git clone https://github.com/your_name/your_unique_repo.git

virtualenv venv

source venv/Scripts/activate

pip install dash plotly Flask pandas gunicorn psycopg2-binary SQLAlchemy Flask-SQLAlchemy

# -*- coding:utf-8 -*-

from flask import Flask

app = Flask(__name__)

@app.route('/')
def index():
    return "Hello World"

pip freeze > requirements.txt

$ ls
app.py  Procfile  README.md  requirements.txt  runtime.txt  venv/

from app import app

if __name__ == "__main__":
    app.run(threaded=True, port=5000)

heroku login
heroku create your_project_repo
git add .
git commit -m "initial updated"
git push # github repo에 추가
git push heroku main

$ git clone https://github.com/your_id/python_dash_sales.git

C:\Program Files\heroku\bin

$ heroku -v
heroku/7.53.0 win32-x64 node-v12.21.0
(base)

$ heroku login
heroku: Press any key to open up the browser to login or q to exit:
Opening browser to https://cli-auth.heroku.com/auth/cli/browser/93982084-f22f-4a6b-b347-94f1aa4b6b47?requestor=SFMyNTY.g2gDbQAAAA4xMTIuMTQ0LjIyOC43Nm4GACiKMnR9AWIAAVGA.j9hng63oLOpCVOcHcWyOYDqT4s11jMHDtEesGw5xUD4
heroku: Waiting for login...
Logging in... done
Logged in as your_email@gmail.com

$ git clone https://github.com/your_name/heroku-app-green.git

$ heroku create heroku-app
 »   Warning: heroku update available from 7.53.0 to 7.59.2.
Creating heroku-app... !
 !    Name heroku-app is already taken                   

$ heroku create heroku-app-green
 »   Warning: heroku update available from 7.53.0 to 7.59.2.
Creating heroku-app-green... done
https://heroku-app-green.herokuapp.com/ | https://git.heroku.com/heroku-app-green.git
(base)

$ heroku login
heroku: Press any key to open up the browser to login or q to exit: 
Opening browser to https://cli-auth.heroku.com/auth/cli/browser/9320abcd-b8c6-406d-9198-ca14d1e59a26?requestor=SFMyNTY.g2gDbQAAAA4yMjEuMTU3LjM3LjIxNm4GAGgtTBB7AWIAAVGA.GlyVc8jbyiW6NG0MVzCS0bOjtzBWvYRfjB9-gnkQaoQ
Logging in... done
Logged in as your_email_address

$ heroku git:remote -a your_app
 »   Warning: heroku update available from 7.53.0 to 7.59.2.
set git remote heroku to https://git.heroku.com/heroku-app-green.git

import pandas as pd
import re

def text_cleanser(FILE_PATH):
    with open(FILE_PATH, 'r') as f:
        logLines = f.read().splitlines()
    cleaned_lines = [x for x in logLines if "CPU utilization" in x]
    clean_text = re.sub('/[0-9]%', '', cleaned_lines[0])
    print("temp:", clean_text)
    result_list = re.findall("\d+", clean_text)
    return result_list
        
FILE_PATH = "data/cpu_test.txt"
result_list = text_cleanser(FILE_PATH)
result_list

temp: CPU utilization for five seconds: 4%; one minute: 3%; five minutes: 3%
['4', '3', '3']

data = pd.DataFrame({"분류":["cpu"],
                     "점검내용": ["CPU 사용률 점검 및 불필요한 프로세스 확인"],
                     "점검기준": ["MEM 임계치: 70% (MAX)"],
                     "점검방법": ["show processes cpu | in five"],
                     "5초 동안 CPU 사용률": [result_list[0]], 
                     "1분 동안 CPU 사용률": [result_list[1]], 
                     "5분 동안 CPU 사용률": [result_list[2]], 
                    })
data

# 크롤링 라이브러리
from bs4 import BeautifulSoup
import requests
import re

# 데이터프레임
import pandas as pd

# 샘플 URL을 적용한다. 
url = "https://news.naver.com/main/read.naver?mode=LSD&mid=shm&sid1=100&oid=022&aid=0003609357" 

def get_df(url):
    # 댓글을 달 빈 리스트를 생성합니다.
    List = []
    url = url
    oid = url.split("oid=")[1].split("&")[0]
    aid = url.split("aid=")[1]
    page = 1
    header = {
        "User-agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/65.0.3325.181 Safari/537.36",
        "referer": url,

    }
    while True:
        c_url = "https://apis.naver.com/commentBox/cbox/web_neo_list_jsonp.json?ticket=news&templateId=default_society&pool=cbox5&_callback=jQuery1707138182064460843_1523512042464&lang=ko&country=&objectId=news" + oid + "%2C" + aid + "&categoryId=&pageSize=20&indexSize=10&groupId=&listType=OBJECT&pageType=more&page=" + str(
            page) + "&refresh=false&sort=FAVORITE"
    # 파싱하는 단계입니다.
        r = requests.get(c_url, headers=header)
        cont = BeautifulSoup(r.content, "html.parser")
        total_comm = str(cont).split('comment":')[1].split(",")[0]

        match = re.findall('"contents":([^\*]*),"userIdNo"', str(cont))
        # 댓글을 리스트에 중첩합니다.
        List.append(match)

        # 한번에 댓글이 20개씩 보이기 때문에 한 페이지씩 몽땅 댓글을 긁어 옵니다.
        if int(total_comm) <= ((page) * 20):
            break
        else:
            page += 1

