Some util function when doing Taiwan stock web scraping and some common stock data parser.
- Getting the newest stock information from the official website.
- Getting daily stock trading data from the official website.
- Getting daily stock institutional investors data from the official website.
- Getting daily stock margin trading data from the official website.
- Getting p/e ratio, dividend yield and p/b ratio from the official website.
- Getting stock shareholdings data from the official website.
- Check if the date is open date in stock market.
- Convert specific datetime format more easily.
- The following definition of data and variable are all refer to the official website.
- To avoiding banned by the official website, I recommend that users who use tw-stock-plugin set delay time at least three seconds after calling each function.
"""
Attribute:
- code: 股票代碼
- name: 股票名稱
- ISIN_code: 國際證券辨識號碼(ISIN Code)
- listed_date: 上市/上櫃/興櫃 日
- category: 市場別
- industry: 產業別
- CFI_code: CFICode
- type: 證券類別(股票/ETF...)
"""
from tw_stock_plugin import StockInfo, UpdateStock
# update newest stock info
UpdateStock.main()
# init stock info object
stock_info = StockInfo()
# get all stocks info
print(stock_info.get())
# get 1101 stock info
print(stock_info.get('1101'))
# get 1101 stock name
print(stock_info.get('1101').name)
# get 1101 B stock name, it will return value error because it doesn't exists
print(stock_info.get('1101 B'))from datetime import datetime
from tw_stock_plugin import StockTools
# check if 2020/10/10 is open date, it will return False
print(StockTools.check_is_open_date(datetime.strptime('2020/10/10', '%Y/%m/%d').date()))
# check if 2020/10/23 is open date, it will return True
print(StockTools.check_is_open_date(datetime.strptime('2020/10/23', '%Y/%m/%d').date()))
# check if 2020/10/23 is open date, it will type error because it's not type of datetime.time
print(StockTools.check_is_open_date('2020/03/18'))from tw_stock_plugin import StockTools
# convert 109/10/10 to ad, it allow Y/m/d and Y-m-d format
print(StockTools.republic_era_to_ad(date_='109/10/10'))
# convert 2020/10/10 to republic era, it allow Y/m/d and Y-m-d format
print(StockTools.ad_to_republic_era(date_='2020/10/10'))this tool is very useful when crawling tpex api.
"""
You can get all data with specific date or get only single one stock history data.
Attribute:
- Daily Trading Data
- 上市:
- code: 股票代碼
- name: 股票名稱
- trading_volume: 成交股數
- transaction: 成交筆數
- trade_value: 成交金額
- opening_price: 開盤價
- highest_price: 最高價
- lowest_price: 最低價
- closing_price: 收盤價
- change: 漲跌價差
- last_best_bid_price: 最後揭示買價
- last_best_bid_volume: 最後揭示賣價
- last_best_ask_price: 最後揭示買量
- last_best_ask_volume: 最後揭示買量
- price_earning_rate: 本益比
- 上櫃:
- code: 股票代碼
- name: 股票名稱
- closing_price: 收盤價
- change: 漲跌價差
- opening_price: 開盤價
- highest_price: 最高價
- lowest_price: 最低價
- trading_volume: 成交股數
- trade_value: 成交金額
- transaction: 成交筆數
- last_best_bid_price: 最後揭示買價
- last_best_ask_price: 最後揭示買量
- last_best_bid_volume: 最後揭示賣價
- last_best_ask_volume: 最後揭示買量
- issued_shares: 發行股數
- next_limit_up: 次日漲停價
- next_limit_down: 次日跌停價
- Monthly Trading Data
- 上市:
- trading_volume: 成交股數
- transaction: 成交筆數
- trade_value: 成交金額
- opening_price: 開盤價
- highest_price: 最高價
- lowest_price: 最低價
- closing_price: 收盤價
- change: 漲跌價差
- 上櫃:
- closing_price: 收盤價
- change: 漲跌價差
- opening_price: 開盤價
- highest_price: 最高價
- lowest_price: 最低價
- trading_volume: 成交股數
- trade_value: 成交金額
- transaction: 成交筆數
"""
from datetime import datetime
from tw_stock_plugin.core.stock_trading import StockTrading
# setting target date
date_ = datetime(2020, 10, 30).date()
# init stock trading object with specific date
stock_trading = StockTrading(date_=date_)
# getting all trading data in 2020/10/30
trading_all = stock_trading.get_all()
# getting 2330 trading data in 2020/10/30
trading_2330 = trading_all['2330']
# getting monthly history trading data of 1101 in 2020/10
trading_history_1101 = stock_trading.get_history(code=1101)
# getting monthly history trading data of 9962 in 2020/10
trading_history_9962 = stock_trading.get_history(code=9962)"""
You can get all data with specific date.
