rmv sector

app.py

@@ -16,7 +16,8 @@ navbar = show_navbar()
 if navbar == "Home":
     st.session_state.page = home.show_page()
 elif navbar == "Sector Matches":
-    st.session_state.page = sector.show_page()
+    pass
+    #st.session_state.page = sector.show_page()
 elif navbar == "Similarity Matches":
     st.session_state.page = similarity.show_page()
 

sector.py

@@ -10,7 +10,7 @@ import pandas as pd
 import utils.crs_table as crs_table
 import utils.sdg_table as sdg_table
 import utils.filter_modules as filter_modules
-
+"""
 from importlib.machinery import SourceFileLoader
 crs_overlap = SourceFileLoader("crs_overlap", "data/models/crs_overlap.py").load_module()
 sdg_overlap = SourceFileLoader("sdg_overlap", "data/models/sdg_overlap.py").load_module()
@@ -68,12 +68,13 @@ SHOW_ALL_COUNTRIES = False # If all countries should be showed in matching
 ## ORGANIZATION
 SPECIAL_ORGA_SLECTIONS = ["All"]
 SHOW_ALL_ORGAS = False
-
+"""
 ########
 # PAGE #
 ########
 def show_page():
     
+    """
     def show_crs():
         # SESSION STATES
         st.session_state.crs5_option_disabled = True
@@ -219,4 +220,6 @@ def show_page():
         show_crs()
     elif match_option == "SDG":
         show_sdg()
+    
+    """
 

similarity.py

@@ -9,6 +9,12 @@ import streamlit as st
 import pandas as pd
 from scipy.sparse import load_npz
 import utils.similarity_table as similarity_table
+import psutil
+import os
+
+def get_process_memory():
+    process = psutil.Process(os.getpid())
+    return process.memory_info().rss / (1024 * 1024) 
 
 # Catch DATA
 # Load Similarity matrix
@@ -17,10 +23,8 @@ def load_sim_matrix():
     loaded_matrix = load_npz("app/src/similarities.npz")
     dense_matrix = loaded_matrix.toarray()
 
-
     return dense_matrix
 
-
 @st.cache_data
 def load_projects():
     orgas_df = pd.read_csv("app/src/projects/project_orgas.csv")
@@ -41,6 +45,7 @@ sim_matrix = load_sim_matrix()
 projects_df = load_projects()
 
 def show_page():
+    st.write(f"Current RAM usage of this app: {get_process_memory():.2f} MB")
     st.write("Similarities")
 
     df_subset = projects_df.head(10)