Skip to main content

Data extraction SDK for Playwright 🐒🍌

Project description

Tarsier Monkey

🦍 Harambe Web extraction SDK 🦍

Harambe

Harambe is the extraction SDK for Reworkd. It provides a simple interface for interacting with the web. It provides a unified interface and runtime for both manual and automatically created web extractors



Setup and Installation

To install Harambe, clone the repository and install the requirements. All requirements are managed via poetry.

git clone https://github.com/reworkd/harambe.git
poetry install

Example Scraper

Generally scrapers come in two types, listing and detail scrapers. Listing scrapers are used to collect a list of items to scrape. Detail scrapers are used to scrape the details of a single item.

If all the items that you want to scrape are available on a single page, then you can use a detail scraper to scrape all the items. If the items are spread across multiple pages, then you will need to use a listing scraper to collect the items and then use a detail scraper to scrape the details of each item.

ALL scrapers must be decorated with SDK.scraper. This decorator registers the scraper with the SDK and provides the SDK with the necessary information to run the scraper.

Detail Only Scraper

Shown below is an example detail scraper. The context parameter is used to pass data from the listing scraper to the detail scraper. In this example, the context parameter is used to pass the phone

import asyncio
import math
import re
from typing import Any
from playwright.async_api import Page
from harambe import SDK, Schemas
from harambe import PlaywrightUtils as Pu

@SDK.scraper(
    domain="https://food.kp.gov.pk",
    stage="detail",
)
async def scrape(sdk: SDK, url: str, *args: Any, **kwargs: Any) -> None:
    page: Page = sdk.page
    await page.goto(url)
    await page.wait_for_selector("#main_content a")
    cards = await page.query_selector_all("#main_content a")
    for card in cards:
        title = await card.inner_text()
        href = await card.get_attribute("href")
        if title and href:
            await sdk.save_data(
                {
                    "title": title,
                    "document_url": href,
                }
            )


if __name__ == "__main__":
    asyncio.run(
        SDK.run(
            scrape,
            "https://food.kp.gov.pk/page/rules_and_regulations",
            schema={},
        )
    )

Listing Scraper

Shown below is an example listing scraper. Use SDK.enqueue to to add urls that will need be scraped by the detail scraper. The context parameter is used to pass data from the listing scraper to the detail scraper.

import asyncio
import math
import re
from typing import Any
from playwright.async_api import Page
from harambe import SDK
from harambe import PlaywrightUtils as Pu

@SDK.scraper(
    domain="https://kpcode.kp.gov.pk",
    stage="listing",
)
async def listing_scrape(sdk: SDK, url: str, *args: Any, **kwargs: Any) -> None:
    page: Page = sdk.page
    await page.wait_for_selector(".artlist a")
    docs = await page.query_selector_all(".artlist a")
    for doc in docs:
        href = await doc.get_attribute("href")
        await sdk.enqueue(href)

    async def pager():
        next_page_element = await page.query_selector("li[title='Next'] > a")
        return next_page_element

    await sdk.paginate(pager)


@SDK.scraper(
    domain="https://kpcode.kp.gov.pk",
    stage="detail",
)
async def detail_scrape(sdk: SDK, url: str, *args: Any, **kwargs: Any) -> None:
    page: Page = sdk.page
    await page.wait_for_selector(".header_h2")
    title = await Pu.get_text(page, ".header_h2")
    link = await Pu.get_link(page, "a[href*=pdf]")
    await sdk.save_data({"title": title, "document_url ": link})


if __name__ == "__main__":
    asyncio.run(
        SDK.run(
            listing_scrape,
            "https://kpcode.kp.gov.pk/homepage/list_all_law_and_rule/879351",
            headless=False,
            schema={},
        )
    )
    asyncio.run(SDK.run_from_file(detail_scrape, schema={}))

Using Cache

The code below is an example detail scraper that relies on HAR cache that it creates during initial run, subsequently using it as source of data to improve speed and consume less bandwidth.

import asyncio
import os.path
from typing import Any

from playwright.async_api import Page

from harambe import SDK
from harambe import PlaywrightUtils as Pu

HAR_FILE_PATH = "bananas.har"
SELECTORS = {
    "last_page": "",
    "list_view": "//div[@class='et_pb_blurb_content']",
    "name": "//h4/*[self::span or self::a]",
    "fax": ">Fax.*?strong>(.*?)<br>",
    # etc...
}


async def setup(sdk: SDK) -> None:
    page: Page = sdk.page

    already_cached = os.path.isfile(HAR_FILE_PATH)

    if already_cached:
        await page.route_from_har(HAR_FILE_PATH, not_found="fallback")
    else:
        await page.route_from_har(HAR_FILE_PATH, not_found="fallback", update=True)


# Annotation registers the scraper with the SDK
@SDK.scraper(domain="https://apprhs.org/our-locations/", stage="detail")
async def scrape(sdk: SDK, url: str, *args: Any, **kwargs: Any) -> None:
    page: Page = sdk.page

    locations = await page.locator(SELECTORS["list_view"]).all()
    for location in locations:
        # Save the data to the database or file
        await sdk.save_data(
            {
                "name": await Pu.get_text(location, SELECTORS["name"]),
                "fax": await Pu.parse_by_regex(location, SELECTORS["fax"]),
                # etc...
            }
        )


if __name__ == "__main__":
    asyncio.run(SDK.run(scrape, "https://apprhs.org/our-locations/", setup=setup , schema= {}))

Running a Scraper

You can use poetry to run a scraper. The run command takes the scraper function and the url to scrape. The run_from_file command takes the scraper function and the path to the file containing the urls to scrape.

poetry run python <path_to_your_file>

Happy extraction! 🦍

Project details


Release history Release notifications | RSS feed

Download files

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

Source Distribution

harambe_sdk-0.28.10.tar.gz (26.9 kB view details)

Uploaded Source

Built Distribution

harambe_sdk-0.28.10-py3-none-any.whl (34.1 kB view details)

Uploaded Python 3

File details

Details for the file harambe_sdk-0.28.10.tar.gz.

File metadata

  • Download URL: harambe_sdk-0.28.10.tar.gz
  • Upload date:
  • Size: 26.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.6.1 CPython/3.12.7 Linux/6.5.0-1025-azure

File hashes

Hashes for harambe_sdk-0.28.10.tar.gz
Algorithm Hash digest
SHA256 5991343d680b753ce56f9e2d8096cc6f5ffcd6e2b1053e184df0032ffb9c6023
MD5 6433f185b81a6f411b1bc3ba905eb1ea
BLAKE2b-256 be3414a0d6ad9caa4063fa6d403bb4ed155441097d4ccd72b5819d2de1b6fa0f

See more details on using hashes here.

File details

Details for the file harambe_sdk-0.28.10-py3-none-any.whl.

File metadata

  • Download URL: harambe_sdk-0.28.10-py3-none-any.whl
  • Upload date:
  • Size: 34.1 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.6.1 CPython/3.12.7 Linux/6.5.0-1025-azure

File hashes

Hashes for harambe_sdk-0.28.10-py3-none-any.whl
Algorithm Hash digest
SHA256 dcd1d3f177873e8b357e37ab49e6aa3ebf194dc2345a0a6edc4783e230c70894
MD5 165bd69e691eca5e6490b1068d8c4002
BLAKE2b-256 d1e01e0426bdadbbf23fd25a4445088d3d9ee6e359113ffd36161b41286ddb62

See more details on using hashes here.

Supported by

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