uppdate

,dockerignore

@@ -1,6 +0,0 @@
-.venv
-__pycache__/
-*.pyc
-data/
-artifacts/
-.git

app.py

@@ -1,3 +1,7 @@
+import os, sys
+
+sys.path.append(os.path.join(os.path.dirname(__file__), "src"))
+
 import streamlit as st
 import pandas as pd
 from data import load_statcast, default_window
@@ -5,9 +9,7 @@ from featurize import infer_ivb_sign, engineer_pitch_features
 from model import fit_kmeans, nearest_comps
 from tags import xy_cluster_tags
 from plots import movement_scatter_xy, radar_quality
-import os, sys
 
-sys.path.append(os.path.join(os.path.dirname(__file__), "src"))
 
 st.set_page_config(page_title="PitchXY (Handedness-Aware)", layout="wide")
 st.title("⚾ PitchXY — Handedness-Aware Pitch Archetypes & Scouting Cards")

src/streamlit_app.py

@@ -1,40 +0,0 @@
-import altair as alt
-import numpy as np
-import pandas as pd
-import streamlit as st
-
-"""
-# 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])),
-    ))