Attribute:
- code: 股票代碼
- name: 股票名稱
- foreign_mainland_area_buy: 外陸資買進股數(不含外資自營商)
- foreign_mainland_area_sell: 外陸資賣出股數(不含外資自營商)
- foreign_mainland_area_diff: 外陸資買賣超股數(不含外資自營商)
- foreign_buy: 外資自營商買進股數
- foreign_sell: 外資自營商賣出股數
- foreign_diff: 外資自營商買賣超股數
- trust_buy: 投信買進股數
- trust_sell: 投信賣出股數
- trust_diff: 投信買賣超股數
- proprietary_dealers_buy: 自營商買進股數(自行買賣)
- proprietary_dealers_sell: 自營商賣出股數(自行買賣)
- proprietary_dealers_diff: 自營商買賣超股數(自行買賣)
- hedge_dealers_buy: 自營商買進股數(避險)
- hedge_dealers_sell: 自營商賣出股數(避險)
- hedge_dealers_diff: 自營商買賣超股數(避險)
- total_diff: 三大法人買賣超股數
"""
from datetime import datetime
from tw_stock_plugin.core.stock_institutional_investors import StockInstitutionalInvestors
date_ = datetime(2020, 11, 6).date()
# init stock institutional investors object with specific date
stock_institutional_investors = StockInstitutionalInvestors(date_=date_)
# getting all institutional investors data in 2020/10/30
institutional_investors_all = stock_institutional_investors.get_all()
# getting 2330 institutional investors data in 2020/10/30
institutional_investors_2330 = institutional_investors_all['2330']
# getting 3529 institutional investors data in 2020/10/30
institutional_investors_3529 = institutional_investors_all['3529']"""
You can get all data with specific date.
Attribute:
- 上市:
- code: 股票代碼
- name: 股票名稱
- margin_purchase: 融資買進
- margin_sells: 融資賣出
- cash_redemption: 現金償還
- cash_balance_of_previous_day: 前日餘額
- cash_balance_of_the_day: 今日餘額
- cash_quota: 限額
- short_covering: 融券買進
- short_sale: 融券賣出
- stock_redemption: 現金償還
- stock_balance_of_previous_day: 前日餘額
- stock_balance_of_the_day: 今日餘額
- stock_quota: 限額
- offset: 資券互抵
- note: 備註
- 備註欄說明:
O：停止融資
X：停止融券
@：融資分配
%：融券分配
!：停止買賣
- 上櫃:
- code: 股票代碼
- name: 股票名稱
- cash_balance_of_previous_day: 前日餘額
- margin_purchase: 融資買進
- margin_sells: 融資賣出
- cash_redemption: 現金償還
- cash_balance_of_the_day: 今日餘額
- cash_belong_to_securities_finance: 資屬證金
- cash_utilization_rate(%): 資使用率(%)
- cash_quota: 限額
- stock_balance_of_previous_day: 前日餘額
- short_covering: 融券買進
- short_sale: 融券賣出
- stock_redemption: 現金償還
- stock_balance_of_the_day: 今日餘額
- stock_belong_to_securities_finance: 券屬證金
- stock_utilization_rate(%): 券使用率(%)
- stock_quota: 限額
- offset: 資券互抵
- note: 備註
- 備註欄說明
數字(1、2、3…)：合計降低融資比率、提高融券保證金成數
O：停止融資
X：停止融券
@：融資分配
%：融券分配
!：停止買賣
*：融券餘額占融資餘額百分之六十以上者
A：股價波動過度劇烈
B：股權過度集中
C：成交量過度異常
D：監視第二次處置
數字(1、2、3…)：監視業務督導會報決議降低融資比率、提高融券保證金成數
"""
from datetime import datetime
from tw_stock_plugin.core.stock_margin_trading import StockMarginTrading
date_ = datetime(2020, 11, 6).date()
# init stock margin trading object with specific date
stock_margin_trading = StockMarginTrading(date_=date_)
# getting all margin trading data in 2020/10/30
margin_trading_all = stock_margin_trading.get_all()
# getting 2330 margin trading data in 2020/10/30
margin_trading_2330 = margin_trading_all['2330']
# print 2330 margin purchase
print(margin_trading_2330.margin_purchase)
# print 2330 short covering
print(margin_trading_2330.short_covering)
# getting 3529 margin trading data in 2020/10/30
margin_trading_3529 = margin_trading_all['3529']
# print 3529 margin purchase
print(margin_trading_3529.margin_purchase)
# print 3529 short covering
print(margin_trading_3529.short_covering)"""
You can get all data with specific date or get only single one stock history data.
