PythonMonkey is a Mozilla SpiderMonkey JavaScript engine embedded into the Python Runtime, using the Python engine to provide the Javascript host environment.

We feature JavaScript Array and Object methods implemented on Python List and Dictionaries using the cPython C API, and the inverse using the Mozilla Firefox Spidermonkey JavaScript C++ API.

This project has reached MVP as of September 2024. It is under maintenance by Distributive.

External contributions and feedback are welcome and encouraged.

$ pip install pythonmonkey

from pythonmonkey import eval as js_eval

js_eval("console.log")('hello, world')

• Fast and memory-efficient
• Make writing code in either JS or Python a developer preference
• Use JavaScript libraries from Python
• Use Python libraries from JavaScript
• The same process runs both JavaScript and Python VirtualMachines - no serialization, pipes, etc
• Python Lists and Dicts behave as Javacript Arrays and Objects, and vice-versa, fully adapting to the given context.

• Strings share immutable backing stores whenever possible (when allocating engine choses UCS-2 or Latin-1 internal string representation) to keep memory consumption under control, and to make it possible to move very large strings between JavaScript and Python library code without memory-copy overhead.
• TypedArrays share mutable backing stores.
• JS objects are represented by Python dicts through a Dict subclass for optimal compatibility. Similarly for JS arrays and Python lists.
• JS Date objects are represented by Python datetime.datetime objects
• Intrinsics (boolean, number, null, undefined) are passed by value
• JS Functions are automatically wrapped so that they behave like Python functions, and vice-versa
• Python Lists are represented by JS true arrays and support all Array methods through a JS API Proxy. Similarly for Python Dicts and JS objects.

• [done] JS instrinsics coerce to Python intrinsics
• [done] JS strings coerce to Python strings
• [done] JS objects coerce to Python dicts [own-properties only]
• [done] JS functions coerce to Python function wrappers
• [done] JS exceptions propagate to Python
• [done] Implement eval() function in Python which accepts JS code and returns JS->Python coerced values
• [done] NodeJS+NPM-compatible CommonJS module system
• [done] Python strings coerce to JS strings
• [done] Python intrinsics coerce to JS intrinsics
• [done] Python dicts coerce to JS objects
• [done] Python require function, returns a coerced dict of module exports
• [done] Python functions coerce to JS function wrappers
• [done] CommonJS module system .py loader, loads Python modules for use by JS
• [done] Python host environment supplies event loop, including EventEmitter, setTimeout, etc.
• [done] Python host environment supplies XMLHttpRequest
• [done] Python TypedArrays coerce to JS TypeArrays
• [done] JS TypedArrays coerce to Python TypeArrays
• [done] Python lists coerce to JS Arrays
• [done] JS arrays coerce to Python lists
• [done] PythonMonkey can run the dcp-client npm package from Distributive.

Read this if you want to build a local version.

1. You will need the following installed (which can be done automatically by running ./setup.sh):

   • bash
   • cmake
   • Doxygen 1.9 series (if you want to build the docs)
   • graphviz (if you want to build the docs)
   • llvm
   • rust
   • python3.8 or later with header files (python3-dev)
   • spidermonkey latest from mozilla-central
   • npm (nodejs)
   • Poetry
   • poetry-dynamic-versioning

2. Run poetry install. This command automatically compiles the project and installs the project as well as dependencies into the poetry virtualenv. If you would like to build the docs, set the BUILD_DOCS environment variable, like so: BUILD_DOCS=1 poetry install. PythonMonkey supports multiple build types, which you can build by setting the BUILD_TYPE environment variable, like so: BUILD_TYPE=Debug poetry install. The build types are (case-insensitive):

• Release: stripped symbols, maximum optimizations (default)
• DRelease: same as Release, except symbols are not stripped
• Debug: minimal optimizations
• Sanitize: same as Debug, except with AddressSanitizer enabled
• Profile: same as Debug, except profiling is enabled
• None: don't compile (useful if you only want to build the docs)

If you are using VSCode, you can just press Ctrl + Shift + B to run build task - We have the tasks.json file configured for you.

