56 lines
1.7 KiB
Python
56 lines
1.7 KiB
Python
import influxdb_client, os, time
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from influxdb_client import InfluxDBClient, Point, WritePrecision
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from influxdb_client.client.write_api import SYNCHRONOUS
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from sqlalchemy import create_engine
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import pandas as pd
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token = "AcU0_L5vtfH-9ycHnk0txF3jgHIcWRcMOElzAVtIrAGXC0oNSjwZUzPBsWCBZHNbaJmr-9x34E1Hycow59MnQg=="
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org = "econ"
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url = "http://localhost:8086"
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bucket="econ"
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posturl='postgresql://admin:econ@localhost:15432/econ'
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write_client = None
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EXInit=False
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EXBooksData=[]
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EXTradeData=[]
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BUSINESSData=[]
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PerformanceData=[]
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def get_client():
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global write_client
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if write_client==None:
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write_client=influxdb_client.InfluxDBClient(url=url, token=token, org=org)
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return write_client
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def writeEXData():
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db = create_engine(posturl)
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df=pd.DataFrame(EXBooksData)
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types=df.dtypes
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start=time.time()
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df.to_sql('cx_books', con=db, if_exists='replace',
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index=False,chunksize=200000)
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t1=time.time()
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print(f"cx_books completed: {t1-start}/{df.size}")
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df=pd.DataFrame(EXTradeData)
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df.to_sql("cx_trades",con=db, if_exists='replace',
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index=False,chunksize=10000)
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t2=time.time()
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print(f"cx_trades completed: {t2-t1}/{df.size}")
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def writeBusinessData():
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db = create_engine(posturl)
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df=pd.DataFrame(BUSINESSData)
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df.to_sql('business', con=db, if_exists='replace',
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index=False,chunksize=10000)
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print(f"business completed: {df.size}")
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def writePerformanceData():
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db = create_engine(posturl)
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df=pd.DataFrame(PerformanceData)
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df.to_sql('performance', con=db, if_exists='replace',
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index=False,chunksize=10000)
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print(f"performance completed: {df.size}")
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def clearlog():
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EXBooksData=[]
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EXTradeData=[]
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BUSINESSData=[] |