def toCsv(data_path, result_path, stock=None, year=None):
weak_path = os.path.join(data_path, 'csv', 'strategy', '', 'yesterday_red')
if stock is None:
stock = data.Stock(os.path.join(data_path, 'csv', 'stock'))
stock.readAll()
dates = stock.dates()
if year is None:
year = "*"
else:
year += "*"
result = []
for dir_path in sorted(glob.glob(os.path.join(weak_path, year)),
reverse=False):
if os.path.isdir(dir_path) == False:
continue
for csv_path in sorted(glob.glob(os.path.join(dir_path, "*.csv")),
reverse=False):
date = os.path.basename(csv_path).split('.')[0]
print(date)
date = dates[dates.index(date) + 1]
for index, value in pd.read_csv(csv_path).iterrows():
increase = value[f"y_{name.INCREASE}"]
if increase >= 10.5:
continue
open = value[f"y_{name.OPEN}"]
close = value[f"y_{name.CLOSE}"]
code = value[name.CODE]
[otp, ot] = tick(open)
[ctp, ct] = tick(close)
if ot == ct:
t = round((close - open) / ot)
else:
t = round((otp - open) / ot) + round((close - otp) / ct)
result.append([
code, date, increase, value[f"y_{name.AMPLITUDE}"], t,
round(((close - open) / open) * 100,
2), open, close, value[f"y_{name.HIGH}"],
value[f"y_{name.LOW}"], value[f"y_{name.VOLUME}"]
])
pd.DataFrame(result,
columns=[
name.CODE, name.DATE, name.INCREASE, name.AMPLITUDE,
'tick', f"c_{name.INCREASE}", name.OPEN, name.CLOSE,
name.HIGH, name.LOW, name.VOLUME
]).to_csv(result_path)
def __init__(self, dir, stock_path):
self.dir = dir
self.trends = {}
self.stock = data.Stock(stock_path)
trend_files = glob.glob(os.path.join(dir, '*.json'))
if len(trend_files) == 0:
for dir in sorted(glob.glob(os.path.join(dir, '*')), reverse=True):
if os.path.isdir(dir):
self.trends[os.path.basename(dir)] = glob.glob(
os.path.join(dir, '*.json'))
else:
self.trends[os.path.basename(dir)] = trend_files
def __init__(self, root, master, w, h, config=None):
ui.process.__init__(self, master, w, h)
self.start_now_date = tk.StringVar()
self.end_date = tk.StringVar()
self.stock = data.Stock(other.stock_csv_path(config))
tk.Label(master, text='日期:', font=ui.FONT).place(x=10, y=10)
tk.Entry(master, textvariable=self.end_date,
font=ui.FONT).place(x=self.ex * 1.5, y=10)
tk.Label(master, text='現在開始年月:', font=ui.FONT).place(x=10, y=self.ey)
tk.Entry(master, textvariable=self.start_now_date,
font=ui.FONT).place(x=self.ex * 1.5, y=self.ey)
tk.Button(master, text='K', font=ui.BTN_FONT,
command=lambda: self.k()).place(x=10, y=self.h * 18)
self.keyEvent(root)
def __init__(self, root, config=None, path=None):
self.root = root
self.size = pyautogui.size()
self.width = self.size.width
self.height = self.size.height
self.dir = ''
self.config = config
self.stock = data.Stock(other.stock_csv_path(config))
self.root.state('zoomed')
self._mainLayout()
self._button_layout()
self._list_layout()
filename = os.path.join(path,
datetime.now().strftime(f"%Y-%m-%d-watch.log"))
logging.basicConfig(level=logging.INFO,
format='%(asctime)s [%(levelname)s] %(message)s',
datefmt='%Y-%m-%d %H:%M:%S',
filename=filename)
def calendarXY(date, dir):
if date in prevDays:
return prevDays[date]
else:
prevDays[date] = []
prevDay = data.Stock(dir).afterDates(date).__len__()
dateT = datetime.fromisoformat(date)
nM = datetime.now().month
nY = datetime.now().year
prevMonth = 0
dayX = 1
dayY = dateT.isocalendar()[1] % 6
if nY != dateT.year:
prevMonth += ((nY - dateT.year) * 12)
if nM != dateT.month:
prevMonth += abs(nM - dateT.month)
if dateT.isocalendar()[2] != 7:
dayX = dateT.isocalendar()[2] + 1
weeks = calendar.Calendar(calendar.SUNDAY).monthdayscalendar(
dateT.year, dateT.month)
for index in range(weeks.__len__()):
if dateT.day in weeks[index]:
dayY = index + 1
d = [prevDay, prevMonth, dayX, dayY]
for v in d:
prevDays[date].append(v)
return d
from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg
import matplotlib.ticker as ticker
import tkinter
from xlsx import trend
from stock import data, name, weak
from ui import pattern
from scipy.interpolate import UnivariateSpline
from tkinter import ttk
from matplotlib.lines import Line2D
from pywinauto.application import Application
import pyautogui
import mplfinance as mpf
from ui import k
d = []
stock = data.Stock("D:\\data\\csv\\stock")
trend = data.Trend("D:\\data\\csv")
# paths = glob.glob(
# os.path.join('D:\\data\\csv\\strategy\\weak\\yesterday_red_trend_high10_low11_left_head', '*', '*.csv'))
#
# for path in sorted(paths, reverse=True):
# date = os.path.basename(path).split('.')[0]
#
# for i, v in pd.read_csv(path).iterrows():
# d.append([
# v['code'],
# v['name'],
# date,
# v['increase'],
# v['d_increase'],
# 統計弱勢股紅黑K比例
import pandas as pd
import glob
import configparser
import os
from stock import name, data
NAME = 'weak_black_red'
config = configparser.ConfigParser()
config.read('../config.ini')
data_path = os.path.abspath(dict(config['path'])['data'])
weak_path = os.path.join(data_path, 'csv', 'strategy', '', 'all')
stock = data.Stock(os.path.join(data_path, 'csv', 'stock'))
stock.readAll()
dates = stock.dates()
result = []
for year in ['2020', '2019', '2018', '2017']:
total = 0
red = 0
red_1_5 = 0
black = 0
for dir_path in sorted(glob.glob(os.path.join(weak_path, year + '*')), reverse=False):
if os.path.isdir(dir_path) == False:
continue
for csv_path in sorted(glob.glob(os.path.join(dir_path, "*.csv")), reverse=False):
date = os.path.basename(csv_path).split('.')[0]
import math
import pyautogui
import time
import pandas as pd
import numpy as np
import os
import glob
from xlsx import cmoney, xq, csv
from stock import data, name
import matplotlib.pyplot as plt
stock = data.Stock('D:\\data\\csv\\stock')
trend = data.Trend("D:\\data\\csv")
data.calendar_xy('2017-01-11', year=2020, month=12) # 47 4 3
data.calendar_xy('2019-01-02') # 24 4 1
data.calendar_xy('2020-01-02') # 12 5 1
data.calendar_xy('2019-01-02', year=2020, month=8) # 19 4 1
data.calendar_xy('2018-09-21', year=2020, month=8) # 23 6 4
d = {}
d1 = []
def DirToCode(path):
for p in glob.glob(f"{path}\\*.csv"):
for i, v in pd.read_csv(p).iterrows():
d1.append(
[v['code'], v['name'],
os.path.basename(p).split('.')[0]])
def __init__(self, dir, csv_dir):
Trend.__init__(self, dir)
self.stock = data.Stock(csv_dir)