180 lines
5.8 KiB
Plaintext
180 lines
5.8 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 2,
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"id": "2d9eb12f",
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"metadata": {},
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"outputs": [],
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"source": [
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"from operator import index\n",
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"\n",
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"import tushare as ts\n",
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"import pandas as pd\n",
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"import time\n",
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"\n",
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"ts.set_token('3a0741c702ee7e5e5f2bf1f0846bafaafe4e320833240b2a7e4a685f')\n",
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"pro = ts.pro_api()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"id": "0c5a87ba",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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" ts_code trade_date his_low his_high cost_5pct cost_15pct \\\n",
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"0 000001.SZ 20180104 0.2 12.3 7.2 8.7 \n",
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"1 000002.SZ 20180104 0.2 25.6 15.0 17.6 \n",
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"2 000004.SZ 20180104 0.8 53.2 21.6 22.0 \n",
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"3 000008.SZ 20180104 0.1 13.9 7.2 7.8 \n",
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"4 000009.SZ 20180104 0.3 15.0 5.8 5.9 \n",
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"... ... ... ... ... ... ... \n",
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"3095 603991.SH 20180104 12.0 67.8 26.4 27.0 \n",
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"3096 603993.SH 20180104 1.4 8.6 5.4 5.6 \n",
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"3097 603997.SH 20180104 5.4 31.5 9.9 10.2 \n",
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"3098 603998.SH 20180104 3.8 18.3 9.5 9.8 \n",
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"3099 603999.SH 20180104 3.6 30.6 6.9 6.9 \n",
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"\n",
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" cost_50pct cost_85pct cost_95pct weight_avg winner_rate \n",
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"0 10.8 11.8 12.1 10.39 44.59 \n",
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"1 22.2 24.4 24.8 21.31 97.14 \n",
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"2 23.6 27.6 29.6 24.71 45.41 \n",
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"3 8.6 9.2 10.5 8.64 47.04 \n",
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"4 6.6 7.6 7.8 6.74 38.85 \n",
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"... ... ... ... ... ... \n",
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"3095 27.6 30.6 34.2 28.54 57.36 \n",
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"3096 6.1 6.9 7.3 6.15 72.78 \n",
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"3097 10.5 11.7 11.7 10.84 11.28 \n",
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"3098 11.5 13.0 15.2 11.72 18.44 \n",
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"3099 7.8 9.3 9.9 8.00 31.89 \n",
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"\n",
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"[3100 rows x 11 columns]\n"
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]
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}
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],
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"source": [
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"\n",
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"df = pro.cyq_perf(trade_date='20180104')\n",
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"print(df)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"id": "500292d5",
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"metadata": {},
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"outputs": [],
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"source": [
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"import pandas as pd\n",
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"import time\n",
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"\n",
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"\n",
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"trade_cal = pro.trade_cal(exchange='', start_date='20170101', end_date='20250820')\n",
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"trade_cal = trade_cal[trade_cal['is_open'] == 1] # 只保留交易日\n",
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"trade_dates = trade_cal['cal_date'].tolist()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "4ae3cb65",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"✅ 日历文件已保存至: /mnt/d/PyProject/NewStock/data/qlib/calendar/day.txt\n",
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"📅 共 2097 个交易日\n"
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]
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}
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],
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"source": [
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"import os\n",
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"\n",
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"calendar_dir = \"/mnt/d/PyProject/NewStock/data/qlib/calendars\"\n",
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"os.makedirs(calendar_dir, exist_ok=True) # 自动创建目录（包括父目录）\n",
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"\n",
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"# 排序为升序（Qlib 要求日历按时间升序）\n",
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"trade_dates_sorted = sorted(trade_dates)\n",
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"\n",
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"# 写入 day.txt\n",
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"day_txt_path = os.path.join(calendar_dir, \"day.txt\")\n",
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"with open(day_txt_path, \"w\") as f:\n",
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" for date_str in trade_dates_sorted:\n",
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" f.write(date_str + \"\\n\")\n",
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"\n",
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"print(f\"✅ 日历文件已保存至: {day_txt_path}\")\n",
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"print(f\"📅 共 {len(trade_dates_sorted)} 个交易日\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 9,
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"id": "7a6e529b",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"✅ all.txt 已生成，共 5685 只股票\n"
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]
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}
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],
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"source": [
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"stocks_df = pd.read_csv('/mnt/d/PyProject/NewStock/stocks_list.csv', encoding='utf-8-sig')\n",
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"\n",
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"import os\n",
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"\n",
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"# 假设你有一个包含所有股票代码的列表（来自 stocks_df['ts_code']）\n",
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"# 例如：\n",
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"# instrument_list = ['600000.SH', '000001.SZ', '300001.SZ', ...]\n",
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"\n",
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"instrument_list = stocks_df['ts_code'].unique().tolist()\n",
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"\n",
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"# 获取你的数据时间范围（从 trade_dates）\n",
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"start_date = min(trade_dates) # e.g., '20201106'\n",
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"end_date = max(trade_dates) # e.g., '20210125'\n",
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"\n",
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"# 创建 instruments 目录\n",
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"instr_dir = \"/mnt/d/PyProject/NewStock/data/qlib/instruments\"\n",
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"os.makedirs(instr_dir, exist_ok=True)\n",
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"\n",
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"# 写入 all.txt\n",
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"with open(os.path.join(instr_dir, \"all.txt\"), \"w\") as f:\n",
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" for inst in instrument_list:\n",
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" f.write(f\"{inst}\\t{start_date}\\t{end_date}\\n\")\n",
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"\n",
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"print(f\"✅ all.txt 已生成，共 {len(instrument_list)} 只股票\")"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "stock",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.13.2"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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