Jupyter Service Development Guide

1. Take Kylin data

Import Requestsimport Pandas as Pddef getdtu (dtuid,addr):    sqldata = ' {' SQL ': ' select * from DTU where dtuid=\ '%s\ ' and Addr=\ '%s\ ' ORDER by dtutime Desc, ' project ': ' Yongli ', ' offset ': 0, ' limit ': '% ' (dtuid, addr)    response = Requests . Post (URL     = ' http://kylin1.wdp:7070/kylin/api/query ',                             data    = SqlData,                             auth    = (' admin ', ' admin ') ),                              headers = {"Content-type": "Application/json"})    Dfcols = PD. DataFrame (Response.json () ["Columnmetas"])    df = PD. DataFrame (Response.json () ["Results"], columns=dfcols["label"].values)    values = PD. DataFrame ({' Dtutime ': df["Dtutime"].map (PD. Timestamp),                            addr:df["Dtuvalue"]})        return valuesgetdtu (' 8627427973 ', ' 1800 ')

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2. Merging rows

From pandas import Series, Dataframeimport pandas as Pddef getdtustd (Dtuid, Addrs):    addrlist = Addrs.strip (). Split (', ')    result = PD. DataFrame ({' addr ': [],                           ' std ': []}) for        i in addrlist:        std = getstd (dtuid, i)        result = Result.append (STD, Ignore_index=true)        return result    getdtustd (' 8627427973 ', ' 1820,1810,0004 ')

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3. Merging columns

Import pandas as Pddef Getstdjson (dtuid,addr= ' 0002,0004,1019,101a,101b,101c,101d, 1023,1024,1025,1800,1802,1804,1806,1808,180A,180C,180E,1810,1812,1814,1816,1818,181A,181C,181E, 1820,1822,1824,1826,1828,182a,182c,182e,1830,2000,2002,2004,2006,2008,200a,200c,200e, 2100,2102,2104,2106,2108,210a,210c,210e '): data = GETDTUSTD (dtuid,addr) comments = PD. DataFrame ({' addr ': [' 0002 ', ' 0004 ', ' 1019 ', ' 101A ', ' 101B ', ' 101C ', ' 101D ', ' 1023 ', ' 1024 ', ' 1025 ', ' 1800 ', ' 1802 ', ' 1804 ', ' 1806 ', ' 1808 ', ' 180A ', ' 180C ', ' 180E ', ' 1810 ', ' 1812 ', ' 1814 ', ' 1816 ', ' 1818 ', ' 181A ', ' 181C ', ' 181E ', ' 1820 ', ' 1822 ', ' 1824 ', ' 1826 ', ' 1828 ', ' 182A ', ' 182C ', ' 182E ', ' 1830 ', ' + ', ' 2002 ', ' 2004 ', ' 2006 ', ' The ', ' 200A ', ' 200C ', ' 200E ', ' 2100 ', ' 2102 ', ' 2104 ', ' 2106 ', ' 2108 ', ' 210A ', ' 210C ', ' 210E ', ' comment ': [' voltage-to-ratio ', ' current-to-ratio ', ' A-phase power factor ', ' B-phase power factor ', ' C ' Phase factor ', ' total power factor ', ' frequency ', ' a phase phase angle ', ' b phase phase angle ', ' c phase angle ', ' a phase voltage ', ' B phase voltage ', ' C phase voltage ', ' average phase voltage ', ' ab line voltage ', ' BC line voltage ', ' CA line voltage ', ' average line voltage ', ' a phase current ', ' B-Phase current ', ' C-phase current ', ' Average current ', ' 0-wire current ', ' A-phase active power ', ' B-phase active power ', ' C-phase active power ', ' total active power ', ' A-phase reactive energy ', ' B-phase reactive energy ', ' C-phase reactive energy '', ' total reactive power ', ' A at the same rate ', ' b see in power ', ' C in power ', ' total apparent power ', ' a phase positive active energy ', ' B phase positive active energy ', ' c phase positive active energy ', ' total positive active energy ', ' a phase positive reactive energy ', ' B phase positive to reactive energy ',        ' C-phase positive reactive energy ', ' total forward reactive energy ', ' a opposite to active energy ', ' b opposite to active energy ', ' c opposite to active energy ', ' total reverse active energy ', ' a contrary to reactive energy ', ' b opposite to reactive energy ', ' C to reactive energy ', ' total reverse reactive energy '}) result = Pd.merge (data, comments, on= ' addr ') #print result return "{\" code\ ": 200,\" message\ ": \" Success\ ", \" data\ ":" + Result.to_json (orient= ' Records ', force_ascii=false) + "}" #getStdJson (' 8627427973 ', ' 1820,1810,0004 ')?

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4. Drawing

%matplotlib Inlineimport Matplotlib.pyplot as PLT, mpld3from matplotlib.ticker import Multiplelocator,         Funcformatterimport matplotlib.dates as Mdatedef drawdtu (dtuid,addr): #print "-------ENTER drawdtu (%s)-------"%dtuid data = GETDTU (DTUID,ADDR) FIG, ax = plt.subplots (figsize= (5,3)) Ax.plot (Data[0], data[1], '-', label= '%s '%ad DR, color = ' Blue ') Majorlocator = Multiplelocator (5) Majorformatter = Mdate. Dateformatter ('%H ') Minorlocator = Multiplelocator (1) ax.xaxis.set_major_locator (majorlocator) ax.xaxis.set_major _formatter (Majorformatter) # for the minor ticks, use no labels; Default Nullformatter ax.xaxis.set_minor_locator (minorlocator) #plt. Xlabel ("Date") #plt. Ylabel ("Value") #p    Lt.title ("DTU Monitor") plt.legend (loc= ' Upper Center ', bbox_to_anchor= (0.5,0.98), ncol=3,fancybox=true,shadow=true)    Ax.grid (color= "Lightgray", alpha=0.7) #fig. Set_size_inches (4, 4) #plt. Show () HTML = mpld3.fig_to_html (Fig) return HTML#DRAWDTU (' 8627427973 ', ' 0004 ') 

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5. Publishing services

From flask import flask, make_response, Requestapp = Flask (__name__) @app. Route ("/dtustd/", methods=["GET", "OPTIONS"]) def dtustd (dtuid):    #o = DRAWDTUSTD (dtuid)    o = Getstdjson (dtuid)    resp = Make_response (o)    resp.headers[ "Access-control-allow-origin"] = "*"    resp.headers["access-control-request-method"] = "post,get,put,delete, OPTIONS "    resp.headers[" access-control-allow-methods "] =" post,get,put,delete,options "    resp.headers[" Access-control-allow-headers "] =" X-requested-with,content-type "        if Request.method = = ' OPTIONS ':        print" It ' s OPTIONS "    return Respapp.run (host=" 0.0.0.0 ", port=5007)

Jupyter Service Development Guide