Basic prediction webserver

app.py

@@ -0,0 +1,36 @@
+from bottle import hook, request, response, route, run
+from sklearn.externals import joblib
+
+mlb, classifier = joblib.load('offClassifier.pkl')
+
+
+@hook('after_request')
+def enable_cors():
+    """
+    You need to add some headers to each request.
+    Don't use the wildcard '*' for Access-Control-Allow-Origin in production.
+    """
+    response.headers['Access-Control-Allow-Origin'] = '*'
+    response.headers['Access-Control-Allow-Methods'] = 'PUT, GET, POST, DELETE, OPTIONS'
+    response.headers['Access-Control-Allow-Headers'] = 'Origin, Accept, Content-Type, X-Requested-With, X-CSRF-Token'
+
+
+@route('/predict', method=['OPTIONS', 'POST'])
+def predict():
+    if request.method == 'OPTIONS':
+        return {}
+
+    products = request.json
+    predictions = mlb.inverse_transform(
+        classifier.predict([p['name'] for p in products])
+    )
+    return {
+        'data': [
+            product.update({'predictedCategories': categories}) or product
+            for product, categories in zip(products, predictions)
+        ]
+    }
+
+
+if __name__ == '__main__':
+    run(host='localhost', port=4242)