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"""
Multi-Page Chatnificent App Example
====================================

This file shows how to create a multi-page app with Chatnificent.
Since Chatnificent is a subclass of Dash, you can use all Dash features
including multi-page apps with the pages/ directory structure.

Directory Structure:
--------------------

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# /// script
# requires-python = ">=3.13"
# dependencies = [
#     "anthropic>=0.77.0",
#     "chatnificent>=0.0.10",
#     "dash-bootstrap-components>=2.0.4",
# ]
# ///
import chatnificent as chat
from anthropic.types import TextBlock

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# /// script
# requires-python = ">=3.12"
# dependencies = [
#     "dash",
#     "dash-bootstrap-components",
# ]
# ///

from dash import Dash, html, dcc, Output, Input
import dash_bootstrap_components as dbc

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import plotly.express as px

fig = px.line(
    stocks,
    x='date',
    template='plotly_white',
    y=stocks.columns[1:],
    color_discrete_sequence=cat_scale,
    labels={'y': 'stock price'},
    height=600,)

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import plotly.express as px
import adviz
import numpy as np
import pandas as pd

population = pd.read_html('https://en.wikipedia.org/wiki/List_of_countries_and_dependencies_by_population')
pop = population[0][['Location', 'Population']].copy()
flags = []
for country in pop['Location']:
    try:

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import os
import datetime

import pandas as pd

today = datetime.datetime.now(datetime.UTC).strftime('%Y_%m_%d')

url_status_time = pd.concat(
    pd.read_json(f'/path/to/status_codes/{file}',
    lines=True)

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import datetime

import advertools as adv

today = datetime.datetime.now(datetime.UTC).strftime("%Y_%m_%d")

sitemap = adv.sitemap_to_df("https://example/sitemap.xml")

adv.crawl_headers(
    sitemap["loc"],

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import pandas as pd
xpath = pd.read_html('https://advertools.readthedocs.io/en/master/advertools.code_recipes.spider_strategies.html')
df = xpath[2].iloc[:, [1, 2]]
df = df.assign(expression=[f'=textjoin("@@",100,IMPORTXML(A2,"{expression}"))' for expression in df['XPath Expression']])
display(df[['Suggested Name', 'expression']].T)
df[['Suggested Name', 'expression']].T.to_clipboard(index=False)

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# Create anchors for all letters:

import string
print('<h3>' + '&nbsp;&nbsp;&nbsp;&nbsp;'.join([f'<a href="#{letter}">{letter}</a>' for letter in string.ascii_uppercase]) + '</h3>')

# Assuming you have a DataFrame with the columns "full_name" and "loc":

for letter in string.ascii_uppercase:
    df = players_df[players_static['full_name'].str[0].eq(letter)]
    print()

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import datetime
import pandas as pd
lastmod = datetime.datetime.now(datetime.UTC).strftime('%Y-%m-%d')
url_list = [
    'https://nbastats.pro/player/Eric_Moreland',
    'https://nbastats.pro/player/Marc_Iavaroni',
    'https://nbastats.pro/player/Keith_Tower',
    'https://nbastats.pro/player/Hakeem_Olajuwon',
    'https://nbastats.pro/player/Mike_Price',
    'https://nbastats.pro/player/Doug_Collins',