Final

app.py

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+
+from app.files import files
+from app.analyze import analyze
+from app.utils import *
+from socialnetworkanalysis import sna
+
+st.set_page_config(layout='wide', page_title='SNA: G34', page_icon=':bar_chart"', initial_sidebar_state='collapsed')
+
+st.markdown(f'''
+    <style>
+    .stApp .main .block-container{{
+        padding:30px 50px
+    }}
+    .stApp [data-testid='stSidebar']>div:nth-child(1)>div:nth-child(2){{
+        padding-top:50px
+    }}
+    iframe{{
+        display:block;
+    }}
+    .stRadio div[role='radiogroup']>label{{
+        margin-right:5px
+    }}
+    </style>
+    ''', unsafe_allow_html=True)
+
+with st.sidebar.container():
+
+    if 'name' in st.session_state:
+
+        st.title(f'SNA: G34')
+        # menu
+        menu = sac.menu(
+            items=[
+                sac.MenuItem('files'),
+                sac.MenuItem('analyze'),
+                
+            ],
+            key='menu',
+            open_all=True, indent=20,
+            format_func='title',
+        )
+
+with st.container():
+    if 'name' in st.session_state:
+        if menu == 'files':
+            files()
+        elif menu == 'analyze':
+            analyze()
+    else:
+        st.title("SNA: G34")
+        st.subheader("Enter you name to start session")
+        name = st.text_input('Name')
+        if st.button('Start Session'):
+            if name is None or name == '':
+                st.error('Please enter your name to start session')
+                st.stop()
+            else:
+                st.session_state['name'] = name
+                st.session_state['menu'] = 'files'
+                st.session_state['sna'] = sna.SocialNetworkAnalysis(name)
+                st.rerun()

app/__init__.py

@@ -0,0 +1 @@
+

app/analyze.py

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+
+import streamlit as st
+import streamlit_antd_components as sac
+import pandas as pd
+from streamlit_monaco import st_monaco
+import os
+from pygwalker.api.streamlit import StreamlitRenderer
+import networkx as nx
+from streamlit_agraph import agraph, Node, Edge, Config
+import numpy as np
+
+def get_pyg_renderer(df,spec) -> StreamlitRenderer:
+    if os.path.exists(f"./{spec}_config.json"):
+        os.remove(f"./{spec}_config.json")
+    return StreamlitRenderer(df, spec=f"./{spec}_config.json", spec_io_mode="rw")
+
+
+def get_nodes(df:pd.DataFrame,source,target):
+    nodes = []
+    unique_node_id = []    
+    df.replace(np.nan, None, regex=True,inplace=True)
+    # remove rows with null source or target
+    df = df.dropna(subset=[source,target])
+    for index, row in df.iterrows():                
+        cols = df.columns            
+
+        if row[source] is not None or row[source] != "" or row[source] != np.nan:
+            meta_data = {}
+            for col in cols:
+                if col != source and col != target and col != "relation":
+                    if row[col] is not None:
+                        meta_data[col] = row[col]
+
+            if str(row[source]).replace(".0","") not in unique_node_id:
+                unique_node_id.append(str(row[source]).replace(".0",""))
+                nodes.append(Node(
+                    id=str(row[source]).replace(".0",""),
+                    label=str(row[source]).replace(".0",""),
+                    size=10,
+                    color="red",                           
+                ))
+        if row[target] is not None or row[target] != "" or row[target] != np.nan:
+            meta_data = {}
+            for col in cols:
+                if col != source and col != target and col != "relation":
+                    if row[col] is not None:
+                        meta_data[col] = row[col]
+
+            if str(row[target]).replace(".0","") not in unique_node_id:
+                unique_node_id.append(str(row[target]).replace(".0",""))
+                nodes.append(Node(
+                    id=str(row[target]).replace(".0",""),
+                    label=str(row[target]).replace(".0",""),
+                    size=10,
+                    color="red",
+                ))
+
+    return nodes
+
+def get_edges(df:pd.DataFrame,source,target):
+    edges = []
+    df.replace(np.nan, None, regex=True,inplace=True)
+    for index, row in df.iterrows():
+        if str(row[source]).replace(".0","") is not None and str(row[target]).replace(".0","") is not None:            
+            edges.append(Edge(
+                source=str(row[source]).replace(".0",""),
+                target=str(row[target]).replace(".0",""),
+                label=row["relation"],
+                size=1,
+            ))
+    return edges
+
+def analyze():
+    st.title('Analyze')
+    
+    col = st.columns([4, 1])
+    with col[0]:
+        st.subheader("Analyze loaded data and visualize it.")  
+
+    with col[1]:
+        query_mode = st.radio("Query Mode",["Visual","Raw"],horizontal=True,index=0,key="query_type")
+
+
+    query_controls = st.columns([1,1,1,1,1])
+    with query_controls[0]:
+        saved_queries = st.session_state.sna.get_queries()
+        if saved_queries is None:
+            saved_queries = {}
+        selected_query = st.selectbox("Select Query",saved_queries.keys(),index=None,key="selected_query")       
+    with query_controls[1]:
+        if selected_query is None:                  
+
+            query_name = st.text_input(key="query_name",value="New Query",label="Query Name")
+            if query_name not in st.session_state:                
+                st.session_state[query_name] = "MATCH (n) RETURN n LIMIT 25"
+                st.session_state.sna.save_query(query_name,st.session_state[query_name])
+                st.rerun()            
+
+        else:
+            query_name = st.text_input(key="query_name",value=selected_query,label="Query Name")
+            st.session_state[query_name] = saved_queries[selected_query]
+            
+    helpers = st.session_state.sna.get_helper()
+    if helpers is not None:
+        files = []
+        for helper in helpers:
+            if not helper.endswith(".json"):
+                files.append(helper.split("/")[-1])
+        select_files_cols = st.columns([1,1,1,1,1])
+        with select_files_cols[0]:
+            selected_files = st.selectbox("Select Loaded File",files)
+        if selected_files is not None:
+            for helper in helpers:
+                if helper.endswith(selected_files):
+                    helper_json = helpers[helper]
+                    tables = {}
+                    relationships = {}
+                    for object in helper_json:
+                        if helper_json[object]["isTable"]:
+                            tables[helper_json[object]["object_name"]] = helper_json[object]["columns"]
+                        elif helper_json[object]["isRelationship"]:
+                            relationships[helper_json[object]["object_name"]] = {
+                                "source": helper_json[object]["source"],
+                                "target": helper_json[object]["target"]
+                            }
+    
+    if query_mode == "Raw":
+        query_cols = st.columns([4,6])
+
+        with query_cols[0]:
+            with st.expander("Objects",expanded=True):                                    
+                st.write("Tables")
+                st.write(tables)
+                st.write("Relationships")
+                st.write(relationships)
+
+
+        
+        with query_cols[1]:
+            with st.expander("Query",expanded=True):
+                if selected_query is None:
+                    query_text = st_monaco(value="", height="200px", language="cypher",theme="vs-dark",lineNumbers=True)
+                else:
+                    query_text = st_monaco(value=saved_queries[selected_query], height="200px", language="cypher",theme="vs-dark",lineNumbers=True)
+
+    if query_mode == "Visual":
+        query_text = st.session_state[query_name]
+        node_edge_template = """MATCH 
+        q = (s:##source_node##)-[r##relationship##]->(t:##target_node##)
+        """
+        with st.expander("Node and Edges Selection",expanded=True):
+            st.write("Select the source and target nodes for the network")
+            node_edge_selection_columns = st.columns([1,1,1,1,1])
+            with node_edge_selection_columns[0]:
+                source_node = st.selectbox("Source Node",list(tables.keys()),index=0,key="source_node")
+            with node_edge_selection_columns[1]:
+                target_node = st.selectbox("Target Node",list(tables.keys()),index=1,key="target_node")            
+
+            if source_node is not None and target_node is not None:
+                st.write("Select the relationship between the source and target nodes")
+                node_edge_selection_columns = st.columns([1,1,1,1,1])   
+                with node_edge_selection_columns[0]:
+                    filtered_relationship = {}
+                    for relationship in relationships:
+                        if relationships[relationship]["source"] == source_node and relationships[relationship]["target"] == target_node:
+                            filtered_relationship[relationship] = relationships[relationship]
+                    relationship = st.multiselect("Relationships",list(filtered_relationship.keys()),key="relationship")
+
+        if source_node is not None and target_node is not None and len(relationship) > 0:
+            relationship_str = ""
+            for rel in relationship:
+                relationship_str += f":{rel.strip()}|"
+            relationship_str = relationship_str[:-1]
+            node_edge_template_stg = node_edge_template
+            node_edge = node_edge_template_stg.replace("##source_node##",source_node).replace("##target_node##",target_node).replace("##relationship##",relationship_str)
+
+            source_primary_key = ""
+            target_primary_key = ""
+            for column in tables[source_node]:
+                if tables[source_node][column] == "INT64":
+                    source_primary_key = column
+                    break
+            for column in tables[target_node]:
+                if tables[target_node][column] == "INT64":
+                    target_primary_key = column
+                    break
+
+            return_template = f"""RETURN (nodes(q)[1]).{source_primary_key} as source,
+            (rels(q)[1])._label as relation,
+            (nodes(q)[2]).{target_primary_key} as target
+            ##return##"""
+            with st.expander("Returned Columns"):
+                source_columns = []
+                target_columns = []
+                for column in tables[source_node]:
+                    if column != source_primary_key:
+                        source_columns.append(column)
+                for column in tables[target_node]:
+                    if column != target_primary_key:
+                        target_columns.append(column)
+                returned_columns = st.columns([3,3,1])
+                with returned_columns[0]:
+                    source_node_columns = st.multiselect("Source Node Columns",source_columns,key="source_node_columns")
+                with returned_columns[1]:
+                    target_node_columns = st.multiselect("Target Node Columns",target_columns,key="target_node_columns")
+                with returned_columns[-1]:
+                    limit = st.number_input("Limit",min_value=1,max_value=10000,value=200,key="limit")
+
+                return_str = ""
+                return_template_stg = return_template
+                if len(source_node_columns) > 0:
+                    for column in source_node_columns:
+                        return_str += f"\n,(nodes(q)[1]).{column} as source_{column}"
+                if len(target_node_columns) > 0:
+                    for column in target_node_columns:
+                        return_str += f"\n,(nodes(q)[2]).{column} as target_{column}"
+                return_statement = return_template_stg.replace("##return##",return_str)
+
+                prepared_query = node_edge + return_statement + f"\n LIMIT {limit};"
+                query_text = prepared_query
+
+            
+
+            
+
+            
+
+        
+                
+    query_actions = st.columns([1,1,1,1,1,1,1,1,1,1,1])
+    with query_actions[0]:
+        if st.button("Save",key="save_query"):
+            st.session_state["results"] = None
+            st.session_state[query_name] = query_text
+            st.session_state.sna.save_query(query_name,st.session_state[query_name])
+    with query_actions[1]:
+        if st.button("Execute",type="primary",key="execute_query"):
+            st.session_state["results"] = None
+            st.session_state["results"] = st.session_state.sna.execute_query(query_text)
+
+
+    if "results" in st.session_state:
+        with st.expander('Results',expanded=False):
+            result_renderer = get_pyg_renderer(st.session_state["results"],"result")            
+            result_renderer.explorer()
+
+        with st.expander('Network',expanded=False):
+            if st.session_state["results"] is not None:
+                netwok_columns = st.columns([1,1,1,1])
+                networkx_result = st.session_state.sna.apply_networkx_analysis(st.session_state["results"],"source","target")
+                ergm_result = st.session_state.sna.apply_ergm(st.session_state["results"],"source","target")
+                with netwok_columns[-1]:
+                    analysis_type = st.radio("Analysis Type",["Graph","Visualization"],index=0,key="network_type",horizontal=True)
+
+                if analysis_type == "Visualization":                
+                    networkx_renderer = get_pyg_renderer(networkx_result,"networkx")
+                    networkx_renderer.explorer()
+                elif analysis_type == "Graph":
+                    config = Config(width=1000,height=750,directed=True,physics=True,hierarchical=True)
+                    nodes = get_nodes(networkx_result,"source","target")
+                    edges = get_edges(networkx_result,"source","target")
+                    graph_columns = st.columns([9,3])
+
+                    with graph_columns[0]:                
+                        return_value = agraph(nodes=nodes, edges=edges, config=config)
+                    with graph_columns[1]:
+                        st.write("Ergm Analysis")
+                        ergm_result_to_display = ergm_result["ergm"]
+                        del ergm_result_to_display["degree_distribution"]
+                        ergm_result_df = pd.DataFrame.from_dict(ergm_result_to_display,orient="index",columns=["Value"])
+                        st.dataframe(ergm_result_df)
+
+                        if return_value is not None:
+                            st.write("Networkx Analysis")
+                            with open(f"./output.csv","w") as f:
+                                f.write(networkx_result.to_csv(index=False))
+                            networkx_result_search = networkx_result
+                            # convert source and target to string
+                            networkx_result_search["source"] = networkx_result_search["source"].astype(str).replace(".0","")
+                            networkx_result_search["target"] = networkx_result_search["target"].astype(str).replace(".0","")
+                            # search for a node in the networkx_result_search with return value
+                            search = networkx_result_search[networkx_result_search["source"].str.contains(return_value)]
+                            if search.empty:
+                                search = networkx_result_search[networkx_result_search["target"].str.contains(return_value)]
+                            if not search.empty:
+                                st.write(search)
+
+
+                                                             
+                    
+
+
+                    
+

