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.gitattributes

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Procfile

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+web: sh setup.sh && streamlit run app.py 

app.py

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+import pickle
+import datetime
+import streamlit as st
+import pandas as pd
+import requests
+
+st.set_page_config(
+   page_title="Movie Recommender System App",
+   page_icon="🧊",
+   layout="wide",
+   initial_sidebar_state="expanded",
+)
+# d = st.date_input(
+#     "When\'s your birthday",
+#     datetime.date(2019, 7, 6))
+# st.write('Your birthday is:', d)
+
+st.title('Movie Recommender System')
+movies_dict = pickle.load(open('movie_dict.pkl','rb'))
+similarity = pickle.load(open('similarity.pkl','rb'))
+movies = pd.DataFrame (movies_dict)
+
+hide = """
+<style>
+div[data-testid="stConnectionStatus"] {
+    display: none !important;
+</style>
+"""
+
+st.markdown(hide, unsafe_allow_html=True)
+
+def fetch_poster(movie_id):
+    response = requests.get('https://api.themoviedb.org/3/movie/{}?api_key=263cccc7902c444e5a0231f11b54d71f&language=en-US'.format(movie_id))
+    data = response.json()
+    return "https://image.tmdb.org/t/p/w500/" + data['poster_path']
+
+def recommend(movie):
+    movie_index = movies[movies['title']== movie ].index[0]
+    distances = similarity[movie_index]
+    movie_list = sorted(list(enumerate(distances)),reverse = True,key= lambda x:x[1])[1:11]
+    recommended_movies = []
+    recommended_movies_posters = []
+    
+    for i in movie_list:
+        movie_id = movies.iloc[i[0]].movie_id
+
+        recommended_movies.append(movies.iloc[i[0]].title)
+        # fetch poster from API 
+        recommended_movies_posters.append(fetch_poster(movie_id))
+    return recommended_movies,recommended_movies_posters
+
+selected_movie_name = st.selectbox("Type or select a movie from the dropdown", movies['title'].values)
+
+if st.button('Recommend'):
+    names,posters = recommend(selected_movie_name)
+    c1, c2, c3, c4, c5 = st.columns(5)
+    with c1:
+        st.image(posters[0])
+        st.info(names[0])
+    with c2:
+        st.image(posters[1])
+        st.info(names[1])
+    with c3:
+        st.image(posters[2])
+        st.info(names[2])
+    with c4:
+        st.image(posters[3])
+        st.info(names[3])
+    with c5:
+        st.image(posters[4])
+        st.info(names[4])
+
+    st.header("Some other Movies")
+    c6, c7, c8, c9, c10 = st.columns(5)
+    with c6:
+        st.image(posters[5])
+        st.info(names[5])
+    with c7:
+        st.image(posters[6])
+        st.info(names[6])
+    with c8:
+        st.image(posters[7])
+        st.info(names[7])
+    with c9:
+        st.image(posters[8])
+        st.info(names[8])
+    with c10:
+        st.image(posters[9])
+        st.info(names[9])

movie_dict.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:a2cb397bf04eb7f72d05e56aa452b176bd3e3efc2ec89f7b1d472271b24f2f99
+size 2166675

pyvenv.cfg

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+home = /Library/Developer/CommandLineTools/usr/bin
+include-system-site-packages = false
+version = 3.9.6

requirements.txt

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+streamlit
+requests

setup.sh

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+mkdir -p ~/.streamlit/
+echo "\
+[server]\n\
+port = $PORT\n\
+enableCORS = false\n\
+headless = true\n\
+\n\
+" > ~/.streamlit/config.toml