| |
| |
| """ |
| NOTE: |
| - This scripts is a demo to import example data import Qlib |
| - !!!!!!!!!!!!!!!TODO!!!!!!!!!!!!!!!!!!!: |
| - Its structure is not well designed and very ugly, your contribution is welcome to make importing dataset easier |
| """ |
|
|
| from datetime import date, datetime as dt |
| import os |
| from pathlib import Path |
| import random |
| import shutil |
| import time |
| import traceback |
|
|
| from arctic import Arctic, chunkstore |
| import arctic |
| from arctic import Arctic, CHUNK_STORE |
| from arctic.chunkstore.chunkstore import CHUNK_SIZE |
| import fire |
| from joblib import Parallel, delayed, parallel |
| import numpy as np |
| import pandas as pd |
| from pandas import DataFrame |
| from pandas.core.indexes.datetimes import date_range |
| from pymongo.mongo_client import MongoClient |
|
|
| DIRNAME = Path(__file__).absolute().resolve().parent |
|
|
| |
| N_JOBS = -1 |
| LOG_FILE_PATH = DIRNAME / "log_file" |
| DATA_PATH = DIRNAME / "raw_data" |
| DATABASE_PATH = DIRNAME / "orig_data" |
| DATA_INFO_PATH = DIRNAME / "data_info" |
| DATA_FINISH_INFO_PATH = DIRNAME / "./data_finish_info" |
| DOC_TYPE = ["Tick", "Order", "OrderQueue", "Transaction", "Day", "Minute"] |
| MAX_SIZE = 3000 * 1024 * 1024 * 1024 |
| ALL_STOCK_PATH = DATABASE_PATH / "all.txt" |
| ARCTIC_SRV = "127.0.0.1" |
|
|
|
|
| def get_library_name(doc_type): |
| if str.lower(doc_type) == str.lower("Tick"): |
| return "ticks" |
| else: |
| return str.lower(doc_type) |
|
|
|
|
| def is_stock(exchange_place, code): |
| if exchange_place == "SH" and code[0] != "6": |
| return False |
| if exchange_place == "SZ" and code[0] != "0" and code[:2] != "30": |
| return False |
| return True |
|
|
|
|
| def add_one_stock_daily_data(filepath, type, exchange_place, arc, date): |
| """ |
| exchange_place: "SZ" OR "SH" |
| type: "tick", "orderbook", ... |
| filepath: the path of csv |
| arc: arclink created by a process |
| """ |
| code = os.path.split(filepath)[-1].split(".csv")[0] |
| if exchange_place == "SH" and code[0] != "6": |
| return |
| if exchange_place == "SZ" and code[0] != "0" and code[:2] != "30": |
| return |
|
|
| df = pd.read_csv(filepath, encoding="gbk", dtype={"code": str}) |
| code = os.path.split(filepath)[-1].split(".csv")[0] |
|
|
| def format_time(day, hms): |
| day = str(day) |
| hms = str(hms) |
| if hms[0] == "1": |
| return ( |
| "-".join([day[0:4], day[4:6], day[6:8]]) + " " + ":".join([hms[:2], hms[2:4], hms[4:6] + "." + hms[6:]]) |
| ) |
| else: |
| return ( |
| "-".join([day[0:4], day[4:6], day[6:8]]) + " " + ":".join([hms[:1], hms[1:3], hms[3:5] + "." + hms[5:]]) |
| ) |
|
|
| |
| timestamp = list(zip(list(df["date"]), list(df["time"]))) |
| error_index_list = [] |
| for index, t in enumerate(timestamp): |
| try: |
| pd.Timestamp(format_time(t[0], t[1])) |
| except Exception: |
| error_index_list.append(index) |
|
|
| |
|
|
| if len(error_index_list) > 0: |
| print("error: {}, {}".format(filepath, len(error_index_list))) |
|
|
| df = df.drop(error_index_list) |
| timestamp = list(zip(list(df["date"]), list(df["time"]))) |
| |
| pd_timestamp = pd.DatetimeIndex( |
| [pd.Timestamp(format_time(timestamp[i][0], timestamp[i][1])) for i in range(len(df["date"]))] |
| ) |
| df = df.drop(columns=["date", "time", "name", "code", "wind_code"]) |
| |
| df["date"] = pd.to_datetime(pd_timestamp) |
| df.set_index("date", inplace=True) |
|
|
| if str.lower(type) == "orderqueue": |
| |
| df["ab"] = [ |
| ",".join([str(int(row["ab" + str(i + 1)])) for i in range(0, row["ab_items"])]) |