app/files.py

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+
+import streamlit as st
+import streamlit_antd_components as sac
+import pandas as pd
+from st_aggrid import AgGrid
+import time
+import json
+
+
+def files():
+    st.title('Files')
+    
+    col = st.columns([4, 1])
+    with col[0]:
+        st.subheader("Below are the files that are uploaded for current session.")        
+
+    with st.expander('Upload', False):
+        uploaded_file = st.file_uploader("Choose a file", type=['xlsx'], accept_multiple_files=False)
+        if uploaded_file is not None:
+            st.session_state.sna.add_file(uploaded_file)
+            st.info("File uploaded successfully.")
+            uploaded_file = None
+
+
+    with st.expander('Files', True):
+
+        files = st.session_state.sna.get_files()
+
+        file_tree_items = []
+
+        for file in files:
+            parts = file.split('/')
+            file_tree_items.append(sac.TreeItem(parts[-1]))
+            
+            
+
+        selected_files = sac.tree(items=file_tree_items,checkbox=True)
+        raw_selected_files = None
+
+        if len(selected_files) == 1:
+
+            for file in selected_files:
+
+                for raw_file in files:
+                    if raw_file.endswith(file):
+                        raw_selected_files = raw_file
+                        st.write("Selected file: ",raw_file)
+
+    if raw_selected_files is not None:
+
+        if str(raw_selected_files).endswith(".json"):
+            with st.expander('View', False):
+                with open(raw_selected_files) as f:
+                    data = json.load(f)
+                    st.json(data)
+        else:
+
+
+            with st.expander('View', False):
+                all_sheets = pd.read_excel(raw_selected_files,sheet_name=None, engine='openpyxl')
+
+                tab_items = []
+
+                for sheet_name, df in all_sheets.items():
+                    tab_items.append(sac.TabsItem(label=sheet_name))
+
+                tab = sac.tabs(tab_items,key="view",index=None)
+
+                if tab is not None:
+                    for sheet_name, df in all_sheets.items():
+                        if sheet_name == tab:
+                            st.dataframe(df)
+                            break
+                    
+        
+            with st.expander('Load', True):
+                data_loading_response = None
+                generate_helper = st.session_state.sna.generate_data_dictionary(raw_selected_files)
+                generate_helper_reset = generate_helper.copy()
+
+                load_action_controls = st.columns([1,1,1,1,1,1,1,1,1,1,1,1,1])
+
+                with load_action_controls[-3]:
+                    if st.button("Save",type="primary"):
+                        st.rerun()
+                
+                with load_action_controls[-2]:
+                    if st.button("Reset",type="primary"):
+                        st.session_state[raw_selected_files] = generate_helper_reset.copy()
+                        generate_helper = generate_helper_reset.copy()
+                        st.rerun()
+
+                with load_action_controls[-1]:
+                    if st.button("Load",type="primary"):
+                        print("Loading") 
+                        load_response = st.session_state.sna.load_data(raw_selected_files,st.session_state[raw_selected_files])
+                        data_loading_response = load_response
+                        
+
+                if data_loading_response is not None:
+                    container_message = st.empty()
+                    if data_loading_response["status"]:
+                        container_message.success(data_loading_response["message"])
+                        time.sleep(3)
+                        container_message.empty()
+                    else:
+                        container_message.error(data_loading_response["message"])
+                        time.sleep(3)
+                        container_message.empty()        
+
+
+                if raw_selected_files in st.session_state:
+                    generate_helper = st.session_state[raw_selected_files]
+                else:
+                    st.session_state[raw_selected_files] = generate_helper.copy()
+
+                tab_items_load = []
+
+                for sheet_name in generate_helper:
+                    tab_items_load.append(sac.TabsItem(label=sheet_name))
+
+                tab_load = sac.tabs(tab_items_load,key='load')
+
+                if tab_load is not None:
+                    for sheet_name in generate_helper:
+                        if sheet_name == tab_load:
+                            loading_columns = st.columns([1,1,1])
+                            
+                            with loading_columns[0]:
+                                if generate_helper[sheet_name]["isTable"]:
+                                    st.write("Columns")
+                                    if "columns" in generate_helper[sheet_name]:
+                                        for column in generate_helper[sheet_name]["columns"]:
+                                            data_type_stg = 0
+                                            if generate_helper[sheet_name]["columns"][column] == "STRING":
+                                                data_type_stg = 0
+                                            elif generate_helper[sheet_name]["columns"][column] == "INT64":
+                                                data_type_stg = 1
+                                            elif generate_helper[sheet_name]["columns"][column] == "FLOAT":
+                                                data_type_stg = 2
+                                            value = st.radio(column,["STRING","INT64","FLOAT"],index=data_type_stg,horizontal=True,key=f"{sheet_name}_{column}")   
+                                            if value is not None:
+                                                generate_helper[sheet_name]["columns"][column] = value
+                                                st.session_state[raw_selected_files] = generate_helper.copy()
+                                
+                                elif generate_helper[sheet_name]["isRelationship"]:
+                                    tables = []
+                                    for table in generate_helper:
+                                        if "isTable" in generate_helper[table]:
+                                            if generate_helper[table]["isTable"]:
+                                                tables.append(table)
+
+                                    st.write("Relationship")
+
+                                    source_stg = 0
+                                    target_stg = 0
+                                    if "source" in generate_helper[sheet_name]:
+                                        if generate_helper[sheet_name]["source"] in tables:
+                                            source_stg = tables.index(generate_helper[sheet_name]["source"])
+                                    if "target" in generate_helper[sheet_name]:
+                                        if generate_helper[sheet_name]["target"] in tables:
+                                            target_stg = tables.index(generate_helper[sheet_name]["target"])
+
+                                    source = st.selectbox("Source",tables,index=source_stg,key=f"source_{sheet_name}")
+                                    target = st.selectbox("Target",tables,index=target_stg,key=f"target_{sheet_name}")
+                                    if source is not None:
+                                        generate_helper[sheet_name]["source"] = source
+                                        st.session_state[raw_selected_files] = generate_helper.copy()
+                                    if target is not None:
+                                        generate_helper[sheet_name]["target"] = target
+                                        st.session_state[raw_selected_files] = generate_helper.copy()
+                                else:
+                                    st.write("Ignored")
+
+
+                            with loading_columns[1]:
+                                st.write("Object Properties")
+                                if generate_helper[sheet_name]["isTable"]:
+                                    object_type_stg = 0
+                                elif generate_helper[sheet_name]["isRelationship"]:
+                                    object_type_stg = 1
+                                else:
+                                    object_type_stg = 2
+                                        
+                                object_type = st.radio("Object Type",["Table","Relationship","Ignore"],index=object_type_stg,horizontal=True,key=f"object_type_{sheet_name}")
+
+                                if object_type == "Table":
+                                    if not generate_helper[sheet_name]["isTable"]:
+                                        generate_helper[sheet_name]["isTable"] = True