1. Compile the project
2. Install development dependencies: poetry install --no-root --only=dev
3. From the root directory, run poetry run pytest ./tests/python
4. From the root directory, run poetry run bash ./peter-jr ./tests/js/

For VSCode users, similar to the Build Task, we have a Test Task ready to use.

npm (Node.js) is required during installation only to populate the JS dependencies.

$ pip install pythonmonkey

$ pip install --extra-index-url https://nightly.pythonmonkey.io/ --pre pythonmonkey

pythonmonkey is available in the poetry virtualenv once you compiled the project using poetry.

$ poetry run python

Python 3.10.6 (main, Nov 14 2022, 16:10:14) [GCC 11.3.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import pythonmonkey as pm
>>> hello = pm.eval("() => {return 'Hello from Spidermonkey!'}")
>>> hello()
'Hello from Spidermonkey!'

Alternatively, you can build installable packages by running

$ cd python/pminit && poetry build --format=sdist && cd - && mv -v python/pminit/dist/* ./dist/
$ poetry build --format=wheel

and install them by pip install ./dist/*.

Installing pythonmonkey will also install the pminit package as a dependency. However, pip uninstalling a package won't automatically remove its dependencies.
If you want to cleanly remove pythonmonkey from your system, do the following:

$ pip uninstall pythonmonkey pminit

1. build the project locally
2. To use gdb, run poetry run gdb python. See Python Wiki: DebuggingWithGdb

If you are using VSCode, it's more convenient to debug in VSCode's built-in debugger. Simply press F5 on an open Python file in the editor to start debugging - We have the launch.json file configured for you.

• examples/
• https://github.com/Distributive-Network/PythonMonkey-examples
• https://github.com/Distributive-Network/PythonMonkey-Crypto-JS-Fullstack-Example

These methods are exported from the pythonmonkey module. See definitions in python/pythonmonkey/pythonmonkey.pyi.

Evaluate JavaScript code. The semantics of this eval are very similar to the eval used in JavaScript; the last expression evaluated in the code string is used as the return value of this function. To evaluate code in strict mode, the first expression should be the string "use strict".

The eval function supports an options object that can affect how JS code is evaluated in powerful ways. They are largely based on SpiderMonkey's CompileOptions. The supported option keys are:

• filename: set the filename of this code for the purposes of generating stack traces etc.
• lineno: set the line number offset of this code for the purposes of generating stack traces etc.
• column: set the column number offset of this code for the purposes of generating stack traces etc.
• mutedErrors: if set to True, eval errors or unhandled rejections are ignored ("muted"). Default False.
• noScriptRval: if False, return the last expression value of the script as the result value to the caller. Default False.
• selfHosting: experimental
• strict: forcibly evaluate in strict mode ("use strict"). Default False.
• module: indicate the file is an ECMAScript module (always strict mode code and disallow HTML comments). Default False.
• fromPythonFrame: generate the equivalent of filename, lineno, and column based on the location of the Python call to eval. This makes it possible to evaluate Python multiline string literals and generate stack traces in JS pointing to the error in the Python source file.

• function literals evaluate as undefined in JavaScript; if you want to return a function, you must evaluate an expression:

  pythonmonkey.eval("myFunction() { return 123 }; myFunction")

  or

  pythonmonkey.eval("(myFunction() { return 123 })")

• function expressions are a great way to build JS IIFEs that accept Python arguments

  pythonmonkey.eval("(thing) => console.log('you said', thing)")("this string came from Python")

Return the exports of a CommonJS module identified by moduleIdentifier, using standard CommonJS semantics

• modules are singletons and will never be loaded or evaluated more than once
• moduleIdentifier is relative to the Python file invoking require
• moduleIdentifier should not include a file extension
• moduleIdentifiers which do not begin with ./, ../, or / are resolved by search require.path and module.paths.
• Modules are evaluated immediately after loading
• Modules are not loaded until they are required
• The following extensions are supported:

• .js - JavaScript module; source code decorates exports object
• .py - Python module; source code decorates exports dict
• .json - JSON module; exports are the result of parsing the JSON text in the file

A Python Dict which is equivalent to the globalThis object in JavaScript.

