{"expression":"0 9 * * 1-5","timezone":"America/Sao_Paulo","human_readable":"At 09:00 AM, Monday through Friday","next_runs":["2026-07-13T12:00:00.000Z","2026-07-14T12:00:00.000Z","2026-07-15T12:00:00.000Z"]}
curl --location --request GET 'https://zylalabs.com/api/13158/schedule+expression+parser+api/26704/parse+schedule+expression' --header 'Authorization: Bearer YOUR_API_KEY'
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 Schedule Expression Parser API 进行身份验证,只需在 Authorization 标头中包含您的 bearer token。
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应为 Bearer access_key. 订阅后,请查看上方的"您的 API 访问密钥"。
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Understand and validate scheduler expressions before deploying them. One call parses the expression, computes the next execution times in the time zone you choose, and explains the schedule in plain language.
Useful for validating schedules in continuous integration, showing next run times in dashboards and admin panels, and explaining existing schedules to non-technical stakeholders.
The Parse Schedule Expression endpoint returns a JSON object containing the parsed scheduler expression, the next execution times as universal timestamps, a plain language description of the schedule, and an error message if the expression is invalid.
The key fields in the response data include "expression" (the original schedule expression), "timezone" (the specified time zone), "human_readable" (a plain language description), and "next_runs" (an array of upcoming execution timestamps).
The response data is organized in a JSON format with key-value pairs. It includes the original expression, the requested time zone, a human-readable description, and an array of next execution times, making it easy to parse and utilize programmatically.
The primary parameters for the endpoint are "expression" (the scheduler expression to parse) and "timezone" (the desired time zone for the execution times). Users can customize their requests by specifying these parameters.
Typical use cases include validating schedule expressions in CI/CD pipelines, displaying upcoming execution times in dashboards, and providing clear explanations of schedules to non-technical stakeholders, enhancing understanding and communication.
Users can utilize the returned data by integrating the next execution times into applications, displaying the human-readable description in user interfaces, and using the error messages to troubleshoot invalid expressions before deployment.
Data accuracy is maintained through robust parsing algorithms that validate scheduler expressions and handle daylight saving time correctly, ensuring that the computed execution times are reliable and accurate for the specified time zone.
Users can expect standard data patterns such as consistent formatting of timestamps in ISO 8601 format, clear human-readable descriptions, and structured error messages for invalid expressions, facilitating easy integration and error handling.