Total FE Overhaul (#4)

* table don't work great

* streamlit addition

* changes to deploy streamlit

* remove matchup overview

* bunch of minor FE updates

aws/spacejam-server-cli-input.json → .aws/spacejam-server-cli-input.json

@@ -48,7 +48,7 @@
             "healthCheck": {
                 "command": [
                     "CMD-SHELL",
-                    "curl -f 0.0.0.0:5006/liveness || exit 1"
+                    "curl -f 0.0.0.0:5006/healthz || exit 1"
                 ],
                 "interval": 30,
                 "timeout": 5,

dockerignore → .dockerignore

@@ -1,3 +1,4 @@
 .venv/*
 .github/*
-.vscode/*
+.vscode/*
+.aws/*

.github/workflows/deploy.yaml

@@ -12,7 +12,7 @@ env:
   ECR_REPOSITORY: spacejamprod/server          # set this to your Amazon ECR repository name
   ECS_SERVICE: spacejam                 # set this to your Amazon ECS service name
   ECS_CLUSTER: SpacejamProd                 # set this to your Amazon ECS cluster name
-  ECS_TASK_DEFINITION: aws/spacejam-server-cli-input.json # set this to the path to your Amazon ECS task definition
+  ECS_TASK_DEFINITION: .aws/spacejam-server-cli-input.json # set this to the path to your Amazon ECS task definition
                                                # file, e.g. .aws/task-definition.json
   CONTAINER_NAME: spacejam-server           # set this to the name of the container in the
 

Dockerfile

@@ -6,8 +6,8 @@ WORKDIR /app
 
 ADD . /app
 
-ENV PATH="/app/.venv/bin:$PATH"
+ENV PYTHONPATH=.
 
 RUN uv sync --frozen 
 
-CMD ["uv", "run", "panel", "serve", "src/frontend.py", "--address", "0.0.0.0", "--port", "5006", "--allow-websocket-origin=18.222.161.54:5006", "--liveness" ] 
+CMD ["uv", "run",  "streamlit", "run", "src/streamlit_frontend.py", "--server.port", "5006" ] 

pyproject.toml

@@ -8,4 +8,20 @@ dependencies = [
     "espn-api>=0.43.0",
     "pandas>=2.2.3",
     "panel>=1.5.4",
+    "streamlit-autorefresh>=1.0.1",
+    "streamlit>=1.40.2",
+    "watchfiles>=1.0.0",
+    "matplotlib>=3.9.3",
 ]
+
+[tool.ruff]
+line-length = 100
+indent-width = 4
+
+[tool.ruff.lint]
+select = ["E4", "E7", "E9", "F", "I"]
+ignore = []
+
+[tool.ruff.format]
+quote-style = "double"
+skip-magic-trailing-comma = true

src/backend.py

@@ -1,26 +1,29 @@
-import pandas as pd
+from copy import deepcopy
 
-from espn_api.basketball import League
+import pandas as pd
+from espn_api.basketball import League, Team
 
-import constants as const
+import src.constants as const
 
 
 def get_league(league_id: int = const.SPACEJAM_LEAGUE_ID, year: int = const.YEAR):
-    return League(league_id, year)
+    league = League(league_id, year)
+    league.teams = {team.team_name: team for team in league.teams}
+    return league
 
 
 def get_league_all_raw_stats_df(league: League):
     league_stats = []
-    for team in league.teams:
-        temp_dict = team.stats.copy()
+    for team in league.teams.values():
+        temp_dict = deepcopy(team.stats)
         temp_dict["Team"] = team.team_name
         temp_dict["Standing"] = team.standing
         league_stats.append(temp_dict)
 
     df = pd.DataFrame(league_stats)
 
     df = df.astype(const.ALL_RAW_DATA_TABLE_DEF)
-    return df[list(const.ALL_RAW_DATA_TABLE_DEF.keys())]
+    return df[list(const.ALL_RAW_DATA_TABLE_DEF.keys())].sort_values(by="Standing")
 
 
 def get_league_all_raw_data_rankings(league: League):
@@ -34,29 +37,23 @@ def get_league_all_raw_data_rankings(league: League):
     ranked_df["Avg. Cat. Rank"] = ranked_df.mean(axis=1)
 