+                                        generate_helper[sheet_name]["isRelationship"] = False
+                                        st.session_state[raw_selected_files] = generate_helper.copy()
+                                        st.rerun()                                
+                                    
+                                    
+                                elif object_type == "Relationship":                                
+                                    if not generate_helper[sheet_name]["isRelationship"]:
+                                        generate_helper[sheet_name]["isTable"] = False
+                                        generate_helper[sheet_name]["isRelationship"] = True
+                                        st.session_state[raw_selected_files] = generate_helper.copy()
+                                        st.rerun()
+                                    
+                                else:
+                                    if generate_helper[sheet_name]["isTable"] or generate_helper[sheet_name]["isRelationship"]:
+                                        generate_helper[sheet_name]["isTable"] = False
+                                        generate_helper[sheet_name]["isRelationship"] = False
+                                        st.session_state[raw_selected_files] = generate_helper.copy()
+                                        st.rerun()
+
+                                object_name = st.text_input("Object Name",generate_helper[sheet_name]["object_name"])
+                                if object_name is not None:
+                                    generate_helper[sheet_name]["object_name"] = object_name
+                                    st.session_state[raw_selected_files] = generate_helper.copy()
+
+                                
+                                if generate_helper[sheet_name]["isTable"]:
+                                    int_64_keys = []
+                                    if "columns" in generate_helper[sheet_name]:
+                                        for column in generate_helper[sheet_name]["columns"]:
+                                            if generate_helper[sheet_name]["columns"][column] == "INT64":
+                                                int_64_keys.append(column)
+
+                                    primary_key_staging = 0
+                                    if generate_helper[sheet_name]["primary_key"] in int_64_keys:
+                                        primary_key_staging = int_64_keys.index(generate_helper[sheet_name]["primary_key"])
+                                    
+                                    primary_key = st.selectbox("Primary Key",int_64_keys,index=primary_key_staging,key=f"primary_key_{sheet_name}")
+                                    if primary_key is not None:
+                                        generate_helper[sheet_name]["primary_key"] = primary_key       
+                                        st.session_state[raw_selected_files] = generate_helper.copy()                                                                                                                             
+                                    
+
+                            with loading_columns[2]:
+                                st.write("Helper Object")
+                                st.write(generate_helper[sheet_name])
+                                                                            
+                            break

app/utils.py

@@ -0,0 +1,149 @@
+from typing import Callable
+import streamlit as st
+import streamlit_antd_components as sac
+import inspect
+
+FORMAT = [None, 'title', 'upper', "lambda x:f'A_{x}'"]
+LABEL = [
+    None,
+    'label',
+    '**label**',
+    '**label** <span class="badge rounded-pill badge-info">Info</span>'
+]
+MartineColor = ['dark', 'gray', 'red', 'pink', 'grape', 'violet', 'indigo', 'blue', 'cyan', 'teal', 'green', 'lime',
+                'yellow', 'orange']
+MartineSize = ['xs', 'sm', 'md', 'lg', 'xl']
+AntColor = {
+    'magenta': '#c41d7f',
+    'red': '#cf1322',
+    'volcano': '#d4380d',
+    'orange': '#d46b08',
+    'gold': '#d48806',
+    'lime': '#7cb305',
+    'green': '#389e0d',
+    'cyan': '#08979c',
+    'blue': '#0958d9',
+    'geekblue': '#1d39c4',
+    'purple': '#531dab'
+}
+
+size_help = 'support mantine size and int in px'
+md_help = 'support str and markdown str'
+
+
+def show_label(container=None, value='label', key=None):
+    if container is not None:
+        with container:
+            return st.text_input('label', value, key=f'{key}-label', help=md_help)
+    return st.text_input('label', value, key=f'{key}-label', help=md_help)
+
+
+def show_description(container=None, value='', key=None):
+    if container is not None:
+        with container:
+            return st.text_input('description', value, key=f'{key}-desc', help=md_help)
+    return st.text_input('description', value, key=f'{key}-desc', help=md_help)
+
+
+def show_index(container=None, option=None, index=0, key=None):
+    if container is not None:
+        with container:
+            return st.selectbox('index', option, index=index, key=f'{key}-index')
+    return st.selectbox('index', option, index=index, key=f'{key}-index')
+
+
+def show_format_func(container=None, key=None):
+    if container is not None:
+        with container:
+            return st.selectbox('format_func', FORMAT, 0, key=f'{key}-format', help='item label format')
+    return st.selectbox('format_func', FORMAT, 0, key=f'{key}-format', help='item label format')
+
+
+def show_color(index=0, label='color', options=(None, *MartineColor, '#4682b4', 'rgb(20,80,90)'),
+               none_color='--primary-color', key=None, martine=True):
+    colors = {'info': 'rgb(0, 66, 128)', 'success': 'rgb(23, 114, 51)', 'warning': 'rgb(146, 108, 5)',
+              'error': 'rgb(125, 53, 59)', 'transparent': 'lightgray', None: none_color}
+    btn = sac.buttons(
+        items=[sac.ButtonsItem(
+            label='None' if i is None else i,
+            color=colors.get(i) if i in colors.keys() else (i if martine else AntColor.get(i, i))) for i in options
+        ],
+        label=label, index=index,
+        size='xs', gap='xs', variant='filled', radius='lg', key=f'{key}-color'
+    )
+    return None if btn == 'None' else btn
+
+
+def show_size(index=2, include_int=True, key=None):
+    return st.radio('size', options=MartineSize + [25] if include_int else MartineSize, index=index, horizontal=True,
+                    key=f'{key}-size', help=size_help)
+
+
+def show_radius(index=2, key=None):
+    return st.radio('radius', MartineSize + [20, 2], index=index, horizontal=True, key=f'{key}-radius', help=size_help)
+
+
+def show_variant(options, index=0, key=None):
+    return st.radio('variant', options, index=index, horizontal=True, key=f'{key}-variant')
+
+
+def show_align(index=1, key=None):
+    return st.radio('align', ['start', 'center', 'end'], index=index, horizontal=True, key=f'{key}-align')
+
+
+def show_direction(index=0, key=None):
+    return st.radio('direction', ["horizontal", "vertical"], index=index, horizontal=True, key=f'{key}-direction')
+
+
+def show_checkbox(label, container=None, value=False, key=None):
+    if container is not None:
+        with container:
+            return st.checkbox(label, value=value, key=f'{key}-{label}')
+    return st.checkbox(label, value=value, key=f'{key}-{label}')
+
+
+def show_radio(label=None, options=None, container=None, index=0, key=None):
+    if container is not None:
+        with container:
+            return st.radio(label, options=options, index=index, horizontal=True, key=f'{key}-{label}')
+    return st.radio(label, options=options, index=index, horizontal=True, key=f'{key}-{label}')
+
+
+def show_space(number=3):
+    st.markdown('<br>' * number, unsafe_allow_html=True)
+
+
+def update_kw(d: dict, remove_keys: list = None):
+    ff = d.get("format_func")
+    if isinstance(ff, str) and 'lambda' in ff:
+        d.update({"format_func": eval(ff)})
+    label = d.get('label')
+    if isinstance(label, str) and not label:
+        d.update({'label': None})
+    desc = d.get('description')
+    if isinstance(desc, str) and not desc:
+        d.update({'description': None})
+    if remove_keys is not None:
+        for i in remove_keys:
+            if i in d.keys():
+                del d[i]
+    return d
+
+
+def code_kw(kw: dict, _func):
+    # func default kw
+    default_kw = {
+        k: v.default for k, v in inspect.signature(_func).parameters.items() if
+        v.default is not inspect.Parameter.empty
+    }
+    # filter kw
+    new_kw = {k: v for k, v in kw.items() if v != default_kw.get(k)}
+    # dict to kw string
+    return ", ".join(f'{k}={FORMAT[-1]}' if isinstance(v, Callable) else f'{k}={v!r}' for k, v in new_kw.items())
+
+
+def show_code(x: str, open: bool = False):
+    with st.expander('code', open):
+        st.code(f'''
+        import streamlit_antd_components as sac\n{x}
+        ''', line_numbers=True)

