SUFFIX= '.bz2'
URLS = [
PREFIX+'yellow_tripdata_2015-01.csv'+SUFFIX,
PREFIX+'yellow_tripdata_2015-02.csv'+SUFFIX,
PREFIX+'yellow_tripdata_2015-03.csv'+SUFFIX,
PREFIX+'yellow_tripdata_2015-04.csv'+SUFFIX,
PREFIX+'yellow_tripdata_2015-05.csv'+SUFFIX,
PREFIX+'yellow_tripdata_2015-06.csv'+SUFFIX,
]
filenames = pd.DataFrame({'filename': URLS})
cst = Constant(df=filenames, scheduler=s)
csv = CSVLoader(index_col=False,skipinitialspace=True,usecols=['pickup_longitude', 'pickup_latitude'], filter=filter, scheduler=s)
#csv = CSVLoader(index_col=False,skipinitialspace=True,usecols=['pickup_longitude', 'pickup_latitude'], scheduler=s)
csv.input.filenames = cst.output.df
pr = Every(scheduler=s)
pr.input.df = csv.output.df
scatterplot = ScatterPlot('pickup_longitude', 'pickup_latitude', scheduler=s)
scatterplot.create_dependent_modules(csv,'df')
if __name__=='__main__':
s.start()
while True:
time.sleep(2)
scheluder.to_json()
scatterplot.to_json() # simulate a web query
scatterplot.get_image()
s.join()
print len(csv.df())
