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app.py
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app.py
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import streamlit as st
import pickle
st.title("Movie Recommender System")
year_values = st.slider("Select Range of Release Year", 1950, 2020, (2000, 2020))
def recommend(movie_name):
movie_index = movies[movies['title'] == movie_name].index[0]
distances = similarity[movie_index]
movies_lists = sorted(list(enumerate(distances)), reverse=True, key=lambda x: x[1])
recommended_movies = []
c = 0
for i in movies_lists:
mov_year=int(movies.iloc[i[0]].year_of_release)
if((mov_year >= year_values[0]) & (mov_year <= year_values[1])):
recommended_movies.append(movies.iloc[i[0]].title)
c = c + 1
if c == 10:
return recommended_movies
xs = pickle.load(open('x.pkl', 'rb'))
movies = pickle.load(open('df.pkl', 'rb'))
similarity = pickle.load(open('sim.pkl', 'rb'))
selected_movie = st.selectbox(
'Movies', xs
)
if st.button('Recommend'):
names = recommend(selected_movie)
col1, col2 = st.columns(2)
with col1:
st.text(names[0])
with col2:
st.text(names[1])
col1, col2 = st.columns(2)
with col1:
st.text(names[2])
with col2:
st.text(names[3])
col1, col2 = st.columns(2)
with col1:
st.text(names[4])
with col2:
st.text(names[5])
col1, col2 = st.columns(2)
with col1:
st.text(names[6])
with col2:
st.text(names[7])
col1, col2 = st.columns(2)
with col1:
st.text(names[8])
with col2:
st.text(names[9])