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System save at 11/10/2024 14:07 by user_client2024

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user_client2024 2024-10-11 08:37:48 +00:00
parent 64181e87ae
commit 18bb89a410
3 changed files with 35 additions and 18 deletions
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6
.ipynb_checkpoints/main-checkpoint.ipynb
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@ -24,7 +24,7 @@
" -- Create a time window for each trade\n", " -- Create a time window for each trade\n",
" date_time - INTERVAL '1 second' * {time_window_s} AS window_start,\n", " date_time - INTERVAL '1 second' * {time_window_s} AS window_start,\n",
" date_time AS window_end\n", " date_time AS window_end\n",
" FROM {trade_data_1b}\n", " FROM {trade_10m_v3}\n",
"),\n", "),\n",
"\n", "\n",
"aggregated_trades AS (\n", "aggregated_trades AS (\n",
@ -64,7 +64,7 @@
"\"\"\"\n", "\"\"\"\n",
"\n", "\n",
"class Scenario:\n", "class Scenario:\n",
" seq = SQLQueryInterface(schema=\"internal\")\n", " seq = SQLQueryInterface(schema=\"trade_schema\")\n",
"\n", "\n",
" def logic(self, **kwargs):\n", " def logic(self, **kwargs):\n",
" validation_window = kwargs.get('validation_window')\n", " validation_window = kwargs.get('validation_window')\n",
@ -81,7 +81,7 @@
" cols = [\n", " cols = [\n",
" 'START_DATE_TIME',\n", " 'START_DATE_TIME',\n",
" 'END_DATE_TIME',\n", " 'END_DATE_TIME',\n",
" 'PARTICIPANT',\n", " 'FOCAL_ID',\n",
" 'MIN_PRICE',\n", " 'MIN_PRICE',\n",
" 'MAX_PRICE',\n", " 'MAX_PRICE',\n",
" 'PRICE_CHANGE (%)',\n", " 'PRICE_CHANGE (%)',\n",

32
main.ipynb
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@ -2,7 +2,7 @@
"cells": [ "cells": [
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 2, "execution_count": 4,
"id": "90c70e46-71a0-44a6-8090-f53aad3193c3", "id": "90c70e46-71a0-44a6-8090-f53aad3193c3",
"metadata": { "metadata": {
"tags": [] "tags": []
@ -24,7 +24,7 @@
" -- Create a time window for each trade\n", " -- Create a time window for each trade\n",
" date_time - INTERVAL '1 second' * {time_window_s} AS window_start,\n", " date_time - INTERVAL '1 second' * {time_window_s} AS window_start,\n",
" date_time AS window_end\n", " date_time AS window_end\n",
" FROM {trade_data_1b}\n", " FROM {trade_10m_v3}\n",
"),\n", "),\n",
"\n", "\n",
"aggregated_trades AS (\n", "aggregated_trades AS (\n",
@ -46,7 +46,7 @@
" RANGE BETWEEN {time_window_s} PRECEDING AND CURRENT ROW) AS lowest_price,\n", " RANGE BETWEEN {time_window_s} PRECEDING AND CURRENT ROW) AS lowest_price,\n",
" COUNT(*) OVER (PARTITION BY td.trader_id ORDER BY td.date_time \n", " COUNT(*) OVER (PARTITION BY td.trader_id ORDER BY td.date_time \n",
" RANGE BETWEEN {time_window_s} PRECEDING AND CURRENT ROW) AS number_of_trades\n", " RANGE BETWEEN {time_window_s} PRECEDING AND CURRENT ROW) AS number_of_trades\n",
" FROM trade_data td\n", " FROM {trade_10m_v3} td\n",
")\n", ")\n",
"\n", "\n",
"SELECT \n", "SELECT \n",
@ -74,14 +74,14 @@
" print(\"Query start time:\", query_start_time)\n", " print(\"Query start time:\", query_start_time)\n",
"\n", "\n",
" row_list = self.seq.execute_raw(query.format(\n", " row_list = self.seq.execute_raw(query.format(\n",
" trade_data_1b=\"trade_data_2b\",\n", " trade_10m_v3=\"trade_10m_v3\",\n",
" time_window_s=time_window_s\n", " time_window_s=time_window_s\n",
" ))\n", " ))\n",
"\n", "\n",
" cols = [\n", " cols = [\n",
" 'START_DATE_TIME',\n", " 'START_DATE_TIME',\n",
" 'END_DATE_TIME',\n", " 'END_DATE_TIME',\n",
" 'FOCAL ID',\n", " 'FOCAL_ID',\n",
" 'MIN_PRICE',\n", " 'MIN_PRICE',\n",
" 'MAX_PRICE',\n", " 'MAX_PRICE',\n",
" 'PRICE_CHANGE (%)',\n", " 'PRICE_CHANGE (%)',\n",
@ -104,11 +104,27 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": null, "execution_count": 6,
"id": "caee5554-5254-4388-bf24-029281d77890", "id": "caee5554-5254-4388-bf24-029281d77890",
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [
"source": [] {
"ename": "TypeError",
"evalue": "unsupported operand type(s) for /: 'NoneType' and 'int'",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)",
"Cell \u001b[0;32mIn[6], line 2\u001b[0m\n\u001b[1;32m 1\u001b[0m scenario \u001b[38;5;241m=\u001b[39m Scenario()\n\u001b[0;32m----> 2\u001b[0m \u001b[43mscenario\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mlogic\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n",
"Cell \u001b[0;32mIn[4], line 60\u001b[0m, in \u001b[0;36mScenario.logic\u001b[0;34m(self, **kwargs)\u001b[0m\n\u001b[1;32m 58\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mlogic\u001b[39m(\u001b[38;5;28mself\u001b[39m, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[1;32m 59\u001b[0m validation_window \u001b[38;5;241m=\u001b[39m kwargs\u001b[38;5;241m.\u001b[39mget(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mvalidation_window\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[0;32m---> 60\u001b[0m time_window_s \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mint\u001b[39m(\u001b[43mvalidation_window\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m/\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m1000\u001b[39;49m)\n\u001b[1;32m 62\u001b[0m query_start_time \u001b[38;5;241m=\u001b[39m datetime\u001b[38;5;241m.\u001b[39mnow()\n\u001b[1;32m 63\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mQuery start time:\u001b[39m\u001b[38;5;124m\"\u001b[39m, query_start_time)\n",
"\u001b[0;31mTypeError\u001b[0m: unsupported operand type(s) for /: 'NoneType' and 'int'"
]
}
],
"source": [
"scenario = Scenario()\n",
"scenario.logic()"
]
} }
], ],
"metadata": { "metadata": {

