add an example

example.py

@@ -0,0 +1,39 @@
+#!/usr/bin/env python3
+import wget
+import zipfile
+import pandas as pd
+import os
+import shutil
+import sys
+from pdb import set_trace as bp
+#
+def dclean(dfiles):
+    if os.path.exists('asset'):
+        shutil.rmtree('asset')
+    for i, ival in enumerate(dfiles):
+        try:
+            os.remove(ival)
+        except OSError:
+            pass
+    return
+#
+zipfilename = 'occupancy_data.zip'
+dfiles = ['datatest2.txt', 'datatest.txt', 'datatraining.txt']
+dfiles.append(zipfilename)
+dclean(dfiles)
+if len(sys.argv) > 1:
+    if sys.argv[1] == 'clean':
+        sys.exit()
+url = 'http://archive.ics.uci.edu/ml/machine-learning-databases/00357/'+zipfilename
+filename = wget.download(url)
+zip_ref = zipfile.ZipFile(filename, 'r')
+zip_ref.extractall('./')
+zip_ref.close()
+df = pd.read_csv('datatraining.txt')
+directory = 'asset/data'
+if not os.path.exists(directory):
+    os.makedirs(directory)
+df['time'] = df.index
+df[['time','Temperature','Humidity']].to_csv(directory+'/sample.csv', index=False)
+import train
+dclean(dfiles)