{"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'
Após se cadastrar, cada desenvolvedor recebe uma chave de acesso à API pessoal, uma combinação única de letras e dígitos para acessar nosso endpoint de API. Para autenticar com a Schedule Expression Parser API basta incluir seu token Bearer no cabeçalho Authorization.
| Cabeçalho | Descrição |
|---|---|
Authorization
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Obrigatório
Deve ser Bearer access_key. Veja "Sua chave de acesso à API" acima quando você estiver inscrito.
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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.