'''

import requests
import json
import datetime
import streamlit as st
from itertools import zip_longest
import os
import seaborn as sns
import pandas as pd
import matplotlib.pyplot as plt

sns.set_theme(style="darkgrid")


def basic_info():
    config = dict()
    config["access_token"] = st.secrets["access_token"]
    config['instagram_account_id'] = st.secrets.get("instagram_account_id", "")
    config["version"] = 'v16.0'
    config["graph_domain"] = 'https://graph.facebook.com/'
    config["endpoint_base"] = config["graph_domain"] + config["version"] + '/'
    return config


def InstaApiCall(url, params, request_type):
    if request_type == 'POST':
        req = requests.post(url, params)
    else:
        req = requests.get(url, params)
    res = dict()
    res["url"] = url
    res["endpoint_params"] = params
    res["endpoint_params_pretty"] = json.dumps(params, indent=4)
    res["json_data"] = json.loads(req.content)
    res["json_data_pretty"] = json.dumps(res["json_data"], indent=4)
    return res


def getUserMedia(params, pagingUrl=''):
    Params = dict()
    Params['fields'] = 'id,caption,media_type,media_url,permalink,thumbnail_url,timestamp,username,like_count,comments_count'
    Params['access_token'] = params['access_token']

    if not params['endpoint_base']:
        return None

    if pagingUrl == '':
        url = params['endpoint_base'] + params['instagram_account_id'] + '/media'
    else:
        url = pagingUrl

    return InstaApiCall(url, Params, 'GET')


def getUser(params):
    Params = dict()
    Params['fields'] = 'followers_count'
    Params['access_token'] = params['access_token']

    if not params['endpoint_base']:
        return None

    url = params['endpoint_base'] + params['instagram_account_id']

    return InstaApiCall(url, Params, 'GET')


def saveCount(count, filename):
    with open(filename, 'w') as f:
        json.dump(count, f, indent=4)


def getCount(filename):
    try:
        with open(filename, 'r') as f:
            return json.load(f)
    except (FileNotFoundError, json.decoder.JSONDecodeError):
        return {}


st.set_page_config(layout="wide")
params = basic_info()

count_filename = "count.json"

if not params['instagram_account_id']:
    st.write('.envファイルでinstagram_account_idを確認')
else:
    response = getUserMedia(params)
    user_response = getUser(params)
    if not response or not user_response:
        st.write('.envファイルでaccess_tokenを確認')
    else:
        posts = response['json_data']['data'][::-1]
        user_data = user_response['json_data']
        followers_count = user_data.get('followers_count', 0)

        NUM_COLUMNS = 6
        MAX_WIDTH = 1000
        BOX_WIDTH = int(MAX_WIDTH / NUM_COLUMNS)
        BOX_HEIGHT = 400

        yesterday = (datetime.datetime.now(datetime.timezone(datetime.timedelta(hours=9))) - datetime.timedelta(days=1)).strftime('%Y-%m-%d')
        follower_diff = followers_count - getCount(count_filename).get(yesterday, {}).get('followers_count', followers_count)
        st.markdown(f"<h4 style='font-size:1.2em;'>Follower: {followers_count} ({'+' if follower_diff >= 0 else ''}{follower_diff})</h4>", unsafe_allow_html=True)

        show_description = st.checkbox("キャプションを表示")
        show_summary_charts = st.checkbox("サマリーグラフを表示")
        show_charts = st.checkbox("いいね/コメント数グラフを表示")

        posts.reverse()
        post_groups = [list(filter(None, group)) for group in zip_longest(*[iter(posts)] * NUM_COLUMNS)]

        count = getCount(count_filename)
        today = datetime.datetime.now(datetime.timezone(datetime.timedelta(hours=9))).strftime('%Y-%m-%d')

        if today not in count:
            count[today] = {}

        count[today]['followers_count'] = followers_count

        if datetime.datetime.now(datetime.timezone(datetime.timedelta(hours=9))).strftime('%H:%M') == '23:59':
            count[yesterday] = count[today]

        max_like_diff = 0
        max_comment_diff = 0

        chart_data = []
        chart_data_likes = {}
        chart_data_comments = {}

        for key, value in count.items():
            for c in value:
                if c != 'followers_count':
                    post = count[list(count.keys())[-1]][c]
                    like_count_diff = value[c]['like_count'] - count.get(yesterday, {}).get(c, {}).get('like_count', post['like_count'])
                    comment_count_diff = value[c]['comments_count'] - count.get(yesterday, {}).get(c, {}).get('comments_count', post['comments_count'])

            total_likes_count_diff = sum(value[c]['like_count'] - count.get(yesterday, {}).get(c, {}).get('like_count', like_count_diff) for c in value if c != 'followers_count')
            total_comments_count_diff = sum(value[c]['comments_count'] - count.get(yesterday, {}).get(c, {}).get('comments_count', comment_count_diff) for c in value if c != 'followers_count')

            if 'followers_count' in value:
                chart_data_likes[key] = total_likes_count_diff
                chart_data_comments[key] = total_comments_count_diff
                chart_data.append([key, value['followers_count'], total_likes_count_diff, total_comments_count_diff])