output.csv

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requirements.txt

@@ -0,0 +1,113 @@
+altair==4.2.2
+altgraph==0.17.4
+annotated-types==0.6.0
+anyio==4.3.0
+appdirs==1.4.4
+arrow==1.3.0
+astor==0.8.1
+asttokens==2.4.1
+attrs==23.2.0
+backoff==2.2.1
+blinker==1.8.2
+cachetools==5.3.3
+click==8.1.7
+comm==0.2.2
+dateutils==0.6.12
+decorator==5.1.1
+dnspython==2.6.1
+duckdb==0.10.1
+email_validator==2.1.1
+entrypoints==0.4
+et-xmlfile==1.1.0
+executing==2.0.1
+fastapi==0.111.0
+fastapi-cli==0.0.3
+gitdb==4.0.11
+GitPython==3.1.43
+gw_dsl_parser==0.1.48a3
+h11==0.14.0
+httpcore==1.0.5
+httptools==0.6.1
+httpx==0.27.0
+ipython==8.24.0
+ipywidgets==8.1.2
+isodate==0.6.1
+jedi==0.19.1
+Jinja2==3.1.4
+jsonpointer==2.1
+jsonschema==4.22.0
+jsonschema-specifications==2023.12.1
+jupyterlab_widgets==3.0.10
+kanaries_track==0.0.4
+kuzu==0.4.1
+macholib==1.16.3
+markdown-it-py==3.0.0
+MarkupSafe==2.1.5
+matplotlib-inline==0.1.7
+mdurl==0.1.2
+modulegraph==0.19.6
+monotonic==1.6
+networkx==3.3
+numpy==1.26.4
+openpyxl==3.1.2
+orjson==3.10.3
+pandas==2.2.2
+parso==0.8.4
+pexpect==4.9.0
+pillow==10.3.0
+prompt-toolkit==3.0.43
+protobuf==4.25.3
+psutil==5.9.8
+ptyprocess==0.7.0
+pure-eval==0.2.2
+py2app==0.28.7
+pyarrow==16.0.0
+pydantic==2.7.1
+pydantic_core==2.18.2
+pydeck==0.9.1
+Pygments==2.18.0
+pygwalker==0.4.8.3
+pyparsing==3.1.2
+python-dateutil==2.9.0.post0
+python-decouple==3.8
+python-dotenv==1.0.1
+python-multipart==0.0.9
+pytz==2024.1
+PyYAML==6.0.1
+rdflib==7.0.0
+referencing==0.35.1
+rich==13.7.1
+rpds-py==0.18.1
+scipy==1.13.0
+segment-analytics-python==2.2.3
+shellingham==1.5.4
+six==1.16.0
+smmap==5.0.1
+sniffio==1.3.1
+SQLAlchemy==2.0.30
+sqlglot==23.15.8
+stack-data==0.6.3
+starlette==0.37.2
+streamlit==1.34.0
+streamlit-aggrid==1.0.5
+streamlit-agraph==0.0.45
+streamlit-antd-components==0.3.2
+streamlit-monaco==0.1.3
+tenacity==8.3.0
+toml==0.10.2
+toolz==0.12.1
+tornado==6.4
+traitlets==5.14.3
+typer==0.12.3
+types-python-dateutil==2.9.0.20240316
+typing_extensions==4.11.0
+tzdata==2024.1
+ujson==5.9.0
+uvicorn==0.29.0
+uvloop==0.19.0
+wasmtime==12.0.0
+watchfiles==0.21.0
+wcwidth==0.2.13
+websockets==12.0
+wheel==0.41.2
+widgetsnbextension==4.0.10

setup.py

@@ -0,0 +1,27 @@
+from setuptools import setup
+
+APP = ['app.py']
+DATA_FILES = []
+OPTIONS = {
+    'argv_emulation': True,
+    'packages': [
+        'streamlit',
+        'numpy',
+        'pandas',
+        'networkx',
+        'openpyxl',
+        'uuid',
+        'streamlit_antd_components',
+        'st_aggrid',
+        'pygwalker',
+        'streamlit_monaco',
+        'streamlit_agraph',
+    ],
+}
+
+setup(
+    app=APP,
+    data_files=DATA_FILES,
+    options={'py2app': OPTIONS},
+    setup_requires=['py2app'],
+)

