%%time
result, foodId = [], 'I0490'  # 회수요청제품 (400개)
data = FoodSafe().getData(foodId, 1, 1000, FoodSafe().apiKey[foodId]['cols'], display=True)
data.to_excel("data/food_recall.xls", index=None)

%%time
result, foodId = [], 'I0750' # 식품 영양정보
_ = FoodSafe().getData(foodId, 1, 2, FoodSafe().apiKey[foodId]['cols'], display=True)
# for _ in tqdm(range(1, 13824+1, 1000)):
#     result.append(FoodSafe().getData(foodId, _, _+999, FoodSafe().apiKey[foodId]['cols']))    
# pd.concat(result).to_excel('data/food_nutrient.xls', index=None)

%%time
result, foodId = [], 'COOKRCP01'  # 레시피 데이터
_ = FoodSafe().getData(foodId, 1, 2, FoodSafe().apiKey[foodId]['cols'], display=True)
# for _ in tqdm(range(1, 1500+1, 1000)):
#     result.append(FoodSafe().getData(foodId, _, _+999, FoodSafe().apiKey[foodId]['cols']))
# pd.concat(result).to_excel('data/food_recipe_info.xls', index=None)

%%time
result, foodId = [], 'C005'  # 제품 바코드 번호
# _ = FoodSafe().getData(foodId, 1, 2, FoodSafe().apiKey[foodId]['cols'], display=True)
# for _ in tqdm(range(1, 100200+1, 1000)):
from collections import OrderedDict
for _ in tqdm(range(1, 100200+1, 1000)):
    result.append(FoodSafe().getData(foodId, _, _+999, 
            FoodSafe().apiKey[foodId]['cols']).loc[:,
                list(OrderedDict(FoodSafe().apiKey['C005']['cols']).values())])
pd.concat(result).to_csv('data/food_barcode.csv', index=None)
pd.concat(result).to_excel('data/food_barcode.xls', index=None)

%%time
result, foodId = [], "I2570"  # 유통 바코드
_ = FoodSafe().getData(foodId, 1, 2, FoodSafe().apiKey[foodId]['cols'], display=True)
# for _ in tqdm(range(1, 49000+1, 1000)):
#     result.append(FoodSafe().getData(foodId, _, _+999, FoodSafe().apiKey[foodId]['cols']))
# pd.concat(result).to_excel('data/food_barcode_info.xls', index=None)

%%time
from momukji import Kamis
Kamis().getData('2019-10-15', "100").head()

%%time
from momukji import Kamis
Kamis().getData('2019-10-15', "100" ,types=2).head()

from momukji import Kamis
resp = Kamis().getApi('2019-10-21', 500, cd=2)
resp.head(3)

# 문제점...
# Page 를 순환하면서 1개의 객체만 있으면 list 갯수가 1개로만 출력

# 해결방법... (https://rfriend.tistory.com/482)
# 1개의 dict 을 DataFrame 변환 시, 데이터를 list로 변경해서 적용
# 그래야 컬럼, 데이터와 "인덱스" 를 자동으로 계산할 수 있다.

date_info = '20191022'

import pandas as pd
from momukji import Garak
xml_d_1   = Garak().getData(cd=1) # date_info, 
xml_d_2   = Garak().getData(cd=2) # date_info, 
xml_data  = pd.concat([xml_d_1, xml_d_2]).reset_index(drop=True)
xml_data.to_excel("data/food_Garak.xls", index=None)

# https://www.garakprice.com/index.php?go_date=20191021
from urllib import parse, request
def urllib_request(url, params, encode='utf-8'):
    params = parse.urlencode(params).encode(encode)
    url  = request.Request(url, params)
    resp = request.data/lopen(url).read()
    resp = parse.quote_plus(resp)
    return parse.unquote_plus(resp)

# params = { "go_date":20191021 }
# url    = "https://www.garakprice.com/index.php"
# urllib_request(url, params)[:500]

from momukji import Product
item_list = Product().getList()
item_list.head(3)

url = "http://ksetup.com/bbs/page.php?hid=code"

import re
import pandas as pd
from urllib import request, parse
resp = request.urlopen(url).read()
resp = parse.quote_plus(resp)
resp = parse.unquote_plus(resp)
table = re.findall(r'<table class="table table-bordered".*?>(.*?)</table>', resp, re.M|re.I|re.S)
table = "<table>" + table[0] + "</table>"
table = pd.read_html(table)[0]
# table.to_excel('company_code.xls', index=None, columns=None)
table.head(3)

"{:02d}".format(2)

query = {
    "schulCode":"F100000120",
    "schulCrseScCode":4,
    "schulKndScCode":"04",
    "ay":2019,  # 년도
    "mm":10     # 월
}
from urllib import parse, request
url = "https://stu.gen.go.kr/sts_sci_md00_001.do?" + parse.urlencode(query)
resp = request.urlopen(url).read()
resp = parse.quote_plus(resp)
resp = parse.unquote_plus(resp)
resp[:200]

import re
re.findall()

