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DBaccess.py
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DBaccess.py
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# -*- coding: utf-8 -*-
import sqlite3
import statistics
import csv
import os
class DBaccess:
dbName = 'trade_history.db' # DB名
tableName_Routes = 'Routes' # 取引1巡ごと
tableName_Trades = 'Trades' # 取引ごと
def __init__(self):
print('DB init...')
con = sqlite3.connect(self.dbName)
# テーブルがなければ作る
# integer + primary keyなら自動連番もする
con.execute("create table if not exists %s("
"num integer primary key,"
"route text not null,"
"prev integer not null,"
"estimate integer not null,"
"profit integer not null)" % (self.tableName_Routes))
con.commit() # トランザクションをコミット
con.execute("create table if not exists %s("
"num integer primary key,"
"route text not null,"
"trade text not null,"
"minutes integer not null,"
"retrades integer not null)" % (self.tableName_Trades))
con.commit()
con.close()
# デバッグ用データ登録テスト
def insertTest(self):
print('insert test...')
con = sqlite3.connect(self.dbName)
con.execute(
"insert into %s(route,prev,estimate,profit)"
"values('JPY->BTC->MONA',3,2,1)" %
(self.tableName_Routes))
con.commit()
con.execute(
"insert into %s(route,trade,minutes,retrades)"
"values('JPY->BTC->MONA','JPY->BTC',2,1)" %
(self.tableName_Trades))
con.commit()
con.execute(
"insert into %s(route,trade,minutes,retrades)"
"values('JPY->BTC->MONA','BTC->MONA',2,1)" %
(self.tableName_Trades))
con.commit()
con.execute(
"insert into %s(route,trade,minutes,retrades)"
"values('JPY->BTC->MONA','MONA->JPY',2,1)" %
(self.tableName_Trades))
con.commit()
con.close()
# 取引1回の結果を登録
def insertTrade(self, route: str, trade: str, minutes: int, retrades: int):
print('insert Trade...')
con = sqlite3.connect(self.dbName)
con.execute(
"insert into %s(route,trade,minutes,retrades)"
"values(?,?,?,?)" %
(self.tableName_Trades),
[route, trade, minutes, retrades])
con.commit()
con.close()
# 取引1巡の結果を登録
def insertRoute(self, route: str, prevJPY: int, estJPY: int, profit: int):
print('insert Route...')
con = sqlite3.connect(self.dbName)
con.execute(
"insert into %s(route,prev,estimate,profit)"
"values(?,?,?,?)" %
(self.tableName_Routes),
[route, prevJPY, estJPY, profit])
con.commit()
con.close()
# DB全データをCSV出力
def exportToCSV(self):
print('exporting to CSV...', end=' ', flush=True)
con = sqlite3.connect(self.dbName)
cur = con.cursor()
cur.execute("select * from %s" % (self.tableName_Routes))
data = cur.fetchall()
csvPath = 'dbData_Route.csv'
if os.path.exists(csvPath):
state = 'w'
else:
state = 'a'
with open(csvPath, state, newline='', encoding='shift-jis') as f:
writer = csv.writer(f)
writer.writerow(['番号', '取引順', '投資額', '予想利益', '損益'])
for row in data:
writer.writerow(row)
cur.execute("select * from %s" % (self.tableName_Trades))
data = cur.fetchall()
csvPath = 'dbData_Trade.csv'
if os.path.exists(csvPath):
state = 'w'
else:
state = 'a'
with open(csvPath, state, newline='', encoding='shift-jis') as f:
writer = csv.writer(f)
writer.writerow(['番号', '取引順', '取引', '経過(分)', '再取引数'])
for row in data:
writer.writerow(row)
con.close()
print('Complete. Ready >')
def statisticsTradeResult(self):
print('read from database and statistics...')
# 損益を格納，平均と標準偏差の計算に使う========================
All_Profits = []
JpyBtcMona_Profits = []
JpyMonaBtc_Profits = []
JpyBtcBch_Profits = []
JpyBchBtc_Profits = []
JpyBtcXem_Profits = []
JpyXemBtc_Profits = []
JpyBtcEth_Profits = []
JpyEthBtc_Profits = []
# 取引時間を格納，平均の計算に使う====================
BTC_JPY_minutes = []
MONA_BTC_minutes = []
MONA_JPY_minutes = []
BCH_BTC_minutes = []
BCH_JPY_minutes = []
XEM_BTC_minutes = []
XEM_JPY_minutes = []
ETH_BTC_minutes = []
ETH_JPY_minutes = []
# 再取引回数を格納，平均の計算に使う==================
BTC_JPY_retrades = []
MONA_BTC_retrades = []
MONA_JPY_retrades = []
BCH_BTC_retrades = []
BCH_JPY_retrades = []
XEM_BTC_retrades = []
XEM_JPY_retrades = []
ETH_BTC_retrades = []
ETH_JPY_retrades = []
profitsList = [] # 損益に関わる統計結果を格納
minutesList = [] # 取引時間に関わる統計結果を格納
