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#pythonjs
PythonJS is a Python to Javascript and Dart translator written in Python, created by Amirouche Boubekki and Brett Hartshorn, currently maintained and developed by Brett. It features: list comprehensions, classes, multiple inheritance, operator overloading, function and class decorators, generator functions, HTML DOM, and easily integrates with JavaScript and external JavaScript libraries. The generated code works in the Browser and in NodeJS. Note: the Dart backend is still very experimental.
PythonJS allows you to select which features you need for each section of your code, where you need performance you can disable operator overloading, and other slow operations. Features can be switched off and on for blocks of code using pythonjs.configure() or the special with statements and decorators described below. When PythonJS is run in fastest mode (javascript mode) it beats PyPy in the Richards, and N-Body benchmarks.
N-Body benchmark, PythonJS in javascript mode has similar performance to Dart.
Using PythonJS you can quickly port your server side code to using NodeJS. If you are using Tornado, porting is even simpler because we have written a compatibility layer that emulates the Tornado API and hides the NodeJS internal modules.
Translation to JavaScript is done in two steps:
+------------+ +-----------------+ +------------+ ¦ .py source ¦--->¦ pythonjs subset ¦--->¦ .js source ¦ +------------+ +-----------------+ +------------+
First, the script walks the AST tree of Python source and translates it into the subset of Python called pythonjs. This reduced subset is still valid Python code, and its AST gets parsed again in the second translation phase that converts it into final JavaScript form.
Get Source Code:
git clone https://github.com/PythonJS/PythonJS.git
Translate Your Script:
cd PythonJS/pythonjs ./translator.py myscript1.py myscript2.py > ~/myapp.js
The translator.py script can take in multiple Python scripts, these are appended together, and translated into a single JavaScript. The output is printed to stdout. If no command line arguments is given, then translator.py takes input from stdin.
PythonJS has three main types of functions: "normal", "fastdef", and "javascript".
By default a function is "normal" and fully emulates the Python standard, it allows for: arguments, keyword args with defaults, variable length arguments (*args) and variable length keyword args (**kwargs). Functions that are "normal" also have special logic that allows them to be called from external JavaScript like normal JavaScript functions (keyword args become normal positional arguments when called from JavaScript). Calling "normal" functions is slow because of this overhead, when you need faster function calls you can use "fastdef" or "javascript".
Functions decorated with @fastdef, or inside a "with fastdef:" block become "fastdef" type functions. This makes calling them much faster, but they do not support variable length arguments (*args) or variable length keyword args (**kwargs). Another limitation is that when called from external JavaScript you must pack args into an Array as the first argument, and pack keyword arguments into an Object as the second argument.
Functions decorated with @javascript, or inside a "with javascript:" block, or following the call: "pythonjs.configure(javascript=True)" become "javascript" type functions, these offer the highest calling speed. They do not support *args or **kwargs. When called from external JavaScript, keyword arguments are not given by name, they become positional arguments that default to the default value if undefined. When called from within PythonJS code, they need to be called from inside a "with javascript:" block, or following the call pythonjs.configure(javascript=True) that sets all following code to be in "javascript" mode.
Example:
pythonjs.configure( javascript=True )
def myfunc(x,y,z, a=1,b=2,c=3):
print x,y,z,a,b,c
Example JavaScript Translation:
myfunc = function(x, y, z, a, b, c) {
if (a === undefined) a = 1;
if (b === undefined) b = 2;
if (c === undefined) c = 3;
console.log(x, y, z, a, b, c);
}
PythonJS has two types of classes: "normal" and "javascript". By default classes are "normal" and support operator overloading and properties. Calling methods on a "javascript" class is much faster than method calls on a "normal" class, but follow the same rules as described above for "javascript" type functions. Both class types can be used from external JavaScript, the only difference is that instances of a "normal" class can pass their methods directly as arguments to a function that will use the method as a callback - even if that external function depends on the context of "this". Whereas instances of a "javascript" class can not directly pass their methods as arguments, because they depend on the calling context of "this" - if you are familiar with JavaScript this comes as no surprise.
