def get_quote():
    pd.set_option('display.width', 200)
    search_quote = input("Enter stock symbol: ")
    try:
        url = 'http://dev.markitondemand.com/MODApis/Api/v2/Quote/json?symbol=' + search_quote
        df = pd.DataFrame([requests.get(url).json()])
        print("\n")
        dropped_columns = ["MSDate", "Status", "Timestamp"]
        df1 = df.drop(dropped_columns, axis="columns")
        df1 = df.drop(dropped_columns, axis="columns")
        df2 = df1
        df1 = df1.reindex(
            ['Symbol', 'Name', 'Open', 'LastPrice', 'Change', 'ChangePercent'],
            axis=1)
        df2 = df2.reindex([
            'Symbol', 'Low', 'High', 'MarketCap', 'ChangePercentYTD',
            'ChangeYTD'
        ],
                          axis=1)

        print("Quote for " + search_quote.upper() + " as of " +
              datetime.now().strftime('%Y-%m-%d %H:%M:%S') + " UTC:\n\n")

        print(th.md_table(df1, formats={-1: 'c'}))
        print("\n" + th.md_table(df2, formats={-1: 'c'}))

    except:
        print("Server not responding. Try again later. ")
        time.sleep(1)
        pass
def leaderboard():
    print("Leaderboard: \n\n")
    with sqlite3.connect('data.db') as db:
        df = pd.read_sql_query('SELECT * from stocks', db)
        df_1 = pd.read_sql_query('SELECT username , bankAccount from users',
                                 db)
        df_1.sort_values(by=['bankAccount'], inplace=True, ascending=False)
        df_1 = df_1.rename(columns={
            'username': "******",
            'bankAccount': "Money:"
        })
        try:
            df_1 = df_1.head(10)
            print(th.md_table(df_1, formats={-1: 'c'}))
        except AttributeError:
            print(th.md_table(df_1, formats={-1: 'c'}))
def company_search():
    search = input("Enter company name or symbol to search: ")
    url = 'http://dev.markitondemand.com/Api/v2/Lookup/json?input=' + search
    data = pd.read_json(url)
    if data.empty:
        print('No results found')
    else:
        print("\nCompany Search Results:\n\n" +
              th.md_table(data, formats={-1: 'c'}))
Ejemplo n.º 4
0
      def __call__(self, t_shape):
        import numpy as np
        n = t_shape[0]
        num_bytes = np.prod(t_shape) * self.dtype_size_bytes
        self.observer.stop_block(n=n, num_bytes=num_bytes)
        self.observer.maybe_log_progress()
        
        # Tensorboard is very picky about wanting Markdown :P
        import tabulatehelper as th
        stats = self.observer.get_stats()
        out = th.md_table(stats, headers=[name])

        self.observer.start_block()
        return out
def view_portfolio():
    #//TO: Use pandas to easily display portfolio
    with sqlite3.connect('data.db') as db:
        # cursor = db.cursor()
        df = pd.read_sql_query(
            'SELECT * from stocks WHERE username="******";', db)
        df = df.reindex(["stockSymbol", "numShares"], axis=1)
        df = df.rename(columns={
            'stockSymbol': "Stocks Owned:",
            'numShares': "# of Shares:"
        })
        print("\nYour Current Portfolio:\n\n" +
              th.md_table(df, formats={-1: 'c'}))