will be thrown. Also, in JavaScript,
true !== 1
and false !== 0
, but in Python, True == 1
and False == 0
.
This has the result that a JavaScript map can use true
and 1
as distinct
keys but a Python dict
cannot. If the JavaScript map contains both
true
and 1
a ConversionError
will be thrown.
Functions#
Calling Python objects from JavaScript#
If a Python object is callable, the proxy will be callable too. The arguments
will be translated from JavaScript to Python as appropriate, and the return
value will be translated from JavaScript back to Python. If the return value is
a PyProxy
, you must explicitly destroy it or else it will be leaked.
An example:
let test = pyodide.runPython(`
def test(x):
return [n*n for n in x]
test
`);
let result_py = test([1,2,3,4]);
// result_py is a PyProxy of a list.
let result_js = result_py.toJs();
// result_js is the array [1, 4, 9, 16]
result_py.destroy();
If a function is intended to be used from JavaScript, you can use
to_js()
on the return value. This prevents the return
value from leaking without requiring the JavaScript code to explicitly destroy
it. This is particularly important for callbacks.
let test = pyodide.runPython(`
from pyodide.ffi import to_js
def test(x):
return to_js([n*n for n in x])
test
`);
let result = test([1,2,3,4]);
// result is the array [1, 4, 9, 16], nothing needs to be destroyed.
If you need to use a key word argument, use callKwargs()
. The
last argument should be a JavaScript object with the key value arguments.
let test = pyodide.runPython(`
from pyodide.ffi import to_js
def test(x, *, offset):
return to_js([n*n + offset for n in x])
to_js(test)
`);
let result = test.callKwargs([1,2,3,4], { offset : 7});
// result is the array [8, 12, 16, 23]
Calling JavaScript functions from Python#
What happens when calling a JavaScript function from Python is a bit more complicated than calling a Python function from JavaScript. If there are any keyword arguments, they are combined into a JavaScript object and used as the final argument. Thus, if you call:
f(a=2, b=3)
then the JavaScript function receives one argument which is a JavaScript object
{a : 2, b : 3}
.
When a JavaScript function is called, if the return value not a
Promise
, a Generator
, or an AsyncGenerator
,
any arguments that are PyProxies that were created in the process of argument
conversion are also destroyed. If the result is a
PyProxy
it is also destroyed.
As a result of this, if a PyProxy
is persisted to be
used later, then it must either be copied using copy()
in
JavaScript, or it must be created with create_proxy()
or
create_once_callable()
. If it’s only going to be called
once use create_once_callable()
:
from pyodide import create_once_callable
from js import setTimeout
def my_callback():
print("hi")
setTimeout(create_once_callable(my_callback), 1000)
If it’s going to be called many times use create_proxy()
:
from pyodide import create_proxy
from js import document
def my_callback():
print("hi")
proxy = pyodide.create_proxy(my_callback)
document.body.addEventListener("click", proxy)
# ...
# make sure to hold on to proxy
document.body.removeEventListener("click", proxy)
proxy.destroy()
When a JavaScript function returns a Promise
(for example, if the
function is an async function), it is assumed that the Promise
is
going to do some work that uses the arguments of the function, so it is not safe
to destroy them until the Promise
resolves. In this case, the
proxied function returns a Python Future
instead of the
original Promise
. When the Promise
resolves, the result
is converted to Python and the converted value is used to resolve the
Future
. Then if the result is a
PyProxy
it is destroyed. Any PyProxies created in
converting the arguments are also destroyed at this point.
Similarly, if the return value is a Generator
or
AsyncGenerator
, then the arguments (and all values sent to the
generator) are kept alive until it is exhausted, or until
close()
is called.
Buffers#
Using JavaScript Typed Arrays from Python#
JavaScript ArrayBuffer
and TypedArray
objects are
proxied into Python. Python can’t directly access arrays if they are outside the
WASM heap, so it’s impossible to directly use these proxied buffers as Python
buffers. You can convert such a proxy to a Python memoryview
using
the to_py()
api. This makes it easy to correctly convert the array to a Numpy
array using numpy.asarray()
:
self.jsarray = new Float32Array([1,2,3, 4, 5, 6]);
pyodide.runPython(`
from js import jsarray
array = jsarray.to_py()
import numpy as np
numpy_array = np.asarray(array).reshape((2,3))
print(numpy_array)
`);
After manipulating numpy_array
you can assign the value back to
jsarray
using assign()
:
pyodide.runPython(`
numpy_array[1,1] = 77
jsarray.assign(a)
`);
console.log(jsarray); // [1, 2, 3, 4, 77, 6]
The assign()
and
assign_to()
methods can be used to assign a
JavaScript buffer from / to a Python buffer which is appropriately sized and
contiguous. The assignment methods will only work if the data types match, the
total length of the buffers match, and the Python buffer is contiguous.
Using Python Buffer objects from JavaScript#
Python objects supporting the Python Buffer
protocol are proxied into
JavaScript. The data inside the buffer can be accessed via the
toJs()
method or the
getBuffer()
method. The
toJs()
API copies the buffer into JavaScript,
whereas the getBuffer()
method allows low level
access to the WASM memory backing the buffer. The
getBuffer()
API is more powerful but requires
care to use correctly. For simple use cases the
toJs()
API should be preferred.
If the buffer is zero or one-dimensional, then
toJs()
will in most cases convert it to a single
TypedArray
. However, in the case that the format of the buffer is
's'
, we will convert the buffer to a string and if the format is '?'
we will
convert it to an Array
of booleans.