| for timestamp, row in df.iterrows() |
| ] |
| df = df.drop(columns=["ab" + str(i) for i in range(1, 51)]) |
|
|
| type = get_library_name(type) |
| |
| lib = arc[type] |
|
|
| symbol = "".join([exchange_place, code]) |
| if symbol in lib.list_symbols(): |
| print("update {0}, date={1}".format(symbol, date)) |
| if df.empty == True: |
| return error_index_list |
| lib.update(symbol, df, chunk_size="D") |
| else: |
| print("write {0}, date={1}".format(symbol, date)) |
| lib.write(symbol, df, chunk_size="D") |
| return error_index_list |
|
|
|
|
| def add_one_stock_daily_data_wrapper(filepath, type, exchange_place, index, date): |
| pid = os.getpid() |
| code = os.path.split(filepath)[-1].split(".csv")[0] |
| arc = Arctic(ARCTIC_SRV) |
| try: |
| if index % 100 == 0: |
| print("index = {}, filepath = {}".format(index, filepath)) |
| error_index_list = add_one_stock_daily_data(filepath, type, exchange_place, arc, date) |
| if error_index_list is not None and len(error_index_list) > 0: |
| f = open(os.path.join(LOG_FILE_PATH, "temp_timestamp_error_{0}_{1}_{2}.txt".format(pid, date, type)), "a+") |
| f.write("{}, {}, {}\n".format(filepath, error_index_list, exchange_place + "_" + code)) |
| f.close() |
|
|
| except Exception as e: |
| info = traceback.format_exc() |
| print("error:" + str(e)) |
| f = open(os.path.join(LOG_FILE_PATH, "temp_fail_{0}_{1}_{2}.txt".format(pid, date, type)), "a+") |
| f.write("fail:" + str(filepath) + "\n" + str(e) + "\n" + str(info) + "\n") |
| f.close() |
|
|
| finally: |
| arc.reset() |
|
|
|
|
| def add_data(tick_date, doc_type, stock_name_dict): |
| pid = os.getpid() |
|
|
| if doc_type not in DOC_TYPE: |
| print("doc_type not in {}".format(DOC_TYPE)) |
| return |
| try: |
| begin_time = time.time() |
| os.system(f"cp {DATABASE_PATH}/{tick_date + '_{}.tar.gz'.format(doc_type)} {DATA_PATH}/") |
|
|
| os.system( |
| f"tar -xvzf {DATA_PATH}/{tick_date + '_{}.tar.gz'.format(doc_type)} -C {DATA_PATH}/ {tick_date + '_' + doc_type}/SH" |
| ) |
| os.system( |
| f"tar -xvzf {DATA_PATH}/{tick_date + '_{}.tar.gz'.format(doc_type)} -C {DATA_PATH}/ {tick_date + '_' + doc_type}/SZ" |
| ) |
| os.system(f"chmod 777 {DATA_PATH}") |
| os.system(f"chmod 777 {DATA_PATH}/{tick_date + '_' + doc_type}") |
| os.system(f"chmod 777 {DATA_PATH}/{tick_date + '_' + doc_type}/SH") |
| os.system(f"chmod 777 {DATA_PATH}/{tick_date + '_' + doc_type}/SZ") |
| os.system(f"chmod 777 {DATA_PATH}/{tick_date + '_' + doc_type}/SH/{tick_date}") |
| os.system(f"chmod 777 {DATA_PATH}/{tick_date + '_' + doc_type}/SZ/{tick_date}") |
|
|
| print("tick_date={}".format(tick_date)) |
|
|
| temp_data_path_sh = os.path.join(DATA_PATH, tick_date + "_" + doc_type, "SH", tick_date) |
| temp_data_path_sz = os.path.join(DATA_PATH, tick_date + "_" + doc_type, "SZ", tick_date) |
| is_files_exist = {"sh": os.path.exists(temp_data_path_sh), "sz": os.path.exists(temp_data_path_sz)} |
|
|
| sz_files = ( |
| ( |
| set([i.split(".csv")[0] for i in os.listdir(temp_data_path_sz) if i[:2] == "30" or i[0] == "0"]) |
| & set(stock_name_dict["SZ"]) |
| ) |
| if is_files_exist["sz"] |
| else set() |
| ) |
| sz_file_nums = len(sz_files) if is_files_exist["sz"] else 0 |
| sh_files = ( |
| ( |
| set([i.split(".csv")[0] for i in os.listdir(temp_data_path_sh) if i[0] == "6"]) |
| & set(stock_name_dict["SH"]) |
| ) |
| if is_files_exist["sh"] |
| else set() |
| ) |
| sh_file_nums = len(sh_files) if is_files_exist["sh"] else 0 |
| print("sz_file_nums:{}, sh_file_nums:{}".format(sz_file_nums, sh_file_nums)) |