     # Concatenate with non-numeric columns
-    ranked_df = pd.concat(
-        [
-            ranked_df,
-            raw_stats_df.select_dtypes(exclude="number"),
-        ],
-        axis=1,
-    )
+    ranked_df = pd.concat([ranked_df, raw_stats_df.select_dtypes(exclude="number")], axis=1)
 
-    return ranked_df[list(const.ALL_DATA_RANKED_TABLE_DEF.keys())]
+    return ranked_df[list(const.ALL_DATA_RANKED_TABLE_DEF.keys())].sort_values(by="Standing")
 
 
 def get_league_cat_raw_stats_df(league: League):
     league_stats = []
-    for team in league.teams:
-        temp_dict = team.stats.copy()
+    for team in league.teams.values():
+        temp_dict = deepcopy(team.stats)
         temp_dict["Team"] = team.team_name
         temp_dict["Standing"] = team.standing
         league_stats.append(temp_dict)
 
     df = pd.DataFrame(league_stats)
 
     df = df.astype(const.CAT_ONLY_RAW_DATA_TABLE_DEF)
-    return df[list(const.CAT_ONLY_RAW_DATA_TABLE_DEF.keys())]
+    return df[list(const.CAT_ONLY_RAW_DATA_TABLE_DEF.keys())].sort_values(by="Standing")
 
 
 def get_league_cat_data_rankings(league: League):
@@ -70,14 +67,15 @@ def get_league_cat_data_rankings(league: League):
     ranked_df["Avg. Cat. Rank"] = ranked_df.mean(axis=1)
 
     # Concatenate with non-numeric columns
-    ranked_df = pd.concat(
-        [
-            ranked_df,
-            raw_stats_df.select_dtypes(exclude="number"),
-        ],
-        axis=1,
-    )
-    return ranked_df[list(const.CAT_ONLY_DATA_RANKED_TABLE_DEF.keys())]
+    ranked_df = pd.concat([ranked_df, raw_stats_df.select_dtypes(exclude="number")], axis=1)
+    return ranked_df[list(const.CAT_ONLY_DATA_RANKED_TABLE_DEF.keys())].sort_values(by="Standing")
+
+
+def get_average_team_stats(team: Team, num_days: int):
+    """Get Stats for team averaged over specified number of days From todays date."""
+    stat_key = f"{const.YEAR}_last_{num_days}"
+    player_avgs = {player.name: player.stats[stat_key].get("avg", {}) for player in team.roster}
+    return player_avgs
 
 
 if __name__ == "__main__":

src/constants.py

@@ -1,6 +1,8 @@
 SPACEJAM_LEAGUE_ID = 233677
 YEAR = 2025
 
+NINE_CATS = ["PTS", "BLK", "STL", "AST", "REB", "TO", "3PM", "FG%", "FT%"]
+
 ALL_RAW_DATA_TABLE_DEF = {
     "Team": str,
     "Standing": int,
@@ -67,19 +69,8 @@
     "FT%": int,
 }
 
-WANT_BIG_NUM = [
-    "PTS",
-    "BLK",
-    "STL",
-    "AST",
-    "REB",
-    "FGM",
-    "FGA",
-    "FTM",
-    "FTA",
-    "3PM",
-    "FG%",
-    "FT%",
-]
+WANT_BIG_NUM = ["PTS", "BLK", "STL", "AST", "REB", "FGM", "FGA", "FTM", "FTA", "3PM", "FG%", "FT%"]
+
+WANT_BIG_NUM_CATS = ["PTS", "BLK", "STL", "AST", "REB", "3PM", "FG%", "FT%"]
 
 WANT_SMALL_NUM = ["Standing", "TO"]

