kopia lustrzana https://github.com/gshau/wxserver
199 wiersze
6.6 KiB
Python
199 wiersze
6.6 KiB
Python
import sqlite3
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import pandas as pd
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import stationDB as st
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from jinja2 import Template
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from bokeh.plotting import *
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from bokeh.resources import INLINE
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# from bokeh.util.browser import view
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from bokeh.models import HoverTool
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from bokeh.embed import components
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import time
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import datetime
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import os.path
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class DB:
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def __init__(self,fileName, table):
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self.fileName=fileName
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self.table=table
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self.columnNames=[]
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if not os.path.isfile(self.fileName):
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self.createTable()
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self.getColumnNames()
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def createTable(self):
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con=sqlite3.connect(self.fileName)
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c=con.cursor()
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c.execute("CREATE TABLE %s (timestamp real, timeString text)" % self.table)
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con.close()
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def addColumn(self, name):
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con=sqlite3.connect(self.fileName)
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c=con.cursor()
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type="real"
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c.execute("ALTER TABLE %s ADD COLUMN %s %s" % (self.table, name, type))
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con.close()
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def getColumnNames(self):
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con=sqlite3.connect(self.fileName)
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command="SELECT * from %s" % self.table
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self.df=pd.read_sql_query(command, con)
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self.columnNames=self.df.columns
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con.close()
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def addData(self, packet):
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con=sqlite3.connect(self.fileName)
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c=con.cursor()
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# create column if not present
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for key in packet.keys():
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if key not in self.columnNames:
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self.addColumn(key)
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self.getColumnNames()
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columns=', '.join(packet.keys())
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placeholders = ', '.join('?' * len(packet))
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sql = 'INSERT INTO master ({}) VALUES ({})'.format(columns, placeholders)
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c.execute(sql, packet.values())
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# # command="create table if not exists %s (date real, dateString text, name text, value real)" % name
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# c.execute(command)
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# timeString=datetime.datetime.fromtimestamp(time).strftime('%Y/%m/%d %H:%M:%S')
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# dataTuple=(time, timeString, name, data,)
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# command="INSERT INTO %s VALUES (?, ?, ?, ?)" % name
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# c.execute(command, dataTuple)
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con.commit()
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con.close()
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def loadDB(self,name):
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con=sqlite3.connect(self.fileName)
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command="SELECT * from %s" % name
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self.df=pd.read_sql_query(command, con)
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con.close()
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class DBview:
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def __init__(self,db,df,UTCOffset):
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# self.timeRange=timeRange
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self.db = db
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self.df = df
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self.UTCOffset = UTCOffset
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def qp(self,attrList, name, timeRange):
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now=datetime.datetime.now()
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epoch=datetime.datetime.utcfromtimestamp(0)
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tstart=now-datetime.timedelta(days=timeRange)
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tcut=(tstart-epoch).total_seconds()
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dataFrame=self.df[self.df.timestamp>tcut]
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dataFrame['t']=dataFrame.timestamp*1000
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# y1=getattr(self.df,attr1)
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# y2=getattr(self.df,attr2)
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output_file(name+'.html')
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timeString=[datetime.datetime.fromtimestamp(dt).strftime('%Y/%m/%d %H:%M:%S') for dt in dataFrame.timestamp]
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source=ColumnDataSource(data=dataFrame.to_dict('list'))
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TOOLS="resize,hover,crosshair,pan,wheel_zoom,box_zoom,reset,tap,previewsave,box_select,poly_select,lasso_select"
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p=figure(x_axis_type="datetime",tools=TOOLS)
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for key in attrList:
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print key
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p.scatter('t',key, source=source)
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p.select(dict(type=HoverTool)).tooltips=[
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("Time", "@timeString"),
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("Value", "@y1"),
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("Value", "@y2"),
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]
