import pandas as pd
import codecs
import csv
def load_staff_date():
    dates=[
            [1,'Alex Li',22,'<13651054608>','IT','2013‐04‐01'],
            [2,'Jack Wang',28,'<13451024608>','HR','2015‐01‐07'],
            [3,'Rain Wang',21,'<13451054608>','IT','2017‐04‐01'],
            [4,'Mack Qiao',44,'<15653354208>','Sales','2016‐02‐01'],
            [5,'Rachel Chen',23,'<13351024606>','IT','2013‐03‐16'],
            [6,'Eric Liu',19,'<18531054602>','Marketing','2012‐12‐01'],
            [7,'Chao Zhang',21,'<13235324334>','Administration','2011‐08‐08'],
            [8,'Kevin Chen',22,'<13151054603>','Sales','2013‐04‐01'],
            [9,'Shit Wen',20,'<13351024602>','IT','2017‐07‐03'],
            [10,'Shanshan Du',26,'<13698424612>','Operation','2017‐07‐02']
    ]
    fileName = 'StaffDate.csv'
    filenames = ['staff_id',"name","age","phone_number","dept","enroll_date"]

    data = pd.DataFrame(columns=filenames)
    data.to_csv('StaffDate.csv', mode='w+', index=False, encoding='utf-8')

    with codecs.open(fileName, ' a+ ' , ' utf-8') as csvfile:
        csv_write = csv.writer(csvfile)
        for dateline in dates:
            csv_write.writerow(dateline)
    # df = pd.read_csv(fileName)
    # df.head(10)


def find_data(cmd):
    factor, term, require, condition = cmd.split()[1], cmd.split()[5], cmd.split()[6], cmd.split()[7]
    df = pd.read_csv("StaffDate.csv")

    if condition.isdigit():
        condition = int(condition)
    else:
        condition = condition.upper()[1:-1]
    # 設定flag標記語句第一個字串是否為*
    flag = 1
    if factor == '*':
        flag = 0
    if flag == 1:
        factor = factor.split(',')

    if require == '=':
        finds = df[df[term] == condition]
        if flag == 1:
            for word in factor:
                print(word)
                print(finds[word])
        else:
            print(finds)

    elif require == 'like':
        test = []
        Test = []
        with open("StaffDate.csv", 'r', encoding='utf-8')as f:
            read = csv.reader(f)
            for i, line in enumerate(read):
                if len(line) == 6:
                    test.append(line)
                    i += 1
            #         print(test)
            for i, line in enumerate(test):
                if line[5][0:4] == str(condition):
                    Test.append(line)
            for line in Test:
                print(line)

    elif require == '>':
        print(2)
        finds = df[df[term] > condition]
        if flag == 1:
            for word in factor:
                print(finds[word])
        else:
            print(finds)

    else:
        print(3)
        finds = df[df[term] < condition]
        if flag == 1:
            for word in factor:
                print(finds[word])
        else:
            print(finds)


def del_staff_data(number):
    df = pd.read_csv('StaffDate.csv')
    df = df[~df['staff_id'].isin([number])]
    count = len(df['staff_id'])
    print(df.head(count))
    #df.to_csv('StaffDate.csv', mode='w+', index=False, encoding='utf-8')


def add_staff_data(cmd):
    '''
    對add staff_table Alex Li,25,134435344,IT,2015‐10‐29進行處理只擷取
    後面的Alex Li,25,134435344,IT,2015‐10‐29賦值為臨時變數b，並整合Alex 和Li
    還有 對電話加上尖括號，因為csv檔案處理長整形時會自動轉為科學計演算法。

    '''
    cmd_mid = cmd.split()[2]
    cmd_last = list(cmd.split()[3].split(','))
    cmd_last[0] = cmd_mid + " " + cmd_last[0]
    cmd_last[2] = "<" + cmd_last[2] + '>'

    name, age, phone, dept, enroll_date = cmd_last[0], cmd_last[1], cmd_last[2], cmd_last[3], cmd_last[4]
    df = pd.read_csv('StaffDate.csv')

    for ph in df['phone_number']:
        if phone == ph:
            print("該電話已存在")
            exit()

    count = len(df['staff_id']) + 1
    df.loc[count, :] = [count, name, age, name, dept, enroll_date]
    print(df.head(count))
    #df.to_csv('StaffDate.csv', mode='w+', index=False, encoding='utf-8')


def update_staff_data(contact, current_group, current_value):
    Test = contact.split('=')
    target_group = Test[0]
    target_value = Test[1]

    # 去除‘’
    if target_value.isdigit():
        pass
    else:
        target_value = target_value[1:-1]

    current_value = current_value[1:-1]
    df = pd.read_csv('StaffDate.csv')

    # 這裡預設只有dept這一列是全改其他都是改一個
    if target_group == 'dept':
        target_value = target_value.title()
        current_value = current_value.upper()
        df['dept'] = df['dept'].replace([current_value], [target_value])

    elif target_group == 'age':
        current_value = current_value.title()
        replace_value = int(df[df[current_group].isin([current_value])][target_group])

        df[df[current_group].isin([current_value])] = df[df[current_group].isin([current_value])].replace(
            [replace_value], [target_value])

    count = len(df['staff_id'])
    print(df.head(count))
    #df.to_csv('StaffDate.csv', mode='w+', index=False, encoding='utf-8')


def syntax_parser(cmd):
    if 'add' == cmd.split()[0]:
        if cmd.split()[1] == "staff_table":
            add_staff_data(cmd)

    elif 'find' == cmd.split()[0]:
        if cmd.split()[2] == 'from' and cmd.split()[3] == 'staff_table' and cmd.split()[4] == 'where':
            find_data(cmd)

    elif 'del' == cmd.split()[0]:
        if "del from staff where id=" == cmd[0:24]:
            del_staff_data(int(cmd[24:]))

    elif 'update' == cmd.split()[0]:
        if cmd.split()[1] == 'staff_table' and cmd.split()[2] == "set" and cmd.split()[4] == 'where':
            if cmd.split()[5] == 'name':
                Name = cmd.split()[7] + " " + cmd.split()[8]
            else:
                Name = cmd.split()[7]
            update_staff_data(cmd.split()[3], cmd.split()[5], Name)

    else:
        print("語句不合法")


def main():
    load_staff_date()

    cmd = input("請輸入解析語句:").strip(" ").lower()
    syntax_parser(cmd)


if __name__ == '__main__':
    main()