mirror of
https://gitee.com/coder-xiaomo/leetcode-problemset
synced 2025-01-10 18:48:13 +08:00
59 lines
5.5 KiB
JSON
59 lines
5.5 KiB
JSON
{
|
|
"data": {
|
|
"question": {
|
|
"questionId": "3257",
|
|
"questionFrontendId": "100175",
|
|
"categoryTitle": "Database",
|
|
"boundTopicId": 2653972,
|
|
"title": "Maximize Items",
|
|
"titleSlug": "maximize-items",
|
|
"content": null,
|
|
"translatedTitle": null,
|
|
"translatedContent": null,
|
|
"isPaidOnly": true,
|
|
"difficulty": "Hard",
|
|
"likes": 0,
|
|
"dislikes": 0,
|
|
"isLiked": null,
|
|
"similarQuestions": "[]",
|
|
"contributors": [],
|
|
"langToValidPlayground": null,
|
|
"topicTags": [],
|
|
"companyTagStats": null,
|
|
"codeSnippets": null,
|
|
"stats": "{\"totalAccepted\": \"13\", \"totalSubmission\": \"15\", \"totalAcceptedRaw\": 13, \"totalSubmissionRaw\": 15, \"acRate\": \"86.7%\"}",
|
|
"hints": [],
|
|
"solution": null,
|
|
"status": null,
|
|
"sampleTestCase": "{\"headers\":{\"Inventory\":[\"item_id\",\"item_type\",\"item_category\",\"square_footage\"]},\"rows\":{\"Inventory\":[[1374,\"prime_eligible\",\"Watches\",68.00],[4245,\"not_prime\",\"Art\",26.40],[5743,\"prime_eligible\",\"Software\",325.00],[8543,\"not_prime\",\"Clothing\",64.50],[2556,\"not_prime\",\"Shoes\",15.00],[2452,\"prime_eligible\",\"Scientific\",85.00],[3255,\"not_prime\",\"Furniture\",22.60],[1672,\"prime_eligible\",\"Beauty\",8.50],[4256,\"prime_eligible\",\"Furniture\",55.50],[6325,\"prime_eligible\",\"Food\",13.20]]}}",
|
|
"metaData": "{\"mysql\":[\"Create table If Not Exists Inventory ( item_id int, item_type varchar(50), item_category varchar(50), square_footage decimal(10,2))\"],\"mssql\":[\"Create table Inventory ( item_id int, item_type varchar(50), item_category varchar(50), square_footage decimal(10,2))\"],\"oraclesql\":[\"Create table Inventory ( item_id int, item_type varchar(50), item_category varchar(50), square_footage decimal(10,2))\"],\"database\":true,\"name\":\"maximize_items\",\"pythondata\":[\"Inventory = pd.DataFrame([], columns=['item_id', 'item_type', 'item_category', 'square_footage']).astype({'item_id':'Int64', 'item_type':'object', 'item_category':'object', 'square_footage':'Float64'})\\n\"],\"postgresql\":[\"Create table If Not Exists Inventory ( item_id int, item_type varchar(50), item_category varchar(50), square_footage decimal(10,2))\\n\"],\"database_schema\":{\"Inventory\":{\"item_id\":\"INT\",\"item_type\":\"VARCHAR(50)\",\"item_category\":\"VARCHAR(50)\",\"square_footage\":\"DECIMAL(10, 2)\"}}}",
|
|
"judgerAvailable": true,
|
|
"judgeType": "large",
|
|
"mysqlSchemas": [
|
|
"Create table If Not Exists Inventory ( item_id int, item_type varchar(50), item_category varchar(50), square_footage decimal(10,2))",
|
|
"Truncate table Inventory",
|
|
"insert into Inventory (item_id, item_type, item_category, square_footage) values ('1374', 'prime_eligible', 'Watches', '68.0')",
|
|
"insert into Inventory (item_id, item_type, item_category, square_footage) values ('4245', 'not_prime', 'Art', '26.4')",
|
|
"insert into Inventory (item_id, item_type, item_category, square_footage) values ('5743', 'prime_eligible', 'Software', '325.0')",
|
|
"insert into Inventory (item_id, item_type, item_category, square_footage) values ('8543', 'not_prime', 'Clothing', '64.5')",
|
|
"insert into Inventory (item_id, item_type, item_category, square_footage) values ('2556', 'not_prime', 'Shoes', '15.0')",
|
|
"insert into Inventory (item_id, item_type, item_category, square_footage) values ('2452', 'prime_eligible', 'Scientific', '85.0')",
|
|
"insert into Inventory (item_id, item_type, item_category, square_footage) values ('3255', 'not_prime', 'Furniture', '22.6')",
|
|
"insert into Inventory (item_id, item_type, item_category, square_footage) values ('1672', 'prime_eligible', 'Beauty', '8.5')",
|
|
"insert into Inventory (item_id, item_type, item_category, square_footage) values ('4256', 'prime_eligible', 'Furniture', '55.5')",
|
|
"insert into Inventory (item_id, item_type, item_category, square_footage) values ('6325', 'prime_eligible', 'Food', '13.2')"
|
|
],
|
|
"enableRunCode": true,
|
|
"envInfo": "{\"mysql\":[\"MySQL\",\"<p>\\u7248\\u672c\\uff1a<code>MySQL 8.0<\\/code><\\/p>\"],\"mssql\":[\"MS SQL Server\",\"<p>mssql server 2019.<\\/p>\"],\"oraclesql\":[\"Oracle\",\"<p>Oracle Sql 11.2.<\\/p>\"],\"pythondata\":[\"Pandas\",\"<p>Python 3.10 with Pandas 2.0.2 and NumPy 1.25.0<\\/p>\"],\"postgresql\":[\"PostgreSQL\",\"<p>PostgreSQL 16<\\/p>\"]}",
|
|
"book": null,
|
|
"isSubscribed": false,
|
|
"isDailyQuestion": false,
|
|
"dailyRecordStatus": null,
|
|
"editorType": "CKEDITOR",
|
|
"ugcQuestionId": null,
|
|
"style": "LEETCODE",
|
|
"exampleTestcases": "{\"headers\":{\"Inventory\":[\"item_id\",\"item_type\",\"item_category\",\"square_footage\"]},\"rows\":{\"Inventory\":[[1374,\"prime_eligible\",\"Watches\",68.00],[4245,\"not_prime\",\"Art\",26.40],[5743,\"prime_eligible\",\"Software\",325.00],[8543,\"not_prime\",\"Clothing\",64.50],[2556,\"not_prime\",\"Shoes\",15.00],[2452,\"prime_eligible\",\"Scientific\",85.00],[3255,\"not_prime\",\"Furniture\",22.60],[1672,\"prime_eligible\",\"Beauty\",8.50],[4256,\"prime_eligible\",\"Furniture\",55.50],[6325,\"prime_eligible\",\"Food\",13.20]]}}",
|
|
"__typename": "QuestionNode"
|
|
}
|
|
}
|
|
} |