@powershell -c "Get-Content '%~0' | Select-Object -Skip 1 | Out-String | Invoke-Expression" & pause&exit
#根据时间获取数据
function Get-Data([datetime]$inputDateTime){
    $d=$inputDateTime.AddDays(-1)
    $utcStr='{0:0000}-{1:00}-{2:00}T16:00:00.000Z' -f $d.Year,$d.Month,$d.Day
    return @('{0:0000}-{1:00}-{2:00} 00:00' -f $inputDateTime.Year,$inputDateTime.Month,$inputDateTime.Day)+(($Script:json.data -match $utcStr)[0] | Select-Object -Skip 1)
}
#批量获取前n天数据
function Get-DataArray([datetime]$beginTime,$last){
    $dataArray=[System.Collections.ArrayList]::new();
    [void]$dataArray.Add((Get-Data -inputDateTime $beginTime))
    for($i=1;$i -lt $last;$i++){
        $inputDateTime=$inputDateTime.AddDays(-1)
        [void]$dataArray.Add((Get-Data -inputDateTime $inputDateTime))
    }
    return $dataArray
}
#URL
$url="https://www.okex.me/v2/spot/instruments/BTC-USDT/candles?granularity=86400&size=1000&t=1592064786686"
$resp=Invoke-WebRequest -UseBasicParsing -Uri $url
#获取JSON
$Script:json=$resp.Content | ConvertFrom-Json
#输入数据
$input=(Read-Host "输入年月日(格式:20200614)").Trim()
$inputDateTime=[System.DateTime]::ParseExact($input,"yyyyMMdd",[cultureinfo]::InstalledUICulture)
#爬取数据
#计算MA7
$MA7=0;
$datas=Get-DataArray -beginTime $inputDateTime -last 7
$datas | foreach { $MA7+=$_[4] }
$MA7=[System.Math]::Round($MA7/7,1)
#计算MA30
$MA30=0;
$datas=Get-DataArray -beginTime $inputDateTime -last 30
$datas | foreach { $MA30+=$_[4] }
$MA30=[System.Math]::Round($MA30/30,1)
'MA7:  '+$MA7
'MA30: '+$MA30
#计算KDJ
#https://baike.baidu.com/item/KDJ%E6%8C%87%E6%A0%87/6328421?fr=aladdin
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#! /usr/bin/env python3
# -*- coding: UTF-8 -*-


import pandas as pd
import requests
import json
import numpy as np
import datetime

api_url = "https://www.okex.me/v2/spot/instruments/BTC-USDT/candles?granularity=86400&size=1000&t=1592091928445"

html = requests.get(api_url)
stock_datas = pd.DataFrame()

for i in json.loads(html.text)['data']:
    date = (datetime.datetime.strptime(i[0].split('T')[0], "%Y-%m-%d") + datetime.timedelta(days=1)).strftime("%Y%m%d")
    df_insert = pd.DataFrame(
        {'date': date, 'open': i[1], 'high': i[2], 'low': i[3], 'close': np.float(i[4]), 'volume': i[5]}, index=[0])
    stock_datas = stock_datas.append(df_insert)

ma_list = [7, 30]  # ma移动平均

for ma in ma_list:
    stock_datas['MA_' + str(ma)] = np.round(pd.Series.rolling(stock_datas['close'], window=ma).mean(), 1)

low_list = stock_datas['low'].rolling(9, min_periods=9).min()
low_list.fillna(value=stock_datas['low'].expanding().min(), inplace=True)
high_list = stock_datas['high'].rolling(9, min_periods=9).max()
high_list.fillna(value=stock_datas['high'].expanding().max(), inplace=True)
rsv = (stock_datas['close'] - low_list) / (high_list - low_list) * 100

stock_datas['K'] = pd.Series.ewm(rsv, com=2).mean()
stock_datas['D'] = pd.Series.ewm(stock_datas['K'], com=2).mean()
stock_datas['J'] = 3 * stock_datas['K'] - 2 * stock_datas['D']

custom_date = input("""
    Example:20200401 2020年04月01日
    Enter datetime please:"""
                    )
result = stock_datas[stock_datas['date'] == custom_date][['date', 'K', 'D', 'J', 'MA_7', 'MA_30']]
if result.__len__() > 0:
    result = "MA7:{}\r\nMA30:{}\r\nK:{}\r\nD:{}\r\nJ:{}\r\n".format(result['MA_7'].values[0], result['MA_30'].values[0],
                                                                    np.round(result['K'].values[0], 2),
                                                                    np.round(result['D'].values[0], 2),
                                                                    np.round(result['J'].values[0], 2))
    print(result)
    with open('a.txt', 'w+') as f:
        f.write(result)
else:
    print("Found nothing!!!")
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