Example:
pythonjs.configure( javascript=True )
class A:
def __init__(self, x,y,z):
self.x = x
self.y = y
self.z = z
def foo(self, w):
return self.x + w
Example JavaScript Translation:
A = function(x, y, z) {
A.__init__(this, x,y,z);
}
A.prototype.__init__ = function(x, y, z) {
this.x=x;
this.y=y;
this.z=z;
}
A.__init__ = function () { return A.prototype.__init__.apply(arguments[0], Array.prototype.slice.call(arguments,1)) };
A.prototype.foo = function(w) {
return (this.x + w);
}
A.foo = function () { return A.prototype.foo.apply(arguments[0], Array.prototype.slice.call(arguments,1)) };
In the example above, you might be wondering why in the JavaScript translation, is the class A constructor calling "A.__init__(this, x,y,z)", and why is the __init__ method assigned A.prototype and then wrapped and assigned to A.__init__. This is done so that subclasses are able to override their parent's methods, but still have a way of calling them, an example that subclasses A will make this more clear.
Example:
class B( A ):
def __init__(self, w):
A.__init__(self, 10, 20, 30)
self.w = w
Example JavaScript Translation:
B = function(w) {
B.__init__(this, w);
}
B.prototype.__init__ = function(w) {
A.__init__(this,10,20,30);
this.w=w;
}
B.__init__ = function () { return B.prototype.__init__.apply(arguments[0], Array.prototype.slice.call(arguments,1)) };
for (var n in A.prototype) { if (!(n in B.prototype)) { B.prototype[n] = A.prototype[n] }};
The above output Javascript shows how the constructor for B calls B.__init__ which then calls B.prototype.__init__. B.prototype.__init__ calls A.__init__ passing "this" as the first argument. This emulates in JavaScript how unbound methods work in Python. When using the Dart backend, the output is different but the concept is the same - static "class methods" are created that implement the method body, the instance methods are just short stubs that call the static "class methods".
Example Dart Translation:
class B implements A {
var y;
var x;
var z;
var w;
B(w) {B.__init__(this,w);}
static void __init__(self, w) {
A.__init__(self,10,20,30);
self.w=w;
}
foo(w) { return A.__foo(this,w); }
}
Above the method "foo" calls the static class method A.__foo. Note that the static class methods are automatically prefixed with "__".
Multiple inheritance is fully supported for both JavaScript and Dart backends. When using the Dart backend it will generate stub-methods that call static class methods that are prefixed with "__". Methods that the subclass extends can call: ParentClassName.some_method(self) and this will be translated into: ParentClassName.__some_method(this)
Example:
class A:
def foo(self):
print 'foo'
class B:
def bar(self):
print 'bar'
class C( A, B ):
def call_foo_bar(self):
print 'call_foo_bar in subclass C'
self.foo()
self.bar()
## extend foo ##
def foo(self):
A.foo(self)
print 'foo extended'
Example Dart Translation:
class A {
foo() { return A.__foo(this); }
static __foo(self) {
print("foo");
}
}
class B {
bar() { return B.__bar(this); }
static __bar(self) {
print("bar");
}
}
class C implements A, B {
call_foo_bar() { return C.__call_foo_bar(this); }
static __call_foo_bar(self) {
print("call_foo_bar in subclass C");
self.foo();
self.bar();
}
foo() { return C.__foo(this); }
static __foo(self) {
A.__foo(self);
print("foo extended");
}
bar() { return B.__bar(this); }
}
Functions that use the yield keyword are generator functions. They allow you to quickly write complex iterables. PythonJS supports simple generator functions that have a single for loop, and up to three yield statements. The first yield comes before the for loop, and the final yield comes after the for loop. The compiler will translate your generator function into a simple class with state-machine. This implementation bypasses using the native JavaScript yield keyword, and ensures that your generator function can work in all web browsers.
Instances of the generator function will have a next method. Using a for loop to iterate over a generator function will automatically call its next method.