socialnetworkanalysis/sna.py

@@ -0,0 +1,417 @@
+import kuzu
+import hashlib
+import os
+import logging
+import openpyxl
+import pandas as pd
+import uuid
+import json
+import networkx as nx
+import time
+import numpy as np
+
+
+class SocialNetworkAnalysis:
+    data_dir: str
+    k_client: kuzu.Connection
+
+    def __init__(self,name:str):
+        session_id = hashlib.sha256(name.encode("utf-8")).hexdigest()
+        db = kuzu.Database(f"./db/{session_id}_db")
+        self.k_client = kuzu.Connection(db)
+        if not os.path.exists(f"./data/{session_id}"):
+            os.makedirs(f"./data/{session_id}")
+        self.data_dir = f"./data/{session_id}"
+
+    def get_files(self):
+        all_files = []
+        logging.info("Getting files")
+        logging.info(f"Data dir: {self.data_dir}")
+        for root, dirs, files in os.walk(self.data_dir):
+            for file in files:
+                all_files.append(os.path.join(root, file))
+
+        return all_files
+    
+    def add_file(self, file):
+        logging.info(f"Adding file: {file}")
+        with open(f"{self.data_dir}/{file.name}","wb") as f:
+            f.write(file.getvalue())
+
+    def generate_data_dictionary(self, file_path):
+        try:
+            workbook = openpyxl.load_workbook(file_path,data_only=True)
+        except Exception as e:
+            return {
+                'status': False,
+                'message': str(e)
+            }
+
+        helper = {}
+
+        try:
+            for sheet_name in workbook.sheetnames:
+                helper[sheet_name] = {}
+                sheet = workbook[sheet_name]
+                if "net_" in sheet_name:
+                    helper[sheet_name]["object_name"] = sheet_name.replace("net_","").split("_")[1].lower().replace(" ","_").replace("-","_").replace(".","_").replace("(","_").replace(")","_")
+                    helper[sheet_name]["isTable"] = False
+                    helper[sheet_name]["isRelationship"] = True
+                    helper[sheet_name]["source"] = "?"
+                    helper[sheet_name]["target"] = "?"
+                else:
+                    
+                    is_header_row = True
+                    for row in sheet.iter_rows(values_only=True):
+                        if is_header_row:
+                            helper[sheet_name]["object_name"] = sheet_name.lower().replace(" ","_").replace("-","_").replace(".","_").replace("(","_").replace(")","_")
+                            helper[sheet_name]["primary_key"] = "?"
+                            helper[sheet_name]["columns"] = {}
+                            helper[sheet_name]["isTable"] = True
+                            helper[sheet_name]["isRelationship"] = False
+                            header_row = row
+                            is_header_row = False
+                            for column in header_row:
+                                if column is not None:
+                                    helper[sheet_name]["columns"][column.lower().replace(" ","_").replace("-","_").replace(".","_").replace("(","_").replace(")","_")] = "STRING"
+                            break
+                
+        except Exception as e:
+            return {
+                'status': False,
+                'message': str(e)
+            }
+        
+        return helper
+    
+    def clean_data(self, df):
+        # reads the data provided in pandas dataframe and cleans missing values.
+        df.replace('N/A', None, inplace=True)         
+        df.replace('NA', None, inplace=True)
+        non_none_columns = [col for col in df.columns if col is not None]
+        # Create a new DataFrame containing only columns with non-None names
+        df = df[non_none_columns]
+        return df
+
+    def load_data(self, file_path,helper):
+
+        if not os.path.exists(self.data_dir+"/helpers.json"):
+            with open(self.data_dir+"/helpers.json","w") as f:
+                f.write(json.dumps({}))
+
+        helpers = {}
+
+        with open(self.data_dir+"/helpers.json","r") as f:
+            helpers = json.load(f)
+        
+        helpers[file_path] = helper
+        with open(self.data_dir+"/helpers.json","w") as f:
+            f.write(json.dumps(helpers))
+
+
+        try:
+            workbook = openpyxl.load_workbook(file_path,data_only=True)
+        except Exception as e:
+            return {
+                'status': False,
+                'message': str(e)
+            }
+
+        all_data = {}
+
+        try:
+            for sheet_name in workbook.sheetnames:
+                sheet = workbook[sheet_name]            
+                sheet_data = []
+
+                is_header_row = True
+                for row in sheet.iter_rows(values_only=True):
+                    if is_header_row:
+                        header_row = row
+                        is_header_row = False
+                        continue
+
+                    sheet_data.append(dict(zip(header_row, row)))
+                all_data[sheet_name] = sheet_data
+        except Exception as e:
+            return {
+                'status': False,
+                'message': str(e)
+            }
+        
+
+        try:
+            for key, value in all_data.items():
+
+                if key not in helper.keys():
+                    continue
+
+                if helper[key]["isTable"]:
+                    cleaned_data = self.clean_data(pd.DataFrame(value))     
+                    create_table_response = self.create_tables(helper[key])  
+                    if create_table_response['status'] == False:
+                        return create_table_response
+                    
+                    if not os.path.exists("./tmp"):
+                        os.makedirs("./tmp")
+                    
+                    tmp_file_path = f"""./tmp/{str(uuid.uuid4()).replace("-","")}.csv"""
+                    cleaned_data.to_csv(tmp_file_path, index=False,header=False)
+                    self.ingest_data(helper[key],tmp_file_path)
+                    os.remove(tmp_file_path)
+
+                    continue
+        except Exception as e:
+            return {
+                'status': False,
+                'message': str(e)
+            }
+        
+        try:
+            for key, value in all_data.items():
+
+                if key not in helper.keys():
+                    continue
+
+                if helper[key]["isRelationship"] and key in helper.keys():
+                    cleaned_data = self.clean_data(pd.DataFrame(value))     
+                    create_rel_response = self.create_relationships(helper[key])  
+                    if create_rel_response['status'] == False:
+                        return create_rel_response
+                    
+                    if not os.path.exists("./tmp"):
+                        os.makedirs("./tmp")
+                    
+                    tmp_file_path = f"""./tmp/{str(uuid.uuid4()).replace("-","")}.csv"""
+                    cleaned_data.to_csv(tmp_file_path, index=False,header=False)
+                    self.ingest_relationships(helper[key],tmp_file_path)
+                    os.remove(tmp_file_path)
+
+                    continue
+        except Exception as e:
+            return {
+                'status': False,
+                'message': str(e)
+            }
+        
+        return {
+            'status': True,
+            'message': "Data loaded successfully"
+        }
+    
+    def create_tables(self, helper):
+        columns = ""
+        logging.info(helper)
+        for key, value in helper["columns"].items():
+            columns += f"{key} {value},"
+
+        columns += f"""PRIMARY KEY ({helper["primary_key"]})"""
+        try:
+            self.k_client.execute(f"""CREATE NODE TABLE {helper["object_name"]}(
+                {columns}
+            )""")
+        except Exception as e:
+            if "already exists" in str(e):
+                return {
+                    'status': True,
+                    'message': "Table already exists"
+                }
+        
+        return {
+            'status': True,
+            'message': "Table created successfully"
+        }
+    
+    def create_relationships(self, helper):
+        # CREATE REL TABLE LivesIn(FROM User TO City)
+        try:
+            self.k_client.execute(f"""CREATE REL TABLE {helper["object_name"]}(
+                FROM {helper["source"]} TO {helper["target"]}
+            )""")
+        except Exception as e:
+            if "already exists" in str(e):
+                return {
+                    'status': True,
+                    'message': "Relationship already exists"
+                }
+        
+        return {
+            'status': True,
+            'message': "Relationship created successfully"
+        }
+    
+    def ingest_relationships(self,helper,tmp_csv_path):
+        try:
+            self.k_client.execute(f"""COPY {helper["object_name"]} FROM "{tmp_csv_path}" """)
+            return {
+                'status': True,
+                'message': "Relationsip ingested successfully"
+            }
+        except Exception as e:
+            print(str(e))
+            if "COPY commands can only" in str(e):
+                return {
+                    'status': True,
+                    'message': "Relationship already exists"
+                }
+
+
+    def ingest_data(self,helper,tmp_csv_path):
+        try:
+            self.k_client.execute(f"""COPY {helper["object_name"]} FROM "{tmp_csv_path}" """)
+            return {
+                'status': True,
+                'message': "Data ingested successfully"
+            }
+        except Exception as e:
+            print(str(e))
+            if "COPY commands can only" in str(e):
+                return {
+                    'status': True,
+                    'message': "Data already exists"
+                }
+            
+
+    def get_helper(self):
+        with open(self.data_dir+"/helpers.json","r") as f:
+            return json.load(f)
+        
+    def save_query(self,query_name,query):
+
+        if not os.path.exists(self.data_dir+"/queries.json"):
+            with open(self.data_dir+"/queries.json","w") as f:
+                f.write(json.dumps({
+                    "sample_query": "MATCH (n) RETURN n LIMIT 10"
+                }))
+        time.sleep(0.5)      
+
+        queries = {}
+        with open(self.data_dir+"/queries.json","r") as f:
+            queries = json.load(f)
+            queries[query_name] = query            
+
+        with open(self.data_dir+"/queries.json","w") as f:
+            f.write(json.dumps(queries))
+
+    def get_queries(self):
+
+        if not os.path.exists(self.data_dir+"/queries.json"):
+            with open(self.data_dir+"/queries.json","w") as f:
+                f.write(json.dumps({
+                    "sample_query": "MATCH (n) RETURN n LIMIT 10"
+                }))
+
+        time.sleep(1)
+
+        with open(self.data_dir+"/queries.json","r") as f:
+            return json.load(f)
+        
+    
+    def execute_query(self,query):
+        try:
+            results = self.k_client.execute(query)        
+            return results.get_as_df()
+
+        except Exception as e:
+            return {
+                'status': False,
+                'message': str(e)
+            }
+    
+    def apply_networkx_analysis(self,df:pd.DataFrame,source,target): 
+        G = nx.from_pandas_edgelist(df, source=source, target=target)
+        # Calculate the degree of each node
+        degree = dict(nx.degree(G))
+        degree_centrality = nx.degree_centrality(G)
+        closeness_centrality = nx.closeness_centrality(G)
+        betweenness_centrality = nx.betweenness_centrality(G)
+        eigenvector_centrality = nx.eigenvector_centrality(G)
+        clustering = nx.clustering(G)
+        pagerank = nx.pagerank(G)
+        edge_betweenness_centrality = nx.edge_betweenness_centrality(G) 
+
+        df['degree'] = df[source].map(degree)
+        df['degree_centrality'] = df[source].map(degree_centrality)
+        df['closeness_centrality'] = df[source].map(closeness_centrality)
+        df['betweenness_centrality'] = df[source].map(betweenness_centrality)
+        df['eigenvector_centrality'] = df[source].map(eigenvector_centrality)
+        df['clustering'] = df[source].map(clustering)
+        df['pagerank'] = df[source].map(pagerank)
+        df['edge_betweenness_centrality'] = df.apply(lambda row: edge_betweenness_centrality.get((row[source], row[target]), np.nan), axis=1)
+        
+        return df
+    
+    
+    def fit_ergm(self,G: nx.DiGraph):
+        num_edges = len(G.edges())
+        
+        # Calculate the number of reciprocated edges
+        num_recip_edges = sum((v, u) in G.edges() for u, v in G.edges())
+        
+        # Calculate the density
+        density = num_edges / (len(G.nodes()) * (len(G.nodes()) - 1))
+        
+        # Calculate the reciprocity
+        reciprocity = num_recip_edges / num_edges if num_edges > 0 else np.nan
+        
+        # Calculate the degree distribution
+        degree_dist = dict(G.degree())
+        
+        # Calculate the clustering coefficient
+        clustering_coefficient = nx.average_clustering(G)
+        
+        # Calculate the transitivity
+        transitivity = nx.transitivity(G)
+        
+        summary = {
+            'Density': density,
+            'Reciprocity': reciprocity,
+            'Degree Distribution': degree_dist,
+            'Clustering Coefficient': clustering_coefficient,
+            'Transitivity': transitivity
+        }
+
+        num_params = len(summary)
+
+        num_edges = len(G.edges())
+        n = len(G.nodes())
+        
+        # Calculate the log-likelihood
+        log_likelihood = -0.5 * (num_edges * np.log(n * (n - 1)) - num_params)
+
+        # Calculate AIC and BIC
+        aic = -2 * log_likelihood + 2 * num_params
+        bic = -2 * log_likelihood + num_params * np.log(n * (n - 1))
+
+        return {
+            'density': density,
+            'reciprocity': reciprocity,
+            'degree_distribution': degree_dist,
+            'clustering_coefficient': clustering_coefficient,
+            'transitivity': transitivity,
+            'num_edges': num_edges,
+            'num_nodes': n,
+            'log_likelihood': log_likelihood,
+            'aic': aic,
+            'bic': bic
+        }
+
+
+    def apply_ergm(self,df,source,target):
+        G = nx.from_pandas_edgelist(df, source=source, target=target,create_using=nx.DiGraph())
+        observed_ergm_summary = self.fit_ergm(G)
+
+
+        return {
+            'ergm': observed_ergm_summary
+        }
+
+
+
+        
+
+
+
+
+        
+    

