koaning

Marimo notebook assistant

I am a specialized AI assistant designed to help create data science notebooks using marimo. I focus on creating clear, efficient, and reproducible data analysis workflows with marimo's reactive programming model.

<assistant_info>

• I specialize in data science and analytics using marimo notebooks
• I provide complete, runnable code that follows best practices
• I emphasize reproducibility and clear documentation
• I focus on creating interactive data visualizations and analysis
• I understand marimo's reactive programming model

koaning

/* Custom CSS for Marimo - Font customization */

/* Import Press Start 2P font from Google Fonts */
@import url('https://fonts.googleapis.com/css2?family=Press+Start+2P&display=swap');

:root {
    --marimo-monospace-font: 'Press Start 2P', 'Courier New', monospace;
    --marimo-text-font: 'Press Start 2P', 'Courier New', monospace;
    --marimo-heading-font: 'Press Start 2P', 'Courier New', monospace;
}

koaning

import curses
import time
import random

MAX_STARS = 50
STAR_CHARS = ['.', '*']
EXPLOSION_DURATION = 3 # Frames
EXPLOSION_ART_PARTS = [ # New name, list of lists of (char, color_key) tuples
    [(' ', None), (' ', None), ('`', "exp_yellow"), ('*', "exp_yellow"), ('`', "exp_yellow"), (' ', None), (' ', None)],
    [(' ', None), ('*', "exp_dark_red"), ('X', "exp_yellow"), ('X', "exp_yellow"), ('X', "exp_yellow"), ('*', "exp_dark_red"), (' ', None)],

koaning

import anywidget
import traitlets

class TangleWidget(anywidget.AnyWidget):
    _esm = """
    export default { render };

    function render({ model, el }) {
        const input = document.createElement('span');
        input.style.borderBottom = '1px dashed #3498db';

koaning

pork chop noodle soup
5 ingredient almond cake with fresh berries
shrimp cakes
chili roasted okra
slow cooker chicken chili
fall superfood beef stew
rotisserie turkey breast tenderloin with pesto
j . alexander's mac and cheese
spinach stuffed pork roast
lasagna soup

koaning

{
  "name": "NuPhy Air60 V2",
  "vendorProductId": 435499605,
  "macros": [
    "{+KC_LSFT}{+KC_LGUI} {-KC_LSFT}{-KC_LGUI}",
    "{KC_LGUI} ",
    "{+KC_LSFT} ",
    "",
    "",
    "",

koaning

import prodigy 
from typing import List, Optional, Union, Iterable

from prodigy.components.loaders import get_stream
from prodigy.components.preprocess import fetch_media as fetch_media_preprocessor
from prodigy.util import log, msg, get_labels, split_string
from prodigy.types import TaskType, RecipeSettingsType


def remove_base64(examples: List[TaskType]) -> List[TaskType]:

koaning

import timeit
import requests

import html_text
import justext 
from selectolax.parser import HTMLParser

# There's a difference between these two
html_long = requests.get("http://planet.python.org/").content.decode("utf-8")
html_short = "<p><b>This</b> is just a small example.</p>"

koaning

import spacy
from spacy import displacy


def show_results(text, patterns):
    nlp = spacy.blank("en")
    ruler = nlp.add_pipe("entity_ruler")

    ruler.add_patterns(patterns)
    doc = nlp(text)

koaning

"""
This script combines two datasets to generate a file with all found patterns. 
"""

import srsly 
from prodigy.components.db import connect
import spacy 

nlp = spacy.blank("en")