Example:
def fib(n):
yield 'hello'
a, b = 0, 1
for x in range(n):
yield a
a,b = b, a+b
yield 'world'
def test():
for n in fib(20):
print n
Example Output:
fib = function(n) {
this.n = n;
this.__head_yield = "hello";
this.__head_returned = 0;
var __r_0;
__r_0 = [0, 1];
this.a = __r_0[0];
this.b = __r_0[1];
this.__iter_start = 0;
this.__iter_index = 0;
this.__iter_end = this.n;
this.__done__ = 0;
}
fib.prototype.next = function() {
if (( this.__head_returned ) == 0) {
this.__head_returned = 1;
return this.__head_yield;
} else {
if (( this.__iter_index ) < this.__iter_end) {
__yield_return__ = this.a;
var __r_1;
__r_1 = [this.b, (this.a + this.b)];
this.a = __r_1[0];
this.b = __r_1[1];
this.__iter_index += 1
return __yield_return__;
} else {
this.__done__ = 1;
__yield_return__ = "world";
return __yield_return__;
}
}
}
test = function(args, kwargs) {
var __iterator__, n;
var n, __generator__;
__generator__ = new fib(20);
while(( __generator__.__done__ ) != 1) {
n = __generator__.next();
console.log(n);
}
}
PythonJS has two primary modes you can write code in: "python" and "javascript". The default mode is "python", you can mark sections of your code to use either mode with "pythonjs.configure(javascript=True/False)" or nesting blocks inside "with python:" or "with javascript:". The "javascript" mode can be used for sections of code where performance is a major concern. When in "javascript" mode the literal "[]" syntax will return a JavaScript Array instead of a PythonJS list, and a literal "{}" returns a JavaScript Object instead of a PythonJS dict. In both modes you can directly call external JavaScript functions, its only faster in "javascript" mode because function calls are direct without any wrapping.
HTML DOM Example:
<html><head>
<script src="pythonscript.js"></script>
<script type="text/python">
count = 0
def mycallback():
global count
print( con.getAttribute('id') )
btn = document.getElementById('mybutton')
btn.firstChild.nodeValue = 'COUNTER:'+count
count += 1
a = 'hello'
b = 'world'
def test():
con = document.createElement( 'div' )
con.setAttribute('id', 'mydiv')
document.body.appendChild(con)
txt = document.createTextNode( a+b )
con.appendChild(txt)
window.setInterval( mycallback, 1000 )
</script>
</head><body>
<button id="mybutton" onclick="test()">click me</button>
</body>
</html>
PythonJS allows you to call any JavaScript function directly by wrapping it at runtime. Attributes of JavaScript objects are also returned directly, like document.body. This allows you to use the HTML DOM API just as you would in normal JavaScript.
If the JavaScript function you are calling takes a JavaScript Object as the last argument you can call the function using keyword arguments and they will be automatically converted to a JavaScript Object. Any dictionaries or lists you pass to a JavaScript function will be converted to: Array or Object.
Example:
<script type="text/javascript">
function js_function( a,b,c, options ) {
console.log('abc', a,b,c);
console.log( c[0] ); // mylist was automatically converted to an Array
console.log( c[1] );
return options.x + options.y + options.z;
}
</script>
<script type="text/python">
def test():
mylist = ['hello', 'world']
print js_function( 'A','B', mylist, x=1, y=2, z=3 )
</script>
There are times that JavaScript needs to be directly inlined into PythonJS code, this is done with the special 'JS([str])' function that takes a string literal as its only argument. The compiler will insert the string directly into the final output JavaScript.
JS Example:
JS("var arr = new Array()")
JS("var ob = new Object()")
JS("ob['key'] = 'value'")
if JS("Object.prototype.toString.call( arr ) === '[object Array]'"):
JS("arr.push('hello world')")
JS("arr.push( ob )")
In the example above we create a new JavaScript Array. Notice that the if-statement above has a condition that is inlined JavaScript. Lets take a look at two alternative ways this can be rewritten.
JSArray, JSObject, and instanceof:
arr = JSArray() ob = JSObject() if instanceof(arr, Array): arr.push('hello world') arr.push( ob )
The special function JSArray will create a new JavaScript Array object, and JSObject creates a new JavaScript Object. The 'instanceof' function will be translated into using the 'instanceof' JavaScript operator. At the end, arr.push is called without wrapping it in JS(), this is allowed because from PythonJS, we can directly call JavaScript functions by dynamically wrapping it at runtime.
This code is more clear than before, but the downside is that the calls to arr.push will be slower because it gets wrapped at runtime. To have fast and clear code we need to use the final method below, 'with javascript'
with javascript:
with javascript: arr = [] ob = {} if instanceof(arr, Array): arr.push('hello world') arr.push( ob )
The "with javascript:" statement can be used to mark a block of code as being direct JavaScript. The compiler will basically wrap each line it can in JS() calls. The calls to arr.push will be fast because there is no longer any runtime wrapping. Instead of using JSArray and JSObject you just use the literal notation to create them.