test.ipynb

@@ -0,0 +1,2580 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import kuzu\n",
+    "import networkx as nx\n",
+    "import matplotlib.pyplot as plt"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "db = kuzu.Database(\"/Users/yashpulse/Library/CloudStorage/OneDrive-SwinburneUniversity/Semester 3/COS70008/project/StreamlitAntdComponentsDemo/db/a4bf60cb3ad87a629b9c104f155837ef8470155c07d95e2814357a3816d30a3d_db\")\n",
+    "k_client = kuzu.Connection(db)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[32437, 'friends', 32523]\n",
+      "[32437, 'friends', 32420]\n",
+      "[32437, 'friends', 32540]\n",
+      "[32437, 'friends', 32397]\n",
+      "[32437, 'friends', 32432]\n",
+      "[32437, 'friends', 32428]\n",
+      "[32437, 'influential', 32540]\n",
+      "[32437, 'influential', 32420]\n",
+      "[32437, 'influential', 32523]\n",
+      "[32437, 'feedback', 32420]\n",
+      "[32437, 'feedback', 32540]\n",
+      "[32437, 'feedback', 32523]\n",
+      "[32437, 'feedback', 32397]\n",
+      "[32540, 'friends', 32420]\n",
+      "[32540, 'friends', 32409]\n",
+      "[32540, 'friends', 32469]\n",
+      "[32540, 'friends', 32513]\n",
+      "[32540, 'friends', 32517]\n",
+      "[32540, 'friends', 32462]\n",
+      "[32540, 'friends', 32534]\n",
+      "[32540, 'friends', 32546]\n",
+      "[32540, 'friends', 32476]\n",
+      "[32540, 'friends', 32490]\n",
+      "[32540, 'friends', 32528]\n",
+      "[32540, 'friends', 32558]\n",
+      "[32540, 'friends', 32493]\n",
+      "[32540, 'friends', 32565]\n",
+      "[32540, 'friends', 32432]\n",
+      "[32540, 'influential', 32396]\n",
+      "[32540, 'influential', 32485]\n",
+      "[32540, 'influential', 32408]\n",
+      "[32540, 'influential', 32529]\n",
+      "[32540, 'feedback', 32420]\n",
+      "[32540, 'feedback', 32468]\n",
+      "[32540, 'feedback', 32432]\n",
+      "[32540, 'feedback', 32476]\n",
+      "[32540, 'feedback', 32469]\n",
+      "[32540, 'moretime', 32528]\n",
+      "[32540, 'moretime', 32469]\n",
+      "[32540, 'moretime', 32420]\n",
+      "[32540, 'moretime', 32476]\n",
+      "[32540, 'moretime', 32490]\n",
+      "[32540, 'moretime', 32513]\n",
+      "[32540, 'moretime', 32409]\n",
+      "[32540, 'advice', 32420]\n",
+      "[32540, 'advice', 32468]\n",
+      "[32540, 'advice', 32469]\n",
+      "[32540, 'advice', 32409]\n",
+      "[32540, 'advice', 32528]\n",
+      "[32540, 'disrespect', 32485]\n",
+      "[32443, 'friends', 32518]\n",
+      "[32443, 'friends', 32491]\n",
+      "[32443, 'friends', 32544]\n",
+      "[32443, 'friends', 32405]\n",
+      "[32443, 'friends', 32485]\n",
+      "[32443, 'friends', 32393]\n",
+      "[32443, 'friends', 32507]\n",
+      "[32443, 'friends', 32413]\n",
+      "[32443, 'friends', 32411]\n",
+      "[32443, 'friends', 32396]\n",
+      "[32443, 'friends', 32463]\n",
+      "[32443, 'influential', 32443]\n",
+      "[32443, 'influential', 32518]\n",
+      "[32443, 'influential', 32491]\n",
+      "[32443, 'influential', 32405]\n",
+      "[32443, 'feedback', 32518]\n",
+      "[32443, 'feedback', 32491]\n",
+      "[32443, 'moretime', 32439]\n",
+      "[32443, 'moretime', 32491]\n",
+      "[32443, 'moretime', 32535]\n",
+      "[32443, 'moretime', 32518]\n",
+      "[32443, 'moretime', 32396]\n",
+      "[32443, 'advice', 32491]\n",
+      "[32443, 'advice', 32405]\n",
+      "[32443, 'advice', 32544]\n",
+      "[32443, 'disrespect', 32466]\n",
+      "[32514, 'friends', 32477]\n",
+      "[32514, 'friends', 32400]\n",
+      "[32514, 'friends', 32401]\n",
+      "[32514, 'friends', 32478]\n",
+      "[32514, 'friends', 32550]\n",
+      "[32514, 'friends', 32405]\n",
+      "[32514, 'friends', 32418]\n",
+      "[32514, 'friends', 32470]\n",
+      "[32514, 'friends', 32555]\n",
+      "[32514, 'friends', 32544]\n",
+      "[32514, 'friends', 32535]\n",
+      "[32514, 'friends', 32396]\n",
+      "[32514, 'friends', 32508]\n",
+      "[32514, 'friends', 32426]\n",
+      "[32514, 'advice', 32477]\n",
+      "[32514, 'advice', 32401]\n",
+      "[32514, 'advice', 32550]\n",
+      "[32514, 'advice', 32478]\n",
+      "[32514, 'advice', 32400]\n",
+      "[32514, 'advice', 32508]\n",
+      "[32485, 'friends', 32393]\n",
+      "[32485, 'friends', 32544]\n",
+      "[32485, 'friends', 32405]\n",
+      "[32485, 'friends', 32443]\n",
+      "[32485, 'friends', 32525]\n",
+      "[32485, 'friends', 32463]\n",
+      "[32485, 'advice', 32540]\n",
+      "[32485, 'advice', 32517]\n",
+      "[32485, 'advice', 32412]\n",
+      "[32485, 'advice', 32485]\n",
+      "[32436, 'friends', 32422]\n",
+      "[32436, 'friends', 32421]\n",
+      "[32436, 'friends', 32521]\n",
+      "[32436, 'friends', 32504]\n",
+      "[32436, 'friends', 32432]\n",
+      "[32436, 'friends', 32545]\n",
+      "[32436, 'friends', 32522]\n",
+      "[32436, 'influential', 32406]\n",
+      "[32436, 'influential', 32491]\n",
+      "[32436, 'influential', 32408]\n",
+      "[32436, 'influential', 32485]\n",
+      "[32436, 'influential', 32405]\n",
+      "[32436, 'advice', 32521]\n",
+      "[32436, 'advice', 32432]\n",
+      "[32436, 'disrespect', 32455]\n",
+      "[32553, 'friends', 32467]\n",
+      "[32553, 'friends', 32402]\n",
+      "[32553, 'friends', 32534]\n",
+      "[32553, 'friends', 32392]\n",
+      "[32553, 'friends', 32419]\n",
+      "[32553, 'friends', 32544]\n",
+      "[32553, 'friends', 32411]\n",
+      "[32553, 'friends', 32448]\n",
+      "[32553, 'friends', 32473]\n",
+      "[32553, 'friends', 32493]\n",
+      "[32553, 'friends', 32516]\n",
+      "[32553, 'friends', 32541]\n",
+      "[32553, 'feedback', 32540]\n",
+      "[32553, 'feedback', 32468]\n",
+      "[32553, 'advice', 32468]\n",
+      "[32553, 'advice', 32534]\n",
+      "[32553, 'advice', 32402]\n",
+      "[32444, 'friends', 32557]\n",
+      "[32444, 'friends', 32475]\n",
+      "[32444, 'friends', 32500]\n",
+      "[32444, 'friends', 32526]\n",
+      "[32444, 'friends', 32447]\n",
+      "[32444, 'friends', 32448]\n",
+      "[32444, 'feedback', 32448]\n",
+      "[32444, 'moretime', 32500]\n",
+      "[32444, 'advice', 32476]\n",
+      "[32444, 'advice', 32448]\n",
+      "[32444, 'disrespect', 32466]\n",
+      "[32444, 'disrespect', 32405]\n",
+      "[32428, 'friends', 32479]\n",
+      "[32428, 'friends', 32475]\n",
+      "[32428, 'friends', 32448]\n",
+      "[32428, 'influential', 32406]\n",
+      "[32428, 'influential', 32491]\n",
+      "[32428, 'influential', 32408]\n",
+      "[32428, 'influential', 32516]\n",
+      "[32428, 'feedback', 32420]\n",
+      "[32428, 'disrespect', 32466]\n",
+      "[32428, 'disrespect', 32459]\n",
+      "[32494, 'friends', 32495]\n",
+      "[32494, 'friends', 32395]\n",
+      "[32494, 'friends', 32454]\n",
+      "[32494, 'friends', 32512]\n",
