app had to be restructured in order to not use the graph object as a global...

app had to be restructured in order to not use the graph object as a global variable, I think this was causing the bug

dash_app/app.py

 import os
+import json
 import dash
 import dash_core_components as dcc
 import dash_html_components as html
+from dash.exceptions import PreventUpdate
 from dash.dependencies import Input, Output, State
 from dash_app.graph import Graph
+from dash_app.words import AssociatedWords
 
 
 external_stylesheets = [
@@ -18,9 +21,12 @@ external_stylesheets = [
 
 app = dash.Dash(name=__name__, external_stylesheets=external_stylesheets, url_base_pathname='/msx/',
                 suppress_callback_exceptions=True)
-graph = Graph()
-graph.fill_with_associations('fruit')
-cyto_graph = graph.get_graph('msx-graph')
+
+server = app.server
+server.config['SECRET_KEY'] = os.environ['MSX_SECRET_KEY']
+
+
+word2vec_model = AssociatedWords()
 
 
 app.layout = html.Div(children=[
@@ -40,7 +46,13 @@ app.layout = html.Div(children=[
                 ])
             ]),
         html.Br(),
-        html.Div(id='msx-graph-div', children=[cyto_graph]),
+        html.Div(id='base-word-div',
+                 style={'display': 'none'},
+                 ),
+        html.Div(id='graph-elements-div',
+                 style={'display': 'none'},
+                 ),
+        html.Div(id='msx-graph-div', children=[]),
         html.Div(children=[
             html.Div(className='row', children=[
                 html.Div(className='col-3', children=[
@@ -55,41 +67,94 @@ app.layout = html.Div(children=[
                     html.Button(id='remove-word-button', n_clicks_timestamp=0, children='Remove Selected Association', className='btn btn-danger btn-lg')]),
                 ]),
             ]),
-
     ]),
 ])
 
 
-server = app.server
-server.config['SECRET_KEY'] = os.environ['MSX_SECRET_KEY']
+@app.callback(
+    Output(component_id='msx-graph-div', component_property='children'),
+    Input(component_id='submit-word-button', component_property='n_clicks'),
+)
+def update_graph_div(submit_word_button):
+    graph = Graph()
+    graph.set_nodes_and_edges({'nodes': [], 'edges': []})
+    return graph.get_cytoscape_graph('msx-graph')
 
 
 @app.callback(
-    Output(component_id='msx-graph', component_property='autoRefreshLayout'),
-    Output(component_id='msx-graph', component_property='elements'),
-    Input(component_id='add-word-button', component_property='n_clicks_timestamp'),
-    Input(component_id='remove-word-button', component_property='n_clicks_timestamp'),
-    Input(component_id='submit-word-button', component_property='n_clicks_timestamp'),
-    State(component_id='msx-graph', component_property='tapNodeData'),
-    State(component_id='add-word-input', component_property='value'),
+    Output(component_id='base-word-div', component_property='children'),
+    Input(component_id='submit-word-button', component_property='n_clicks'),
+    State(component_id='base-word-input', component_property='value'),
+)
+def update_base_word(submit_word_button, base_word_input):
+    return base_word_input
+
+
+@app.callback(
+    Output(component_id='graph-elements-div', component_property='children'),
+    Input(component_id='submit-word-button', component_property='n_clicks'),
+    Input(component_id='add-word-button', component_property='n_clicks'),
+    Input(component_id='remove-word-button', component_property='n_clicks'),
     State(component_id='base-word-input', component_property='value'),
+    State(component_id='add-word-input', component_property='value'),
+    State(component_id='graph-elements-div', component_property='children'),
+    State(component_id='msx-graph', component_property='tapNodeData'),
+    State(component_id='base-word-div', component_property='children'),
+    prevent_initial_call=True
+)
+def update_graph_elements(submit_word_button, add_word_button, remove_word_button, base_word_input, add_word_input,
+                          nodes_and_edges, selected_nodes, base_word_state):
+
+    callback_context = dash.callback_context
+    button_id = callback_context.triggered[0]['prop_id'].split('.')[0]
+
+    graph = Graph()
+
+    if button_id == 'submit-word-button':
+        graph.fill_with_associations(word2vec_model, base_word_input)
+        new_nodes_and_edges = graph.get_nodes_and_edges()
+        return json.dumps(new_nodes_and_edges)
+
+    if button_id == 'add-word-button':
+        graph.set_nodes_and_edges(json.loads(nodes_and_edges))
+        if add_word_input is not None and add_word_input != '' and add_word_input not in graph.get_all_words():
+            graph.add_node(add_word_input)
+            graph.add_edge(base_word_state, add_word_input)
+            new_nodes_and_edges = json.dumps(graph.get_nodes_and_edges())
+            return new_nodes_and_edges
+        else:
+            raise PreventUpdate
+
+    if button_id == 'remove-word-button':
+        graph.set_nodes_and_edges(json.loads(nodes_and_edges))
+        if selected_nodes is not None:
+            selected_word = selected_nodes['label']
+            if selected_word in graph.get_all_words() and selected_word != base_word_state:
+                graph.remove_node(selected_nodes['label'])
+                new_nodes_and_edges = json.dumps(graph.get_nodes_and_edges())
+                return new_nodes_and_edges
+            else:
+                raise PreventUpdate
+        else:
+            raise PreventUpdate
+
+
+@app.callback(
+    Output(component_id='msx-graph', component_property='elements'),
+    Input(component_id='graph-elements-div', component_property='children'),
+    prevent_initial_call=True
+)
+def update_graph(nodes_and_edges):
+    graph = Graph()
+    graph.set_nodes_and_edges(json.loads(nodes_and_edges))
+    return graph.get_elements()
+
+
+@app.callback(
+    Output(component_id='msx-graph', component_property='autoRefreshLayout'),
+    Input(component_id='add-word-button', component_property='n_clicks'),
+    Input(component_id='remove-word-button', component_property='n_clicks'),
+    prevent_initial_call=True
 )
-def graph_elements_callback(add_button_ts, remove_button_ts, submit_button_ts, graph_selected, add_word, base_word):
-    if submit_button_ts > remove_button_ts and submit_button_ts > add_button_ts:
-        graph.fill_with_associations(base_word)
-        graph_elements = graph.get_graph_elements()
-        return True, graph_elements
-
-    if remove_button_ts > add_button_ts:
-        if graph_selected is not None:
-            selected_word = graph_selected['label']
-            if selected_word in graph.get_all_words() and selected_word != graph.get_base_word():
-                graph.remove_node(graph_selected['label'])
-
-    if add_button_ts > remove_button_ts:
-        if add_word is not None and add_word != '' and add_word not in graph.get_all_words():
-            graph.add_node(add_word)
-            graph.add_edge(graph.get_base_word(), add_word)
-
-    graph_elements = graph.get_graph_elements()
-    return False, graph_elements
+def set_auto_refresh_layout(add_word_button, remove_word_button):
+    return False