, "/sts_sci_md00_001.do?"

from menu_parser import MenuParser
from school import School
school = School(School.Region.GWANGJU, School.Type.HIGH, "F100000120")
parser = MenuParser(school)
menus  = parser.get_menu()
print(menus.today)

class School:
    class Region:
        BUSAN = "stu.pen.go.kr"
        CHUNGBUK = "stu.cbe.go.kr"
        CHUNGNAM = "stu.cne.go.kr"
        DAEJEON = "stu.dge.go.kr"
        DEAGU = "stu.dge.go.kr"
        GWANGJU = "stu.gen.go.kr"
        GYEONGBUK = "stu.gbe.go.kr"
        GYEONGGI = "stu.goe.go.kr"
        GYEONGNAM = "stu.gne.go.kr"
        INCHEON = "stu.ice.go.kr"
        JEJU = "stu.jje.go.kr"
        JEONBUK = "stu.jbe.go.kr"
        JEONNAM = "stu.jne.go.kr"
        KANGWON = "stu.kwe.go.kr"
        SEJONG = "stu.sje.go.kr"
        SEOUL = "stu.sen.go.kr"
        ULSAN = "stu.use.go.kr"

    class Type:
        KINDERGARTEN = 1
        ELEMENTARY = 2
        MIDDLE = 3
        HIGH = 4

    def __init__(self, school_region, school_type, school_code):
        self.region = school_region
        self.type = school_type
        self.code = school_code

school = School(School.Region.GWANGJU, School.Type.HIGH, "F100000120")
school

class MenuParser:
    
    def __init__(self, school):
        self.school = school

    def get_menu(self, year=None, month=None):
        """
        해당 학교로부터 급식을 가져온다.
        year와 month가 모두 주어졌다면 해당하는 정보를 가져온다.
        주어지지 않았을 때에는 자동으로 가져오게 된다.
        """
        if year is None or month is None:
            today = datetime.date.today()
            url = self.__create_url(today.year, today.month)
        else:
            url = self.__create_url(year, month)
        page = self.__get_page(url); print(url)
        soup = BeautifulSoup(page, "html.parser")
        items = soup.select("#contents > div > table > tbody > tr > td > div")
        return Menu(items)

    def __get_page(self, url):
        try:
            page = requests.get(url).text 
        except Exception as e:
            logging.error(e)
        return page

    def __create_url(self, year, month):
        today = datetime.date(year, month, 1)
        url  = f"https://{self.school.region}/sts_sci_md00_001.do?"
        url += f"schulCode={self.school.code}&"
        url += f"schulCrseScCode={self.school.type}&"
        url += f"schulKndScCode={self.school.type:02d}&"
        url += f"ay={today.year}&"
        url += f"mm={today.month:02d}"
        print(url)
        return url

parser = MenuParser(school)
parser

def __create_url(self, year, month):
    today = datetime.date(year, month, 1)
    url  = f"https://{self.school.region}/sts_sci_md00_001.do?"
    url += f"schulCode={self.school.code}&"
    url += f"schulCrseScCode={self.school.type}&"
    url += f"schulKndScCode={self.school.type:02d}&"
    url += f"ay={today.year}&"
    url += f"mm={today.month:02d}"
    print(url)
    return url

# 교육청 코드
school.region

# 학교종류
school.type

# 개별 학교코드
school.code

"schulKndScCode={:02d}".format(4)

parser = MenuParser(school)

parser.

temp = datetime.today()
temp.strftime('%Y%m%d')

datetime.strftime(temp, '%Y%m%d')

query = {
    "KeyWord":"파이썬", #"%C6%C4%C0%CC%BD%E3",
    "ViewType":"Detail",
    "SortOrder":5,  # 5:출시일순, 11:등록순
    "ViewRowCount":50,
    "page":2,    
}

url = "https://www.aladin.co.kr/search/wsearchresult.aspx?SearchTarget=UsedStore"
from urllib import parse, request
params = parse.urlencode(query).encode('cp949') # Params 인코딩 변환
resp   = request.Request(url, params)           # url 주소값 생성
resp   = request.urlopen(resp).read()           # url 을 활용한 response 수집
resp   = parse.quote_plus(resp)                 # response 의 byte 를 string 변환
resp   = parse.unquote_plus(resp, encoding='cp949') # string 인코딩 변환 (default='utf-8')

with open('book.html','w') as f:
    f.write(resp)

# decoding (기본값 utf-8)
parse.unquote_plus('%C4%F6%C6%AE', encoding='cp949')

# encodings
parse.quote_plus("퀀트", encoding='cp949')

# <div class="Search3_Pager">
#     <table 

with open("data/food_recipie.json", "r", encoding='utf-8-sig') as f:
    recipe = f.read()

import json
food_data = json.loads(recipe)
foods = [_ for _ in food_data.keys()]

food_data[foods[0]]

import codecs
decoded_data=codecs.decode(r.text, 'utf-8-sig')