Merge pull request #3112 from jeff1evesque/bug-3100

#3100: Ensure flask logs errors to designated file

Author: jeff1evesque

README.md

@@ -68,9 +68,10 @@ The following lines, indicate the application is accessible via `localhost:8080`
 ```bash
 ...
   ## Create a forwarded port mapping which allows access to a specific port
-  #  within the machine from a port on the host machine. In the example below,
-  #  accessing "localhost:8080" will access port 80 on the guest machine.
-  config.vm.network "forwarded_port", guest: 5000, host: 8080
+  ## within the machine from a port on the host machine. In the example below,
+  ## accessing "localhost:8080" will access port 80 on the guest machine.
+  main.vm.network 'forwarded_port', guest: 5000, host: 8080
+  main.vm.network 'forwarded_port', guest: 6000, host: 9090
 ...
 ```
 
@@ -85,8 +86,8 @@ Both the web-interface, and the programmatic-api, have corresponding
 
 ### Web Interface
 
-The [web-interface](https://github.com/jeff1evesque/machine-learning/blob/master/interface/templates/index.html)
-, or GUI implementation, allow users to implement the following sessions:
+The [web-interface](https://github.com/jeff1evesque/machine-learning/blob/master/interface/templates/index.html),
+ or GUI implementation, allow users to implement the following sessions:
 
 - `data_new`: store the provided dataset(s), within the implemented sql
  database.
@@ -139,13 +140,21 @@ A post request, can be implemented in python, as follows:
 ```python
 import requests
 
-endpoint_url = 'https://localhost:8080/load-data'
-headers = {'Content-Type': 'application/json'}
+endpoint = 'https://localhost:9090/load-data'
+headers = {
+    'Authorization': 'Bearer ' + token,
+    'Content-Type': 'application/json'
+}
 
-requests.post(endpoint_url, headers=headers, data=json_string_here)
+requests.post(endpoint, headers=headers, data=json_string_here)
 ```
 
-**Note:** the above `post` request, can be implemented in a different language,
- respectively.
+**Note:** more information, regarding how to obtain a valid `token`, can be further
+ reviewed, in the `/login` [documentation](https://github.com/jeff1evesque/machine-learning/tree/master/doc/programmatic_interface/authentication/login.rst).
 
 **Note:** various `data` [attributes](https://github.com/jeff1evesque/machine-learning/blob/master/doc/programmatic_interface/data_attributes.rst) can be nested in above `POST` request.
+
+It is important to remember that the [`Vagrantfile`](https://github.com/jeff1evesque/machine-learning/blob/98c7f57986cbe56ca14f8ee47859b50a08c2ef9b/Vagrantfile#L54-L55),
+ as denoted by the above snippet, has defined two port forwards. Specifically, on
+ the host, `8080` is reserved for the web-interface, while `9090`, is reserved for
+ the programmatic rest-api.

Vagrantfile

@@ -52,6 +52,7 @@ Vagrant.configure(2) do |config|
         ## within the machine from a port on the host machine. In the example below,
         ## accessing "localhost:8080" will access port 80 on the guest machine.
         main.vm.network 'forwarded_port', guest: 5000, host: 8080
+        main.vm.network 'forwarded_port', guest: 6000, host: 9090
 
         ## Run r10k
         main.r10k.puppet_dir      = "puppet/environment/#{puppet_environment}"

app.py

@@ -22,10 +22,10 @@
             '--cov', '.',
             'test/live_server'
         ])
-    elif sys.argv[1] == 'run':
+    elif sys.argv[1] == 'run-api':
         args = {
             'prefix': 'test/hiera',
-            'settings': ''
+            'instance': 'programmatic'
         }
         app = create_app(args)
         app.run(host='0.0.0.0')

brain/database/account.py

@@ -152,5 +152,7 @@ def get_uid(self, username):
         # return result
         if response_error:
             return {'error': response_error, 'result': None}
+        elif not response['result']:
+            return {'error': 'no uid', 'result': None}
         else:
             return {'error': None, 'result': response['result'][0][0]}

brain/load_data.py

@@ -14,7 +14,6 @@
 from brain.session.model_generate import ModelGenerate
 from brain.session.model_predict import ModelPredict
 from brain.database.session import Session
-from brain.database.account import Account
 
 
 class Load_Data(object):
@@ -31,7 +30,7 @@ class Load_Data(object):
 
     '''
 
-    def __init__(self, data, username=None):
+    def __init__(self, data, uid=None):
         '''
 
         This constructor is responsible for defining class variables.
@@ -47,17 +46,13 @@ def __init__(self, data, username=None):
         ]
         self.list_error = []
 
-        # flask session user
-        if 'uid' in session and session['uid']:
-            self.uid = session['uid']
+        # programmatic api: flask jwt-token user
+        if uid:
+            self.uid = uid
 
-        # flask jwt-token user
-        elif username:
-            uid = Account().get_uid(username)
-            if uid['result']:
-                self.uid = uid['result']
-            else:
-                self.uid = current_app.config.get('USER_ID')
+        # web interface: flask session user
+        elif (not uid and 'uid' in session and session['uid']):
+            self.uid = session['uid']
 
