athlinks-races 0.0.4

Web scraper for race results hosted on Athlinks.

athlinks_races: web scraper for race results hosted on Athlinks

NOTE

This is a fork of the original scrapy-athlinks. I decided to take over as I want to add features that were not originally available on the project.

Introduction

athlinks_races provides the RaceSpider class.

This spider crawls through all results pages from a race hosted on athlinks.com, building and following links to each athlete's individual results page, where it collects their split data. It also collects some metadata about the race itself.

By default, the spider returns one race metadata object (RaceItem), and one

AthleteItem per participant. Each AthleteItem consists of some basic athlete info and a list of RaceSplitItem containing data from each split they recorded.

How to use this package

Option 1: In python scripts

Scrapy can be operated entirely from python scripts. See the scrapy documentation for more info.

Installation

The package is available on PyPi and can be installed with pip:

python -m venv `$HOME/virtualenv/athlinks_races/`
. $HOME/virtualenv/athlinks_races/bin/activate
pip install athlinks_races

Example usage

A demo script is included in this repo.

"""
Demonstrate the available classes.
You can run as python athlinks_races/demo.py
"""
from scrapy.crawler import CrawlerProcess
from athlinks_races import RaceSpider, AthleteItem, RaceItem


def main():
    # Make settings for two separate output files: one for athlete data,
    # one for race metadata.
    settings = {
        'FEEDS': {
            # Athlete data. Inside this file will be a list of dicts containing
            # data about each athlete's race and splits.
            'athletes.json': {
                'format': 'json',
                'overwrite': True,
                'item_classes': [AthleteItem],
            },
            # Race metadata. Inside this file will be a list with a single dict
            # containing info about the race itself.
            'metadata.json': {
                'format': 'json',
                'overwrite': True,
                'item_classes': [RaceItem],
            },
        }
    }
    process = CrawlerProcess(settings=settings)

    # Crawl results for the 2022 Leadville Trail 100 Run
    process.crawl(RaceSpider, 'https://www.athlinks.com/event/33913/results/Event/1018673/')
    process.start()


if __name__ == "__main__":
    main()

If you do a pip install --editable .[lint,dev] then you can run as

athlinks_cli

Then you can build the wheelhouse to install locally if needed:

python -m build .

Option 2: Command line

Alternatively, you may clone this repo for use like a typical Scrapy project that you might create on your own.

Installation

python -m venv `$HOME/virtualenv/athlink_races`
. $HOME/virtualenv/athlink_races/bin/activate
git clone https://github.com/josevnz/athlinks-races
cd athlink-races
python install --editable .[lint,dev]

Example usage

Run a RaceSpider, few races with different years:

cd athlinks_races
scrapy crawl race -a url=https://www.athlinks.com/event/33913/results/Event/1018673 -O $HOME/1018673.json
scrapy crawl race -a url=https://www.athlinks.com/event/382111/results/Event/1093108 -O $HOME/1093108.json
scrapy crawl race -a url=https://www.athlinks.com/event/382111/results/Event/1062909 -O $HOME/1093108.json

Dependencies

All that is required is Scrapy (and its dependencies).

Testing

. $HOME/virtualenv/athlink_races/bin/activate
pytest tests/*.py

License

This project is licensed under the MIT License. See LICENSE file for details.

Contact

You can get in touch here:

• GitHub: https://github.com/josevnz

Original Author

If you want to take a look at the original project. He is not in charge of this forked version.

• GitHub: github.com/aaron-schroeder