472 lines
15 KiB
Python
Executable file
472 lines
15 KiB
Python
Executable file
#!/usr/bin/env python3
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import json
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import re
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import sys
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from dataclasses import asdict
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import backoff
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import requests
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from bs4 import BeautifulSoup, Tag
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from .models import (
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ContestListResult,
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ContestSummary,
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MetadataResult,
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ProblemSummary,
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TestCase,
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TestsResult,
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)
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def normalize_category_name(category_name: str) -> str:
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return category_name.lower().replace(" ", "_").replace("&", "and")
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def denormalize_category_name(category_id: str) -> str:
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category_map = {
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"introductory_problems": "Introductory Problems",
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"sorting_and_searching": "Sorting and Searching",
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"dynamic_programming": "Dynamic Programming",
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"graph_algorithms": "Graph Algorithms",
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"range_queries": "Range Queries",
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"tree_algorithms": "Tree Algorithms",
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"mathematics": "Mathematics",
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"string_algorithms": "String Algorithms",
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"geometry": "Geometry",
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"advanced_techniques": "Advanced Techniques",
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}
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return category_map.get(category_id, category_id.replace("_", " ").title())
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@backoff.on_exception(
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backoff.expo,
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(requests.exceptions.RequestException, requests.exceptions.HTTPError),
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max_tries=4,
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jitter=backoff.random_jitter,
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on_backoff=lambda details: print(
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f"Request failed (attempt {details['tries']}), retrying in {details['wait']:.1f}s: {details['exception']}",
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file=sys.stderr,
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),
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)
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@backoff.on_predicate(
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backoff.expo,
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lambda response: response.status_code == 429,
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max_tries=4,
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jitter=backoff.random_jitter,
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on_backoff=lambda details: print(
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f"Rate limited, retrying in {details['wait']:.1f}s", file=sys.stderr
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),
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)
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def make_request(url: str, headers: dict) -> requests.Response:
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response = requests.get(url, headers=headers, timeout=10)
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response.raise_for_status()
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return response
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def scrape_category_problems(category_id: str) -> list[ProblemSummary]:
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category_name = denormalize_category_name(category_id)
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try:
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problemset_url = "https://cses.fi/problemset/"
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headers = {
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"User-Agent": "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36"
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}
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response = make_request(problemset_url, headers)
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soup = BeautifulSoup(response.text, "html.parser")
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current_category = None
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problems = []
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target_found = False
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for element in soup.find_all(["h1", "h2", "ul"]):
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if not isinstance(element, Tag):
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continue
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if element.name in ["h1", "h2"]:
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text = element.get_text(strip=True)
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if not text or text.startswith("CSES") or text == "CSES Problem Set":
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continue
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if target_found and current_category != text:
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break
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current_category = text
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if text.lower() == category_name.lower():
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target_found = True
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elif element.name == "ul" and current_category and target_found:
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problem_links = element.find_all(
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"a", href=lambda x: x and "/problemset/task/" in x
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)
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for link in problem_links:
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href = link.get("href", "")
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if not href:
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continue
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problem_id = href.split("/")[-1]
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problem_name = link.get_text(strip=True)
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if not problem_id.isdigit() or not problem_name:
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continue
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problems.append(ProblemSummary(id=problem_id, name=problem_name))
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problems.sort(key=lambda x: int(x.id))
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return problems
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except Exception as e:
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print(f"Failed to scrape CSES category {category_id}: {e}", file=sys.stderr)
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return []
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def parse_problem_url(problem_input: str) -> str | None:
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if problem_input.startswith("https://cses.fi/problemset/task/"):
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return problem_input
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elif problem_input.isdigit():
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return f"https://cses.fi/problemset/task/{problem_input}"
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return None
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def extract_problem_limits(soup: BeautifulSoup) -> tuple[int, float]:
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timeout_ms = None
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memory_mb = None
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constraints_ul = soup.find("ul", class_="task-constraints")
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if not constraints_ul or not isinstance(constraints_ul, Tag):
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raise ValueError("Could not find task-constraints section")
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for li in constraints_ul.find_all("li"):
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text = li.get_text()
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if "Time limit:" in text:
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match = re.search(r"Time limit:\s*(\d+(?:\.\d+)?)\s*s", text)
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if match:
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seconds = float(match.group(1))
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timeout_ms = int(seconds * 1000)
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if "Memory limit:" in text:
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match = re.search(r"Memory limit:\s*(\d+)\s*MB", text)
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if match:
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memory_mb = float(match.group(1))
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if timeout_ms is None:
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raise ValueError("Could not find valid timeout in task-constraints section")