         # unauthenticated user
         else:
@@ -89,7 +84,6 @@ def load_data_new(self):
             }
 
         else:
-            print session.get_errors()
             response = {
                 'status': 1,
                 'msg': 'Dataset(s) not uploaded into database',

doc/programmatic_interface/authentication/login.rst

@@ -32,15 +32,15 @@ a valid token, to the ``/load-data`` endpoint:
 
     # login and get flask-jwt token
     login = client.post(
-        '/login',
+        'https://localhost:9090/login',
         headers={'Content-Type': 'application/json'},
         data=payload
     )
     token = login.json['access_token']
 
     # provide flask-jwt token
-    login = client.post(
-        '/load-data',
+    res = client.post(
+        'https://localhost:9090/load-data',
         headers={
             'Authorization': 'Bearer ' + token,
             'Content-Type': 'application/json'

doc/programmatic_interface/data/data_append.rst

@@ -23,25 +23,13 @@ the ``data`` attribute, in a given ``POST`` request:
 
     import requests
 
-    endpoint_url = 'https://localhost:8080/load-data'
-    headers = {'Content-Type': 'application/json'}
-
-    requests.post(endpoint_url, headers=headers, data=json_string_here)
-
-To submit a ``/load-data`` request, as a valid authenticated user, a valid token
-must be suppied to the ``headers``:
-
-.. code:: python
-
-    import requests
-
-    endpoint_url = 'https://localhost:8080/load-data'
-    headers={
+    endpoint = 'https://localhost:9090/load-data'
+    headers = {
         'Authorization': 'Bearer ' + token,
         'Content-Type': 'application/json'
-    },
+    }
 
-    requests.post(endpoint_url, headers=headers, data=json_string_here)
+    requests.post(endpoint, headers=headers, data=json_string_here)
 
 **Note:** more information, regarding how to obtain a valid ``token``, can be further
 reviewed, in the ``/login`` `documentation <https://github.com/jeff1evesque/machine-learning/tree/master/doc/programmatic_interface/authentication/login.rst>`_.

doc/programmatic_interface/data/data_new.rst

@@ -23,25 +23,13 @@ the ``data`` attribute, in a given ``POST`` request:
 
     import requests
 
-    endpoint_url = 'https://localhost:8080/load-data'
-    headers = {'Content-Type': 'application/json'}
-
-    requests.post(endpoint_url, headers=headers, data=json_string_here)
-
-To submit a ``/load-data`` request, as a valid authenticated user, a valid token
-must be suppied to the ``headers``:
-
-.. code:: python
-
-    import requests
-
-    endpoint_url = 'https://localhost:8080/load-data'
-    headers={
+    endpoint = 'https://localhost:9090/load-data'
+    headers = {
         'Authorization': 'Bearer ' + token,
         'Content-Type': 'application/json'
-    },
+    }
 
-    requests.post(endpoint_url, headers=headers, data=json_string_here)
+    requests.post(endpoint, headers=headers, data=json_string_here)
 
 **Note:** more information, regarding how to obtain a valid ``token``, can be further
 reviewed, in the ``/login`` `documentation <https://github.com/jeff1evesque/machine-learning/tree/master/doc/programmatic_interface/authentication/login.rst>`_.

doc/programmatic_interface/model/model_generate.rst

@@ -17,10 +17,16 @@ the ``data`` attribute, in a given ``POST`` request:
 
     import requests
 
-    endpoint_url = 'https://localhost:8080/load-data'
-    headers = {'Content-Type': 'application/json'}
+    endpoint = 'https://localhost:9090/load-data'
+    headers = {
+        'Authorization': 'Bearer ' + token,
+        'Content-Type': 'application/json'
+    }
 
-    requests.post(endpoint_url, headers=headers, data=json_string_here)
+    requests.post(endpoint, headers=headers, data=json_string_here)
+
+**Note:** more information, regarding how to obtain a valid ``token``, can be further
+reviewed, in the ``/login`` `documentation <https://github.com/jeff1evesque/machine-learning/tree/master/doc/programmatic_interface/authentication/login.rst>`_.
 
 The following properties define the above ``data`` attribute:
 

doc/programmatic_interface/predict/model_predict.rst

@@ -17,10 +17,16 @@ the ``data`` attribute, in a given ``POST`` request:
 
     import requests
 
-    endpoint_url = 'https://localhost:8080/load-data'
-    headers = {'Content-Type': 'application/json'}
+    endpoint = 'https://localhost:9090/load-data'
+    headers = {
+        'Authorization': 'Bearer ' + token,
+        'Content-Type': 'application/json'
+    }
 
-    requests.post(endpoint_url, headers=headers, data=json_string_here)
+    requests.post(endpoint, headers=headers, data=json_string_here)
+
+**Note:** more information, regarding how to obtain a valid ``token``, can be further
+reviewed, in the ``/login`` `documentation <https://github.com/jeff1evesque/machine-learning/tree/master/doc/programmatic_interface/authentication/login.rst>`_.
 
 The following properties define the above ``data`` attribute: