Initial commit loading app.py, app.yaml, and requirements.txt

app.py

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+import streamlit as st
+st.set_page_config(layout="wide")
+import numpy as np
+import pandas as pd
+import pymongo
+import time
+
+@st.cache_resource
+def init_conn():
+        
+        uri = st.secrets['mongo_uri']
+        client = pymongo.MongoClient(uri, retryWrites=True, serverSelectionTimeoutMS=500000)
+        db = client["League_of_Legends_Database"]
+
+        collection = db["gamelogs"] 
+        team_names = collection.distinct("teamname")
+        player_names = collection.distinct("playername")
+
+        return db, team_names, player_names
+    
+db, team_names, player_names = init_conn()
+
+@st.cache_data(ttl = 60)
+def init_team_data(team):  
+        
+        collection = db["gamelogs"] 
+        cursor = collection.find({"teamname": team})
+    
+        raw_display = pd.DataFrame(list(cursor))
+        raw_display = raw_display[['playername', 'teamname', 'playername_avg_kill_share_win', 'playername_avg_death_share_win', 'playername_avg_assist_share_win', 'playername_avg_cs_share_win', 'playername_avg_kill_share_loss', 'playername_avg_death_share_loss', 'playername_avg_assist_share_loss', 'playername_avg_cs_share_loss']]
+
+        team_data = raw_display.drop_duplicates(subset = ['playername'])
+
+        return team_data
+
+st.table(init_team_data("T1"))

app.yaml

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+runtime: python
+env: flex
+
+runtime_config:
+  python_version: 3
+
+entrypoint: streamlit run streamlit-app.py --server.port $PORT
+
+automatic_scaling:
+  max_num_instances: 200

requirements.txt

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+streamlit
+gspread
+openpyxl
+matplotlib
+pymongo
+pulp
+docker
+plotly
+scipy