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Python library for scraping data sources and creating readable deltas

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Python library for scraping data sources and creating readable deltas.

For background, see Scraping hurricane Irma.


This library allows you to define scrapers, which are objects that know how to retrieve information from a source (usually a web API, but scrapers can be written to operate against HTML or other formats) and persist that data somewhere as JSON.

When a scraper fetches fresh information it has the ability to compare that data to the old data and use the difference to create a human-readable message.

These capabilities can be combined with a git repository to create a commit log, with human-readable commit messages that accompany a machine-readable diff againts the generated JSON.

See disaster-scrapers and disaster-data for some examples of this pattern in action.

Basic usage

You can define new scrapers by subclassing DeltaScraper. Here's an example which scrapes a list of FEMA shelters.

class FemaShelters(DeltaScraper):
    url = ""
    owner = "simonw"
    repo = "disaster-data"
    filepath = "fema/shelters.json"

    record_key = "SHELTER_ID"
    noun = "shelter"

    def fetch_data(self):
        data = requests.get(self.url, timeout=10).json()
        return [feature["properties"] for feature in data["features"]]

    def display_record(self, record):
        display = []
            "  {SHELTER_NAME} in {CITY}, {STATE} ({SHELTER_STATUS})".format(**record)
        display.append("    population = {TOTAL_POPULATION}".format(**record))
        return "\n".join(display)

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