PythonJS functions can be used as callbacks in Javascript code, there are no special calling conventions that you need to worry about. Simply define a function in PythonJS and call it from JavaScript. Note that if your PythonJS function uses keyword arguments, you can use them as a normal positional arguments.
Example:
# PythonJS
def my_pyfunction( a,b,c, optional='some default'):
print a,b,c, optional
// javascript
my_pyfunction( 1,2,3, 'my kwarg' );
Calling PythonJS methods is also simple, you just need to create an instance of the class in PythonJS and then pass the method to a JavaScript function, or assign it to a new variable that the JavaScript code will use. PythonJS takes care of wrapping the method for you so that "self" is bound to the method, and is callable from JavaScript.
Example:
// javascript
function js_call_method( method_callback ) {
method_callback( 1,2,3 )
}
# PythonJS
class A:
def my_method(self, a,b,c):
print self, a,b,c
self.a = a
self.b = b
self.c = c
a = A()
js_call_method( a.my_method )
If you are doing something complex like deep integration with an external JavaScript library, the above technique of passing each method callback to JavaScript might become inefficient. If you want to pass the PythonJS instance itself and have its methods callable from JavaScript, you can do this now simply by passing the instance.
Example:
// javascript
function js_function( pyob ) {
pyob.foo( 1,2,3 )
pyob.bar( 4,5,6 )
}
# PythonJS
class A:
def foo(self, a,b,c):
print a+b+c
def bar(self, a,b,c):
print a*b*c
a = A()
js_function( a )
If you are going beyond simple integration with an external JavaScript library, and perhaps want to change the way it works on a deeper level, you can modify JavaScript prototypes from PythonJS using some special syntax.
Example:
with javascript:
@String.prototype.upper
def func():
return this.toUpperCase()
@String.prototype.lower
def func():
return this.toLowerCase()
@String.prototype.index
def func(a):
return this.indexOf(a)
The above example shows how we modify the String type in JavaScript to act more like a Python string type. The functions must be defined inside a "with javascript:" block, and the decorator format is: [class name].prototype.[function name]
The above techniques provide all the tools you will need to interact with JavaScript code, and easily write wrapper code in PythonJS. The last tool you will need, is a standard way of creating JavaScript objects, storing a reference to the instance, and later passing the instance to wrapped JavaScript function. In JavaScript objects are created with the new keyword, in PythonJS you can use the new() function instead. To store an instance created by new(), you should assign it to self like this: self[...] = new( SomeJavaScriptClass() ).
If you have never seen ... syntax in Python it is the rarely used Ellipsis syntax, we have hijacked it in PythonJS as a special case to assign something to a hidden attribute. The builtin types: tuple, list, dict, etc, are wrappers that internally use JavaScript Arrays or Objects, to get to these internal objects you use the Ellipsis syntax. The following example shows how the THREE.js binding wraps the Vector3 object and combines operator overloading.
Example:
class Vector3:
def __init__(self, x=0, y=0, z=0, object=None ):
if object:
self[...] = object
else:
with javascript:
self[...] = new(THREE.Vector3(x,y,z))
@property
def x(self):
with javascript: return self[...].x
@x.setter
def x(self, value):
with javascript: self[...].x = value
@property
def y(self):
with javascript: return self[...].y
@y.setter
def y(self, value):
with javascript: self[...].y = value
@property
def z(self):
with javascript: return self[...].z
@z.setter
def z(self, value):
with javascript: self[...].z = value
def set(self, x,y,z):
self[...].set(x,y,z)
def add(self, other):
assert isinstance(other, Vector3)
self.set( self.x+other.x, self.y+other.y, self.z+other.z )
return self
def addScalar(self, s):
self.set( self.x+s, self.y+s, self.z+s )
return self
def __add__(self, other):
if instanceof(other, Object):
assert isinstance(other, Vector3)
return Vector3( self.x+other.x, self.y+other.y, self.z+other.z )
else:
return Vector3( self.x+other, self.y+other, self.z+other )
def __iadd__(self, other):
if instanceof(other, Object):
self.add( other )
else:
self.addScalar( other )
By default PythonJS functions have runtime call checking that ensures you have called the function with the required number of arguments, and also checks to see if you had called the function from JavaScript - and if so adapt the arguments. This adds some overhead each time the function is called, and will generally be about 15 times slower than normal Python. When performance is a concern you can decorate functions that need to be fast with @fastdef, or use the with fastdef: with statement. Note that functions that do not have arguments are always fast. Using fastdef will make each call to your function 100 times faster, so if you call the same function many times in a loop, it is a good idea to decorate it with @fastdef.
