# with open(file_path, "rt") as f:
#     reader = csv.DictReader(f)
#     for item in reader:
#         db_bar.symbol = symbol
#         db_bar.exchange = exchange.value
#         db_bar.datetime = datetime.strptime(
#             item[datetime_head], datetime_format
#         )
#         db_bar.interval = interval.value
#         db_bar.volume = item[volume_head]
#         db_bar.open_price = item[open_head]
#         db_bar.high_price = item[high_head]
#         db_bar.low_price = item[low_head]
#         db_bar.close_price = item[close_head]
#         db_bar.vt_symbol = vt_symbol
#         db_bar.gateway_name = "DB"
#
#         db_bar.replace()


# #----------
# from vnpy.app.csv_ loader.engine import CsvLoaderEngine
# from vnpy.event import EventEngine
# from vnpy.trader.constant import Exchange, Interval
# from vnpy.trader.engine import MainEngine
# import os
# symbol_list=os.listdir('D:/data/')
# #print(symbol_list)
# a=CsvLoaderEngine(MainEngine,EventEngine)
# for symbol in symbol_list:
#     print(symbol[:-4])
#     a.load(
#             file_path="D:/data/"+symbol,
#             symbol=symbol[:-4],
#             exchange=Exchange.OANDA,
#             interval=Interval.DAILY,
#             datetime_head="time",
#             open_head="o",
#             high_head="h",
#             low_head="l",
#             close_head="c",
#             volume_head="v",
#             datetime_format="%Y-%m-%dT%H:%M:%S.000000000Z")
#-----------
''' def dt_trun(t0):
#     # t0 = imported_data['datetime'][0]
#     # t0
#     t1 = datetime.strptime(t0, "%Y-%m-%d %H:%M:%S")
#     t1
#     t2=  datetime.strftime( t1,"%Y/%m/%d %H:%M:%S")
#     t2
#
#     # dt_format = '%Y%m%d %H:%M:%S'
#     # t3 = datetime.strptime('2015/04/16 09:16:00', "%Y/%m/%d %H:%M:%S" )
#     # t3
#     return  t2
# #
# # imported_data['datetime']
#     datetime_format = '%Y%m%d %H:%M:%S'
# # dt_trun(imported_data['datetime'])
'''

from vnpy.trader.database.initialize import init_sql
from vnpy.trader.database.database import Driver

settings={

    "database": "database.db",
    "host": "localhost",
    "port": 3306,
    "user": "root",
    "password": "",
    "authentication_source": "admin"
}
sqlite_manager = init_sql(driver=Driver.SQLITE, settings=settings)



from vnpy.trader.constant import (Exchange, Interval)
import pandas as pd
from vnpy.trader.database import database_manager
from vnpy.trader.object import (BarData,TickData)
from datetime import datetime
import time

# 封装函数
def move_df_to_mongodb(imported_data:pd.DataFrame):  # ,collection_name:str
    bars = []
    start = None
    count = 0

    # utc_8 = timezone(timedelta(hours=8))
    # datetime = row.datetime.replace(tzinfo=utc_8)

    for row in imported_data.itertuples():

        bar = BarData(
              symbol=row.symbol,
              exchange=row.exchange,
              datetime=row.datetime,
              interval=row.interval,
              volume=row.volume,
              open_price=row.open,
              high_price=row.high,
              low_price=row.low,
              close_price=row.close,
              open_interest=row.open_interest,
              gateway_name="DB",

        )

        bars.append(bar)

        # do some statistics
        count += 1
        if not start:
            start = bar.datetime
    end = bar.datetime

    # insert into database

    database_manager.save_bar_data(bars)     # , collection_name
    database_manager.save_bar_data()
    print(f'Insert Bar: {count} from {start} - {end}')

if __name__ == "__main__":

    # 读取需要入库的csv文件，该文件是用gbk编码
    imported_data = pd.read_csv('D:/VNPYProject/CU2201.csv',encoding='gbk')
    imported_data = imported_data[['datetime','open', 'high', 'low', 'close','volume']]
    # 将csv文件中 `市场代码`的 SC 替换成 Exchange.SHFE SHFE
    # imported_data['市场代码'] = Exchange.SHFE
    # 增加一列数据 `inteval`，且该列数据的所有值都是 Interval.MINUTE
    # imported_data['interval'] = Interval.MINUTE
    # 明确需要是float数据类型的列
    # float_columns =imported_data.columns
    # # for i in range(0,len(float_columns)):
    # for col in float_columns:
    #     imported_data[col] = imported_data[col].astype('float')
    # 明确时间戳的格式s
    # %Y/%m/%d %H:%M:%S 代表着你的csv数据中的时间戳必须是 2020/05/01 08:32:30 格式
    datetime_format = '%Y%m%d %H:%M:%S'
    # imported_data['datetime'] = pd.to_datetime(imported_data['datetime'],format=datetime_format)
    # xt = [dt_trun(i) for i in imported_data['datetime']]
    # imported_data['datetime'] =  pd.to_datetime(xt)
    # 因为没有用到 成交额 这一列的数据，所以该列列名不变
    # imported_data.columns = ['exchange','symbol','datetime','open','high','low','close','volume','成交额','open_interest','interval']
    imported_data.columns = ['datetime','open','high','low','close','volume']
    imported_data['exchange'] =Exchange.CFFEX
    imported_data['interval'] = Interval.MINUTE
    imported_data['open_interest'] = 0
    imported_data['symbol'] ='IC500'

    move_df_to_mongodb(imported_data)




from vnpy.database.mongodb import MongodbDatabase

from datetime import datetime
from vnpy.trader.constant import Exchange,Interval
from vnpy.trader.database import database_manager
import matplotlib.pyplot as plt


# Load history data
bars =database_manager.load_bar_data(
    symbol="rb2201",
    exchange=Exchange.SHFE,
    interval=Interval.MINUTE,
    start=datetime(2021, 8, 1),
    end=datetime(2021, 8, 26)
    )

# Generate x, y
y = []
for bar in bars:
    close_price = bar.close_price
    y.append(close_price)
x = list(range(1,len(y)+1))

# Show foto
plt.figure(figsize=(40, 20))
plt.plot(x, y)

plt.show()

from vnpy.trader.database import  database_manager
import  vnpy.trader.database.database_mogodb


from urllib.request import urlopen
url = 'https://www.baidu.com/'
for line in urlopen(url):
    line = line.decode('utf-8')  # Decoding the binary data to text.
    for i in line:  # look for Eastern Time
        print(i,end="")