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gracyvsralger

MIT - 2 239
895 (month) Feb 05 2023 1.33.0(3 months ago)
152 1 3 MIT
Dec 22 2019 1.1 thousand (month) 2.2.4(3 years ago)

Gracy is an API client library based on httpx that provides an extra stability layer with:

  • Retry logic
  • Logging
  • Connection throttling
  • Tracking/Middleware

In web scraping, Gracy can be a convenient tool for creating scraper based API clients.

ralger is a small web scraping framework for R based on rvest and xml2.

It's goal to simplify basic web scraping and it provides a convenient and easy to use API.

It offers functions for retrieving pages, parsing HTML using CSS selectors, automatic table parsing and auto link, title, image and paragraph extraction.

Example Use


# 0. Import
import asyncio
from typing import Awaitable
from gracy import BaseEndpoint, Gracy, GracyConfig, LogEvent, LogLevel

# 1. Define your endpoints
class PokeApiEndpoint(BaseEndpoint):
    GET_POKEMON = "/pokemon/{NAME}" # 👈 Put placeholders as needed

# 2. Define your Graceful API
class GracefulPokeAPI(Gracy[str]):
    class Config:  # type: ignore
        BASE_URL = "https://pokeapi.co/api/v2/" # 👈 Optional BASE_URL
        # 👇 Define settings to apply for every request
        SETTINGS = GracyConfig(
          log_request=LogEvent(LogLevel.DEBUG),
          log_response=LogEvent(LogLevel.INFO, "{URL} took {ELAPSED}"),
          parser={
            "default": lambda r: r.json()
          }
        )

    async def get_pokemon(self, name: str) -> Awaitable[dict]:
        return await self.get(PokeApiEndpoint.GET_POKEMON, {"NAME": name})

    # Note: since Gracy is based on httpx we can customized the used client with custom headers etc"
    def _create_client(self) -> httpx.AsyncClient:
        client = super()._create_client()
        client.headers = {"User-Agent": f"My Scraper"} 
        return client

pokeapi = GracefulPokeAPI()

async def main():
    try:
      pokemon = await pokeapi.get_pokemon("pikachu")
      print(pokemon)

    finally:
        pokeapi.report_status("rich")


asyncio.run(main())
library("ralger")

url <- "http://www.shanghairanking.com/rankings/arwu/2021"

# retrieve HTML and select elements using CSS selectors:
best_uni <- scrap(link = url, node = "a span", clean = TRUE)
head(best_uni, 5)
#>  [1] "Harvard University"
#>  [2] "Stanford University"
#>  [3] "University of Cambridge"
#>  [4] "Massachusetts Institute of Technology (MIT)"
#>  [5] "University of California, Berkeley"

# ralger can also parse HTML attributes
attributes <- attribute_scrap(
  link = "https://ropensci.org/",
  node = "a", # the a tag
  attr = "class" # getting the class attribute
)

head(attributes, 10) # NA values are a tags without a class attribute
#>  [1] "navbar-brand logo" "nav-link"          NA
#>  [4] NA                  NA                  "nav-link"
#>  [7] NA                  "nav-link"          NA
#> [10] NA
#

# ralger can automatically scrape tables:
data <- table_scrap(link ="https://www.boxofficemojo.com/chart/top_lifetime_gross/?area=XWW")

head(data)
#> # A tibble: 6 × 4
#>    Rank Title                                      `Lifetime Gross`  Year
#>   <int> <chr>                                      <chr>            <int>
#> 1     1 Avatar                                     $2,847,397,339    2009
#> 2     2 Avengers: Endgame                          $2,797,501,328    2019
#> 3     3 Titanic                                    $2,201,647,264    1997
#> 4     4 Star Wars: Episode VII - The Force Awakens $2,069,521,700    2015
#> 5     5 Avengers: Infinity War                     $2,048,359,754    2018
#> 6     6 Spider-Man: No Way Home                    $1,901,216,740    2021

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