diff --git a/Web_app/movie_reviews.csv b/Web_app/movie_reviews.csv new file mode 100644 index 00000000..3d65f364 --- /dev/null +++ b/Web_app/movie_reviews.csv @@ -0,0 +1,2 @@ +Name,Movie,Review + diff --git a/Web_app/pages/API_Documentation.py b/Web_app/pages/API_Documentation.py new file mode 100644 index 00000000..66dac2dd --- /dev/null +++ b/Web_app/pages/API_Documentation.py @@ -0,0 +1,187 @@ +import streamlit as st + +st.subheader(" API Documentation", divider="rainbow") +# Custom CSS for styling +st.markdown( + """ + +""", + unsafe_allow_html=True, +) + +# API Product Overview +st.subheader("πŸ” API Product Overview") +st.write( + "The IMDb API on AWS Data Exchange offers a GraphQL-based approach, enabling efficient data access for movie and TV series metadata, " + "ratings, and box office data in real-time. It provides a streamlined JSON structure and single URL access for reduced API calls." +) + +# Benefits +st.subheader("🌟 Key Benefits") +st.markdown( + """ + - **One Call, All Data**: Access all data via a single URL. + - **Flexible Queries**: Request only the specific fields you need, minimizing data over-fetching. + - **Real-time Updates**: Receive IMDb’s latest data without delay. + - **Multiple Entities**: Query multiple titles/names simultaneously. + """, + unsafe_allow_html=True, +) + +# Getting Access to the API +st.subheader("πŸ”‘ Getting Access to the API") +st.write( + "To access the IMDb API, you need an AWS account and AWS Access Keys. Follow these steps to set up your access." +) +st.markdown( + """ + 1. **Create an AWS Account**: The IMDb API is available through AWS Data Exchange. + 2. **Obtain AWS Access Keys**: Generate your keys for API authentication. + 3. **Enable Cost Explorer (Optional)**: View your usage and cost in AWS Cost Explorer. + """, + unsafe_allow_html=True, +) + +# Authentication and API Key +st.subheader("πŸ”’ Authentication and API Key") +st.write( + "For API calls, the `x-api-key` header must include your API Key. Authenticate requests using AWS credentials in one of the following ways." +) + +# Code Snippet for AWS CLI +st.markdown( + """ + **Example API Call (AWS CLI)**: + """, + unsafe_allow_html=True, +) +st.code( + """ +aws dataexchange send-api-asset \\ +--data-set-id \\ +--revision-id \\ +--asset-id \\ +--request-headers "{ 'x-api-key': ''}" \\ +--region us-east-1 \\ +--body "{ 'query': '{ title(id: \"tt0120338\") { ratingsSummary { aggregateRating voteCount } } }' }" + """, + language="bash", +) + +# Sample GraphQL Query +st.subheader("πŸ’» Sample Query") +st.write("Here’s a sample GraphQL query to retrieve the IMDb rating for *Titanic*:") + +st.markdown( + """ +
+{ + title(id: "tt0120338") { + ratingsSummary { + aggregateRating + voteCount + } + } +} +
+""", + unsafe_allow_html=True, +) + +# Response Example +st.subheader("πŸ“Š Sample API Response") +st.write('{\n "data": {\n "title": {\n "ratingsSummary": {') +st.write(' "aggregateRating": 7.9,\n "voteCount": 1133828') +st.write(" }\n }\n }\n}") + +# Additional Code Snippets +st.subheader("πŸ“œ Additional Code Snippets") + +# Code Snippet for Postman Request +st.write("**Making Requests via Postman**") +st.markdown( + """ +1. **Set Method**: Use `POST` method. +2. **Request URL**: `https://api-fulfill.dataexchange.us-east-1.amazonaws.com/v1` +3. **Headers**: + - `Content-Type`: `application/json` + - `x-api-key`: `` +4. **Body (GraphQL Query)**: + ```graphql + { + title(id: "tt0120338") { + ratingsSummary { + aggregateRating + voteCount + } + } + } + ``` + """, + unsafe_allow_html=True, +) + +# Code Snippet for Python API Call +st.write("**Python Code to Make an API Call**") +st.code( + """ +import requests + +url = "https://api-fulfill.dataexchange.us-east-1.amazonaws.com/v1" +headers = { + "x-api-key": "", + "Content-Type": "application/json" +} +query = ''' +{ + title(id: "tt0120338") { + ratingsSummary { + aggregateRating + voteCount + } + } +} +''' +response = requests.post(url, headers=headers, data=query) +print(response.json()) +""", + language="python", +) + +# Example Use Cases +st.subheader("πŸ“„ Example Use Cases") +st.markdown( + """ +1. **Retrieve Ratings**: Query title ratings and vote counts. +2. **Box Office Data**: Access box office gross data. +3. **Cast and Crew**: Fetch top cast or crew details for movies and shows. +4. **Search Functionality**: Use keywords to find specific titles or names. +5. **Real-time Data Access**: Display data updates as they become available on IMDb. +""", + unsafe_allow_html=True, +) + +# Footer +st.markdown("---") +st.markdown( + "For further assistance, contact support at support@imdbapi.com", + unsafe_allow_html=True, +) diff --git a/Web_app/pages/ReviewSubmission.py b/Web_app/pages/ReviewSubmission.py new file mode 100644 index 00000000..e65a55e1 --- /dev/null +++ b/Web_app/pages/ReviewSubmission.py @@ -0,0 +1,131 @@ +import streamlit as st +import os +import pandas as pd + +# Set the path for storing the reviews +reviews_file = "movie_reviews.csv" + +# Initialize the reviews file if it doesn't exist +if not os.path.exists(reviews_file): + df = pd.DataFrame(columns=["Name", "Movie", "Review"]) + df.to_csv(reviews_file, index=False) + +# Read the existing reviews from the file +df = pd.read_csv(reviews_file) + +# Initialize session state for showing the review form +if "show_review_form" not in st.session_state: + st.session_state.show_review_form = False + +st.title("🎬 Submit Your Movie Review") + +st.markdown( + "
", + unsafe_allow_html=True, +) + +# Updated Custom CSS for Reddit-style reviews with dynamic sizing +st.markdown( + """ + + """, + unsafe_allow_html=True, +) + +# Toggle for review form visibility +show_review_form = st.checkbox( + "βž• Submit Review", value=st.session_state.show_review_form, key="review_checkbox" +) + +# Update session state based on checkbox +st.session_state.show_review_form = show_review_form + +# Form for submitting reviews +if st.session_state.show_review_form: + with st.form(key="review_form"): + name = st.text_input("Your Name") + movie_name = st.text_input("Movie Name") + review = st.text_area("Your Review", height=80) + submit_button = st.form_submit_button(label="Submit Review") + + if submit_button: + if name and movie_name and review: + new_review = pd.DataFrame( + { + "Name": [name], + "Movie": [movie_name], + "Review": [review], + } + ) + df = pd.concat([df, new_review], ignore_index=True) + df.to_csv(reviews_file, index=False) + st.success("Thank you for your review!") + st.session_state.show_review_form = False + st.rerun() + else: + st.error("Please fill in all fields before submitting.") + +# Display the reviews in a Reddit-style comment format +st.subheader("πŸ“œ Reviews") + +if not df.empty: + for index, row in df.iterrows(): + st.markdown( + f""" +
+
+ {row['Name']} + {row['Movie']} +
+
{row['Review']}
+
+ """, + unsafe_allow_html=True, + ) +else: + st.write("No reviews yet. Be the first to leave one!")