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feat: 完善 QMT 交易模块

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liaozhaorun
2026-02-24 13:06:14 +08:00
parent 29706da299
commit 5628fbb34c
13 changed files with 1249 additions and 5368 deletions
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119
main/data/update/update_money_flow.ipynb
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@@ -34,17 +34,17 @@
"output_type": "stream",
"text": [
"<class 'pandas.core.frame.DataFrame'>\n",
"Index: 9387872 entries, 0 to 25863\n",
"Index: 9413748 entries, 0 to 25875\n",
"Data columns (total 2 columns):\n",
" # Column Dtype \n",
"--- ------ ----- \n",
" 0 ts_code object\n",
" 1 trade_date object\n",
"dtypes: object(2)\n",
"memory usage: 214.9+ MB\n",
"memory usage: 215.5+ MB\n",
"None\n",
"20260130\n",
"start_date: 20260202\n"
"20260206\n",
"start_date: 20260209\n"
]
}
],
@@ -99,12 +99,7 @@
"任务 20260212 完成\n",
"任务 20260211 完成\n",
"任务 20260210 完成\n",
"任务 20260209 完成\n",
"任务 20260206 完成\n",
"任务 20260205 完成\n",
"任务 20260204 完成\n",
"任务 20260203 完成\n",
"任务 20260202 完成\n"
"任务 20260209 完成\n"
]
}
],
@@ -194,71 +189,71 @@
"output_type": "stream",
"text": [
" ts_code trade_date buy_sm_vol buy_sm_amount sell_sm_vol \\\n",
"0 002397.SZ 20260206 143016 6566.04 142640 \n",
"1 603882.SH 20260206 32234 10009.25 31819 \n",
"2 002824.SZ 20260206 58407 13856.33 47164 \n",
"3 603379.SH 20260206 31545 21744.99 30955 \n",
"4 600223.SH 20260206 73778 5582.50 67552 \n",
"0 300587.SZ 20260213 154110 9661.44 160598 \n",
"1 601000.SH 20260213 150959 6301.54 197344 \n",
"2 002338.SZ 20260213 9215 5012.78 8260 \n",
"3 688373.SH 20260213 29166 1845.78 30329 \n",
"4 002226.SZ 20260213 101435 6137.98 79302 \n",
"... ... ... ... ... ... \n",
"25871 002774.SZ 20260202 32854 3675.61 20566 \n",
"25872 300188.SZ 20260202 54005 7416.58 48176 \n",
"25873 688173.SH 20260202 64149 10373.20 68049 \n",
"25874 300145.SZ 20260202 132990 6043.37 133529 \n",
"25875 300205.SZ 20260202 8361 364.75 6236 \n",
"25887 603713.SH 20260209 9898 6481.74 10208 \n",
"25888 300004.SZ 20260209 41923 5934.14 50255 \n",
"25889 300975.SZ 20260209 198244 30367.70 159191 \n",
"25890 603381.SH 20260209 85934 22581.16 95505 \n",
"25891 002836.SZ 20260209 27160 4238.25 22047 \n",
"\n",
" sell_sm_amount buy_md_vol buy_md_amount sell_md_vol sell_md_amount \\\n",
"0 6550.08 114346 5247.29 121777 5580.76 \n",
"1 9880.13 15560 4828.56 14519 4506.56 \n",
"2 11195.49 27988 6622.95 30015 7118.27 \n",
"3 21323.49 21708 14968.66 21044 14503.09 \n",
"4 5110.61 53914 4075.02 53354 4037.48 \n",
"0 10061.76 183752 11498.51 186971 11701.15 \n",
"1 8233.85 84549 3527.41 71932 3003.18 \n",
"2 4495.09 9488 5163.47 9035 4920.33 \n",
"3 1918.49 10043 635.49 10005 633.64 \n",
"4 4796.49 104000 6296.98 78239 4741.21 \n",
"... ... ... ... ... ... \n",