		# 
    def flatten(l):
        flatList = []
        for elem in l:
        # if an element of a list is a list
        # iterate over this list and add elements to flatList
            if type(elem) == list:
                for e in elem:
                    flatList.append(e)
            else:
               flatList.append(elem)
        return flatList

    # 리스트 결과입니다.
    # print(flatten(List))

    # convert dataframe
    data = pd.DataFrame(flatten(List), columns=["기사댓글"])
    data = data.rename_axis("index").reset_index()

    # write_excel
    # data.to_excel("news_comments.xlsx", sheet_name="Sheet1")
    return data

# data = get_df(url) # URL 테스트 시, 실행 
data = pd.DataFrame({"index": [0], "기사댓글": ["댓글"]}) # 앱 배포시 실행
# print(data.head())

import pandas as pd
train_df = pd.read_csv("train.csv")

id  level                                           full_log
0   0      0  Sep 24 10:02:22 localhost kibana: {"type":"err...
1   1      0  Feb  8 16:21:00 localhost logstash: [2021-02-0...
2   2      0  Jan 13 01:50:40 localhost kibana: {"type":"err...
3   3      0  Jan  4 10:18:31 localhost kibana: {"type":"err...
4   4      1  type=SYSCALL msg=audit(1603094402.016:52981): ...

index     cnt
0  type=SYSCALL  116496
1           Jan    3019
2           Oct    2904
3           Nov    2646
4           Feb    2381

def get_df(data, level=0):

    # pandas dataframe
    lvl_df = data.loc[data.level == level].full_log.apply(lambda x: x.split(' ')[0]).value_counts().rename(
        'cnt').to_frame().reset_index()

    return lvl_df

data = get_df(train_df, level = 1)
print(data.head())
index     cnt
0  type=SYSCALL  116496
1           Jan    3019
2           Oct    2904
3           Nov    2646
4           Feb    2381

C:.
│  .gitignore
│  app.py
│  README.md
│
│
├─assets
│      style.css
│
├─data
│      train.csv

import dash
import dash_table
import dash_core_components as dcc
import dash_html_components as html
import pandas as pd
from dash.dependencies import Input, Output

# 함수 정의
def get_df(data, level=0):
    # pandas dataframe
    lvl_df = data.loc[data.level == level].full_log.apply(lambda x: x.split(' ')[0]).value_counts().rename(
        'cnt').to_frame().reset_index()

    return lvl_df

DATA_PATH = "data/"
train_df = pd.read_csv(DATA_PATH + "train.csv")
print(train_df.head())

data = get_df(train_df, level=1)
print(data.head()) # 결과치가 잘 나오는지 확인하다. 

.
.
external_stylesheets = [
    {
        "href": "https://fonts.googleapis.com/css2?"
                "family=Lato:wght@400;700&display=swap",
        "rel": "stylesheet",
    },
]
app = dash.Dash(__name__, external_stylesheets=external_stylesheets)
app.title = "Temp Analytics: Understand Your Data!"

app.layout = html.Div(
    html.P("Hello World")
)

if __name__ == "__main__":
	app.run_server(debug=True)

id  level                                           full_log
0   0      0  Sep 24 10:02:22 localhost kibana: {"type":"err...
1   1      0  Feb  8 16:21:00 localhost logstash: [2021-02-0...
2   2      0  Jan 13 01:50:40 localhost kibana: {"type":"err...
3   3      0  Jan  4 10:18:31 localhost kibana: {"type":"err...
4   4      1  type=SYSCALL msg=audit(1603094402.016:52981): ...
          index     cnt
0  type=SYSCALL  116496
1           Jan    3019
2           Oct    2904
3           Nov    2646
4           Feb    2381
Dash is running on http://127.0.0.1:8050/

.
.
app.layout = html.Div(
	children=[
        html.Div(
            children=[
                html.P(children="📈", className="header_emoji"),
                html.H1(children="Temp Analytics", className="header_title", ),
                html.P(children="Temp", className="header_description", ),
            ],
            className='header',
        ),
	]
)
.
.

C:\Users\1\Desktop\dashboard-project21>tree /f
폴더 PATH의 목록입니다.
볼륨 일련 번호는 E657-CFA3입니다.
C:.
│  README.md
│
└─data
        avocado.csv

$ conda create --name dashboard-project21 python=3.8
.
.
$ conda activate dashboard-project21
(dashboard-project21) C:\Users\1\Desktop\dashboard-project21>

$ conda install dash
$ conda install pandas
$ conda install colorama

import dash
import dash_core_components as dcc
import dash_html_components as html
import pandas as pd

# step 1. Data Import
data = pd.read_csv("avocado.csv", index_col=0)
data = data.query("type == 'conventional' and region == 'Albany'")
data["Date"] = pd.to_datetime(data["Date"], format="%Y-%m-%d")
data.sort_values("Date", inplace=True)

# step 2. Dash Class
app = dash.Dash(__name__)

# step 3. HTML
app.layout = html.Div(
	  # Header Message
    children=[
        html.H1(children="Temp Analytics",),
        html.P(
            children="Temp",
        ),
        # 그래프		
        dcc.Graph(
            figure={
                "data": [
                    {
                        "x": data["Date"],
                        "y": data["AveragePrice"],
                        "type": "lines",
                    },
                ],
                "layout": {"title": "Title_1"},
            },
        ),
        dcc.Graph(
            figure={
                "data": [
                    {
                        "x": data["Date"],
                        "y": data["Total Volume"],
                        "type": "lines",
                    },
                ],
                "layout": {"title": "Title_2"},
            },
        ),
    ]
)