Security News
Input Validation Vulnerabilities Dominate MITRE's 2024 CWE Top 25 List
MITRE's 2024 CWE Top 25 highlights critical software vulnerabilities like XSS, SQL Injection, and CSRF, reflecting shifts due to a refined ranking methodology.
@x-python/core
Advanced tools
A complete solution for python-in-browser. (check the Usage section :point_down:)
🔥 A REPL powered by xPython
as React
component is coming soon
⌛️ It's still in beta testing
Clean API to execute Python code, get code completions, format the code, install packages, and many more.
In the past few years we used python in production browser-based applications in quite different scenarios. From just executing a python code to implementing autoformat and autocomplete. And while all of this is possible there are many questionable situations in the implementations. For example, it's been a while since we've had a full Python
distribution for the browser based on webassembly - pyodide. Pyodide
is great! You can just install and use it. But to use it correctly, instead of installing it in the main (UI) thread, it would be desirable to install/run it in a separate thread. Once you've created a separate thread you need to create a channel between main/UI and pyodide worker and come up with some protocol for communication. You also need to do something with error handling, handling standard output streams, non-sequential executions and other all possible corner cases. This was one of the things that xPython
will handle for you :slightly_smiling_face: It also provides a clean API for code completion, installing packages, and formatting the code... and many more are coming soon. Long story short I tried to provide a clean and complete interface to interact with Python in browser-based applications.
npm install @x-python/core
or
yarn add @x-python/core
import * as xPython from '@x-python/core';
// initialize xPython
await xPython.init();
// execute python code
await xPython.exec({ code: '1 + 1' });
await xPython.exec({ code: 'print("test")' });
// multiline example
await xPython.exec({
code: `
import sys
sys.version
`,
});
// you can use built-in packages without additionally installing them
await xPython.exec({
code: `
import numpy as np
np.random.rand()
`,
});
// code completion
await xPython.complete.repl({ code: `import sys; sys.ver` });
// specify the cursor position
await xPython.complete.repl({
code: `
from math import factorial
test = 8
print(tes)
factorial(x)
`,
line: 5,
column: 9,
});
// format the code
const { result } = await xPython.format({
code: `
def add(a, b):
return a + b
print(add(12,
54))
`,
});
console.log(result);
// install packages
await xPython.install(['nicelog']);
// and use the newly installed package :)
const { stderr } = await xPython.exec({
code: `
import logging
import sys
from nicelog.formatters import Colorful
# Setup a logger
logger = logging.getLogger('foo')
logger.setLevel(logging.DEBUG)
# Setup a handler, writing colorful output
# to the console
handler = logging.StreamHandler(sys.stderr)
handler.setFormatter(Colorful())
handler.setLevel(logging.DEBUG)
logger.addHandler(handler)
# Now log some messages..
logger.debug('Debug message')
logger.info('Info message')
logger.warning('Warning message')
logger.error('Error message')
logger.critical('Critical message')
try:
raise ValueError('This is an exception')
except:
logger.exception("An error occurred")
`,
});
console.log(stderr);
It will initialize xPython
. Most importantly it will create a separate thread (dedicated web worker), install pyodide
inside that thread, create a channel, and setup all necessary packages and functions for further usage.
import * as xPython from '@x-python/core';
await xPython.init();
Usually, we do initialize xPython
before using other methods (like exec
, complete
, etc), but it's not mandatory :slightly_smiling_face: So, you can go ahead and do xPython.exec({ code: '...' })
without doing xPython.init()
- it will do xPython.init()
on first xPython.exec
(or .complete
, .format
and any other supported method) call if it's not initialized. The aim of the existence of a separate initialize method is to provide full flexibility to developers. The initialization process takes time and it should be possible to handle that time in the way you want. So, you can do await xPython.init();
at the beginning or do it after a certain user action or, if you are okay with your users waiting a little bit more after the first execution then you can skip the initialization process and it will be handled automatically :slightly_smiling_face:
exec
is one of the most frequently used. Basically, it's for executing python code. A simple usage looks like this:
import * as xPython from '@x-python/core';
await xPython.exec({ code: '1 + 1' });
You can also provide a context
with global variables, like:
import * as xPython from '@x-python/core';
await xPython.exec({ code: 'x + 1', context: { x: 1 } });
But let's take a closer look at what it returns. In both cases we will get something like this:
{ result: 2, error: null, stdout: '', stderr: '' }
result
is what is returned from the executed script. But we also have stdout
(and stderr
) for standard output streams. If we execute print("test")
nothing will be returned, but you will have a stdout
.
import * as xPython from '@x-python/core';
await xPython.exec({ code: 'print("test")' });
// { result: undefined, error: null, stdout: 'test', stderr: '' }
Of course you can exec multiline code snippets:
import * as xPython from '@x-python/core';
await xPython.exec({
code: `
import sys
sys.version
`,
});
You can directly use pyodide
built-in package list without installing them. The full list is here
import * as xPython from '@x-python/core';
await xPython.exec({
code: `
import numpy as np
np.random.rand()
`,
});
It will autodetect numpy
and it will install it if you're using it for the first time.
