179 lines
5.7 KiB
Python
179 lines
5.7 KiB
Python
import asyncio
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import json
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import os
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import os.path
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from typing import List
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import aiohttp
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from bs4 import BeautifulSoup, SoupStrainer, Tag
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from app.pipeline import Extractor as BaseExtractor
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from app.pipeline import Fetcher as BaseFetcher
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from app.pipeline import Pipeline as BasePipeline
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from app.types import Site
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# The number of coach listing pages we will at most iterate through. This number
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# was determined by going to chess.com/coaches?sortBy=alphabetical&page=1 and
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# traversing to the last page.
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MAX_PAGES = 64
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# How long to wait between a batch of network requests.
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SLEEP_SECS = 3
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class Fetcher(BaseFetcher):
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def __init__(self, session: aiohttp.ClientSession):
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super().__init__(site=Site.CHESSCOM, session=session)
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async def scrape_usernames(self, page_no: int) -> List[str] | None:
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if page_no > MAX_PAGES:
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return []
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print(f"{self.site.value}: Scraping page {page_no}/{MAX_PAGES}")
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filepath = self.path_page_file(page_no)
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try:
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with open(filepath, "r") as f:
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return [line.strip() for line in f.readlines()]
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except FileNotFoundError:
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pass
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if self.has_made_request:
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await asyncio.sleep(SLEEP_SECS)
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url = f"https://www.chess.com/coaches?sortBy=alphabetical&page={page_no}"
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response, status_code = await self.fetch(url)
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if response is None:
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return None # Skips this page.
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usernames = []
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soup = BeautifulSoup(response, "lxml")
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members = soup.find_all("a", class_="members-categories-username")
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for member in members:
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href = member.get("href")
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username = href[len("https://www.chess.com/member/") :]
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usernames.append(username)
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# Cache results.
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with open(filepath, "w") as f:
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for username in usernames:
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f.write(f"{username}\n")
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return usernames
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async def download_user_files(self, username: str) -> None:
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maybe_download = [
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(
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f"https://www.chess.com/member/{username}",
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self.path_coach_file(username, f"{username}.html"),
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),
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(
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f"https://www.chess.com/callback/member/activity/{username}?page=1",
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self.path_coach_file(username, "activity.json"),
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),
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(
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f"https://www.chess.com/callback/member/stats/{username}",
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self.path_coach_file(username, "stats.json"),
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),
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]
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to_download = []
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for d_url, d_filename in maybe_download:
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if os.path.isfile(d_filename):
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continue
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to_download.append((d_url, d_filename))
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if not to_download:
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return
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if self.has_made_request:
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await asyncio.sleep(SLEEP_SECS)
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await asyncio.gather(
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*[self._download_file(url=d[0], filename=d[1]) for d in to_download]
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)
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async def _download_file(self, url: str, filename: str) -> None:
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response, _unused_status = await self.fetch(url)
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if response is not None:
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with open(filename, "w") as f:
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f.write(response)
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def _profile_filter(elem: Tag | str | None, attrs={}) -> bool:
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if "profile-header-info" in attrs.get("class", ""):
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return True
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if "profile-card-info" in attrs.get("class", ""):
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return True
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return False
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class Extractor(BaseExtractor):
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def __init__(self, fetcher: BaseFetcher, username: str):
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super().__init__(fetcher, username)
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self.profile_soup = None
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try:
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filename = self.fetcher.path_coach_file(username, f"{username}.html")
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with open(filename, "r") as f:
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self.profile_soup = BeautifulSoup(
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f.read(), "lxml", parse_only=SoupStrainer(_profile_filter)
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)
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except FileNotFoundError:
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pass
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self.stats_json = {}
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try:
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filename = self.fetcher.path_coach_file(username, "stats.json")
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with open(filename, "r") as f:
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for s in json.load(f).get("stats", []):
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if "key" in s and "stats" in s:
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self.stats_json[s["key"]] = s["stats"]
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except FileNotFoundError:
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pass
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def get_name(self) -> str | None:
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if self.profile_soup is None:
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return None
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name = self.profile_soup.find("div", class_="profile-card-name")
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if not isinstance(name, Tag):
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return None
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return name.get_text().strip()
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def get_image_url(self) -> str | None:
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if self.profile_soup is None:
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return None
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div = self.profile_soup.find("div", class_="profile-header-avatar")
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if not isinstance(div, Tag):
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return None
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img = div.find("img")
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if not isinstance(img, Tag):
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return None
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src = img.get("src", "")
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if not isinstance(src, str):
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return None
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if "images.chesscomfiles.com" not in src:
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return None
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return src
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def get_languages(self) -> List[str] | None:
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# TODO: Extract using huggingface model.
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return None
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def get_rapid(self) -> int | None:
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return self.stats_json.get("rapid", {}).get("rating")
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def get_blitz(self) -> int | None:
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return self.stats_json.get("lightning", {}).get("rating")
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def get_bullet(self) -> int | None:
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return self.stats_json.get("bullet", {}).get("rating")
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class Pipeline(BasePipeline):
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def get_fetcher(self, session: aiohttp.ClientSession):
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return Fetcher(session)
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def get_extractor(self, fetcher: BaseFetcher, username: str):
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return Extractor(fetcher, username)
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