def get_realtime_quotes(code_list, open_only=False):
import tushare as ts
max_len = 800
loop_cnt = int(math.ceil(float(len(code_list)) / max_len))
total_df = reduce(lambda df1, df2: df1.append(df2),
[ts.get_realtime_quotes([code for code in code_list[i::loop_cnt]])
for i in range(loop_cnt)])
total_df["is_index"] = False
index_symbol = ["sh", "sz", "hs300", "sz50", "zxb", "cyb"]
index_df = ts.get_realtime_quotes(index_symbol)
index_df["code"] = index_symbol
index_df["is_index"] = True
total_df = total_df.append(index_df)
columns = set(total_df.columns) - set(["name", "time", "date", "code"])
# columns = filter(lambda x: "_v" not in x, columns)
for label in columns:
total_df[label] = total_df[label].map(lambda x: 0 if str(x).strip() == "" else x)
total_df[label] = total_df[label].astype(float)
total_df["chg"] = total_df["price"] / total_df["pre_close"] - 1
total_df["order_book_id"] = total_df["code"]
total_df["order_book_id"] = total_df["order_book_id"].apply(tushare_code_2_order_book_id)
total_df = total_df.set_index("order_book_id").sort_index()
total_df["datetime"] = total_df["date"] + " " + total_df["time"]
total_df["datetime"] = total_df["datetime"].apply(lambda x: convert_dt_to_int(datetime.datetime.strptime(x, "%Y-%m-%d %H:%M:%S")))
total_df["close"] = total_df["price"]
total_df["last"] = total_df["price"]
total_df["limit_up"] = total_df.apply(lambda row: row.pre_close * (1.1 if "ST" not in row["name"] else 1.05), axis=1).round(2)
total_df["limit_down"] = total_df.apply(lambda row: row.pre_close * (0.9 if "ST" not in row["name"] else 0.95), axis=1).round(2)
if open_only:
total_df = total_df[total_df.open > 0]
return total_df
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