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StatsScraper2.0.0

A simple CLI python web scraper that scrapes NBA player data from basketball-reference.org and allows players to be sorted by points, rebounds, and assists and displayed.

Installation

Use pip to install StatsScraper2.0.0

pip install StatsScraper2.0.0

Usage

Code excerpt from __main__.py

from StatsScraper import Scraper

scraper = Scraper()

result = scraper.find_player_by_name("Ivica Zubac")
print("Printing result\n")
for p in result:
    print(p)

sorted_points = scraper.sort_by_points("SG")
print("========Printing top scorers========\n")
for scores in sorted_points:
    print(scores[0], scores[1])

sorted_assists = scraper.sort_by_assists("PF")
print("\n\n\n=========Printing top 10 assisters========\n")
count = 0
for assists in sorted_assists:
    if(count >= 10):
        break
    print(assists[0], assists[1])
    count += 1

sorted_rebounds = scraper.sort_by_rebounds("PG", "SG")
print("\n\n\n=========Printing top 20 rebounders========\n")
count = 0
for rebounds in sorted_rebounds:
    if(count >= 20):
        break
    print(rebounds[0], rebounds[1])
    count += 1

Acknowledgment

Thank you to Oscar Sanchez’s article “Web Scraping NBA Stats” for part of the scraping code

License

MIT

Metadata

Release files for StatsScraper 1.0.0

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Source distribution (sdist)

Source distribution for StatsScraper 1.0.0
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Table of built distributions (wheels) for StatsScraper 1.0.0
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Total release size: 11.9 kB

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