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This commit is contained in:
Oleg Sheynin
2024-08-14 01:54:48 +00:00
parent 80319e0301
commit cd5c78d47f
4 changed files with 1055 additions and 227 deletions
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tensorflow/notebooks/leo/LSTM_All_Crypto_02.ipynb
+51 -28
View File
@@ -2,7 +2,7 @@
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"execution_count": 2,
"id": "1023f2c1-e45f-4e1c-9a1b-66f59f128196",
"metadata": {},
"outputs": [
@@ -10,8 +10,23 @@
"name": "stdout",
"output_type": "stream",
"text": [
"Panda Version: 2.2.2\n",
"Today date is: 2024-06-17\n"
"Panda Version: 2.2.2\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"2024-08-13 13:49:15.756217: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:485] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n",
"2024-08-13 13:49:15.773323: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:8454] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n",
"2024-08-13 13:49:15.778526: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1452] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Today date is: 2024-08-13\n"
]
}
],
@@ -73,7 +88,7 @@
},
{
"cell_type": "code",
"execution_count": 2,
"execution_count": 3,
"id": "c09a37a6-f0d9-48e3-a1d1-65ddaf2c489c",
"metadata": {},
"outputs": [
@@ -82,26 +97,23 @@
"output_type": "stream",
"text": [
"/workspace/leo\n",
"total 22016\n",
"drwxrwxr-x 1 1000 1000 848 Jun 17 10:00 .\n",
"total 15712\n",
"drwxrwxrwx 1 1000 1000 628 Aug 13 13:00 .\n",
"drwxrwxr-x 1 1000 1000 18 Jun 3 23:40 ..\n",
"-rw------- 1 1000 1000 1449984 Jun 4 00:49 20240601.mktdata.ohlcv.db\n",
"-rw------- 1 1000 1000 1445888 Jun 3 23:44 20240602.mktdata.ohlcv.db\n",
"-rw------- 1 1000 1000 1437696 Jun 4 16:45 20240603.mktdata.ohlcv.db\n",
"-rw------- 1 1000 1000 1269760 Jun 5 10:00 20240604.mktdata.ohlcv.db\n",
"-rw------- 1 1000 1000 1081344 Jun 6 10:00 20240605.mktdata.ohlcv.db\n",
"-rw------- 1 1000 1000 1441792 Jun 7 10:00 20240606.mktdata.ohlcv.db\n",
"-rw------- 1 1000 1000 1445888 Jun 8 10:00 20240607.mktdata.ohlcv.db\n",
"-rw------- 1 1000 1000 1449984 Jun 9 10:00 20240608.mktdata.ohlcv.db\n",
"-rw------- 1 1000 1000 1437696 Jun 10 10:00 20240609.mktdata.ohlcv.db\n",
"-rw-r--r-- 1 1000 1000 0 Jun 12 15:29 20240609.mktdata.ohlcvdb\n",
"-rw------- 1 1000 1000 1437696 Jun 11 10:00 20240610.mktdata.ohlcv.db\n",
"-rw------- 1 1000 1000 1449984 Jun 12 10:01 20240611.mktdata.ohlcv.db\n",
"-rw------- 1 1000 1000 1445888 Jun 13 10:01 20240612.mktdata.ohlcv.db\n",
"-rw------- 1 1000 1000 1445888 Jun 14 10:01 20240613.mktdata.ohlcv.db\n",
"-rw------- 1 1000 1000 1404928 Jun 15 10:01 20240614.mktdata.ohlcv.db\n",
"-rw------- 1 1000 1000 1449984 Jun 16 10:00 20240615.mktdata.ohlcv.db\n",
"-rw------- 1 1000 1000 1449984 Jun 17 10:00 20240616.mktdata.ohlcv.db\n"
"drwxrwxr-x 1 1000 1000 1500 Aug 10 21:00 2024-06\n",
"drwxrwxr-x 1 1000 1000 1550 Aug 10 21:00 2024-07\n",
"-rw------- 1 1000 1000 1425408 Aug 2 13:01 20240801.mktdata.ohlcv.db\n",
"-rw------- 1 1000 1000 1396736 Aug 3 13:01 20240802.mktdata.ohlcv.db\n",
"-rw------- 1 1000 1000 1384448 Aug 4 13:01 20240803.mktdata.ohlcv.db\n",
"-rw------- 1 1000 1000 1318912 Aug 6 02:54 20240804.mktdata.ohlcv.db\n",
"-rw------- 1 1000 1000 2269184 Aug 10 17:04 20240805.mktdata.ohlcv.db\n",
"-rw------- 1 1000 1000 1146880 Aug 10 20:59 20240806.mktdata.ohlcv.db\n",
"-rw------- 1 1000 1000 1363968 Aug 8 13:01 20240807.mktdata.ohlcv.db\n",
"-rw------- 1 1000 1000 1187840 Aug 10 17:09 20240808.mktdata.ohlcv.db\n",
"-rw------- 1 1000 1000 1028096 Aug 10 17:10 20240809.mktdata.ohlcv.db\n",