To get code completions you can use xPython.complete.repl
. Simple usage looks like this:
import * as xPython from '@x-python/core';
await xPython.complete.repl({ code: 'import sys; sys.ver' });
This example will return an array with two possible options: version
and version_info
:slightly_smiling_face:
The full signature of this method also includes line
and column
options to specify the cursor position. If line
isn't provided xPython
will assume it's the last line and, correspondingly, if column
isn't provided it will assume that it's the last column. So, in the previous example, it assumed that cursor is at the end of sys.var
and returned code completions based on that assumption. An example with cursor position specified:
await xPython.complete.repl({
code: `
from math import factorial
test = 8
print(tes)
factorial(x)
`,
line: 5,
column: 9,
});
This will return the only available option here: test
.
The curious eye may notice that instead of .complete
we called .complete.repl
. When it comes to code completion at least two environments can be your target: REPL
and Script/File/Editor
. And based on the environment code completion can vary. In the current version, we do support only REPL
, but very soon other options will also be available ⏳
Code formatting is an essential part of interacting with your code. A simple usage looks like this:
import * as xPython from '@x-python/core';
const { result } = await xPython.format({
code: `
def add(a, b):
return a + b
print(add(12,
54))
`,
});
console.log(result);
NOTE: in upcoming versions a full configuration option will be provided.
The entire standard library is available out of the box, so you can import sys
, math
, or os
without doing anything special. In addition to this pyodide
also provides a list of built-in packages, like numpy
, pandas
, scipy
, matplotlib
, scikit-learn
, etc. Check the full list here. You can use any package from the above-mentioned list and it will be installed automatically and on demand. And if that's not enough you can still install any pure Python
packages with wheels available on PyPI
:slightly_smiling_face: Let's install the package called nicelog
.
import * as xPython from '@x-python/core';
await xPython.install(['nicelog']);
That's it :slightly_smiling_face: Now you have nicelog
installed and it's ready to be used. Not familiar with nicelog
? Let's check what's inside:
import * as xPython from '@x-python/core';
await xPython.complete.repl({ code: 'from nicelog import ' });
As it's already installed it should be available for code completion as well :white_check_mark:
Example from the nicelog
PyPI
page.
const { stderr } = await xPython.exec({
code: `
import logging
import sys
from nicelog.formatters import Colorful
# Setup a logger
logger = logging.getLogger('foo')
logger.setLevel(logging.DEBUG)
# Setup a handler, writing colorful output
# to the console
handler = logging.StreamHandler(sys.stderr)
handler.setFormatter(Colorful())
handler.setLevel(logging.DEBUG)
logger.addHandler(handler)
# Now log some messages..
logger.debug('Debug message')
logger.info('Info message')
logger.warning('Warning message')
logger.error('Error message')
logger.critical('Critical message')
try:
raise ValueError('This is an exception')
except:
logger.exception("An error occurred")
`,
});
console.log(stderr);
To play with the library locally do the following steps:
git clone git@github.com:suren-atoyan/x-python.git
npm install # or yarn
npm run dev
That's it :slightly_smiling_face: Under /playground
folder you can find the index.html
file which contains a script with the demo code and under /src
folder you can find the library source code. Enjoy it :tada:
0.0.10
jedi
to black
versionsFAQs
Unknown package
The npm package @x-python/core receives a total of 34 weekly downloads. As such, @x-python/core popularity was classified as not popular.
We found that @x-python/core demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
Did you know?
Socket for GitHub automatically highlights issues in each pull request and monitors the health of all your open source dependencies. Discover the contents of your packages and block harmful activity before you install or update your dependencies.
Security News
MITRE's 2024 CWE Top 25 highlights critical software vulnerabilities like XSS, SQL Injection, and CSRF, reflecting shifts due to a refined ranking methodology.
Security News
In this segment of the Risky Business podcast, Feross Aboukhadijeh and Patrick Gray discuss the challenges of tracking malware discovered in open source softare.
Research
Security News
A threat actor's playbook for exploiting the npm ecosystem was exposed on the dark web, detailing how to build a blockchain-powered botnet.