If the dimension is greater than one, we will convert it to a nested JavaScript array, with the innermost dimension handled in the same way we would handle a 1d array.
An example of a case where you would not want to use the
toJs()
method is when the buffer is bitmapped
image data. If for instance you have a 3d buffer shaped 1920 x 1080 x 4, then
toJs()
will be extremely slow. In this case you
could use getBuffer()
. On the other hand, if you
have a 3d buffer shaped 1920 x 4 x 1080, the performance of
toJs()
will most likely be satisfactory.
Typically, the innermost dimension won’t matter for performance.
The getBuffer()
method can be used to retrieve a reference to
a JavaScript typed array that points to the data backing the Python object,
combined with other metadata about the buffer format. The metadata is suitable
for use with a JavaScript ndarray library if one is present. For instance, if
you load the JavaScript ndarray package, you
can do:
let proxy = pyodide.globals.get("some_numpy_ndarray");
let buffer = proxy.getBuffer();
proxy.destroy();
try {
if (buffer.readonly) {
// We can't stop you from changing a readonly buffer, but it can cause undefined behavior.
throw new Error("Uh-oh, we were planning to change the buffer");
}
let array = new ndarray(
buffer.data,
buffer.shape,
buffer.strides,
buffer.offset,
);
// manipulate array here
// changes will be reflected in the Python ndarray!
} finally {
buffer.release(); // Release the memory when we're done
}
Errors#
All entrypoints and exit points from Python code are wrapped in JavaScript try
blocks. At the boundary between Python and JavaScript, errors are caught,
converted between languages, and rethrown.
JavaScript errors are wrapped in a JsException
.
Python exceptions are converted to a PythonError
.
At present if an exception crosses between Python and JavaScript several times,
the resulting error message won’t be as useful as one might hope.
In order to reduce memory leaks, the PythonError
has a
formatted traceback, but no reference to the original Python exception. The
original exception has references to the stack frame and leaking it will leak
all the local variables from that stack frame. The actual Python exception will
be stored in sys.last_value
so if you need access to it (for instance
to produce a traceback with certain functions filtered out), use that.
Be careful Proxying Stack Frames
If you make a PyProxy
of sys.last_value
, you should be especially
careful to destroy()
it when you are done with it, or
you may leak a large amount of memory if you don’t.
The easiest way is to only handle the exception in Python:
pyodide.runPython(`
def reformat_exception():
from traceback import format_exception
# Format a modified exception here
# this just prints it normally but you could for instance filter some frames
return "".join(
format_exception(sys.last_type, sys.last_value, sys.last_traceback)
)
`);
let reformat_exception = pyodide.globals.get("reformat_exception");
try {
pyodide.runPython(some_code);
} catch(e){
// replace error message
e.message = reformat_exception();
throw e;
}
Importing Objects#
It is possible to access objects in one language from the global scope in the other language. It is also possible to create custom namespaces and access objects on the custom namespaces.
Importing Python objects into JavaScript#
A Python global variable in the __main__
global scope can be imported into
JavaScript using the pyodide.globals.get()
method. Given the
name of the Python global variable, it returns the value of the variable
translated to JavaScript.
let x = pyodide.globals.get("x");
As always, if the result is a PyProxy
and you care about not leaking the
Python object, you must destroy it when you are done. It’s also possible to set
values in the Python global scope with pyodide.globals.set()
or remove them with pyodide.globals.delete()
:
pyodide.globals.set("x", 2);
pyodide.runPython("print(x)"); // Prints 2
If you execute code with a custom globals dictionary, you can use a similar approach:
let my_py_namespace = pyodide.globals.get("dict")();
pyodide.runPython("x=2", my_py_namespace);
let x = my_py_namespace.get("x");
To access a Python module from JavaScript, use pyimport()
:
let sys = pyodide.pyimport("sys");
Importing JavaScript objects into Python#
JavaScript objects in the globalThis
global scope can be imported
into Python using the js
module.
When importing a name from the js
module, the js
module looks up JavaScript
attributes of the globalThis
scope and translates the JavaScript
objects into Python.
import js
js.document.title = 'New window title'
from js.document.location import reload as reload_page
reload_page()
You can also assign to JavaScript global variables in this way:
pyodide.runPython("js.x = 2");
console.log(window.x); // 2
You can create your own custom JavaScript modules using
pyodide.registerJsModule()
and they will behave like the js
module except
with a custom scope:
let my_js_namespace = { x : 3 };
pyodide.registerJsModule("my_js_namespace", my_js_namespace);
pyodide.runPython(`
from my_js_namespace import x
print(x) # 3
my_js_namespace.y = 7
`);
console.log(my_js_namespace.y); // 7
If the JavaScript object’s name is a reserved Python keyword, the setattr()
function can be used to access the object by name within the js module::
lambda = (x) => {return x + 1};
//'from js import lambda' will cause a Syntax Error, since 'lambda' is a Python reserved keyword. Instead:
pyodide.runPython(`
import js
js_lambda = getattr(js, 'lambda')
print(js_lambda(1))
`);
If a JavaScript object has a property that is a reserved Python keyword, the setattr()
and getattr()
function can be used to access that property by name:
people = {global: "lots and lots"};
//Trying to access 'people.global' will raise a Syntax Error, since 'global' is a Python reserved keyword. Instead:
pyodide.runPython(`
from js import people
setattr(people, 'global', 'even more')
print(getattr(people, 'global'))
`);