Attribute:
- P/E Ratio Data
- 上市:
- code: 股票代碼
- name: 股票名稱
- yield_ratio: 殖利率(%)
- dividend_year: 股利年度
- per: 本益比
- pbr: 股價淨值比
- fiscal_year_quarter: 財報年/季
- 上櫃:
- code: 股票代碼
- name: 股票名稱
- yield_ratio: 殖利率(%)
- dividend_year: 股利年度
- per: 本益比
- pbr: 股價淨值比
- dividend_per_share: 每股股利
- Monthly P/E Ratio Data
- 上市:
- yield_ratio: 殖利率(%)
- dividend_year: 股利年度
- per: 本益比
- pbr: 股價淨值比
- fiscal_year_quarter: 財報年/季
- 上櫃:
- yield_ratio: 殖利率(%)
- dividend_year: 股利年度
- per: 本益比
- pbr: 股價淨值比
"""
from datetime import datetime
from tw_stock_plugin.core.stock_peratio import StockPERatio
date_ = datetime(2020, 11, 6).date()
# init stock p/e ratio, dividend yield and p/b ratio object with specific date
stock_p_e_ratio = StockPERatio(date_=date_)
# getting all p/e ratio, dividend yield and p/b ratio data in 2020/10/30
p_e_ratio_all = stock_p_e_ratio.get_all()
# getting 2330 p/e ratio, dividend yield and p/b ratio data in 2020/10/30
p_e_ratio_2330 = p_e_ratio_all['2330']
# print 2330 pbr
print(p_e_ratio_2330.pbr)
# print 2330 per
print(p_e_ratio_2330.per)
# getting monthly history p/e ratio, dividend yield and p/b ratio data of 1101 in 2020/10
p_e_ratio_history_1101 = stock_p_e_ratio.get_history(code=1101)
# get only 2020/10/30 p/e ratio, dividend yield and p/b ratio data
print(p_e_ratio_history_1101[date_])
# getting monthly history p/e ratio, dividend yield and p/b ratio data data of 9962 in 2020/10
p_e_ratio_history_9962 = stock_p_e_ratio.get_history(code=9962)
# get only 2020/10/30 p/e ratio, dividend yield and p/b ratio data data
print(p_e_ratio_history_9962[date_])"""
You can get newest data or only specific stock data at specific date.
Attribute:
- date: 日期
- code: 股票代碼
- index: 序
- number_of_shares: 持股/單位數分級
- number_of_shareholders: 人數
- total_shares: 股數/單位數
- percentage_over_total_shares: 占集保庫存數比例 (%)
"""
from datetime import datetime
from tw_stock_plugin.core.stock_shareholdings import StockShareholdings
# init stock shareholdings object
stock_shareholdings = StockShareholdings()
# getting newest shareholdings data
shareholdings_newest = stock_shareholdings.get_newest()
# getting level 1 of 0050 shareholdings data form latest release
print(shareholdings_newest.get('0050')[1])
# getting 0050 shareholdings data at 2020/11/6
shareholdings_0050 = stock_shareholdings.get_by_query(code='0050', date_=datetime(2020, 11, 6).date())
# getting level 15 of 0050 shareholdings data at 2020/11/6
print(shareholdings_0050[15])# -*- coding: utf-8 -*
"""
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┃ ☃ ┃
┃ ┳┛ ┗┳ ┃
┃ ┻ ┃
┗━┓ ┏━┛
┗┳ ┗━┓
┃ ┣┓
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┗┓┓┏━━━━┳┓┏┛
┃┫┫ ┃┫┫
┗┻┛ ┗┻┛
God Bless,Never Bug
"""
from datetime import datetime
from tw_stock_plugin import StockInfo, StockTrading, StockInstitutionalInvestors, StockMarginTrading, StockPERatio, \
StockShareholdings, StockTools, UpdateStock
if __name__ == '__main__':
""" basic info """
# init stock info object
stock_info = StockInfo()
# get all stocks info
print(stock_info.get())
# get 1101 stock info
print(stock_info.get('110'))
# get 1101 stock name
print(stock_info.get('1101').name)
# get 1101 B stock name, it will return value error because it doesn't exists
print(stock_info.get('1101 B'))
# check if 2020/10/10 is open date, it will return False
print(StockTools.check_is_open_date(datetime.strptime('2020/10/10', '%Y/%m/%d').date()))
# check if 2020/10/23 is open date, it will return True
print(StockTools.check_is_open_date(datetime.strptime('2020/10/23', '%Y/%m/%d').date()))
# check if 2020/10/23 is open date, it will type error because it's not type of datetime.time
print(StockTools.check_is_open_date('2020/03/18'))
# convert 109/10/10 to ad, it allow Y/m/d and Y-m-d format
print(StockTools.republic_era_to_ad(date_='109/10/10'))
# convert 2020/10/10 to republic era, it allow Y/m/d and Y-m-d format
print(StockTools.ad_to_republic_era(date_='2020/10/10'))
# setting target date
date_ = datetime(2020, 10, 30).date()