"-rw------- 1 1000 1000 1187840 Aug 11 13:00 20240810.mktdata.ohlcv.db\n",
"-rw------- 1 1000 1000 1187840 Aug 12 13:00 20240811.mktdata.ohlcv.db\n",
"-rw------- 1 1000 1000 1191936 Aug 13 13:00 20240812.mktdata.ohlcv.db\n"
]
}
],
@@ -133,15 +145,26 @@
},
{
"cell_type": "code",
"execution_count": 3,
"execution_count": 4,
"id": "5d2aed0b-8c9d-4f5a-9166-785da4811390",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"89716\n"
"ename": "DatabaseError",
"evalue": "Execution failed on sql 'select * from coinbase_ohlcv_1min': no such table: coinbase_ohlcv_1min",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mOperationalError\u001b[0m Traceback (most recent call last)",
"File \u001b[0;32m/usr/local/lib/python3.11/dist-packages/pandas/io/sql.py:2674\u001b[0m, in \u001b[0;36mSQLiteDatabase.execute\u001b[0;34m(self, sql, params)\u001b[0m\n\u001b[1;32m 2673\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m-> 2674\u001b[0m \u001b[43mcur\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mexecute\u001b[49m\u001b[43m(\u001b[49m\u001b[43msql\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 2675\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m cur\n",
"\u001b[0;31mOperationalError\u001b[0m: no such table: coinbase_ohlcv_1min",
"\nThe above exception was the direct cause of the following exception:\n",
"\u001b[0;31mDatabaseError\u001b[0m Traceback (most recent call last)",
"Cell \u001b[0;32mIn[4], line 32\u001b[0m\n\u001b[1;32m 29\u001b[0m conn \u001b[38;5;241m=\u001b[39m sqlite3\u001b[38;5;241m.\u001b[39mconnect(filename)\n\u001b[1;32m 31\u001b[0m \u001b[38;5;66;03m# Read the data into a DataFrame\u001b[39;00m\n\u001b[0;32m---> 32\u001b[0m df \u001b[38;5;241m=\u001b[39m \u001b[43mpd\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mread_sql_query\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mselect * from coinbase_ohlcv_1min\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mconn\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 34\u001b[0m df_concat \u001b[38;5;241m=\u001b[39m pd\u001b[38;5;241m.\u001b[39mconcat([df_concat, df], axis \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m0\u001b[39m,ignore_index \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mTrue\u001b[39;00m)\n\u001b[1;32m 35\u001b[0m \u001b[38;5;66;03m# Print the combined DataFrame\u001b[39;00m\n\u001b[1;32m 36\u001b[0m \u001b[38;5;66;03m# print(df_concat.shape[0])\u001b[39;00m\n\u001b[1;32m 37\u001b[0m \u001b[38;5;66;03m# print(df_concat.shape[1])\u001b[39;00m\n",
"File \u001b[0;32m/usr/local/lib/python3.11/dist-packages/pandas/io/sql.py:526\u001b[0m, in \u001b[0;36mread_sql_query\u001b[0;34m(sql, con, index_col, coerce_float, params, parse_dates, chunksize, dtype, dtype_backend)\u001b[0m\n\u001b[1;32m 523\u001b[0m \u001b[38;5;28;01massert\u001b[39;00m dtype_backend \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m lib\u001b[38;5;241m.\u001b[39mno_default\n\u001b[1;32m 525\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m pandasSQL_builder(con) \u001b[38;5;28;01mas\u001b[39;00m pandas_sql:\n\u001b[0;32m--> 526\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mpandas_sql\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mread_query\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 527\u001b[0m \u001b[43m \u001b[49m\u001b[43msql\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 528\u001b[0m \u001b[43m \u001b[49m\u001b[43mindex_col\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mindex_col\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 529\u001b[0m \u001b[43m \u001b[49m\u001b[43mparams\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mparams\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 530\u001b[0m \u001b[43m \u001b[49m\u001b[43mcoerce_float\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcoerce_float\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 531\u001b[0m \u001b[43m \u001b[49m\u001b[43mparse_dates\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mparse_dates\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 532\u001b[0m \u001b[43m \u001b[49m\u001b[43mchunksize\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mchunksize\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 533\u001b[0m \u001b[43m \u001b[49m\u001b[43mdtype\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdtype\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 534\u001b[0m \u001b[43m \u001b[49m\u001b[43mdtype_backend\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdtype_backend\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 535\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n",
"File \u001b[0;32m/usr/local/lib/python3.11/dist-packages/pandas/io/sql.py:2738\u001b[0m, in \u001b[0;36mSQLiteDatabase.read_query\u001b[0;34m(self, sql, index_col, coerce_float, parse_dates, params, chunksize, dtype, dtype_backend)\u001b[0m\n\u001b[1;32m 2727\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mread_query\u001b[39m(\n\u001b[1;32m 2728\u001b[0m \u001b[38;5;28mself\u001b[39m,\n\u001b[1;32m 2729\u001b[0m sql,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 2736\u001b[0m dtype_backend: DtypeBackend \u001b[38;5;241m|\u001b[39m Literal[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mnumpy\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mnumpy\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[1;32m 2737\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m DataFrame \u001b[38;5;241m|\u001b[39m Iterator[DataFrame]:\n\u001b[0;32m-> 2738\u001b[0m cursor \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mexecute\u001b[49m\u001b[43m(\u001b[49m\u001b[43msql\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mparams\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 2739\u001b[0m columns \u001b[38;5;241m=\u001b[39m [col_desc[\u001b[38;5;241m0\u001b[39m] \u001b[38;5;28;01mfor\u001b[39;00m col_desc \u001b[38;5;129;01min\u001b[39;00m cursor\u001b[38;5;241m.\u001b[39mdescription]\n\u001b[1;32m 2741\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m chunksize \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n",
"File \u001b[0;32m/usr/local/lib/python3.11/dist-packages/pandas/io/sql.py:2686\u001b[0m, in \u001b[0;36mSQLiteDatabase.execute\u001b[0;34m(self, sql, params)\u001b[0m\n\u001b[1;32m 2683\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m ex \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01minner_exc\u001b[39;00m\n\u001b[1;32m 2685\u001b[0m ex \u001b[38;5;241m=\u001b[39m DatabaseError(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mExecution failed on sql \u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;132;01m{\u001b[39;00msql\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mexc\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m-> 2686\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m ex \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mexc\u001b[39;00m\n",
"\u001b[0;31mDatabaseError\u001b[0m: Execution failed on sql 'select * from coinbase_ohlcv_1min': no such table: coinbase_ohlcv_1min"
]
}
],
tensorflow/notebooks/leo/TimeSeries_Crypt.ipynb
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