src/panel_frontend.py

@@ -0,0 +1,62 @@
+import datetime as dt
+import logging
+
+import panel as pn
+
+import backend as be
+
+pn.extension("tabulator")
+
+logger = logging.getLogger()
+
+
+class LeagueData:
+    def __init__(self):
+        self.data = be.get_league()
+        self.last_updated = dt.datetime.now()
+
+    def update(self):
+        self.data = be.get_league()
+        self.last_updated = dt.datetime.now()
+
+
+def get_dataframe(mode: str, league_data: LeagueData):
+    logger.info(f"Returning League Wide stats Dataframe for {league_data.data.league_id}")
+    if mode == "All Data - Raw Stats":
+        df = be.get_league_all_raw_stats_df(league_data.data)
+    elif mode == "All Data - Ranked":
+        df = be.get_league_all_raw_data_rankings(league_data.data)
+    elif mode == "Categories - Raw Stats":
+        df = be.get_league_cat_raw_stats_df(league_data.data)
+    elif mode == "Categories - Rankings":
+        df = be.get_league_cat_data_rankings(league_data.data)
+    return df
+
+
+def app():
+    league_data = LeagueData()
+
+    mode = pn.widgets.Select(
+        name="Mode",
+        options=[
+            "Categories - Rankings",
+            "Categories - Raw Stats",
+            "All Data - Ranked",
+            "All Data - Raw Stats",
+        ],
+    )
+    refresh_button = pn.widgets.Button(
+        name="Refresh Stats"
+    )  # doesn't work. my interactive table is f-d beyond comprehension
+
+    interactive_df = pn.bind(get_dataframe, mode=mode, league_data=league_data)
+    interactive_table = pn.widgets.Tabulator(interactive_df, theme="site", show_index=False)
+    return pn.template.ReactTemplate(
+        title="Space Jam Dashboard",
+        sidebar=[refresh_button, mode],
+        main=[interactive_table],
+        sidebar_width=150,
+    )
+
+
+app().servable()

src/streamlit_frontend.py

@@ -0,0 +1,69 @@
+import matplotlib.pyplot as plt
+import pandas as pd
+import streamlit as st
+from streamlit_autorefresh import st_autorefresh
+
+import src.backend as be
+import src.constants as const
+
+ryg = plt.colormaps["RdYlGn"]
+gyr = plt.colormaps["RdYlGn"].reversed()
+icon_url = "https://spacejam-dashboard.s3.us-east-2.amazonaws.com/assets/the-last-spacejam.jpg"
+st.set_page_config(layout="wide", page_title="Spacejam Dashboard", page_icon=icon_url)
+refresh_in_sec = 60
+count = st_autorefresh(interval=refresh_in_sec * 1000, limit=100, key="statscounter")
+
+
+@st.cache_data
+def update_league_data():
+    return be.get_league()
+
+
+league_data = update_league_data()
+
+teams = [team.team_name for team in league_data.teams.values()]
+
+
+matchup_df = be.get_league_cat_raw_stats_df(league_data)
+team_stats_df = be.get_league_all_raw_data_rankings(league_data)
+
+
+# Sidebar for page selection
+st.sidebar.title("Navigation")
+st.sidebar.markdown("# About")
+st.sidebar.markdown("Welcome to the Space Jam Dashboard!")
+st.sidebar.markdown(
+    "This is my attempt at democratizing data and having fun coding. Let me know what you think (as long as it is good if you think it sucks I hate you.)"
+)
+page = st.sidebar.radio(
+    "Select a Page", ("League Overview", "Team Overview")
+)  # , "Matchup Overview"))
+
+# League Overview Page
+if page == "League Overview":
+    league_df = be.get_league_cat_data_rankings(league_data)
+    league_df_styled = league_df.style.background_gradient(cmap=gyr)
+    st.title("Spacejam League Overview")
+    st.dataframe(league_df_styled, use_container_width=True, hide_index=True, height=460)
+    st.markdown(
+        "As you can imagine, green means that this team is good in that category, and red means the team is bad in that category."
+    )
+
+# Team Overview Page
+elif page == "Team Overview":
+    chosen_team = st.sidebar.selectbox("Team", teams)
+    team_data = league_data.teams[chosen_team]
+    st.title(f"Overview - {chosen_team}")
+    st.write("Stats for", chosen_team)
+    timeframe = st.radio(label="Time:", options=["30 Days", "15 Days", "7 Days"], horizontal=True)
+    timeframe_num = int(timeframe.split(" ")[0])
+    team_avg_stats = be.get_average_team_stats(team_data, timeframe_num)
+    df = pd.DataFrame(team_avg_stats).T.fillna(0)
+    show_cols = st.multiselect("Column Filter", options=df.columns, default=const.NINE_CATS)
+    st.dataframe(df[show_cols], use_container_width=True, height=460)
+
+# Matchup Overview Page
+elif page == "Matchup Overview":
+    st.title(f"Matchup Overview - {chosen_team}")
+    st.write("Matchup Stats for", chosen_team)
+    st.table(matchup_df.loc[matchup_df["Team"] == chosen_team])