Factory function which returns a new require function

• filename: the pathname of the module that this require function could be used for
• extraPaths: [optional] a list of extra paths to search to resolve non-relative and non-absolute module identifiers
• isMain: [optional] True if the require function is being created for a main module

Load and evaluate a program (main) module. Program modules must be written in JavaScript. Program modules are not necessary unless the main entry point of your program is written in JavaScript.

• filename: the location of the JavaScript source code
• argv: the program's argument vector
• extraPaths: [optional] a list of extra paths to search to resolve non-relative and non-absolute module identifiers

Care should be taken to ensure that only one program module is run per JS context.

Examines the string code and returns False if the string might become a valid JS statement with the addition of more lines. This is used internally by pmjs and can be very helpful for building JavaScript REPLs; the idea is to accumulate lines in a buffer until isCompilableUnit is true, then evaluate the entire buffer.

Returns a Python function which invokes function with the JS new operator.

import pythonmonkey as pm

>>> pm.eval("class MyClass { constructor() { console.log('ran ctor') }}")
>>> MyClass = pm.eval("MyClass")
>>> MyClass()
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
pythonmonkey.SpiderMonkeyError: TypeError: class constructors must be invoked with 'new'

>>> MyClassCtor = pm.new(MyClass)
>>> MyClassCtor()
ran ctor
{}
>>>

This is the JS typeof operator, wrapped in a function so that it can be used easily from Python.

All of the JS Standard Classes (Array, Function, Object, Date...) and objects (globalThis, FinalizationRegistry...) are available as exports of the pythonmonkey module. These exports are generated by enumerating the global variable in the current SpiderMonkey context. The current list is:

undefined, Boolean, JSON, Date, Math, Number, String, RegExp, Error, InternalError, AggregateError, EvalError, RangeError, ReferenceError, SyntaxError, TypeError, URIError, ArrayBuffer, Int8Array, Uint8Array, Int16Array, Uint16Array, Int32Array, Uint32Array, Float32Array, Float64Array, Uint8ClampedArray, BigInt64Array, BigUint64Array, BigInt, Proxy, WeakMap, Map, Set, DataView, Symbol, Intl, Reflect, WeakSet, Promise, WebAssembly, WeakRef, Iterator, AsyncIterator, NaN, Infinity, isNaN, isFinite, parseFloat, parseInt, escape, unescape, decodeURI, encodeURI, decodeURIComponent, encodeURIComponent, Function, Object, debuggerGlobal, FinalizationRegistry, Array, globalThis

See definitions in python/pythonmonkey/global.d.ts. Including:

• console
• atob
• btoa
• setTimeout
• clearTimeout

The CommonJS subsystem is activated by invoking the require or createRequire exports of the (Python) pythonmonkey module.

• require
• exports
• module
• __filename
• __dirname
• python.print - the Python print function
• python.getenv - the Python getenv function
• python.stdout - an object with read and write methods, which read and write to stdout
• python.stderr - an object with read and write methods, which read and write to stderr
• python.exec - the Python exec function
• python.eval - the Python eval function
• python.exit - exit via sys.exit(); the exit code is the function argument or python.exit.code.
• python.paths - the Python sys.paths list, visible in JS as an Array

When sending variables from Python into JavaScript, PythonMonkey will intelligently coerce or wrap your variables based on their type. PythonMonkey will share backing stores (use the same memory) for ctypes, typed arrays, and strings; moving these types across the language barrier is extremely fast because there is no copying involved.

Note: There are plans in Python 3.12 (PEP 623) to change the internal string representation so that every character in the string uses four bytes of memory. This will break fast string transfers for PythonMonkey, as it relies on the memory layout being the same in Python and JavaScript. As of this writing (July 2023), "classic" Python strings still work in the 3.12 beta releases.

Where shared backing store is not possible, PythonMonkey will automatically emit wrappers that use the "real" data structure as its value authority. Only immutable intrinsics are copied. This means that if you update an object in JavaScript, the corresponding Dict in Python will be updated, etc.

JavaScript Array and Object methods are implemented on Python List and Dictionaries, and vice-versa.

