PetrFD is film database of top 1000 movies and its actors from http://www.csfd.cz
Welcome page with input field for search in movie and actors
When you click on "Search" button you will be redirected to Search result page
http://localhost:8080/
http://localhost:8080/search
Page with search results for Actors and Movies. Contains also link to search homepage.
List of Actors and Movies and links to /actor/{name} and /movie/{name} endpoints
http://localhost:8080/searchresultpage
Page contains movies where actor star
http://localhost:8080/actor/{name}
e.g. http://localhost:8080/actor/Tom%20Hanks
Page contains list of all actors in the movie
http://localhost:8080/movie/{name}
e.g. http://localhost:8080/movie/Forrest%20Gump
App is build on FASTAPI framework with four endpoints described above. Scrapers of http://csfd.cz content are in csfd_scraper.py file. Packages used aiohttp, requests, beautifulsoup. Top 1000 movies is scraped asynchronously and then each movie is scraped in single thread to avoid blocking/DDoS attack. Possible TODO - rewrite it to scrapy or make request in batches via aiohttp. Results from scraping are stored in actors.csv / movies.csv files where from they are loaded to sqlite3 database named petrfd.db.
DATA ARE ALREADY IN petrfd.db READY TO USE
File database.py contains all methods for loading movies and actors to db as well as for searching in db according to input. Actors and Movies are not changing on CSFD often so I commented out running scraper and loading data to db. Uncomment if you want fresh data.
Data extraction can be done in better&faster (asynchronous) way - with scrapy as well as data processing does not require middle step via .csv files. But I focus more on design FastAPI app its endpoints and sqlite query. Nature of this data is that they cannot be refreshed often.
App run on port 8080. Run commands, when current location is repository:
docker build -t petrfd:1.0 .
docker run -d -p 8080:8080 petrfd:1.0