add cli. add pdf export. add solutions.
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build/
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*.swp
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.venv/
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__pycache__/
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PYTHON=.venv/bin/python
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SET=neetcode150
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.PHONY: build
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build:
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$(PYTHON) src build --problem_set $(SET) --out problems --out solutions
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pandoc build/problems-$(SET).md --pdf-engine=xelatex -o dist/problems-$(SET).pdf
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pandoc build/solutions-$(SET).md --pdf-engine=xelatex -o dist/solutions-$(SET).pdf
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*
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*/
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!.gitignore
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*
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*/
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!.gitignore
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python-leetcode==1.2.1
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tqdm
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python-dotenv
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click
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markdownify
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pandas
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.env
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import click
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from dotenv import load_dotenv
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import neet
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@click.group()
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def cli():
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"""run the leetcode export commands"""
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if __name__ == "__main__":
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load_dotenv()
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cli.add_command(neet.build)
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cli()
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import argparse
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import csv
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import functools
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import itertools
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import json
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import logging
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import math
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import os
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import time
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from typing import Callable, List, Tuple, Type
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from pathlib import Path
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# https://github.com/prius/python-leetcode
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import leetcode.api.default_api # type: ignore
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@ -21,6 +18,7 @@ import leetcode.models.graphql_question_detail # type: ignore
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import urllib3 # type: ignore
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from tqdm import tqdm # type: ignore
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logging.getLogger().setLevel(logging.INFO)
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@ -134,12 +132,12 @@ def _get_problems_data_page(
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title
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titleSlug
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categoryTitle
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frequency
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isPaidOnly
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topicTags {
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name
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slug
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}
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difficulty
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content
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companyTagStats
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}
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}
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@ -162,34 +160,17 @@ def _get_problems_data_page(
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return data
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def parse_args() -> argparse.Namespace:
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"""
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Parse command line arguments for the script
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"""
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parser = argparse.ArgumentParser(
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description="Fetch leetcode problems and output them to a CSV file"
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)
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parser.add_argument(
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"--batch-size",
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type=int,
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help="Fetch this many problems at once (set less if leetcode times out)",
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default=300,
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)
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parser.add_argument(
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"--output",
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type=str,
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help="Write output to file",
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default="problems.csv",
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)
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args = parser.parse_args()
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return args
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def _get_problems_data(
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page_size: int,
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def get_problems(
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page_size: int = 300,
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) -> List[leetcode.models.graphql_question_detail.GraphqlQuestionDetail]:
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import pickle
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pickled = Path(os.getenv("LEETCODE_DATA_PATH")) / 'problems.pkl'
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if pickled.exists():
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with open(pickled, 'rb') as f:
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problems = pickle.load(f)
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return problems
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problem_count = _get_problems_count()
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start = 0
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@ -207,48 +188,7 @@ def _get_problems_data(
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data = _get_problems_data_page(start, page_size, page)
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problems.extend(data)
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with open(pickled, 'wb') as f:
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out = [p.to_dict() for p in problems]
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pickle.dump(out, f, pickle.HIGHEST_PROTOCOL)
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return problems
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def main() -> None:
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args = parse_args()
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problems_data = _get_problems_data(args.batch_size)
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csv_header = [
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"Question id",
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"title",
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"slug",
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"category",
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"frequency",
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"is_paid",
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"topics",
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"companies",
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]
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with open(args.output, "w") as csv_file:
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csv_writer = csv.writer(csv_file, delimiter=";")
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csv_writer.writerow(csv_header)
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for problem_data in problems_data:
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csv_writer.writerow(
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[
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problem_data.question_frontend_id,
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problem_data.title,
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problem_data.title_slug,
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problem_data.category_title,
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problem_data.frequency,
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problem_data.is_paid_only,
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",".join([d.slug for d in problem_data.topic_tags]),
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",".join(
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{
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d["slug"]
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for d in itertools.chain(
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*json.loads(problem_data.company_tag_stats).values()
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)
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}
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),
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]
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)
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if __name__ == "__main__":
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main()
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from download import get_problems
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import pandas as pd
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import json
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from pathlib import Path
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from markdownify import markdownify as md
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import click
