import pyutil as pyu
pyu.get_local_pyinfo()

print(pyu.ps2("python-dotenv"))

from typing import List

class Solution:
  def uniquePathsWithObstacles(self, obstacleGrid: List[List[int]]) -> int:
    m = len(obstacleGrid)
    n = len(obstacleGrid[0])
    # dp[i][j] := unique paths from (0, 0) to (i - 1, j - 1)
    dp …

import pyutil as pyu
pyu.get_local_pyinfo()

print(pyu.ps2("python-dotenv"))

from typing import List

class Solution:
  def scheduleCourse(self, courses: List[List[int]]) -> int:
    time = 0
    maxHeap = []

    for duration, lastDay in sorted(courses, key=lambda x: x[1]):
      heapq.heappush(maxHeap, -duration)
      time += duration
      # If …

import pyutil as pyu
pyu.get_local_pyinfo()

print(pyu.ps2("python-dotenv"))

from typing import List

class Solution:
  def smallestRange(self, nums: List[List[int]]) -> List[int]:
    minHeap = [(row[0], i, 0) for i, row in enumerate(nums)]
    heapq.heapify(minHeap)

    maxRange = max(row[0] for row …

import pyutil as pyu
pyu.get_local_pyinfo()

print(pyu.ps2("python-dotenv"))

from typing import List

class Solution:
  def judgeSquareSum(self, c: int) -> bool:
    l = 0
    r = int(sqrt(c))

    while l <= r:
      summ = l * l + r * r
      if summ == c:
        return True
      if summ < c:
        l …

import pyutil as pyu
pyu.get_local_pyinfo()

print(pyu.ps2("python-dotenv"))

from typing import List

class Solution:
  def findDerangement(self, n: int) -> int:
    kMod = 1_000_000_007

    @functools.lru_cache(None)
    def dp(i: int) -> int:
      if i == 0:
        return 1
      if i == 1:
        return 0
      return (i …

import pyutil as pyu
pyu.get_local_pyinfo()

print(pyu.ps2("python-dotenv"))

from typing import List

class Solution:
  def shoppingOffers(self, price: List[int], special: List[List[int]], needs: List[int]) -> int:
    def dfs(s: int) -> int:
      ans = 0
      for i, need in enumerate(needs):
        ans += need …

import pyutil as pyu
pyu.get_local_pyinfo()

print(pyu.ps2("python-dotenv"))

from typing import List

class Solution:
  def minPathSum(self, grid: List[List[int]]) -> int:
    m = len(grid)
    n = len(grid[0])

    for i in range(m):
      for j in range(n):
        if i > 0 and …

import pyutil as pyu
pyu.get_local_pyinfo()

print(pyu.ps2("python-dotenv"))

from typing import List

class Solution:
  def solveEquation(self, equation: str) -> str:
    def calculate(s: str) -> tuple:
      coefficient = 0
      constant = 0
      num = 0
      sign = 1

      for i, c in enumerate(s):
        if c.isdigit():
          num …

import pyutil as pyu
pyu.get_local_pyinfo()

print(pyu.ps2("python-dotenv"))

from typing import List

class Solution:
  def findMaxAverage(self, nums: List[int], k: int) -> float:
    summ = sum(nums[:k])
    ans = summ

    for i in range(k, len(nums)):
      summ += nums[i] - nums[i - k]
      ans …

import pyutil as pyu
pyu.get_local_pyinfo()

print(pyu.ps2("python-dotenv"))

from typing import List

class Solution:
  def findMaxAverage(self, nums: List[int], k: int) -> float:
    kErr = 1e-5
    l = min(nums)
    r = max(nums)

    # True if there's a subarray with length >= k and average sum …