coach-scraper/app/chesscom.py

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