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import re
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import textwrap
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import os
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import template
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def get_data(series):
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def as_markdown(content):
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content = md(content or "", strip=['strong'])
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long_lines = re.findall(r".*(Explanation.*)", content)
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for l in long_lines:
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content = content.replace(l, textwrap.fill(l, 80))
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return content
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def get_solution(problem_id):
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p = Path(os.getenv("LEETCODE_DATA_PATH")) / 'solutions'
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matches = list(p.glob(f"{int(problem_id):04d}*.py"))
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if not matches:
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return ""
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p = matches[0]
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with open(p, 'r') as f:
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solution = f.read()
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return solution
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open_path = Path(os.getenv('LEETCODE_DATA_PATH')) / 'neetcode.json'
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with open(open_path, 'r') as f:
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neet = json.load(f)
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neet = pd.DataFrame(neet)
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problems = pd.DataFrame([d.to_dict() for d in get_problems()])
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neet['slug'] = neet.link.str.strip('/')
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del(neet['difficulty'])
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problems = pd.merge(problems, neet, left_on="title_slug", right_on="slug")
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problems['tags'] = problems.topic_tags.apply(lambda t: " | ".join([d.get('slug') for d in t]))
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problems['markdown'] = problems.content.apply(lambda c: as_markdown(c))
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problems.rename(columns={"question_frontend_id": "id"}, inplace=True)
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problems['solution'] = problems.id.apply(lambda i: get_solution(i))
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patterns = [
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"Arrays & Hashing"
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,"Two Pointers"
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,"Sliding Window"
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,"Stack"
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,"Binary Search"
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,"Linked List"
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,"Trees"
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,"Tries"
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,"Heap / Priority Queue"
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,"Backtracking"
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,"Graphs"
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,"Advanced Graphs"
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,"1-D Dynamic Programming"
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,"2-D Dynamic Programming"
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,"Greedy"
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,"Intervals"
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,"Math & Geometry"
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,"Bit Manipulation"
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]
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#patterns = pd.DataFrame(patterns, columns=['category'])
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problems = pd.merge(problems, pd.DataFrame(patterns, columns=['pattern']).reset_index(), on='pattern')
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problems = problems[(problems[series] == True) & (problems.premium != True)]
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return problems
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def save_solutions(data, save_to: Path, problem_set):
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out = template.get('main_title.md').render({"problem_set": problem_set})
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keys = ['title', 'slug', 'id', 'solution', 'pattern', 'difficulty', 'tags', 'index']
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number = 0
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total = len(data)
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grouped = data[keys].groupby(['index', 'pattern', 'difficulty'])
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for i, ((pattern_id, pattern, difficulty), group) in enumerate(grouped):
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out += template.get('pattern_title.md').render({"pattern": pattern, "difficulty":difficulty})
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page = template.get("solution.md")
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for j, problem in group.iterrows():
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number += 1
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problem = problem.to_dict()
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problem["total"] = total
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problem["number"] = number
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out += page.render(problem)
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with open(save_to, "w") as f:
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f.write(out)
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def save_problems(problems, save_to: Path, problem_set):
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keys = ['title', 'slug', 'id', 'markdown', 'pattern', 'difficulty', 'index']
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out = template.get('main_title.md').render({"problem_set": problem_set})
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number = 0
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grouped = problems[keys].groupby(['index', 'pattern', 'difficulty'])
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for i, ((pattern_id, pattern, difficulty), group) in enumerate(grouped):
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out += template.get('pattern_title.md').render({"pattern": pattern, "difficulty":difficulty})
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page = template.get("solution.md")
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for j, problem in group.iterrows():
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number += 1
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problem = problem.to_dict()
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problem["total"] = total
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problem["number"] = number
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out += page.render(problem)
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with open(save_to, "w") as f:
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f.write(out)
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@click.command("build")
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@click.option('-o', '--out', type=click.Choice(['problems', 'solutions']), multiple=True, default=['problems'])
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@click.option('--problem_set', default="neetcode150", type=click.Choice(['neetcode150', 'blind75', 'all']))
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def build(out, problem_set):
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data = get_data(problem_set)
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if 'problems' in out:
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save_to = Path(os.getenv("LEETCODE_BUILD_PATH")) / f'problems-{problem_set}.md'
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save_problems(data, save_to, problem_set)
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if 'solutions' in out:
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save_to = Path(os.getenv("LEETCODE_BUILD_PATH")) / f'solutions-{problem_set}.md'
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save_solutions(data, save_to, problem_set)
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print(f"saved: {save_to.absolute()}")
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import jinja2
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from pathlib import Path
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import os
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def get(name):
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templates_path =Path(os.getenv('LEETCODE_APP_PATH')) / 'templates/'
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templateLoader = jinja2.FileSystemLoader(searchpath=templates_path)
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templateEnv = jinja2.Environment(loader=templateLoader)
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template = templateEnv.get_template(name)
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return template
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---
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geometry: margin=2cm
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output: pdf_document
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---
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# LeetCode - {{problem_set}}
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\newpage
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# {{pattern}} - {{difficulty}}
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\newpage
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## {{id}} - {{title}} ({{number}}/{{len(total)}})
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*[https://leetcode.com/problems/{{slug}}](https://leetcode.com/problems/{{slug}})*
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---
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{{markdown}}
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\newpage
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## {{id}} - {{title}} ({{number}}/{{total}})
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*[https://leetcode.com/problems/{{slug}}](https://leetcode.com/problems/{{slug}})*
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---
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```
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{{solution}}
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```
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\newpage
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