To retrieve all the tickets for 2024 without hitting the pagination limit, you can adjust your approach by breaking the request into smaller chunks. Instead of trying to fetch all tickets at once, try querying for smaller date ranges like monthly or weekly. Use the pagination parameters like page and per_page to iterate through the results. After retrieving one page of tickets, check if there are more pages and continue fetching until all tickets are retrieved. This way, you avoid exceeding the 300-item limit per request and can still gather the full data set for the year.

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I am still unable to fetch data from a specific range that is filtered by created_at. Do you know how to correctly query the tickets with a created_at filter to specify a range?

To efficiently retrieve historical ticket data for 2024 while avoiding pagination limits, use Python to handle API requests in batches. Set the maximum allowed limit (e.g., 300) and loop through pages using offset, page, or cursor parameters provided by the API. Continue fetching data until no more pages are available, filtering for the target_date as needed. Implement error handling with retries for failed requests, and log results to ensure no data is lost. You can also check entertainment site if got bored from coding

To retrieve historical ticket data, you would typically start by identifying the relevant data source or platform where the tickets were issued, such as a customer service system, event ticketing platform, or internal database. The data may include ticket numbers, issue dates, status (open, closed, pending), resolution times, and related customer details. Depending on the platform, you can use specific queries to extract the data.