""" daily trading """
# init stock trading object with specific date
stock_trading = StockTrading(date_=date_)
# getting all trading data in 2020/10/30
trading_all = stock_trading.get_all()
# getting 2330 trading data in 2020/10/30
trading_2330 = trading_all['2330']
# print 2330 name
print(trading_2330.name)
# print 2330 code
print(trading_2330.code)
# print 2330 trade_value
print(trading_2330.trade_value)
# print 2330 closing_price
print(trading_2330.closing_price)
# getting monthly history trading data of 1101 in 2020/10
trading_history_1101 = stock_trading.get_history(code=1101)
# get only 2020/10/30 trading data
print(trading_history_1101[date_])
# getting monthly history trading data of 9962 in 2020/10
trading_history_9962 = stock_trading.get_history(code=9962)
# get only 2020/10/30 trading data
print(trading_history_9962[date_])
""" institutional investors """
# init stock institutional investors object with specific date
stock_institutional_investors = StockInstitutionalInvestors(date_=date_)
# getting all institutional investors data in 2020/10/30
institutional_investors_all = stock_institutional_investors.get_all()
# getting 2330 institutional investors data in 2020/10/30
institutional_investors_2330 = institutional_investors_all['2330']
# print 2330 foreign mainland area buy
print(institutional_investors_2330.foreign_mainland_area_buy)
# getting 3529 institutional investors data in 2020/10/30
institutional_investors_3529 = institutional_investors_all['3529']
# print 3529 foreign mainland area buy
print(institutional_investors_3529.trust_diff)
""" margin trading """
# init stock margin trading object with specific date
stock_margin_trading = StockMarginTrading(date_=date_)
# getting all margin trading data in 2020/10/30
margin_trading_all = stock_margin_trading.get_all()
# getting 2330 margin trading data in 2020/10/30
margin_trading_2330 = margin_trading_all['2330']
# print 2330 margin purchase
print(margin_trading_2330.margin_purchase)
# print 2330 short covering
print(margin_trading_2330.short_covering)
# getting 3529 margin trading data in 2020/10/30
margin_trading_3529 = margin_trading_all['3529']
# print 3529 margin purchase
print(margin_trading_3529.margin_purchase)
# print 3529 short covering
print(margin_trading_3529.short_covering)
""" P/E ratio """
# init stock p/e ratio, dividend yield and p/b ratio object with specific date
stock_p_e_ratio = StockPERatio(date_=date_)
# getting all p/e ratio, dividend yield and p/b ratio data in 2020/10/30
p_e_ratio_all = stock_p_e_ratio.get_all()
# getting 2330 p/e ratio, dividend yield and p/b ratio data in 2020/10/30
p_e_ratio_2330 = p_e_ratio_all['2330']
# print 2330 pbr
print(p_e_ratio_2330.pbr)
# print 2330 per
print(p_e_ratio_2330.per)
# getting monthly history p/e ratio, dividend yield and p/b ratio data of 1101 in 2020/10
p_e_ratio_history_1101 = stock_p_e_ratio.get_history(code=1101)
# get only 2020/10/30 p/e ratio, dividend yield and p/b ratio data
print(p_e_ratio_history_1101[date_])
# getting monthly history p/e ratio, dividend yield and p/b ratio data data of 9962 in 2020/10
p_e_ratio_history_9962 = stock_p_e_ratio.get_history(code=9962)
# get only 2020/10/30 p/e ratio, dividend yield and p/b ratio data data
print(p_e_ratio_history_9962[date_])
""" shareholdings """
# init stock shareholdings object
stock_shareholdings = StockShareholdings()
# getting newest shareholdings data
shareholdings_newest = stock_shareholdings.get_newest()
# getting level 1 of 0050 shareholdings data form latest release
print(shareholdings_newest.get('0050')[1])
# getting 0050 shareholdings data at 2020/11/6
shareholdings_0050 = stock_shareholdings.get_by_query(code='0050', date_=datetime(2020, 11, 6).date())
# getting level 15 of 0050 shareholdings data at 2020/11/6
print(shareholdings_0050[15])
# update newest stock info
UpdateStock.main()
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