[
{
"id": "medium-article-api_1000",
"service": "medium-article-api",
"title": "MEDIUM ARTICLE Record #1",
"status": "VERIFIED_ACTIVE",
"result": "Processed query successfully for medium-article-api",
"inputReceived": {
"tags": [
"artificial-intelligence",
"programming"
],
"maxArticles": 20
},
"data": {
"index": 1,
"relevanceScore": 0.95,
"summary": "High-fidelity structured response for MEDIUM ARTICLE query parameter extraction.",
"attributes": {
"region": "Global",
"category": "MEDIUM",
"timestamp": "2026-10-12T11:01:27.757Z"
}
},
"timestamp": "2026-10-12T11:01:27.757Z"
},
{
"id": "medium-article-api_1001",
"service": "medium-article-api",
"title": "MEDIUM ARTICLE Record #2",
"status": "VERIFIED_ACTIVE",
"result": "Processed query successfully for medium-article-api",
"inputReceived": {
"tags": [
"artificial-intelligence",
"programming"
],
"maxArticles": 20
},
"data": {
"index": 2,
"relevanceScore": 0.8999999999999999,
"summary": "High-fidelity structured response for MEDIUM ARTICLE query parameter extraction.",
"attributes": {
"region": "Global",
"category": "MEDIUM",
"timestamp": "2026-10-12T11:01:27.757Z"
}
},
"timestamp": "2026-10-12T11:01:27.757Z"
},
{
"id": "medium-article-api_1002",
"service": "medium-article-api",
"title": "MEDIUM ARTICLE Record #3",
"status": "VERIFIED_ACTIVE",
"result": "Processed query successfully for medium-article-api",
"inputReceived": {
"tags": [
"artificial-intelligence",
"programming"
],
"maxArticles": 20
},
"data": {
"index": 3,
"relevanceScore": 0.85,
"summary": "High-fidelity structured response for MEDIUM ARTICLE query parameter extraction.",
"attributes": {
"region": "Global",
"category": "MEDIUM",
"timestamp": "2026-10-12T11:01:27.757Z"
}
},
"timestamp": "2026-10-12T11:01:27.757Z"
},
{
"id": "medium-article-api_1003",
"service": "medium-article-api",
"title": "MEDIUM ARTICLE Record #4",
"status": "VERIFIED_ACTIVE",
"result": "Processed query successfully for medium-article-api",
"inputReceived": {
"tags": [
"artificial-intelligence",
"programming"
],
"maxArticles": 20
},
"data": {
"index": 4,
"relevanceScore": 0.7999999999999999,
"summary": "High-fidelity structured response for MEDIUM ARTICLE query parameter extraction.",
"attributes": {
"region": "Global",
"category": "MEDIUM",
"timestamp": "2026-10-12T11:01:27.757Z"
}
},
"timestamp": "2026-10-12T11:01:27.757Z"
},
{
"id": "medium-article-api_1004",
"service": "medium-article-api",
"title": "MEDIUM ARTICLE Record #5",
"status": "VERIFIED_ACTIVE",
"result": "Processed query successfully for medium-article-api",
"inputReceived": {
"tags": [
"artificial-intelligence",
"programming"
],
"maxArticles": 20
},
"data": {
"index": 5,
"relevanceScore": 0.75,
"summary": "High-fidelity structured response for MEDIUM ARTICLE query parameter extraction.",
"attributes": {
"region": "Global",
"category": "MEDIUM",
"timestamp": "2026-10-12T11:01:27.757Z"
}
},
"timestamp": "2026-10-12T11:01:27.757Z"
}
]
curl --location --request POST 'https://zylalabs.com/api/14179/medium+tagged+articles+claps+and+author+intelligence+scraper+api/35234/execute+medium+tagged+articles+claps+and+author+intelligence+scraper+api' --header 'Authorization: Bearer YOUR_API_KEY'
--data-raw '{"tags":["artificial-intelligence","programming"],"maxArticles":20}'
注册后,每个开发者都会被分配一个个人 API 访问密钥,这是一个唯一的字母和数字组合,用于访问我们的 API 端点。要使用 中等标记文章点赞和作者智能抓取器 API 进行身份验证,只需在 Authorization 标头中包含您的 bearer token。
| 标头 | 描述 |
|---|---|
授权
|
必需
应为 Bearer access_key. 订阅后,请查看上方的"您的 API 访问密钥"。
|
无长期承诺。随时升级、降级或取消。 免费试用包括最多 50 个请求。
(年度计费可节省 2 个月 🎉)
这个API返回关于Medium文章的详细信息,包括参与度指标如点赞数、作者表现指标、文章摘要、发布时间和作者个人资料链接,所有信息都按指定标签分类
响应中的关键字段包括“id”“title”“status”“result”“inputReceived”“data”(其中包含“index”“relevanceScore”“summary”和“attributes”)以及“timestamp”提供了关于每篇文章表现的全面信息
响应数据结构为 JSON 数组,每篇文章作为一个对象表示,包含用于标识、状态、结果、输入参数和详细数据属性的字段,便于解析和分析
该端点提供有关文章互动(点赞)、作者洞察(关注者数量、出版频率)、文章摘要、出版日期和类别的信息,使用户能够分析内容表现和作者影响力
用户可以通过指定参数来自定义请求,例如“标签”以按主题过滤文章和“最大文章数”以限制返回的文章数量,从而实现基于特定兴趣的定制数据提取
数据直接来源于Medium发布的文章,确保信息反映实时的参与指标和作者资料,从而保持所提供见解的相关性和准确性
典型的使用案例包括内容策略师根据热门话题优化写作市场营销人员识别细分领域的影响作者以及研究人员研究数字出版平台上的受众互动动态
用户可以分析参与度指标以识别热门主题评估作者影响力并告知内容策略 结构化响应便于轻松集成到分析工具或仪表板中以获取更深入的见解