You can force a number in JavaScript to be coerced as an integer by casting it to BigInt:

function myFunction(a, b) {
  const result = calculate(a, b);
  return BigInt(Math.floor(result));
}

The pythonmonkey.bigint object works like an int in Python, but it will be coerced as a BigInt in JavaScript:

import pythonmonkey

def fn myFunction()
  result = 5
  return pythonmonkey.bigint(result)

You can use a JavaScript IIFE to create a scope in which you can inject Python symbols:

globalThis.python.exit = pm.eval("""'use strict';
(exit) => function pythonExitWrapper(exitCode) {
  if (typeof exitCode === 'number')
    exitCode = BigInt(Math.floor(exitCode));
  exit(exitCode);
}
""")(sys.exit);

You need an event-loop running to use setTimeout and Promise<=>awaitable coercion.

import asyncio

async def async_fn():
  await pm.eval("""
    new Promise((resolve) => setTimeout((...args) => {
        console.log(args);
        resolve();
      }, 1000, 42, "abc")
    )
  """)
  await pm.eval("async (x) => await x")(asyncio.sleep(0.5))

asyncio.run(async_fn())

A basic JavaScript shell, pmjs, ships with PythonMonkey. This shell can act as a REPL or run JavaScript programs; it is conceptually similar to the node shell which ships with Node.js.

Pmjs starts PythonMonkey's CommonJS subsystem, which allow it to use CommonJS modules, with semantics that are similar to Node.js - e.g. searching module.paths, understanding package.json, index.js, and so on. See the ctx-module for a full list of supported features.

In addition to CommonJS modules written in JavaScript, PythonMonkey supports CommonJS modules written in Python. Simply decorate a Dict named exports inside a file with a .py extension, and it can be loaded by require() -- in either JavaScript or Python.

The program module, or main module, is a special module in CommonJS. In a program module:

• variables defined in the outermost scope are properties of globalThis
• returning from the outermost scope is a syntax error
• the arguments variable in an Array which holds your program's argument vector (command-line arguments)

$ echo "console.log('hello world')" > my-program.js
$ pmjs my-program.js
hello world
$

// date-lib.js - require("./date-lib")
const d = new Date();
exports.today = `${d.getFullYear()}-${String(d.getMonth()).padStart(2,'0')}-${String(d.getDay()).padStart(2,'0')}`

# date-lib.py - require("./date-lib")
from datetime import date # You can use Python libraries.
exports['today'] = date.today()

If you are having trouble with the CommonJS require function, set environment variable DEBUG='ctx-module*' and you can see the filenames it tries to load.

PythonMonkey has a built-in gdb-like JavaScript command-line debugger called pmdb, which would be automatically triggered on debugger; statements and uncaught exceptions.

To enable pmdb, simply call from pythonmonkey.lib import pmdb; pmdb.enable() before doing anything on PythonMonkey.

import pythonmonkey as pm
from pythonmonkey.lib import pmdb

pmdb.enable()

pm.eval("...")

Run help command in pmdb to see available commands.

(pmdb) > help
List of commands:
• ...
• ...

• there is a .help menu in the REPL
• there is a --help command-line option
• the --inspect option enables pmdb, a gdb-like JavaScript command-line debugger
• the -r option can be used to load a module before your program or the REPL runs
• the -e option can be used evaluate code -- e.g. define global variables -- before your program or the REPL runs
• The REPL can evaluate Python expressions, storing them in variables named $1, $2, etc.

$ pmjs

Welcome to PythonMonkey v1.0.0.
Type ".help" for more information.
> .python import sys
> .python sys.path
$1 = { '0': '/home/wes/git/pythonmonkey2',
  '1': '/usr/lib/python310.zip',
  '2': '/usr/lib/python3.10',
  '3': '/usr/lib/python3.10/lib-dynload',
  '4': '/home/wes/.cache/pypoetry/virtualenvs/pythonmonkey-StuBmUri-py3.10/lib/python3.10/site-packages',
  '5': '/home/wes/git/pythonmonkey2/python' }
> $1[3]
'/usr/lib/python3.10/lib-dynload'
>