basketball_reference_web_scraper
zineb
| basketball_reference_web_scraper | zineb | |
|---|---|---|
| 2 | 2 | |
| 407 | 3 | |
| - | - | |
| 7.2 | 1.8 | |
| 7 days ago | about 1 year ago | |
| Python | HTML | |
| MIT License | MIT License |
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basketball_reference_web_scraper
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How often has a playoff team done what Dallas did yesterday?
Writing a web scraper is one of the most common beginner projects, and many already exist for Basketball Reference, ex: https://github.com/jaebradley/basketball_reference_web_scraper
zineb
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High profile web scrapper
I created a Web scrapper and I'm looking for some testing/critical thoughts on the project and eventually people who are interested in participating. You can take a look at it here Github.com
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Simple web scrapping project for machine learning & al. (Zineb)
I would love to get some feedback if possible. The project is available on Github and on PyPI. So don't forget to leave a star and watch for future improvements.
What are some alternatives?
nba-sql - :basketball: An application to build an NBA database backed by MySQL, Postgres, or SQLite
codeio - Simple platform to allow the creation of problems and the solving of the problems.
extractnet - A fork of Dragnet that also extract author, headline, date, keywords from context, as well as built in metadata extraction all in one package
soak-your-brain-elearning-app - An e-learning platform built in python (django)
py_webScraper - A simple web scraper using beautifulsoup and requests
facebook_page_scraper - Scrapes facebook's pages front end with no limitations & provides a feature to turn data into structured JSON or CSV
letterbox-stats - A web scraping application that retrieves the most viewed directors and actors of a Letterboxd user based on their watched movies. It also can compare the ratings of movies you and other Letterboxd user have seen.