feat: add Best Time to Buy and Sell Stock

Author: wislertt

.templates/leetcode/json/best_time_to_buy_and_sell_stock.json

@@ -0,0 +1,47 @@
+{
+    "problem_name": "best_time_to_buy_and_sell_stock",
+    "solution_class_name": "Solution",
+    "problem_number": "121",
+    "problem_title": "Best Time to Buy and Sell Stock",
+    "difficulty": "Easy",
+    "topics": "Array, Dynamic Programming",
+    "tags": ["grind-75"],
+    "readme_description": "You are given an array `prices` where `prices[i]` is the price of a given stock on the ith day.\n\nYou want to maximize your profit by choosing a **single day** to buy one stock and choosing a **different day in the future** to sell that stock.\n\nReturn *the maximum profit you can achieve from this transaction*. If you cannot achieve any profit, return `0`.",
+    "readme_examples": [
+        {
+            "content": "```\nInput: prices = [7,1,5,3,6,4]\nOutput: 5\n```\n**Explanation:** Buy on day 2 (price = 1) and sell on day 5 (price = 6), profit = 6-1 = 5.\nNote that buying on day 2 and selling on day 1 is not allowed because you must buy before you sell."
+        },
+        {
+            "content": "```\nInput: prices = [7,6,4,3,1]\nOutput: 0\n```\n**Explanation:** In this case, no transactions are done and the max profit = 0."
+        }
+    ],
+    "readme_constraints": "- 1 <= prices.length <= 10^5\n- 0 <= prices[i] <= 10^4",
+    "readme_additional": "",
+    "solution_imports": "",
+    "solution_methods": [
+        {
+            "name": "max_profit",
+            "parameters": "prices: list[int]",
+            "return_type": "int",
+            "dummy_return": "0"
+        }
+    ],
+    "test_imports": "import pytest\nfrom leetcode_py.test_utils import logged_test\nfrom .solution import Solution",
+    "test_class_name": "BestTimeToBuyAndSellStock",
+    "test_helper_methods": [
+        { "name": "setup_method", "parameters": "", "body": "self.solution = Solution()" }
+    ],
+    "test_methods": [
+        {
+            "name": "test_max_profit",
+            "parametrize": "prices, expected",
+            "parametrize_typed": "prices: list[int], expected: int",
+            "test_cases": "[([7, 1, 5, 3, 6, 4], 5), ([7, 6, 4, 3, 1], 0), ([1, 2, 3, 4, 5], 4), ([5, 4, 3, 2, 1], 0), ([1], 0), ([2, 1], 0), ([1, 2], 1), ([3, 2, 6, 5, 0, 3], 4)]",
+            "body": "result = self.solution.max_profit(prices)\nassert result == expected"
+        }
+    ],
+    "playground_imports": "from solution import Solution",
+    "playground_test_case": "# Example test case\nprices = [7, 1, 5, 3, 6, 4]\nexpected = 5",
+    "playground_execution": "result = Solution().max_profit(prices)\nresult",
+    "playground_assertion": "assert result == expected"
+}

Makefile

@@ -1,5 +1,5 @@
 PYTHON_VERSION = 3.13
-PROBLEM ?= merge_two_sorted_lists
+PROBLEM ?= best_time_to_buy_and_sell_stock
 FORCE ?= 0
 COMMA := ,
 

leetcode/best_time_to_buy_and_sell_stock/README.md

@@ -0,0 +1,41 @@
+# Best Time to Buy and Sell Stock
+
+**Difficulty:** Easy
+**Topics:** Array, Dynamic Programming
+**Tags:** grind-75
+
+**LeetCode:** [Problem 121](https://leetcode.com/problems/best-time-to-buy-and-sell-stock/description/)
+
+## Problem Description
+
+You are given an array `prices` where `prices[i]` is the price of a given stock on the ith day.
+
+You want to maximize your profit by choosing a **single day** to buy one stock and choosing a **different day in the future** to sell that stock.
+
+Return _the maximum profit you can achieve from this transaction_. If you cannot achieve any profit, return `0`.
+
+## Examples
+
+### Example 1:
+
+```
+Input: prices = [7,1,5,3,6,4]
+Output: 5
+```
+
+**Explanation:** Buy on day 2 (price = 1) and sell on day 5 (price = 6), profit = 6-1 = 5.
+Note that buying on day 2 and selling on day 1 is not allowed because you must buy before you sell.
+
+### Example 2:
+
+```
+Input: prices = [7,6,4,3,1]
+Output: 0
+```
+
+**Explanation:** In this case, no transactions are done and the max profit = 0.
+
+## Constraints
+
+- 1 <= prices.length <= 10^5
+- 0 <= prices[i] <= 10^4

leetcode/best_time_to_buy_and_sell_stock/__init__.py

@@ -0,0 +1,79 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "imports",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from solution import Solution"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "setup",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Example test case\n",
+    "prices = [7, 1, 5, 3, 6, 4]\n",
+    "expected = 5"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "execute",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "5"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "result = Solution().max_profit(prices)\n",
+    "result"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "test",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "assert result == expected"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "leetcode-py-py3.13",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.13.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

leetcode/best_time_to_buy_and_sell_stock/playground.ipynb

@@ -0,0 +1,12 @@
+class Solution:
+    # Time: O(n)
+    # Space: O(1)
+    def max_profit(self, prices: list[int]) -> int:
+        min_price = prices[0]
+        max_profit = 0
+
+        for price in prices[1:]:
+            max_profit = max(max_profit, price - min_price)
+            min_price = min(min_price, price)
+
+        return max_profit

leetcode/best_time_to_buy_and_sell_stock/solution.py

@@ -0,0 +1,28 @@
+import pytest
+
+from leetcode_py.test_utils import logged_test
+
+from .solution import Solution
+
+
+class TestBestTimeToBuyAndSellStock:
+    def setup_method(self):
+        self.solution = Solution()
+
+    @pytest.mark.parametrize(
+        "prices, expected",
+        [
+            ([7, 1, 5, 3, 6, 4], 5),
+            ([7, 6, 4, 3, 1], 0),
+            ([1, 2, 3, 4, 5], 4),
+            ([5, 4, 3, 2, 1], 0),
+            ([1], 0),
+            ([2, 1], 0),
+            ([1, 2], 1),
+            ([3, 2, 6, 5, 0, 3], 4),
+        ],
+    )
+    @logged_test
+    def test_max_profit(self, prices: list[int], expected: int):
+        result = self.solution.max_profit(prices)
+        assert result == expected