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if memory_mb is None:
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raise ValueError(
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"Could not find valid memory limit in task-constraints section"
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)
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return timeout_ms, memory_mb
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def scrape_categories() -> list[ContestSummary]:
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try:
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headers = {
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"User-Agent": "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36"
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}
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response = make_request("https://cses.fi/problemset/", headers)
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soup = BeautifulSoup(response.text, "html.parser")
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categories = []
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for h2 in soup.find_all("h2"):
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category_name = h2.get_text().strip()
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if category_name == "General":
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continue
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category_id = normalize_category_name(category_name)
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display_name = category_name
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categories.append(
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ContestSummary(
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id=category_id, name=category_name, display_name=display_name
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)
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)
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return categories
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except Exception as e:
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print(f"Failed to scrape CSES categories: {e}", file=sys.stderr)
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return []
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def process_problem_element(
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element,
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current_category: str | None,
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all_categories: dict[str, list[ProblemSummary]],
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) -> str | None:
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if element.name == "h1":
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category_name = element.get_text().strip()
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if category_name not in all_categories:
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all_categories[category_name] = []
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return category_name
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if element.name != "a" or "/problemset/task/" not in element.get("href", ""):
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return current_category
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href = element.get("href", "")
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if not href:
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return current_category
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problem_id = href.split("/")[-1]
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problem_name = element.get_text(strip=True)
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if not (problem_id.isdigit() and problem_name and current_category):
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return current_category
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problem = ProblemSummary(id=problem_id, name=problem_name)
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all_categories[current_category].append(problem)
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return current_category
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def scrape_all_problems() -> dict[str, list[ProblemSummary]]:
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try:
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problemset_url = "https://cses.fi/problemset/"
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headers = {
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"User-Agent": "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36"
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}
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response = requests.get(problemset_url, headers=headers, timeout=10)
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response.raise_for_status()
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soup = BeautifulSoup(response.text, "html.parser")
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all_categories: dict[str, list[ProblemSummary]] = {}
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current_category = None
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for element in soup.find_all(["h1", "h2", "ul"]):
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if not isinstance(element, Tag):
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continue
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if element.name in ["h1", "h2"]:
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text = element.get_text(strip=True)
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if text and not text.startswith("CSES") and text != "CSES Problem Set":
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current_category = text
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if current_category not in all_categories:
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all_categories[current_category] = []
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print(f"Found category: {current_category}", file=sys.stderr)
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elif element.name == "ul" and current_category:
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problem_links = element.find_all(
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"a", href=lambda x: x and "/problemset/task/" in x
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)
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for link in problem_links:
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href = link.get("href", "")
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if href:
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problem_id = href.split("/")[-1]
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problem_name = link.get_text(strip=True)
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if problem_id.isdigit() and problem_name:
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problem = ProblemSummary(id=problem_id, name=problem_name)
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all_categories[current_category].append(problem)
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for category in all_categories:
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all_categories[category].sort(key=lambda x: int(x.id))
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print(
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f"Found {len(all_categories)} categories with {sum(len(probs) for probs in all_categories.values())} problems",
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file=sys.stderr,
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)
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return all_categories
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except Exception as e:
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print(f"Failed to scrape CSES problems: {e}", file=sys.stderr)
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return {}
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def extract_example_test_case(soup) -> tuple[str, str] | None:
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example_header = soup.find("h1", string="Example")
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if not example_header:
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return None
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current = example_header.find_next_sibling()
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input_text = None
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output_text = None
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while current:
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if current.name == "p" and "Input:" in current.get_text():
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input_pre = current.find_next_sibling("pre")
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if input_pre:
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input_text = input_pre.get_text().strip()
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elif current.name == "p" and "Output:" in current.get_text():
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output_pre = current.find_next_sibling("pre")
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if output_pre:
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output_text = output_pre.get_text().strip()
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break
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current = current.find_next_sibling()
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if not input_text or not output_text:
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return None
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return (input_text, output_text)
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def scrape(url: str) -> list[TestCase]:
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try:
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headers = {
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"User-Agent": "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36"
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}
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response = make_request(url, headers)
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soup = BeautifulSoup(response.text, "html.parser")
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test_case = extract_example_test_case(soup)