|
|
| f = (DATA_INFO_PATH / "data_info_log_{}_{}".format(doc_type, tick_date)).open("w+") |
| f.write("sz:{}, sh:{}, date:{}:".format(sz_file_nums, sh_file_nums, tick_date) + "\n") |
| f.close() |
|
|
| if sh_file_nums > 0: |
| |
| Parallel(n_jobs=N_JOBS)( |
| delayed(add_one_stock_daily_data_wrapper)( |
| os.path.join(temp_data_path_sh, name + ".csv"), doc_type, "SH", index, tick_date |
| ) |
| for index, name in enumerate(list(sh_files)) |
| ) |
| if sz_file_nums > 0: |
| |
| Parallel(n_jobs=N_JOBS)( |
| delayed(add_one_stock_daily_data_wrapper)( |
| os.path.join(temp_data_path_sz, name + ".csv"), doc_type, "SZ", index, tick_date |
| ) |
| for index, name in enumerate(list(sz_files)) |
| ) |
|
|
| os.system(f"rm -f {DATA_PATH}/{tick_date + '_{}.tar.gz'.format(doc_type)}") |
| os.system(f"rm -rf {DATA_PATH}/{tick_date + '_' + doc_type}") |
| total_time = time.time() - begin_time |
| f = (DATA_FINISH_INFO_PATH / "data_info_finish_log_{}_{}".format(doc_type, tick_date)).open("w+") |
| f.write("finish: date:{}, consume_time:{}, end_time: {}".format(tick_date, total_time, time.time()) + "\n") |
| f.close() |
|
|
| except Exception as e: |
| info = traceback.format_exc() |
| print("date error:" + str(e)) |
| f = open(os.path.join(LOG_FILE_PATH, "temp_fail_{0}_{1}_{2}.txt".format(pid, tick_date, doc_type)), "a+") |
| f.write("fail:" + str(tick_date) + "\n" + str(e) + "\n" + str(info) + "\n") |
| f.close() |
|
|
|
|
| class DSCreator: |
| """Dataset creator""" |
|
|
| def clear(self): |
| client = MongoClient(ARCTIC_SRV) |
| client.drop_database("arctic") |
|
|
| def initialize_library(self): |
| arc = Arctic(ARCTIC_SRV) |
| for doc_type in DOC_TYPE: |
| arc.initialize_library(get_library_name(doc_type), lib_type=CHUNK_STORE) |
|
|
| def _get_empty_folder(self, fp: Path): |
| fp = Path(fp) |
| if fp.exists(): |
| shutil.rmtree(fp) |
| fp.mkdir(parents=True, exist_ok=True) |
|
|
| def import_data(self, doc_type_l=["Tick", "Transaction", "Order"]): |
| |
| for fp in LOG_FILE_PATH, DATA_INFO_PATH, DATA_FINISH_INFO_PATH, DATA_PATH: |
| self._get_empty_folder(fp) |
|
|
| arc = Arctic(ARCTIC_SRV) |
| for doc_type in DOC_TYPE: |
| |
| arc.set_quota(get_library_name(doc_type), MAX_SIZE) |
| arc.reset() |
|
|
| |
| for doc_type in doc_type_l: |
| date_list = list(set([int(path.split("_")[0]) for path in os.listdir(DATABASE_PATH) if doc_type in path])) |
| date_list.sort() |
| date_list = [str(date) for date in date_list] |
|
|
| f = open(ALL_STOCK_PATH, "r") |
| stock_name_list = [lines.split("\t")[0] for lines in f.readlines()] |
| f.close() |
| stock_name_dict = { |
| "SH": [stock_name[2:] for stock_name in stock_name_list if "SH" in stock_name], |
| "SZ": [stock_name[2:] for stock_name in stock_name_list if "SZ" in stock_name], |
| } |
|
|
| lib_name = get_library_name(doc_type) |
| a = Arctic(ARCTIC_SRV) |
| |
|
|
| stock_name_exist = a[lib_name].list_symbols() |
| lib = a[lib_name] |
| initialize_count = 0 |
| for stock_name in stock_name_list: |
| if stock_name not in stock_name_exist: |
| initialize_count += 1 |
| |
| pdf = pd.DataFrame(index=[pd.Timestamp("1900-01-01")]) |
| pdf.index.name = "date" |
| lib.write(stock_name, pdf) |
| print("initialize count: {}".format(initialize_count)) |
| print("tasks: {}".format(date_list)) |
| a.reset() |
|
|
| |
| |
| date_list = ["20201231"] |
| Parallel(n_jobs=min(2, len(date_list)))( |
| delayed(add_data)(date, doc_type, stock_name_dict) for date in date_list |
| ) |
|
|
|
|
| if __name__ == "__main__": |
| fire.Fire(DSCreator) |
|
|