Merge c0f92a5 into 1f7398c

brain/session/model_generate.py

@@ -82,7 +82,16 @@ def generate_model(self):
                 self.list_error,
                 random_state=rand
             )
-
+        if model_type == 'bagr':
+            rand = current_app.config.get('RANDOM_STATE')
+            rand = None if rand == 'None' else rand
+            result = baggen(
+                model_type,
+                self.collection,
+                payload,
+                self.list_error,
+                random_state=rand
+            )
         # store any errors
         if result and result['error']:
             self.list_error.extend(result['error'])

brain/session/predict/bag.py

@@ -8,14 +8,18 @@ def predict(model, collection, predictors):
     decision_function = None
     collection_adjusted = collection.lower().replace(' ', '_')
     list_model_type = current_app.config.get('MODEL_TYPE')
-    rs = [list_model_type[3],
-          list_model_type[5],
-          list_model_type[7],
-          list_model_type[9]]
-    cs = [list_model_type[2],
-          list_model_type[4],
-          list_model_type[6],
-          list_model_type[8]]
+    rs = [
+        list_model_type[3],
+        list_model_type[5],
+        list_model_type[7],
+        list_model_type[9]
+    ]
+    cs = [
+        list_model_type[2],
+        list_model_type[4],
+        list_model_type[6],
+        list_model_type[8]
+    ]
 
     clf = Model().uncache(
         model + '_model',
@@ -50,6 +54,7 @@ def predict(model, collection, predictors):
             },
             'error': None
         }
+
     elif model in rs:
         r2 = Hset().uncache(
             model + '_r2',

interface/static/data/json/programmatic_interface/bagr/dataset_url/bagr-model-predict.json

@@ -0,0 +1,15 @@
+{
+    "properties": {
+        "collection": "bagr-1",
+        "session_type": "model_predict",
+        "prediction_input[]": [
+            "22.22",
+            "96.24",
+            "338",
+            "72.55",
+            "0.001",
+            "28",
+            "0.678"
+        ]
+    }
+}

interface/static/data/json/programmatic_interface/bagr/file_upload/bagr-data-append.json

@@ -1,6 +1,6 @@
 {
     "properties": {
-        "collection": "bgr-2",
+        "collection": "bagr-2",
         "dataset_type": "file_upload",
         "session_type": "data_append",
         "model_type": "bagr",

interface/static/data/json/programmatic_interface/bagr/file_upload/bagr-data-new.json

@@ -1,7 +1,7 @@
 {
 	"properties": {
             "session_name": "sample_bgr_title",
-            "collection": "bgr-2",
+            "collection": "bagr-2",
             "dataset_type": "file_upload",
             "session_type": "data_new",
             "model_type": "bagr",

interface/static/data/json/programmatic_interface/bagr/file_upload/bagr-model-predict.json

@@ -0,0 +1,15 @@
+{
+    "properties": {
+        "collection": "bagr-2",
+        "session_type": "model_predict",
+        "prediction_input[]": [
+            "22.22",
+            "96.24",
+            "338",
+            "72.55",
+            "0.001",
+            "28",
+            "0.678"
+        ]
+    }
+}

test/live_server/3_programmatic_interface/dataset_url/pytest_bagr_dataset_url.py

@@ -0,0 +1,160 @@
+'''
+
+This file will test the following bagr sessions:
+
+  - data_new: stores supplied dataset into a SQL database.
+  - data_append: appends supplied dataset to an already stored dataset in an
+                 SQL database.
+  - model_generate: generate an model by selecting a particular range of
+                    dataset (session), and store it into a NoSQL cache.
+  - model_predict: generate a prediction by selecting a particular cached
+                   model from the NoSQL cache.
+
+Note: the 'pytest' instances can further be reviewed:
+
+    - https://pytest-flask.readthedocs.io/en/latest
+    - http://docs.pytest.org/en/latest/usage.html
+
+'''
+
+import json
+import os.path
+from flask import current_app, url_for
+
+
+def get_sample_json(jsonfile, model_type):
+    '''
+
+    Get a sample json dataset.
+
+    '''
+
+    # local variables
+    root = current_app.config.get('ROOT')
+
+    # open file
+    json_dataset = None
+
+    with open(
+        os.path.join(
+            root,
+            'interface',
+            'static',
+            'data',
+            'json',
+            'programmatic_interface',
+            model_type,
+            'dataset_url',
+            jsonfile
+        ),
+        'r'
+    ) as json_file:
+        json_dataset = json.load(json_file)
+
+    return json.dumps(json_dataset)
+
+
+def test_data_new(client, live_server):
+    '''
+
+    This method tests the 'data_new' session.
+
+    '''
+
+    @live_server.app.route('/load-data')
+    def get_endpoint():
+        return url_for('name.load_data', _external=True)
+
+    live_server.start()
+
+    res = client.post(
+        get_endpoint(),
+        headers={'Content-Type': 'application/json'},
+        data=get_sample_json('bagr-data-new.json', 'bagr')
+    )
+
+    # assertion checks
+    assert res.status_code == 200
+    assert res.json['status'] == 0
+
+
+def test_data_append(client, live_server):
+    '''
+
+    This method tests the 'data_new' session.
+
+    '''
+
+    @live_server.app.route('/load-data')
+    def get_endpoint():
+        return url_for('name.load_data', _external=True)
+
+    live_server.start()
+
+    res = client.post(
+        get_endpoint(),
+        headers={'Content-Type': 'application/json'},
+        data=get_sample_json('bagr-data-append.json', 'bagr')
+    )
+
+    # assertion checks
+    assert res.status_code == 200
+    assert res.json['status'] == 0
+
+
+def test_model_generate(client, live_server):
+    '''
+
+    This method tests the 'model_generate' session.
+
+    '''
+
+    @live_server.app.route('/load-data')
+    def get_endpoint():
+        return url_for('name.load_data', _external=True)
+
+    live_server.start()
+
+    res = client.post(
+        get_endpoint(),
+        headers={'Content-Type': 'application/json'},
+        data=get_sample_json('bagr-model-generate.json', 'bagr')
+    )
+
+    # assertion checks
+    assert res.status_code == 200
+    assert res.json['status'] == 0
+
+
+def test_model_predict(client, live_server):
+    '''
+
+    This method tests the 'model_predict' session.
+
+    Note: for debugging, the following syntax will output the corresponding
+          json values, nested within 'json.loads()', to the travis ci:
+
+          raise ValueError(res.json['result']['key1'])
+
+    '''
+
+    @live_server.app.route('/load-data')
+    def get_endpoint():
+        return url_for('name.load_data', _external=True)
+
+    live_server.start()
+
+    res = client.post(
+        get_endpoint(),
+        headers={'Content-Type': 'application/json'},
+        data=get_sample_json('bagr-model-predict.json', 'bagr')
+    )
+
+    # assertion checks
+    assert res.status_code == 200
+    assert res.json['status'] == 0
+    assert res.json['result']
+    assert res.json['result']['confidence']
+    assert res.json['result']['confidence']['score'] == '0.96282488659958954'
+    assert res.json['result']['model'] == 'bagr'
+    assert res.json['result']['result'] == '33.4442'