"25871 2300.99 20761 2320.61 21785 2437.00 \n",
"25872 6623.07 52821 7250.13 53449 7347.52 \n",
"25873 11000.03 35320 5706.28 30270 4895.56 \n",
"25874 6066.65 114646 5208.71 97260 4422.03 \n",
"25875 272.25 9374 408.60 9827 427.93 \n",
"25887 6683.01 6735 4413.49 7402 4854.70 \n",
"25888 7133.88 53004 7510.03 58384 8274.31 \n",
"25889 24423.94 164520 25222.01 193044 29612.42 \n",
"25890 25109.67 65977 17316.88 71008 18669.88 \n",
"25891 3438.16 21123 3293.94 20955 3271.07 \n",
"\n",
" buy_lg_vol buy_lg_amount sell_lg_vol sell_lg_amount buy_elg_vol \\\n",
"0 85477 3926.44 87204 3989.37 28400 \n",
"1 5474 1697.68 6390 1982.08 721 \n",
"2 11723 2778.17 15330 3630.71 3939 \n",
"3 13069 9000.74 15789 10882.14 7583 \n",
"4 27279 2062.59 22583 1709.48 10118 \n",
"0 139274 8711.00 168037 10519.91 60907 \n",
"1 57471 2398.28 37552 1567.23 21177 \n",
"2 5873 3195.64 5312 2890.59 514 \n",
"3 8238 521.88 7113 451.02 0 \n",
"4 50394 3048.72 69021 4177.39 9335 \n",
"... ... ... ... ... ... \n",
"25871 8975 1002.99 18793 2100.36 0 \n",
"25872 31050 4271.36 35903 4923.97 7655 \n",
"25873 11829 1915.52 12687 2050.68 2000 \n",
"25874 81164 3682.66 113414 5149.25 41421 \n",
"25875 6887 302.35 8559 375.51 0 \n",
"25887 3515 2307.87 4056 2660.17 2867 \n",
"25888 49767 7060.10 39566 5596.12 8820 \n",
"25889 116306 17856.14 144536 22152.02 51550 \n",
"25890 46270 12156.66 38176 10028.63 11944 \n",
"25891 9676 1508.43 11383 1772.18 1000 \n",
"\n",
" buy_elg_amount sell_elg_vol sell_elg_amount net_mf_vol \\\n",
"0 1293.83 19618 913.39 42201 \n",
"1 223.34 1261 390.07 -823 \n",
"2 935.53 9548 2248.51 2997 \n",
"3 5221.72 6117 4227.39 6215 \n",
"4 766.07 21600 1628.62 -9839 \n",
"0 3816.45 22437 1404.58 142435 \n",
"1 882.70 7328 305.66 -48700 \n",
"2 280.52 2483 1346.40 -483 \n",
"3 0.00 0 0.00 982 \n",
"4 565.27 38602 2333.86 -103058 \n",
"... ... ... ... ... \n",
"25871 0.00 1446 160.86 -20182 \n",
"25872 1053.35 8003 1096.85 -12903 \n",
"25873 319.00 2291 367.73 -5670 \n",
"25874 1881.32 26018 1178.15 -70082 \n",
"25875 0.00 0 0.00 -1678 \n",
"25887 1885.53 1349 890.75 1237 \n",
"25888 1251.47 5309 751.42 8180 \n",
"25889 7924.73 33850 5182.21 -41375 \n",
"25890 3157.32 5436 1403.84 -11696 \n",
"25891 155.40 4574 714.61 1257 \n",
"\n",
" net_mf_amount \n",
"0 1943.09 \n",
"1 -246.33 \n",
"2 705.13 \n",
"3 4367.94 \n",
"4 -741.40 \n",
"0 8918.59 \n",
"1 -2025.73 \n",
"2 -250.58 \n",
"3 64.60 \n",
"4 -6231.26 \n",
"... ... \n",
"25871 -2251.19 \n",
"25872 -1769.73 \n",
"25873 -918.58 \n",
"25874 -3146.31 \n",
"25875 -68.42 \n",
"25887 814.61 \n",
"25888 1173.63 \n",
"25889 -6267.77 \n",
"25890 -3055.51 \n",
"25891 191.86 \n",
"\n",
"[25876 rows x 20 columns]\n"
"[25892 rows x 20 columns]\n"
]
}
],
@@ -283,7 +278,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.12.11"
"version": "3.13.2"
}
},
"nbformat": 4,