        if show_summary_charts:
            df_chart_data = pd.DataFrame(chart_data, columns=["Date", "followers_count", "total_likes_count", "total_comments_count"])
            df_chart_data["Date"] = pd.to_datetime(df_chart_data["Date"], format="%Y-%m-%d")
            fig, ax1 = plt.subplots(figsize=(15, 6))
            sns.lineplot(data=df_chart_data, x="Date", y="followers_count", color="lightskyblue", ax=ax1)
            ax1.set(ylabel="followers_count")
            ax2 = ax1.twinx()
            sns.lineplot(data=df_chart_data, x="Date", y="total_likes_count", color="orange", ax=ax2)
            sns.lineplot(data=df_chart_data, x="Date", y="total_comments_count", color="green", ax=ax2)
            ax2.set(ylabel="total_likes_count & total_comments_count")
            plt.title("Summary Chart")
            sns.despine()

            st.pyplot(fig)

        for post_group in post_groups:
            with st.container():
                columns = st.columns(NUM_COLUMNS)
                for i, post in enumerate(post_group):
                    like_count_diff = post['like_count'] - count.get(yesterday, {}).get(post['id'], {}).get('like_count', post['like_count'])
                    comment_count_diff = post['comments_count'] - count.get(yesterday, {}).get(post['id'], {}).get('comments_count', post['comments_count'])
                    max_like_diff = max(like_count_diff, max_like_diff)
                    max_comment_diff = max(comment_count_diff, max_comment_diff)

                    with columns[i]:
                        st.image(post['media_url'], width=BOX_WIDTH, use_column_width=True)
                        st.write(f"{datetime.datetime.strptime(post['timestamp'], '%Y-%m-%dT%H:%M:%S%z').astimezone(datetime.timezone(datetime.timedelta(hours=9))).strftime('%Y-%m-%d %H:%M:%S')}")
                        st.markdown(
                            f"👍: {post['like_count']} <span style='{'' if like_count_diff != max_like_diff or max_like_diff == 0 else 'color:green;'}'>({'+' if like_count_diff >= 0 else ''}{like_count_diff})</span>"
                            f"\n💬: {post['comments_count']} <span style='{'' if comment_count_diff != max_comment_diff or max_comment_diff == 0 else 'color:green;'}'>({'+' if comment_count_diff >= 0 else ''}{comment_count_diff})</span>",
                            unsafe_allow_html=True)
                        caption = post['caption']

                        if caption is not None:
                            caption = caption.strip()
                            if "[Description]" in caption:
                                caption = caption.split("[Description]")[1].lstrip()
                            if "[Tags]" in caption:
                                caption = caption.split("[Tags]")[0].rstrip()
                            caption = caption.replace("#", "")
                            caption = caption.replace("[model]", "👗")
                            caption = caption.replace("[Equip]", "📷")
                            caption = caption.replace("[Develop]", "🖨")
                            if show_description:
                                st.write(caption or "No caption provided")
                            else:
                                st.write(caption[:0] if caption is not None and len(caption) > 50 else caption or "No caption provided")

                        if show_charts:
                            days = list(chart_data_likes.keys())
                            likes = [chart_data_likes[d] for d in days]
                            comments = [chart_data_comments[d] for d in days]

                            df_like_data = pd.DataFrame({"Date": days, "likes_count": likes})
                            df_comment_data = pd.DataFrame({"Date": days, "comments_count": comments})

                            fig, ax1 = plt.subplots(figsize=(5, 3))
                            sns.lineplot(data=df_like_data, x="Date", y="likes_count", color="orange", ax=ax1)
                            sns.lineplot(data=df_comment_data, x="Date", y="comments_count", color="green", ax=ax1)
                            plt.xticks(rotation=90)
                            plt.title("Like and Comment Counts")
                            sns.despine()

                            st.pyplot(fig)

                        count[today][post['id']] = {'like_count': post['like_count'], 'comments_count': post['comments_count']}

        saveCount(count, count_filename)

'''

上記のコードを以下の要件をすべて満たして改修してください

- Python用のインデントを行頭に付与して出力する
- コードの説明文は表示しない
- 指示のない部分のコードの改変はしない
- 既存の'like_count'と"comments_count"表示部分は改変しない
- "caption = post['caption']"以降のブロックについては改変しない
- グラフ作成のためのPythonライブラリは"seaborn"のみを使用する

- "followers_count"と'like_count'を左縦軸に表示し、'comments_count'を右縦軸に表示し、グラフデータをそれぞれ"水色"・"オレンジ"・"緑"で色分けしグラフ背景色はダークにした折れ線グラフで表現し、"mm/dd"を横軸にした"サマリーグラフ"を、ページの最上部に横幅いっぱいに表示する機能を作成する
- "サマリーグラフ"の'like_count'と'comments_count'の数は、jsonファイル内の過去すべてのデータを参照し、"対象日とその前日データと比較して増加した数"を算出し日を追って列挙して表示する
- 'like_count'を左縦軸に表示し、'comments_count'を右縦軸に表示し、グラフデータを"オレンジ"・"緑"で色分けしグラフ背景をダークにした折れ線グラフで表現し、"mm/dd"を横軸にした"いいね/コメント数グラフ"を、投稿コンテナ内の"キャプション"の下に表示する機能を作成する
- "いいね/コメント数グラフ"は、jsonファイル内の過去すべてのデータを参照し、各投稿IDの'like_count'と'comments_count'を、それぞれ"対象日とその前日データとの差分"を算出し日付を追って列挙し、各ID別の投稿コンテナに個別のグラフを表示するようにする
- "キャプションを表示"の右隣に"サマリーグラフ"と"いいね/コメント数グラフ"をUI上に表示するためのトグルを各1つずつチェックボックスで作成し、デフォルトではチェックなしでグラフは非表示の状態にする