These examples should give some idea how avaa_api.* codes are used for downloading short piece (one day) of data from different years in a loop.

--------------------------------------------------------------------------------
Matlab

yrs=2011:2012;
fdate=[6,1];
ldate=[6,2];
tablevars={'VAR_META.WS00','VAR_META.WDIR'};
interval=60;
agg='arithmetic';
% leave quality undefined = use default value

for yy=yrs
  fprintf('%d\n',yy)
  data=avaa_api(datenum([yy,fdate]),datenum([yy,ldate]),tablevars,'interval',interval,'aggregation',agg);
end

------------------------------------------------------------------------------
Python

import datetime, avaa_api

yrs=[2011,2012]
fdate=[6,1]
ldate=[6,2]
tablevars=['VAR_META.WS00','VAR_META.WDIR']
interval=60
agg='ARITHMETIC'
# leave quality undefined = use default value

for yy in yrs:
    print('%d' % yy)
    d1=datetime.datetime(yy,fdate[0],fdate[1])    
    d2=datetime.datetime(yy,ldate[0],ldate[1])
    data=avaa_api.getData(d1,d2,tablevars,interval=interval,aggregation=agg)

------------------------------------------------------------------------------
R

source("c:/Matlab/Database/avaa_api.r")

yrs<-c(2011,2012)
fdate<-c(6,1)
ldate<-c(6,2)
tablevars<-c("VAR_META.WS00","VAR_META.WDIR")
interval<-60
agg<-"ARITHMETIC"
# leave quality undefined = use default value

for(yy in yrs) {
  print(yy)
  d1<-ISOdatetime(yy,fdate[1],fdate[2],0,0,0,tz="GMT") # force timezone to UTC/GMT to avoid daylight saving time shifts
  d2<-ISOdatetime(yy,ldate[1],ldate[2],0,0,0,tz="GMT")
  data<-getSmearData(d1,d2,dbtablevariables=tablevars,interval=interval,aggregation=agg)
}