Update Home.py

Home.py

@@ -3,6 +3,7 @@ import streamlit as st
 import pandas as pd
 import numpy as np
 import re
+from eldar import Query
 
 
 #===config===
@@ -40,7 +41,7 @@ c1, c2 = st.columns([6,4])
 text_search = c1.text_input("Cari berdasarkan penulis, judul, hingga full-text. Pisahkan dengan semikolon (;)")
 
 # Get keywords from search bar
-keyword_list_j = [keyword.strip() for keyword in text_search.split(";")]
+#keyword_list_j = [keyword.strip() for keyword in text_search.split(";")]
 
 # option to choose
 part_opt = ["Title", "Abstract (en)", "Abstract (id)", "Keywords", "Introduction", "Method", "Result", "Discussion", "Result & Discussion", "Conclusion", "Full-text"]
@@ -51,17 +52,30 @@ search_opt = c2.multiselect(
      part_opt,
      ["Title", "Abstract (en)", "Keywords"])
 
+
+
 #tab1, tab2 = st.tabs(["🔍 Hasil Pencarian", "📊 Analisis Hasil"])
 
 
 if keyword_list_j is not None:        
-    key_df_j = pd.DataFrame()
-    patterns = [r'\b{}\b'.format(re.escape(word)) for word in keyword_list_j]
+    #key_df_j = pd.DataFrame()
+    #patterns = [r'\b{}\b'.format(re.escape(word)) for word in keyword_list_j]
     
-    for col in search_opt:
-        conditions = [df[col].str.contains(pattern, regex=True, flags=re.IGNORECASE) for pattern in patterns]
-        column_result = df[np.logical_and.reduce(conditions)]
-        key_df_j = pd.concat([key_df_j, column_result]).drop_duplicates()
+    #for col in search_opt:
+        #conditions = [df[col].str.contains(pattern, regex=True, flags=re.IGNORECASE) for pattern in patterns]
+        #column_result = df[np.logical_and.reduce(conditions)]
+        #key_df_j = pd.concat([key_df_j, column_result]).drop_duplicates()
+    @st.cache_data
+    def search_data(text_search):
+        df = key_df_j
+        key_df_j["__combined__"] = key_df_j[selected_cols].fillna("").agg(" ".join, axis=1)
+        query = Query(text_search, ignore_case=True)
+        key_df_j["df_result"] = key_df_j["__combined__"].apply(query)
+        
+        return key_df_j
+
+    key_df_j = search_data(text_search)
+    st.write(key_df_j)
     
     # creating result
     if text_search:
@@ -76,8 +90,6 @@ if keyword_list_j is not None:
         red = popover.checkbox("Show red items.", True)
         blue = popover.checkbox("Show blue items.", True)
 
-        
-
         @st.cache_data
         def get_data(df):
             df = pd.DataFrame(
@@ -89,7 +101,7 @@ if keyword_list_j is not None:
         def convert_for_download(dfs):
             return df.to_csv().encode("utf-8")
         
-        dfs = get_data(df)
+        dfs = get_data(key_df_j)
         csv = convert_for_download(dfs)
 
         popover.download_button(