15
main.py
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@ -1,7 +1,7 @@
#!/usr/bin/env python #!/usr/bin/env python
# coding: utf-8 # coding: utf-8
# In[2]: # In[4]:
from datetime import datetime from datetime import datetime
@ -19,7 +19,7 @@ WITH trade_data AS (
-- Create a time window for each trade -- Create a time window for each trade
date_time - INTERVAL '1 second' * {time_window_s} AS window_start, date_time - INTERVAL '1 second' * {time_window_s} AS window_start,
date_time AS window_end date_time AS window_end
FROM {trade_data_1b} FROM {trade_10m_v3}
), ),
aggregated_trades AS ( aggregated_trades AS (
@ -41,7 +41,7 @@ aggregated_trades AS (
RANGE BETWEEN {time_window_s} PRECEDING AND CURRENT ROW) AS lowest_price, RANGE BETWEEN {time_window_s} PRECEDING AND CURRENT ROW) AS lowest_price,
COUNT(*) OVER (PARTITION BY td.trader_id ORDER BY td.date_time COUNT(*) OVER (PARTITION BY td.trader_id ORDER BY td.date_time
RANGE BETWEEN {time_window_s} PRECEDING AND CURRENT ROW) AS number_of_trades RANGE BETWEEN {time_window_s} PRECEDING AND CURRENT ROW) AS number_of_trades
FROM trade_data td FROM {trade_10m_v3} td
) )
SELECT SELECT
@ -69,14 +69,14 @@ class Scenario:
print("Query start time:", query_start_time) print("Query start time:", query_start_time)
row_list = self.seq.execute_raw(query.format( row_list = self.seq.execute_raw(query.format(
trade_data_1b="trade_data_2b", trade_10m_v3="trade_10m_v3",
time_window_s=time_window_s time_window_s=time_window_s
)) ))
cols = [ cols = [
'START_DATE_TIME', 'START_DATE_TIME',
'END_DATE_TIME', 'END_DATE_TIME',
'FOCAL ID', 'FOCAL_ID',
'MIN_PRICE', 'MIN_PRICE',
'MAX_PRICE', 'MAX_PRICE',
'PRICE_CHANGE (%)', 'PRICE_CHANGE (%)',
@ -97,8 +97,9 @@ class Scenario:
return final_scenario_df return final_scenario_df
# In[ ]: # In[6]:
scenario = Scenario()
scenario.logic()