+      "[32494, 'friends', 32419]\n",
+      "[32484, 'friends', 32452]\n",
+      "[32484, 'friends', 32442]\n",
+      "[32484, 'friends', 32419]\n",
+      "[32484, 'influential', 32540]\n",
+      "[32484, 'influential', 32397]\n",
+      "[32484, 'feedback', 32442]\n",
+      "[32484, 'moretime', 32442]\n",
+      "[32484, 'moretime', 32419]\n",
+      "[32484, 'advice', 32442]\n",
+      "[32484, 'disrespect', 32406]\n",
+      "[32541, 'friends', 32447]\n",
+      "[32541, 'friends', 32408]\n",
+      "[32541, 'friends', 32413]\n",
+      "[32541, 'friends', 32448]\n",
+      "[32541, 'friends', 32405]\n",
+      "[32541, 'friends', 32529]\n",
+      "[32541, 'friends', 32487]\n",
+      "[32541, 'friends', 32491]\n",
+      "[32541, 'friends', 32516]\n",
+      "[32541, 'friends', 32473]\n",
+      "[32541, 'friends', 32499]\n",
+      "[32541, 'friends', 32440]\n",
+      "[32541, 'friends', 32495]\n",
+      "[32541, 'friends', 32550]\n",
+      "[32541, 'friends', 32444]\n",
+      "[32541, 'friends', 32514]\n",
+      "[32541, 'friends', 32477]\n",
+      "[32541, 'advice', 32448]\n",
+      "[32445, 'friends', 32498]\n",
+      "[32445, 'friends', 32404]\n",
+      "[32445, 'friends', 32487]\n",
+      "[32445, 'friends', 32415]\n",
+      "[32445, 'friends', 32421]\n",
+      "[32445, 'influential', 32540]\n",
+      "[32445, 'feedback', 32498]\n",
+      "[32445, 'feedback', 32487]\n",
+      "[32445, 'feedback', 32404]\n",
+      "[32445, 'moretime', 32498]\n",
+      "[32445, 'moretime', 32487]\n",
+      "[32445, 'moretime', 32404]\n",
+      "[32445, 'moretime', 32415]\n",
+      "[32445, 'moretime', 32421]\n",
+      "[32445, 'advice', 32498]\n",
+      "[32445, 'advice', 32487]\n",
+      "[32445, 'advice', 32404]\n",
+      "[32445, 'disrespect', 32466]\n",
+      "[32445, 'disrespect', 32500]\n",
+      "[32445, 'disrespect', 32561]\n",
+      "[32470, 'friends', 32477]\n",
+      "[32470, 'friends', 32431]\n",
+      "[32470, 'friends', 32514]\n",
+      "[32470, 'friends', 32535]\n",
+      "[32470, 'friends', 32555]\n",
+      "[32470, 'friends', 32418]\n",
+      "[32470, 'friends', 32478]\n",
+      "[32470, 'friends', 32426]\n",
+      "[32470, 'friends', 32508]\n",
+      "[32470, 'friends', 32400]\n",
+      "[32470, 'friends', 32466]\n",
+      "[32470, 'friends', 32401]\n",
+      "[32470, 'friends', 32396]\n",
+      "[32470, 'friends', 32507]\n",
+      "[32470, 'friends', 32459]\n",
+      "[32470, 'influential', 32477]\n",
+      "[32470, 'feedback', 32477]\n",
+      "[32470, 'advice', 32477]\n",
+      "[32395, 'friends', 32454]\n",
+      "[32395, 'friends', 32494]\n",
+      "[32395, 'friends', 32475]\n",
+      "[32395, 'friends', 32528]\n",
+      "[32395, 'friends', 32415]\n",
+      "[32395, 'feedback', 32494]\n",
+      "[32395, 'feedback', 32475]\n",
+      "[32395, 'moretime', 32415]\n",
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+      "[32469, 'friends', 32513]\n",
+      "[32469, 'friends', 32517]\n",
+      "[32469, 'friends', 32546]\n",
+      "[32469, 'friends', 32540]\n",
+      "[32469, 'friends', 32440]\n",
+      "[32469, 'friends', 32409]\n",
+      "[32469, 'friends', 32462]\n",
+      "[32469, 'feedback', 32420]\n",
+      "[32469, 'feedback', 32468]\n",
+      "[32469, 'moretime', 32513]\n",
+      "[32469, 'moretime', 32517]\n",
+      "[32469, 'moretime', 32462]\n",
+      "[32469, 'advice', 32540]\n",
+      "[32469, 'advice', 32468]\n",
+      "[32469, 'advice', 32420]\n",
+      "[32469, 'advice', 32501]\n",
+      "[32548, 'friends', 32407]\n",
+      "[32548, 'friends', 32416]\n",
+      "[32548, 'friends', 32461]\n",
+      "[32548, 'friends', 32539]\n",
+      "[32548, 'friends', 32509]\n",
+      "[32548, 'friends', 32563]\n",
+      "[32548, 'friends', 32561]\n",
+      "[32548, 'feedback', 32416]\n",
+      "[32548, 'advice', 32416]\n",
+      "[32507, 'friends', 32396]\n",
+      "[32507, 'friends', 32405]\n",
+      "[32507, 'friends', 32544]\n",
+      "[32507, 'friends', 32535]\n",
+      "[32507, 'friends', 32417]\n",
+      "[32507, 'friends', 32491]\n",
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+      "[32507, 'friends', 32518]\n",
+      "[32507, 'influential', 32396]\n",
+      "[32507, 'moretime', 32417]\n",
+      "[32507, 'moretime', 32491]\n",
+      "[32507, 'moretime', 32443]\n",
+      "[32507, 'moretime', 32405]\n",
+      "[32507, 'moretime', 32518]\n",
+      "[32507, 'moretime', 32396]\n",
+      "[32507, 'moretime', 32544]\n",
+      "[32536, 'friends', 32536]\n",
+      "[32536, 'friends', 32524]\n",
+      "[32536, 'friends', 32511]\n",
+      "[32536, 'friends', 32482]\n",
+      "[32536, 'friends', 32506]\n",
+      "[32536, 'friends', 32450]\n",
+      "[32536, 'friends', 32481]\n",
+      "[32536, 'friends', 32521]\n",
+      "[32536, 'feedback', 32536]\n",
+      "[32536, 'moretime', 32521]\n",
+      "[32536, 'advice', 32536]\n",
+      "[32524, 'friends', 32511]\n",
+      "[32524, 'friends', 32450]\n",
+      "[32524, 'friends', 32482]\n",
+      "[32524, 'friends', 32506]\n",
+      "[32524, 'friends', 32481]\n",
+      "[32524, 'friends', 32410]\n",
+      "[32524, 'friends', 32536]\n",
+      "[32524, 'influential', 32396]\n",
+      "[32524, 'feedback', 32450]\n",
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+      "[32524, 'moretime', 32481]\n",
+      "[32524, 'moretime', 32450]\n",
+      "[32524, 'moretime', 32506]\n",
+      "[32524, 'advice', 32450]\n",
+      "[32524, 'advice', 32482]\n",
+      "[32524, 'disrespect', 32536]\n",
+      "[32482, 'friends', 32481]\n",
+      "[32482, 'friends', 32536]\n",
+      "[32482, 'friends', 32450]\n",
+      "[32482, 'friends', 32524]\n",
+      "[32482, 'friends', 32412]\n",
+      "[32482, 'feedback', 32481]\n",
+      "[32482, 'advice', 32536]\n",
+      "[32482, 'advice', 32450]\n",
+      "[32481, 'friends', 32482]\n",
+      "[32481, 'friends', 32416]\n",
+      "[32481, 'friends', 32506]\n",
+      "[32481, 'friends', 32450]\n",
+      "[32481, 'friends', 32536]\n",
+      "[32481, 'friends', 32511]\n",
+      "[32481, 'friends', 32524]\n",
+      "[32481, 'feedback', 32482]\n",
+      "[32481, 'moretime', 32482]\n",
+      "[32481, 'moretime', 32416]\n",
+      "[32481, 'advice', 32482]\n",
+      "[32481, 'advice', 32506]\n",
+      "[32481, 'disrespect', 32413]\n",
+      "[32481, 'disrespect', 32405]\n",
+      "[32439, 'friends', 32457]\n",
+      "[32439, 'friends', 32503]\n",
+      "[32439, 'friends', 32479]\n",
+      "[32439, 'friends', 32418]\n",
+      "[32439, 'friends', 32403]\n",
+      "[32439, 'influential', 32406]\n",
+      "[32439, 'influential', 32518]\n",
+      "[32439, 'influential', 32443]\n",
+      "[32439, 'influential', 32491]\n",
+      "[32439, 'feedback', 32503]\n",
+      "[32439, 'feedback', 32457]\n",
+      "[32439, 'moretime', 32499]\n",
