Skip to main content

Academy Awards Scraper and Data processor

Project description

The OscarScrapper (1930-2021)

This is the final project for JEM207 Data Processing with Python made by Yann Aubineau and Samuel Božoň of Charles University.

The aim for our project is to scrape and process the historical data of the Academy Awards popularly known as the Oscars, and create a user friendly package with easy way to select categories and years which should be scraped We scrape from oscars.org website historical datas of every nominee and winner for the following 4 categories:

Best Picture (1927-2021) Best Director (1927-2021) Best Actor (1927-2021) Best Actress (1927-2021)

Each dataset would be indexed by year and category.

The sources used for the following datas are:

  • oscars.org
  • tmdb.com's API

Firstly we scrape the data for nominees and winners for each selected year for all the selected categories.

Then, we will use these datas to aks tmdb's API for more informations about the movie. However, given that there may be multiple films and persons with the same name, we are selecting from the API's response only relevant informations.

These are afterwards processed and added to our dataframe, which is later stored for the future use.

User can select categories and years in which he is interested through easy GUI. For each of his selection, new dataset stored in csv file is created, permitting easy creation of multiple datasets with different searches chosen by user.

To use the OscarScrapper, you can either download the repository and execute Package_OscarScrapper/src/Oscarscrapper_package/Oscarscrapper.py or use pip to download it as a package.

# Pypi
pip install OscarScrapper
from Oscarscrapper_package import Oscarscrapper

Scraper = Oscarscrapper.Oscar_Scraper()

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

OscarScrapper-1.3.tar.gz (12.9 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

OscarScrapper-1.3-py3-none-any.whl (13.3 kB view details)

Uploaded Python 3

File details

Details for the file OscarScrapper-1.3.tar.gz.

File metadata

  • Download URL: OscarScrapper-1.3.tar.gz
  • Upload date:
  • Size: 12.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.6.4 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.0 CPython/3.9.6

File hashes

Hashes for OscarScrapper-1.3.tar.gz
Algorithm Hash digest
SHA256 6175a2918b6db36769e5cb45c6bc800f5c7547d5b85e17691c4026e23c9c5de9
MD5 76dd07dbba72567166dcdf4a875eabc4
BLAKE2b-256 b2eb9fa58caed43edec5acd446fba4d2af02d110db4c6978d0c72dd0840f2998

See more details on using hashes here.

File details

Details for the file OscarScrapper-1.3-py3-none-any.whl.

File metadata

  • Download URL: OscarScrapper-1.3-py3-none-any.whl
  • Upload date:
  • Size: 13.3 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.6.4 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.0 CPython/3.9.6

File hashes

Hashes for OscarScrapper-1.3-py3-none-any.whl
Algorithm Hash digest
SHA256 a1317746d5bc88898d6bd42029b4812ff7ea7b2353682af9affdeaaaa1e3c42c
MD5 e05a6195d901cd84effc54859fd28753
BLAKE2b-256 5f0df123bb3281a07c9a7258ad938816f5f4d35a50ff18f9864b8b69c7867f71

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page