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https://gitee.com/coder-xiaomo/leetcode-problemset
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70 lines
4.6 KiB
JSON
70 lines
4.6 KiB
JSON
{
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"data": {
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"question": {
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"questionId": "1453",
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"questionFrontendId": "1322",
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"boundTopicId": null,
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"title": "Ads Performance",
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"titleSlug": "ads-performance",
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"content": null,
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"translatedTitle": null,
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"translatedContent": null,
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"isPaidOnly": true,
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"difficulty": "Easy",
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"likes": 251,
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"dislikes": 60,
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"isLiked": null,
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"similarQuestions": "[]",
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"exampleTestcases": "{\"headers\":{\"Ads\":[\"ad_id\",\"user_id\",\"action\"]},\"rows\":{\"Ads\":[[1,1,\"Clicked\"],[2,2,\"Clicked\"],[3,3,\"Viewed\"],[5,5,\"Ignored\"],[1,7,\"Ignored\"],[2,7,\"Viewed\"],[3,5,\"Clicked\"],[1,4,\"Viewed\"],[2,11,\"Viewed\"],[1,2,\"Clicked\"]]}}",
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"categoryTitle": "Database",
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"contributors": [],
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"topicTags": [
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{
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"name": "Database",
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"slug": "database",
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"translatedName": null,
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"__typename": "TopicTagNode"
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}
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],
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"companyTagStats": null,
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"codeSnippets": null,
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"stats": "{\"totalAccepted\": \"39.4K\", \"totalSubmission\": \"66.1K\", \"totalAcceptedRaw\": 39416, \"totalSubmissionRaw\": 66056, \"acRate\": \"59.7%\"}",
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"hints": [],
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"solution": {
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"id": "2088",
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"canSeeDetail": false,
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"paidOnly": true,
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"hasVideoSolution": false,
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"paidOnlyVideo": true,
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"__typename": "ArticleNode"
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},
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"status": null,
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"sampleTestCase": "{\"headers\":{\"Ads\":[\"ad_id\",\"user_id\",\"action\"]},\"rows\":{\"Ads\":[[1,1,\"Clicked\"],[2,2,\"Clicked\"],[3,3,\"Viewed\"],[5,5,\"Ignored\"],[1,7,\"Ignored\"],[2,7,\"Viewed\"],[3,5,\"Clicked\"],[1,4,\"Viewed\"],[2,11,\"Viewed\"],[1,2,\"Clicked\"]]}}",
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"metaData": "{\"mysql\": [\"Create table If Not Exists Ads (ad_id int, user_id int, action ENUM('Clicked', 'Viewed', 'Ignored'))\"], \"mssql\": [\"Create table Ads (ad_id int, user_id int, action VARCHAR(10) NOT NULL CHECK (action IN ('Clicked', 'Viewed', 'Ignored')))\"], \"oraclesql\": [\"Create table Ads (ad_id int, user_id int, action VARCHAR(10) NOT NULL CHECK (action IN ('Clicked', 'Viewed', 'Ignored')))\"], \"database\": true, \"name\": \"ads_performance\", \"pythondata\": [\"Ads = pd.DataFrame([], columns=['ad_id', 'user_id']).astype({'ad_id':'Int64', 'user_id':'Int64', 'action':'object'})\"], \"postgresql\": [\"Create table If Not Exists Ads (ad_id int, user_id int, action VARCHAR(30) CHECK (action IN ('Clicked', 'Viewed', 'Ignored')))\\n\"], \"database_schema\": {\"Ads\": {\"ad_id\": \"INT\", \"user_id\": \"INT\", \"action\": \"ENUM('Clicked', 'Viewed', 'Ignored')\"}}}",
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"judgerAvailable": true,
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"judgeType": "large",
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"mysqlSchemas": [
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"Create table If Not Exists Ads (ad_id int, user_id int, action ENUM('Clicked', 'Viewed', 'Ignored'))",
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"Truncate table Ads",
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"insert into Ads (ad_id, user_id, action) values ('1', '1', 'Clicked')",
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"insert into Ads (ad_id, user_id, action) values ('2', '2', 'Clicked')",
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"insert into Ads (ad_id, user_id, action) values ('3', '3', 'Viewed')",
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"insert into Ads (ad_id, user_id, action) values ('5', '5', 'Ignored')",
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"insert into Ads (ad_id, user_id, action) values ('1', '7', 'Ignored')",
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"insert into Ads (ad_id, user_id, action) values ('2', '7', 'Viewed')",
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"insert into Ads (ad_id, user_id, action) values ('3', '5', 'Clicked')",
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"insert into Ads (ad_id, user_id, action) values ('1', '4', 'Viewed')",
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"insert into Ads (ad_id, user_id, action) values ('2', '11', 'Viewed')",
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"insert into Ads (ad_id, user_id, action) values ('1', '2', 'Clicked')"
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],
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"enableRunCode": true,
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"enableTestMode": false,
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"enableDebugger": false,
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"envInfo": "{\"mysql\": [\"MySQL\", \"<p><code>MySQL 8.0</code>.</p>\"], \"mssql\": [\"MS SQL Server\", \"<p><code>mssql server 2019</code>.</p>\"], \"oraclesql\": [\"Oracle\", \"<p><code>Oracle Sql 11.2</code>.</p>\"], \"pythondata\": [\"Pandas\", \"<p>Python 3.10 with Pandas 2.0.2 and NumPy 1.25.0</p>\"], \"postgresql\": [\"PostgreSQL\", \"<p>PostgreSQL 16</p>\"]}",
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"libraryUrl": null,
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"adminUrl": null,
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"challengeQuestion": null,
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"__typename": "QuestionNode"
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}
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}
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} |