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

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'''
        Follower: {followers_count} ({'+' if follower_diff >= 0 else ''}{follower_diff})
        ''', unsafe_allow_html=True)

        show_description = st.checkbox("キャプションを表示")
        show_summary_chart = st.checkbox("サマリーチャートを表示")
        show_like_comment_chart = 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
        summary_chart_data = {"Date": [], "Count": [], "Type": []}
        for post_group in post_groups:
            for post in 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)

        if show_summary_chart:
            for date in count.keys():
                if date != today:
                    summary_chart_data["Date"].append(datetime.datetime.strptime(date, '%Y-%m-%d').strftime('%m/%d'))
                    summary_chart_data["Count"].append(count[date].get("followers_count", 0))
                    summary_chart_data["Type"].append("Follower")
                for post_id in count[date].keys():
                    if post_id not in ["followers_count"]:
                        summary_chart_data["Date"].append(datetime.datetime.strptime(date, '%Y-%m-%d').strftime('%m/%d'))
                        summary_chart_data["Count"].append(count[date][post_id].get("like_count", 0))
                        summary_chart_data["Type"].append("Like")
                        summary_chart_data["Date"].append(datetime.datetime.strptime(date, '%Y-%m-%d').strftime('%m/%d'))
                        summary_chart_data["Count"].append(count[date][post_id].get("comments_count", 0))
                        summary_chart_data["Type"].append("Comment")

            summary_chart_df = pd.DataFrame(summary_chart_data)
            plt.figure(figsize=(15, 10))
            summary_chart_palette = {"Follower": "lightblue", "Like": "orange", "Comment": "green"}
            sns.lineplot(data=summary_chart_df, x="Date", y="Count", hue="Type", palette=summary_chart_palette)
            plt.xlabel("Date")
            plt.ylabel("Count")
            plt.title("日別 サマリーチャート")
            st.pyplot()

        for post_group in post_groups:
            with st.container():
                columns = st.columns(NUM_COLUMNS)
                for i, post in enumerate(post_group):
                    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')}")
                        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'])
                        st.markdown(
                        f"👍: {post['like_count']} <span style='{'' if like_count_diff != max_like_diff or max_like_diff == 0 else 'color:green;'}'>({'+1' if like_count_diff >= 0 else ''}{like_count_diff})"
                        f"\n💬: {post['comments_count']} <span style='{'' if comment_count_diff != max_comment_diff or max_comment_diff == 0 else 'color:green;'}'>({'+1' if comment_count_diff >= 0 else ''}{comment_count_diff})",
                        unsafe_allow_html=True)

                        if show_like_comment_chart:
                            like_comment_chart_data = {"Date": [], "Count": [], "Type": []}
                            for date in count.keys():
                                if date != today and post["id"] in count[date]:
                                    like_comment_chart_data["Date"].append(datetime.datetime.strptime(date, '%Y-%m-%d').strftime('%m/%d'))
                                    like_comment_chart_data["Count"].append(count[date][post["id"]].get("like_count", 0))
                                    like_comment_chart_data["Type"].append("Like")
                                    like_comment_chart_data["Date"].append(datetime.datetime.strptime(date, '%Y-%m-%d').strftime('%m/%d'))
                                    like_comment_chart_data["Count"].append(count[date][post["id"]].get("comments_count", 0))
                                    like_comment_chart_data["Type"].append("Comment")

                            if like_comment_chart_data["Date"]:
                                like_comment_chart_df = pd.DataFrame(like_comment_chart_data)
                                plt.figure(figsize=(5, 3))
                                like_comment_chart_palette = {"Like": "orange", "Comment": "green"}
                                sns.lineplot(data=like_comment_chart_df, x="Date", y="Count", hue="Type", palette=like_comment_chart_palette)
                                plt.xlabel("Date")
                                plt.ylabel("Count")
                                plt.title("日別 いいね/コメント数")
                                st.pyplot()

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

        saveCount(count, count_filename)
        
'''

上記コードの機能を一切(画像表示,いいね数表示,コメント数表示,キャプション表示,トグルスイッチ,サマリーチャート,いいね/コメント数チャート)変更せずに、コード全体の文字数削減のための最適化を実施し、処理後のコード全文をPython用インデントを付与して表示してください。