如何撈取台美股所有的股號的資料並儲存於SQLite? Part 1

步驟1

• 於stocksymbol註冊帳號並獲取API金鑰。

• 於Colab筆記本中安裝stocksymbol。

!pip install stocksymbol

步驟2

• 在存取於Google Drive中的SQLite資料庫Stock.db中建立資料表Tickers。

import sqlite3

con = sqlite3.connect('/content/drive/MyDrive/data/Stock.db')

cursor = con.cursor()

query = """
CREATE TABLE "Tickers"
(
    [symbol] varchar(50) NOT NULL,
    [longName] varchar(255) ,
    [exchange] varchar(255) ,
    [market] varchar(255),
    PRIMARY KEY(symbol)
)
"""

cursor.execute(query)

con.commit()

cursor.close()

步驟3

• 開始對於所有股票代碼進行撈取並轉換成DataFrame。

from stocksymbol import StockSymbol

api_key = 'Your API Key'
ss = StockSymbol(api_key)

# get symbol list based on market
symbol_list_us = ss.get_symbol_list(market="US")
symbol_list_tw = ss.get_symbol_list(market="TW")

import pandas as pd

df_us = pd.DataFrame(symbol_list_us)
df_tw = pd.DataFrame(symbol_list_tw)

步驟4

• 將獲取的訊息存入Stock.db中的資料表Tickers。

con = sqlite3.connect('/content/drive/MyDrive/data/Stock.db')

for row in df_us.to_records(index=False):
  con.execute(" INSERT INTO Tickers (symbol, longName, exchange, market) VALUES (?, ?, ? ,?) ", (str(row[0]),str(row[2]), str(row[3]) , str(row[4])) )
con.commit()

for row in df_tw.to_records(index=False):
  con.execute(" INSERT INTO Tickers (symbol, longName, exchange, market) VALUES (?, ?, ? ,?) ", (str(row[0]),str(row[2]), str(row[3]) , str(row[4])) )
con.commit()

我們獲取一萬多筆資料，在接下來的文章，我們將會對此資料進行像是PE, moving average等相關資料的撈取。

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