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show(p)
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def qph(self,attrList, name, timeRange):
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now=datetime.datetime.now()
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epoch=datetime.datetime.utcfromtimestamp(0)
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tstart=now-datetime.timedelta(days=0,hours=timeRange)
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tcut=(tstart-epoch).total_seconds()
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dataFrame=self.df[self.df.timestamp>tcut]
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dataFrame['t']=dataFrame.timestamp*1000
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# y1=getattr(self.df,attr1)
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# y2=getattr(self.df,attr2)
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output_file(name+'.html')
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timeString=[datetime.datetime.fromtimestamp(dt).strftime('%Y/%m/%d %H:%M:%S') for dt in dataFrame.timestamp]
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source=ColumnDataSource(data=dataFrame.to_dict('list'))
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TOOLS="resize,hover,crosshair,pan,wheel_zoom,box_zoom,reset,tap,previewsave,box_select,poly_select,lasso_select"
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p=figure(x_axis_type="datetime",tools=TOOLS)
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for key in attrList:
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print key
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p.scatter('t',key, source=source)
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p.select(dict(type=HoverTool)).tooltips=[
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("Time", "@timeString"),
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("Value", "@y1"),
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("Value", "@y2"),
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]
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show(p)
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return source
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def qphLive(self,attrList, name, timeRange):
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# attrList=['stationLoadVolt']
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now=datetime.datetime.now()
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epoch=datetime.datetime.utcfromtimestamp(0)
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tstart=now-datetime.timedelta(days=0,hours=timeRange-self.UTCOffset)
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tcut=(tstart-epoch).total_seconds()
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dataFrame=self.df[self.df.timestamp>tcut]
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dataFrame['t']=dataFrame.timestamp*1000 - self.UTCOffset*3600*1000
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output_server(name,url='http://10.0.1.2:5006')
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colors=["red","blue","green","orange","purple","black","gray","magenta","cyan","brown","gold","darkkhaki","darksalmon"]
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timeString=[datetime.datetime.fromtimestamp(dt).strftime('%Y/%m/%d %H:%M:%S') for dt in dataFrame.timestamp]
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source=ColumnDataSource(data=dataFrame.to_dict('list'))
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TOOLS="resize,hover,crosshair,pan,wheel_zoom,box_zoom,reset,tap,previewsave,box_select,poly_select,lasso_select"
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keyList=attrList.keys()
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p={}
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ds={}
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for mainKey in keyList:
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if mainKey == keyList[0]:
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p[mainKey]=figure(x_axis_type="datetime",tools=TOOLS, width=600, height=400, title=mainKey)
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else:
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p[mainKey]=figure(x_axis_type="datetime",tools=TOOLS, width=600, height=400, title=mainKey, x_range=p[keyList[0]].x_range)
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ikey=0
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hover={}
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for key in attrList[mainKey]:
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print key
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# keySource=ColumnDataSource({'x': source.data['t'], 'y': series.values, 'series_name': name_for_display, 'Date': toy_df.index.format()})
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p[mainKey].scatter('t',key, source=source, name=key,fill_color=colors[ikey],line_color=colors[ikey], legend=key)
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hover = p[mainKey].select(dict(type=HoverTool))
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# hover[ikey].renderers=[source.data[key]]
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# hover[ikey].tooltips=tooltips+[("Series",key),("Time","@timeString"), ("Value", "@"+key)]
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hover.tooltips=[("Series",key),("Time","@timeString"), ("Value", "@"+key)]
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# hover.mode = "mouse"
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ikey+=1
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p[mainKey].legend.orientation="top_left"
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renderer = p[mainKey].select(dict(name=key))
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ds[mainKey]=renderer[0].data_source
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# allP = vplot(*p.values())
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# allP = gridplot([p.values()])
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group=lambda flat, size: [flat[i:i+size] for i in range(0,len(flat), size)]
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allP = gridplot(group(p.values(),1))
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show(allP)
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while True:
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print 'updating...'
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self.db=st.DB('data.sdb','master')
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self.db.loadDB('master')
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self.df = self.db.df
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now=datetime.datetime.now()
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tstart=now-datetime.timedelta(days=0,hours=timeRange-self.UTCOffset)
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tcut=(tstart-epoch).total_seconds()
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dataFrame=self.df[self.df.timestamp>tcut]
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dataFrame['t']=dataFrame.timestamp*1000 - self.UTCOffset*3600*1000
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for mainKey in keyList:
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ds[mainKey].data = dataFrame.to_dict('list')
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# print ds.data['stationIRTemp']
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cursession().store_objects(ds[mainKey])
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time.sleep(30)
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