Example:
@fastdef
def f1( a, b, c ):
return a+b+c
with fastdef:
def f2( a,b,c, x=1,y=2,z=3):
return a+b+c+x+y+z
If you need to call a fastdef function from JavaScript you will need to call it with arguments packed into an array as the first argument, and keyword args packed into an Object as the second argument.
Example:
// javascript
f2( [1,2,3], {x:100, y:200, z:300} );
If you need fast function that is callable from javascript without packing its arguments like above, you can use the @javascript decorator, or nest the function inside a with javascript: statement.
Example:
@javascript
def f( a,b,c, x=1, y=2, z=3 ):
return a+b+c+x+y+z
// javascript
f( 1,2,3, 100, 200, 300 );
PythonJS can also be used to write server side software using NodeJS. You can use the nodejs.py helper script to translate your python script and run it in NodeJS. This has been tested with NodeJS v0.10.22.
Example:
cd PythonJS ./nodejs.py myscript.py
The directory PythonJS/nodejs/bindings contains wrappers for using NodeJS modules. Some of these wrappers emulate parts of Pythons standard library, like: os, sys, io, and subprocess. The example below imports the fake io and sys libraries, and prints the contents of a file passed as the last command line argument to nodejs.py.
Example:
from nodejs.io import * from nodejs.sys import * path = sys.argv[ len(sys.argv)-1 ] f = open( path, 'rb' ) print f.read()
PythonJS includes two test servers that run the HTML tests in PythonJS/tests. Both of these servers are written using the Tornado API. The NodeJS version is a port of the original test server adapted to work with the Tornado compatible binding.
Install Modules:
sudo npm install -g mime sudo npm install -g ws
Run NodeJS Server:
cd PythonJS ./nodejs.py nodejs/tests/tornado-demo-server.py
Install Tornado for Python3:
wget https://pypi.python.org/packages/source/t/tornado/tornado-3.1.1.tar.gz tar xvf tornado-3.1.1.tar.gz cd tornado-3.1.1 python3 setup.py build sudo python3 setup.py install
Run Python Server:
cd PythonJS/tests ./server.py
Run Python Server in Dart Mode:
./server.py --dart
In Dart mode any test page you visit will be translated to Dart, and then converted back to JavaScript using "dart2js". You need to download the Dart SDK and make sure "dart2js" is located in: ~/dart/dart-sdk/bin/
After running one of the test servers above, open a web browser and go to: http://localhost:8080
The test server dynamically compiles Python into JavaScript, this greatly speeds up the testing and development process. Any html file you place in the PythonJS/tests directory will become available as a new web-page. When this web-page is requested the server will parse the html and check all the <script> tags for external or embedded Python, and dynamically convert it to JavaScript.
External Python Scripts:
<head> <script src="bindings/three.py"></script> </head>
The server knows that the above script needs to be dynamically compiled to JavaScript because the script is located in the "bindings" directory and the file name ends with ".py"
Embedded Python Scripts:
<body> <script type="text/python"> from three import * v1 = Vector3( x=1, y=2, z=3 ) v2 = Vector3( x=4, y=5, z=6 ) v3 = v1 + v2 </script> </body>
The server knows that above is an embedded Python script because the script tag has its type attribute set to "text/python". The server will compile and replace the Python code with JavaScript, change the type attribute to be "text/javascript", and serve the page to the client.
The syntax "from three import *" tells the compiler to load static type information about the previously compiled binding "three.py" into the compilers namespace, this is required because three.py uses operator overloading to wrap the THREE.js API. PythonJS programs are explicitly and implicitly statically typed to allow for operator overloading and optimizations.
