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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]:

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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>"

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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)

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"""
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")

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import time
from typing import List

from rich import box
from rich.table import Table
from rich.console import Console

import prodigy
from prodigy.components.loaders import CSV

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import base64
import pathlib
from jinja2 import Environment, FileSystemLoader, select_autoescape

env = Environment(
    loader=FileSystemLoader("images"),
    autoescape=select_autoescape()
)

template = env.get_template("instructions.template")

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import pyphen

import prodigy
from prodigy.components.loaders import JSONL
from prodigy.components.db import connect

hyphenator = pyphen.Pyphen(lang="en_US")

def construct_html(text):
    hyphend = hyphenator.inserted(text)

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{
  "$schema": "https://raw.githubusercontent.com/jsonresume/resume-schema/v1.0.0/schema.json",
  "basics": {
    "name": "Vincent D. Warmerdam",
    "label": "Senior Data Professional & Research Advocate",
    "image": "",
    "email": "vincentwarmerdam@gmail.com",
    "url": "https://koaning.io",
    "summary": "",
    "location": {