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import streamlit as st
# Configure Streamlit page
st.set_page_config(
page_title="Find the Song that You Like🎸", page_icon="🎸", layout="wide"
)
import pandas as pd
import plotly.express as px
import streamlit.components.v1 as components
from sklearn.neighbors import NearestNeighbors
@st.cache(allow_output_mutation=True)
def data_import():
"""Function for loading in cleaned data csv file."""
df = pd.read_csv("data/clean_data.csv")
df["genres"] = df.genres.apply(
lambda x: [i[1:-1] for i in str(x)[1:-1].split(", ")]
)
df_explode = df.explode("genres")
return df_explode
genre_names = [
"Dance Pop",
"Electronic",
"Electropop",
"Hip Hop",
"Jazz",
"K-pop",
"Latin",
"Pop",
"Pop Rap",
"R&B",
"Rock",
]
audio_params = [
"acousticness",
"danceability",
"energy",
"instrumentalness",
"valence",
"tempo",
]
df_explode = data_import()
def match_song(genre, yr_start, yr_end, test_feat):
"""Function for finding similar songs with KNN algorithm."""
genre = genre.lower()
genre_data = df_explode[
(df_explode["genres"] == genre)
& (df_explode["release_year"] >= yr_start)
& (df_explode["release_year"] <= yr_end)
]
genre_data = genre_data.sort_values(by="popularity", ascending=False)[:500]
# Load KNN from SkLearn
neigh = NearestNeighbors()
neigh.fit(genre_data[audio_params].to_numpy())
n_neighbors = neigh.kneighbors(
[test_feat], n_neighbors=len(genre_data), return_distance=False
)[0]
uris = genre_data.iloc[n_neighbors]["uri"].tolist()
audios = genre_data.iloc[n_neighbors][audio_params].to_numpy()
return uris, audios
# Setup page order
def page():
title = "Find Your Song🎸"
st.title(title)
st.write(
"Get recommended songs on Spotify based on genre and key audio parameters."
)
st.markdown("##")
# Streamlit column layout
with st.container():
col1, col2, col3, col4 = st.columns((2, 0.5, 0.5, 0.5))
with col3:
st.markdown("***Select genre:***")
genre = st.radio("", genre_names, index=genre_names.index("Rock"))
with col1:
st.markdown("***Select audio parameters to customize:***")
yr_start, yr_end = st.slider(
"Select the year range", 1908, 2022, (1980, 2022)
)
acousticness = st.slider("Acousticness", 0.0, 1.0, 0.5)
danceability = st.slider("Danceability", 0.0, 1.0, 0.5)
energy = st.slider("Energy", 0.0, 1.0, 0.5)
instrumentalness = st.slider("Instrumentalness", 0.0, 1.0, 0.5)
valence = st.slider("Valence", 0.0, 1.0, 0.45)
tempo = st.slider("Tempo", 0.0, 244.0, 125.01)
pr_page_tracks = 6
test_feat = [acousticness, danceability, energy, instrumentalness, valence, tempo]
uris, audios = match_song(genre, yr_start, yr_end, test_feat)
tracks = []
for uri in uris:
track = """<iframe src="https://open.spotify.com/embed/track/{}" width="280" height="400" frameborder="0" allowtransparency="true" allow="encrypted-media"></iframe>""".format(
uri
)
tracks.append(track)
if "previous_inputs" not in st.session_state:
st.session_state["previous_inputs"] = [genre, yr_start, yr_end] + test_feat
current_inputs = [genre, yr_start, yr_end] + test_feat
if current_inputs != st.session_state["previous_inputs"]:
if "start_track_i" in st.session_state:
st.session_state["start_track_i"] = 0
st.session_state["previous_inputs"] = current_inputs
if "start_track_i" not in st.session_state:
st.session_state["start_track_i"] = 0
with st.container():
col1, col2, col3 = st.columns([2, 1, 2])
if st.button("More Songs"):
if st.session_state["start_track_i"] < len(tracks):
st.session_state["start_track_i"] += pr_page_tracks
current_tracks = tracks[
st.session_state["start_track_i"] : st.session_state["start_track_i"]
+ pr_page_tracks
]
current_audios = audios[
st.session_state["start_track_i"] : st.session_state["start_track_i"]
+ pr_page_tracks
]
if st.session_state["start_track_i"] < len(tracks):
for i, (track, audio) in enumerate(zip(current_tracks, current_audios)):
if i % 2 == 0:
with col1:
components.html(
track,
height=400,
)
with st.expander("Display Chart"):
df = pd.DataFrame(dict(r=audio[:5], theta=audio_params[:5]))
fig = px.line_polar(
df, r="r", theta="theta", line_close=True
)
fig.update_layout(height=400, width=340)
st.plotly_chart(fig)
else:
with col3:
components.html(
track,
height=400,
)
with st.expander("Display Chart"):
df = pd.DataFrame(dict(r=audio[:5], theta=audio_params[:5]))
fig = px.line_polar(
df, r="r", theta="theta", line_close=True
)
fig.update_layout(height=400, width=340)
st.plotly_chart(fig)
else:
st.write("No more songs")
page()
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