retradesList = [] # 再取引回数に関わる統計結果を格納
# DB接続==============================
con = sqlite3.connect(self.dbName)
cur = con.cursor()
# Routesテーブル中身：
# [0]:num
# [1]:route
# [2]:prev
# [3]:estimate
# [4]:profit
cur.execute("select * from %s" % (self.tableName_Routes))
data = cur.fetchall()
for row in data:
All_Profits.append(row[4])
if row[1] == 'JPY->BTC->MONA':
JpyBtcMona_Profits.append(row[4])
elif row[1] == 'JPY->MONA->BTC':
JpyMonaBtc_Profits.append(row[4])
elif row[1] == 'JPY->BTC->BCH':
JpyBtcBch_Profits.append(row[4])
elif row[1] == 'JPY->BCH->BTC':
JpyBchBtc_Profits.append(row[4])
elif row[1] == 'JPY->BTC->XEM':
JpyBtcXem_Profits.append(row[4])
elif row[1] == 'JPY->XEM->BTC':
JpyXemBtc_Profits.append(row[4])
elif row[1] == 'JPY->BTC->ETH':
JpyBtcEth_Profits.append(row[4])
elif row[1] == 'JPY->ETH->BTC':
JpyEthBtc_Profits.append(row[4])
else:
pass
# Tradesテーブル中身：
# [0]:num
# [1]:route
# [2]:trade
# [3]:minutes
# [4]:retrades
cur.execute("select * from %s" % (self.tableName_Trades))
data = cur.fetchall()
for row in data:
if row[2] == 'JPY->BTC' or row[2] == 'BTC->JPY':
BTC_JPY_minutes.append(row[3])
BTC_JPY_retrades.append(row[4])
elif row[2] == 'BTC->MONA' or row[2] == 'MONA->BTC':
MONA_BTC_minutes.append(row[3])
MONA_BTC_retrades.append(row[4])
elif row[2] == 'JPY->MONA' or row[2] == 'MONA->JPY':
MONA_JPY_minutes.append(row[3])
MONA_JPY_retrades.append(row[4])
elif row[2] == 'BTC->BCH' or row[2] == 'BCH->BTC':
BCH_BTC_minutes.append(row[3])
BCH_BTC_retrades.append(row[4])
elif row[2] == 'BCH->JPY' or row[3] == 'JPY->BCH':
BCH_JPY_minutes.append(row[3])
BCH_JPY_retrades.append(row[4])
elif row[2] == 'BTC->XEM' or row[2] == 'XEM->BTC':
XEM_BTC_minutes.append(row[3])
XEM_BTC_retrades.append(row[4])
elif row[2] == 'JPY->XEM' or row[2] == 'XEM->JPY':
XEM_JPY_minutes.append(row[3])
XEM_JPY_retrades.append(row[4])
elif row[2] == 'BTC->ETH' or row[2] == 'ETH->BTC':
ETH_BTC_minutes.append(row[3])
ETH_BTC_retrades.append(row[4])
elif row[2] == 'JPY->ETH' or row[2] == 'ETH->JPY':
ETH_JPY_minutes.append(row[3])
ETH_JPY_retrades.append(row[4])
else:
pass
con.close()
# 損益統計=============================================
tmpList = [All_Profits,
JpyBtcMona_Profits,
JpyMonaBtc_Profits,
JpyBtcBch_Profits,
JpyBchBtc_Profits,
JpyBtcXem_Profits,
JpyXemBtc_Profits,
JpyBtcEth_Profits,
JpyEthBtc_Profits]
for i in range(len(tmpList)):
profitsList.append(self.calcStat(tmpList[i]))
# 取引時間平均=============================================
tmpList = [BTC_JPY_minutes,
MONA_BTC_minutes,
MONA_JPY_minutes,
BCH_BTC_minutes,
BCH_JPY_minutes,
XEM_BTC_minutes,
XEM_JPY_minutes,
ETH_BTC_minutes,
ETH_JPY_minutes]
for i in range(len(tmpList)):
if len(tmpList[i]) > 0:
ave = int(sum(tmpList[i]) / len(tmpList[i]))
else:
ave = '###'
minutesList.append(ave)
# 再取引回数平均=============================================
tmpList = [BTC_JPY_retrades,
MONA_BTC_retrades,
MONA_JPY_retrades,
BCH_BTC_retrades,
BCH_JPY_retrades,
XEM_BTC_retrades,
XEM_JPY_retrades,
ETH_BTC_retrades,
ETH_JPY_retrades]
for i in range(len(tmpList)):
if len(tmpList[i]) > 0:
ave = round(sum(tmpList[i]) / len(tmpList[i]), 2)
else:
ave = '###'
retradesList.append(ave)
# resultList:
# ┌ All Profits JPY->BTC->MONA
# ｜profitsList[ [0,1,2,3,4], [0,1,2,3,4], ...]
# ｜
# ｜ BTC/JPY MONA/BTC MONA/JPY
# ｜minutesList[ 0 , 1 , 2 , ... ]
# ｜retradesList[ 0 , 1 , 2 , ... ]
# └
resultList = [profitsList, minutesList, retradesList]
return resultList
# 損益リストから統計データを計算して結果リストを返す
# [0]:取引回数
# [1]:利益となった回数
# [2]:利益となった割合
# [3]:損益の平均
# [4]:損益の標準偏差
def calcStat(self, profitsList):
Profit_N = 0
Trade_N = len(profitsList)
for i in range(len(profitsList)):
if profitsList[i] > 0:
Profit_N += 1
if Trade_N > 0:
Profit_Rate = int((Profit_N / Trade_N) * 100)
Ave_Profits = int(sum(profitsList) / Trade_N)
else:
Profit_Rate = '###'
Ave_Profits = '###'
if Trade_N > 1:
SD_Profits = round(statistics.stdev(profitsList), 1)
else:
SD_Profits = '###'
resultList = [Trade_N, Profit_N, Profit_Rate, Ave_Profits, SD_Profits]
return resultList