Update requirements and enhance Streamlit app with MongoDB integration. Added pymongo to requirements and implemented database connection and data retrieval in streamlit_app.py.

requirements.txt

@@ -1,3 +1,4 @@
 altair
 pandas
-streamlit
+streamlit
+pymongo

src/streamlit_app.py

@@ -1,40 +1,33 @@
-import altair as alt
 import numpy as np
 import pandas as pd
 import streamlit as st
+import pymongo
 
-"""
-# Welcome to Streamlit!
-
-Edit `/streamlit_app.py` to customize this app to your heart's desire :heart:.
-If you have any questions, checkout our [documentation](https://docs.streamlit.io) and [community
-forums](https://discuss.streamlit.io).
-
-In the meantime, below is an example of what you can do with just a few lines of code:
-"""
-
-num_points = st.slider("Number of points in spiral", 1, 10000, 1100)
-num_turns = st.slider("Number of turns in spiral", 1, 300, 31)
-
-indices = np.linspace(0, 1, num_points)
-theta = 2 * np.pi * num_turns * indices
-radius = indices
-
-x = radius * np.cos(theta)
-y = radius * np.sin(theta)
-
-df = pd.DataFrame({
-    "x": x,
-    "y": y,
-    "idx": indices,
-    "rand": np.random.randn(num_points),
-})
-
-st.altair_chart(alt.Chart(df, height=700, width=700)
-    .mark_point(filled=True)
-    .encode(
-        x=alt.X("x", axis=None),
-        y=alt.Y("y", axis=None),
-        color=alt.Color("idx", legend=None, scale=alt.Scale()),
-        size=alt.Size("rand", legend=None, scale=alt.Scale(range=[1, 150])),
-    ))
+st.set_page_config(layout="wide")
+
+@st.cache_resource
+def init_conn():
+
+    uri = st.secrets['mongo_uri']
+    client = pymongo.MongoClient(uri, retryWrites=True, serverSelectionTimeoutMS=500000)
+    db = client["MLB_Database"]
+
+    return db
+
+db = init_conn()
+
+@st.cache_resource(ttl = 300)
+def init_baselines():
+        collection = db["HR_Table"] 
+        cursor = collection.find()
+        raw_display = pd.DataFrame(cursor)
+        raw_display.rename(columns={"Names": "Player"}, inplace = True)
+        raw_frame = raw_display.drop_duplicates(subset='Player')
+
+        return raw_frame
+
+
+hr_frame = init_baselines()
+st.title("HR Finder Table")
+
+st.dataframe(hr_frame, use_container_width = True, hide_index = True)