What’s new at Apify? Read on to find out. And for the latest news, follow us on Twitter.
Scheduler now supports timezone set up
Scheduler executes actors and actor tasks at specific times using a CRON-like syntax. Until now, you couldn’t select a time zone for your CRON configuration. This is now possible even with a daylight saving (DST) time.
We’ve started restructuring and updating our documentation based on feedback from our users. Have we missed anything or is anything unclear? Please use the feedback button on any of the documentation pages and tell us what information you would like added or if there’s anything else we can improve.
We’ve received reports from users that the performance of the app isn’t always perfect, so we’re hard at work on improvements. Over the past few weeks, we’ve invested quite a bit of effort in improving the overall performance, responsiveness, and also load time of the app. We reduced the overall web application size by 50% and improved database caching. We’ll continue these efforts and hope to improve your experience!
Small updates to make your life easier
We’ve updated the remaining storage tables and also added an actor (task) runs table to the new system that provides a faster load, improved search capabilities, and most importantly, is not restricted by any number of items you can view.
You can now download the complete source code of an actor as a ZIP archive directly from the multi-file code editor.
Do you have any other ideas on what we could improve? Please let us know.
Upcoming public actors in the Apify Store
We have 3 new public actors in the works for the Apify Store and want to create them in the way that’s most beneficial for you. Let us know what data you’re looking for on LinkedIn, Upwork, and Reddit, and we’ll prepare the solution for you. Just submit your ideas in the Apify roadmap.
New public actors that make Apify more efficient for you
Spawn Workers (pocesar/spawn-workers)
This actor lets you spawn tasks or other actors that share a common output dataset in parallel on the Apify platform, splitting a RequestQueue-like dataset containing request URLs.
Aggregate Fields (pocesar/aggregate-fields)
Create an overview of a dataset by aggregating the possible variations from the selected fields. It’s useful for checking the consistency of data used with Results Checker.
Dedup Datasets (lukaskrivka/dedup-datasets)
Deduplicate one or more datasets by a set of fields and merge them into one dataset of unique items.
That’s all for now. Follow us on Twitter for the latest updates!