Update app.py (#1)

- Update app.py (d12744db7845eabdf43892ab9d73b5f2ba1ec61d)

app.py

@@ -7,9 +7,11 @@ st.set_page_config(layout='wide')
 
 @st.cache(allow_output_mutation=True)
 def load_model():
+    """Load pretrained model from SentenceTransformer"""
     return SentenceTransformer('all-MiniLM-L6-v2')
 
 def semantic_search(model, sentence, corpus_embeddings):
+    """Perform semantic search on the corpus"""
     query_embeddings = model.encode(sentence,
                                     convert_to_tensor=True,
                                     normalize_embeddings=True)
@@ -21,9 +23,10 @@ def semantic_search(model, sentence, corpus_embeddings):
 
     return pd.DataFrame(hits[0])
 
-def top_k_similarity(model, df, query, corpus_embeddings):
+def get_similarity_score(model, data, query, corpus_embeddings):
+    """Get similarity score for each data point"""
     hits = semantic_search(model, [query], corpus_embeddings)
-    result = pd.merge(df, hits, left_on='ID', right_on='corpus_id')
+    result = pd.merge(data, hits, left_on='ID', right_on='corpus_id')
     result.sort_values(by='score', ascending=False, inplace=True)
     return result
 
@@ -49,20 +52,21 @@ def load_dataset(columns: List) -> pd.DataFrame:
     return data
 
 def show_aggrid_table(result: pd.DataFrame):
+    """Show interactive table from similarity result"""
     gb = GridOptionsBuilder.from_dataframe(result)
     gb.configure_pagination(paginationAutoPageSize=True)
     gb.configure_side_bar()
     gb.configure_default_column(min_column_width=200)
     gb.configure_selection('multiple', use_checkbox=True, groupSelectsChildren="Group checkbox select children")
-    gb.configure_column(field="LinkedIn Profile",
-                        headerName="LinkedIn Profile",
+    gb.configure_column(field='LinkedIn Profile',
+                        headerName='LinkedIn Profile',
                         cellRenderer=JsCode('''function(params) {return `<a href=${params.value} target="_blank">${params.value}</a>`}'''))
 
-    gridOptions = gb.build()
+    grid_options = gb.build()
 
     grid_response = AgGrid(
         dataframe=result,
-        gridOptions=gridOptions,
+        gridOptions=grid_options,
         height=1100,
         fit_columns_on_grid_load=True,
         data_return_mode='AS_INPUT',
@@ -73,6 +77,7 @@ def show_aggrid_table(result: pd.DataFrame):
     )
 
 def main():
+    """Main Function"""
     st.title('Job Posting Similarity')
     st.write('This app will help you find similar job titles real-time from ecommurz google sheets.')
 
@@ -87,16 +92,16 @@ def main():
 
     if submitted:
         st.info(f'Showing results for {job_title}')
-        result = top_k_similarity(model, data, job_title, corpus_embeddings)
+        result = get_similarity_score(model, data, job_title, corpus_embeddings)
         result = result[columns]
 
-        st.download_button(
-            "Download Table",
-            result.to_csv().encode('utf-8'),
-            "result.csv",
-            "text/csv",
-            key='download-csv'
-        )
+        # st.download_button(
+        #     "Download Table",
+        #     result.to_csv().encode('utf-8'),
+        #     "result.csv",
+        #     "text/csv",
+        #     key='download-csv'
+        # )
 
         show_aggrid_table(result)