+      "[32439, 'moretime', 32410]\n",
+      "[32439, 'moretime', 32485]\n",
+      "[32439, 'advice', 32503]\n",
+      "[32439, 'advice', 32457]\n",
+      "[32439, 'disrespect', 32552]\n",
+      "[32559, 'friends', 32558]\n",
+      "[32559, 'friends', 32565]\n",
+      "[32559, 'friends', 32509]\n",
+      "[32559, 'friends', 32427]\n",
+      "[32559, 'friends', 32407]\n",
+      "[32559, 'friends', 32562]\n",
+      "[32559, 'friends', 32488]\n",
+      "[32559, 'influential', 32488]\n",
+      "[32559, 'feedback', 32565]\n",
+      "[32559, 'feedback', 32556]\n",
+      "[32559, 'advice', 32565]\n",
+      "[32559, 'advice', 32556]\n",
+      "[32559, 'advice', 32558]\n",
+      "[32460, 'friends', 32458]\n",
+      "[32460, 'friends', 32459]\n",
+      "[32460, 'friends', 32421]\n",
+      "[32460, 'friends', 32422]\n",
+      "[32460, 'friends', 32404]\n",
+      "[32460, 'influential', 32460]\n",
+      "[32460, 'influential', 32458]\n",
+      "[32460, 'feedback', 32458]\n",
+      "[32460, 'feedback', 32459]\n",
+      "[32460, 'feedback', 32417]\n",
+      "[32460, 'moretime', 32458]\n",
+      "[32460, 'moretime', 32459]\n",
+      "[32460, 'moretime', 32421]\n",
+      "[32460, 'moretime', 32422]\n",
+      "[32460, 'advice', 32490]\n",
+      "[32460, 'advice', 32459]\n",
+      "[32460, 'advice', 32458]\n",
+      "[32520, 'friends', 32556]\n",
+      "[32520, 'friends', 32449]\n",
+      "[32520, 'influential', 32547]\n",
+      "[32520, 'influential', 32561]\n",
+      "[32520, 'moretime', 32530]\n",
+      "[32520, 'moretime', 32398]\n",
+      "[32520, 'disrespect', 32455]\n",
+      "[32450, 'friends', 32536]\n",
+      "[32450, 'friends', 32524]\n",
+      "[32450, 'friends', 32511]\n",
+      "[32450, 'friends', 32482]\n",
+      "[32450, 'friends', 32506]\n",
+      "[32450, 'friends', 32481]\n",
+      "[32450, 'friends', 32450]\n",
+      "[32450, 'friends', 32521]\n",
+      "[32450, 'feedback', 32450]\n",
+      "[32450, 'advice', 32450]\n",
+      "[32538, 'friends', 32554]\n",
+      "[32538, 'friends', 32529]\n",
+      "[32538, 'friends', 32549]\n",
+      "[32538, 'friends', 32531]\n",
+      "[32538, 'friends', 32422]\n",
+      "[32538, 'friends', 32460]\n",
+      "[32538, 'friends', 32458]\n",
+      "[32538, 'influential', 32422]\n",
+      "[32538, 'influential', 32549]\n",
+      "[32538, 'influential', 32529]\n",
+      "[32538, 'feedback', 32549]\n",
+      "[32538, 'feedback', 32529]\n",
+      "[32538, 'moretime', 32531]\n",
+      "[32538, 'moretime', 32554]\n",
+      "[32538, 'advice', 32529]\n",
+      "[32538, 'advice', 32531]\n",
+      "[32538, 'advice', 32554]\n",
+      "[32538, 'disrespect', 32500]\n",
+      "[32454, 'friends', 32495]\n",
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+      "[32454, 'friends', 32479]\n",
+      "[32454, 'friends', 32448]\n",
+      "[32454, 'feedback', 32495]\n",
+      "[32454, 'advice', 32495]\n",
+      "[32554, 'friends', 32392]\n",
+      "[32554, 'friends', 32532]\n",
+      "[32554, 'friends', 32538]\n",
+      "[32554, 'friends', 32531]\n",
+      "[32554, 'friends', 32458]\n",
+      "[32554, 'influential', 32422]\n",
+      "[32554, 'influential', 32421]\n",
+      "[32554, 'feedback', 32392]\n",
+      "[32554, 'feedback', 32532]\n",
+      "[32554, 'moretime', 32422]\n",
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+      "[32554, 'moretime', 32546]\n",
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+      "[32554, 'advice', 32392]\n",
+      "[32554, 'advice', 32532]\n",
+      "[32447, 'influential', 32541]\n",
+      "[32447, 'advice', 32541]\n",
+      "[32447, 'advice', 32512]\n",
+      "[32447, 'advice', 32487]\n",
+      "[32447, 'advice', 32448]\n",
+      "[32447, 'advice', 32444]\n",
+      "[32447, 'advice', 32413]\n",
+      "[32447, 'advice', 32502]\n",
+      "[32447, 'advice', 32529]\n",
+      "[32447, 'advice', 32513]\n",
+      "[32447, 'advice', 32440]\n",
+      "[32423, 'friends', 32488]\n",
+      "[32423, 'friends', 32555]\n",
+      "[32423, 'friends', 32434]\n",
+      "[32423, 'friends', 32427]\n",
+      "[32423, 'friends', 32543]\n",
+      "[32423, 'friends', 32407]\n",
+      "[32423, 'influential', 32396]\n",
+      "[32423, 'influential', 32555]\n",
+      "[32423, 'influential', 32488]\n",
+      "[32423, 'feedback', 32488]\n",
+      "[32423, 'feedback', 32407]\n",
+      "[32423, 'feedback', 32434]\n",
+      "[32423, 'advice', 32488]\n",
+      "[32423, 'advice', 32555]\n",
+      "[32486, 'friends', 32519]\n",
+      "[32486, 'friends', 32424]\n",
+      "[32486, 'friends', 32451]\n",
+      "[32486, 'moretime', 32424]\n",
+      "[32486, 'advice', 32464]\n",
+      "[32486, 'advice', 32392]\n",
+      "[32449, 'friends', 32520]\n",
+      "[32449, 'friends', 32531]\n",
+      "[32449, 'moretime', 32531]\n",
+      "[32449, 'moretime', 32538]\n",
+      "[32465, 'friends', 32545]\n",
+      "[32465, 'friends', 32504]\n",
+      "[32465, 'friends', 32422]\n",
+      "[32465, 'friends', 32421]\n",
+      "[32465, 'friends', 32533]\n",
+      "[32465, 'moretime', 32545]\n",
+      "[32465, 'moretime', 32504]\n",
+      "[32465, 'moretime', 32422]\n",
+      "[32465, 'moretime', 32421]\n",
+      "[32465, 'moretime', 32533]\n",
+      "[32465, 'advice', 32465]\n",
+      "[32465, 'advice', 32533]\n",
+      "[32503, 'friends', 32439]\n",
+      "[32503, 'friends', 32468]\n",
+      "[32503, 'friends', 32401]\n",
+      "[32503, 'influential', 32552]\n",
+      "[32503, 'feedback', 32439]\n",
+      "[32503, 'feedback', 32457]\n",
+      "[32503, 'moretime', 32426]\n",
+      "[32503, 'moretime', 32418]\n",
+      "[32503, 'advice', 32439]\n",
+      "[32503, 'advice', 32418]\n",
+      "[32552, 'friends', 32562]\n",
+      "[32552, 'advice', 32562]\n",
+      "[32473, 'friends', 32448]\n",
+      "[32473, 'friends', 32479]\n",
+      "[32473, 'friends', 32484]\n",
+      "[32473, 'friends', 32502]\n",
+      "[32473, 'feedback', 32448]\n",
+      "[32473, 'feedback', 32502]\n",
+      "[32473, 'moretime', 32502]\n",
+      "[32473, 'advice', 32448]\n",
+      "[32473, 'advice', 32484]\n",
+      "[32473, 'advice', 32502]\n",
+      "[32473, 'disrespect', 32460]\n",
+      "[32473, 'disrespect', 32466]\n"
+     ]
+    }
+   ],
+   "source": [
+    "results = k_client.execute(\"\"\"MATCH q = (p:participants)-[f]->(p2:participants)\n",
+    "        RETURN p.participant_id,(rels(q)[1])._label,p2.participant_id;\"\"\")\n",
+    "# results = k_client.execute(\"\"\"CALL SHOW_TABLES() RETURN *;\"\"\")\n",
+    "\n",
+    "\n",
+    "while results.has_next():\n",
+    "    print(results.get_next())\n",
+    "#     print(results.get_next()[1][\"_label\"])"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": ".venv",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}