dash_app/graph.py

 import dash_cytoscape as cyto
-from dash_app.words import AssociatedWords
 
 
 class Graph:
 
     def __init__(self):
-        self.associated_words = AssociatedWords()
         self.nodes = []
         self.edges = []
 
-    def get_base_word(self):
-        return self.associated_words.get_base_word()
-
     def get_all_words(self):
         all_words = [node_dict['data']['label'] for node_dict in self.nodes]
         return all_words
@@ -20,13 +15,8 @@ class Graph:
         self.nodes = []
         self.edges = []
 
-    def fill_with_associations(self, base_word):
-        self.associated_words.set_base_word(base_word)
-        self.fill_graph()
-
-    def fill_graph(self):
-        base_word = self.associated_words.get_base_word()
-        associated_words = self.associated_words.get_associated_words()
+    def fill_with_associations(self, word2vec_model, base_word):
+        associated_words = word2vec_model.get_associated_words(base_word)
         self.clear_graph_elements()
         self.add_node(base_word, is_base_node=1)
         self.add_nodes(associated_words)
@@ -71,14 +61,21 @@ class Graph:
         for edge_idx_to_remove in edges_idxs_to_remove:
             self.edges.pop(edge_idx_to_remove)
 
-    def get_graph_elements(self):
-        nodes_and_edges = []
-        nodes_and_edges.extend(self.nodes)
-        nodes_and_edges.extend(self.edges)
-        return nodes_and_edges
+    def get_nodes_and_edges(self):
+        return {'nodes': self.nodes, 'edges': self.edges}
+
+    def set_nodes_and_edges(self, nodes_and_edges):
+        self.nodes = nodes_and_edges['nodes']
+        self.edges = nodes_and_edges['edges']
+
+    def get_elements(self):
+        elements = []
+        elements.extend(self.nodes)
+        elements.extend(self.edges)
+        return elements
 
-    def get_graph(self, component_id):
-        elements = self.get_graph_elements()
+    def get_cytoscape_graph(self, component_id):
+        elements = self.get_elements()
         return cyto.Cytoscape(id=component_id,
                               autoRefreshLayout=True,
                               layout={'name': 'cose', 'animate': True},

dash_app/words.py

@@ -10,32 +10,23 @@ class AssociatedWords:
         self.model = api.load('glove-twitter-200')
         print(" Word2Vec model is ready. Enjoy!!!\n")
 
-        self.base_word = None
-        self.gensim_result = None
-        self.filtered_results = None
-        self.words = None
-
-    def set_base_word(self, word):
-        self.base_word = word
-        self.gensim_result = self.model.most_similar(self.base_word, topn=self.N_RESULTS)
-        # self.gensim_result = [('apple', 1.0), ('banana', 1.0), ('strawberry', 1.0)]
-        self.filter_results()
-
-    def filter_results(self):
-        self.filtered_results = [result_tuple for result_tuple in self.gensim_result if self.passes_filter(result_tuple[0])]
-        self.words = [result_tuple[0] for result_tuple in self.filtered_results]
-
-    def passes_filter(self, word):
+    def get_associated_words(self, word):
+        gensim_result = self.model.most_similar(word, topn=self.N_RESULTS)
+        # gensim_result = [('apple', 1.0), ('banana', 1.0), ('strawberry', 1.0)]
+        words = self.filter_results(gensim_result, word)
+        return words
+
+    def filter_results(self, gensim_result, base_word):
+        filtered_results = [result_tuple for result_tuple in gensim_result if self.passes_filter(result_tuple[0], base_word)]
+        words = [result_tuple[0] for result_tuple in filtered_results]
+        return words
+
+    @staticmethod
+    def passes_filter(word, base_word):
         if 'www' in word or \
-                    word in self.base_word or \
-                    sdi.rdlevenshtein_norm(word, self.base_word) < 0.5:
+                    word in base_word or \
+                    sdi.rdlevenshtein_norm(word, base_word) < 0.5:
                         
             return False
         else:
             return True
-
-    def get_base_word(self):
-        return self.base_word
-
-    def get_associated_words(self):
-        return self.words