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if not test_case:
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return []
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input_text, output_text = test_case
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return [TestCase(input=input_text, expected=output_text)]
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except Exception as e:
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print(f"Error scraping CSES: {e}", file=sys.stderr)
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return []
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def main() -> None:
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if len(sys.argv) < 2:
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result = MetadataResult(
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success=False,
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error="Usage: cses.py metadata <category_id> OR cses.py tests <category> <problem_id> OR cses.py contests",
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)
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print(json.dumps(asdict(result)))
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sys.exit(1)
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mode: str = sys.argv[1]
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if mode == "metadata":
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if len(sys.argv) != 3:
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result = MetadataResult(
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success=False,
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error="Usage: cses.py metadata <category_id>",
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)
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print(json.dumps(asdict(result)))
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sys.exit(1)
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category_id = sys.argv[2]
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problems = scrape_category_problems(category_id)
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if not problems:
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result = MetadataResult(
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success=False,
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error=f"No problems found for category: {category_id}",
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)
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print(json.dumps(asdict(result)))
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return
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result = MetadataResult(success=True, error="", problems=problems)
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print(json.dumps(asdict(result)))
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elif mode == "tests":
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if len(sys.argv) != 4:
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tests_result = TestsResult(
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success=False,
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error="Usage: cses.py tests <category> <problem_id>",
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problem_id="",
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url="",
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tests=[],
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timeout_ms=0,
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memory_mb=0,
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)
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print(json.dumps(asdict(tests_result)))
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sys.exit(1)
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problem_input: str = sys.argv[3]
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url: str | None = parse_problem_url(problem_input)
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if not url:
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tests_result = TestsResult(
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success=False,
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error=f"Invalid problem input: {problem_input}. Use either problem ID (e.g., 1068) or full URL",
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problem_id=problem_input if problem_input.isdigit() else "",
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url="",
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tests=[],
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timeout_ms=0,
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memory_mb=0,
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)
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print(json.dumps(asdict(tests_result)))
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sys.exit(1)
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tests: list[TestCase] = scrape(url)
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problem_id: str = (
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problem_input if problem_input.isdigit() else problem_input.split("/")[-1]
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)
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try:
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headers = {
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"User-Agent": "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36"
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}
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response = requests.get(url, headers=headers, timeout=10)
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response.raise_for_status()
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soup = BeautifulSoup(response.text, "html.parser")
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timeout_ms, memory_mb = extract_problem_limits(soup)
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except Exception as e:
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tests_result = TestsResult(
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success=False,
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error=f"Failed to extract constraints: {e}",
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problem_id=problem_id,
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url=url,
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tests=[],
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timeout_ms=0,
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memory_mb=0,
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)
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print(json.dumps(asdict(tests_result)))
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sys.exit(1)
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if not tests:
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tests_result = TestsResult(
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success=False,
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error=f"No tests found for {problem_input}",
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problem_id=problem_id,
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url=url,
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tests=[],
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timeout_ms=timeout_ms,
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memory_mb=memory_mb,
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)
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print(json.dumps(asdict(tests_result)))
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sys.exit(1)
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test_cases = tests
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tests_result = TestsResult(
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success=True,
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error="",
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problem_id=problem_id,
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url=url,
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tests=test_cases,
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timeout_ms=timeout_ms,
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memory_mb=memory_mb,
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)
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print(json.dumps(asdict(tests_result)))
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elif mode == "contests":
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if len(sys.argv) != 2:
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contest_result = ContestListResult(
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success=False, error="Usage: cses.py contests"
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)
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print(json.dumps(asdict(contest_result)))
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sys.exit(1)
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categories = scrape_categories()
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if not categories:
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contest_result = ContestListResult(success=False, error="No contests found")
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print(json.dumps(asdict(contest_result)))
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sys.exit(1)
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contest_result = ContestListResult(success=True, error="", contests=categories)
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print(json.dumps(asdict(contest_result)))
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else:
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result = MetadataResult(
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success=False,
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error=f"Unknown mode: {mode}. Use 'metadata <category>', 'tests <category> <problem_id>', or 'contests'",
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)
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print(json.dumps(asdict(result)))
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sys.exit(1)
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if __name__ == "__main__":
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main()
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