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Hello Community Members,I am delighted to announce that from today, the Cognite Python SDK now has support for Time Series Data Quality Status codes.Using the SDK, you may retrieve data points including their status codes, and filter on status codes if desired. You may also insert data points with status codes.For a full description of all the methods and functionality, please refer to the Python SDK Documentation and our Developer DocumentationWhilst this functionality remains in Beta maturity, we are targeting the upcoming June release for General Availability. Cognite relies on customer feedback as key part of its product maturation process, and customers are warmly encouraged to begin implementation of support for data quality status codes and to provide the valuable feedback necessary to allow us to make this feature Generally Available.Thank you for your continued support! Glen
Hello group members, “If you were to use CDF as an Industrial Historian, what features relating to versioning, tracking of changes and auditing would you need from our Time Series API”.In an upcoming release, we are planning to introduce support for versioning on Time Series, with the intention to enable our Time Series service to be used in the same way as you would a traditional industrial Historian.I am keen to gather information and insights from you to understand the scenarios where such a capability is required, in order that we build the right thing. Please feel free to send me a direct message if this is of interest to you!Kind Regards, Glen
This group is an early adopter group for users of the Time Series and Events APIs with a focus on OT data. In this group we will post topics to solicit feedback on future roadmap plans, provide insights into upcoming feature releases and to answer your questions about features. We created this group to be able to maintain ongoing discussions on feature topics, rather than create a new group every time we release a new feature. We hope you enjoy this format and look forward to your participation.For more general 'how to' type questions, please continue to use the Question and Answers section of the Hub, and for Product Idea please continue to submit those via the 'Have a Product Idea' button.
Hello everyone in the group!I’m delighted to announce that in the upcoming release, the Time Series Subscriptions feature will mature to a Generally Available level of maturity. But…! The feedback does not stop there. Please do continue to use this group to ask questions about the feature, request improvements or provide any other form of feedback.In light of the news, I also feel that this group in its current form has served its purpose. However, we would like the group to continue as we appreciated your engagement on our product developments. Therefore, we would like to repurpose this group to cover more topics and features relating to the Time Series API, and our other OT services too, such as Events.We hope you continue to be members of the group, and look forward to collaborating with you with our future developments, and thank you so much for your contributions in bringing the Subscriptions feature to GA!
Hello CDF developers and users,Following feedback about the best practice examples provided in the documentation for how to use Parallel Retrieval / Partitions, Cognite has updated its documentation to make more explicit the limits in place for how many partitions that can be used in a request. The document now makes explicit that a maximum of 10 partitions is supported.This guidance is found in the Pagination section of the Developer GuideIn conjunction with the updated guidance, limit enforcement will be put in place on the Assets, Events and Files APIs, to ensure predictability of performance with these APIs, effective from 1st February 2023. Requests calling for more than 10 partitions will return a HTTP 422 ‘Unprocessable_Entity’ error message. Similar limits will be rolled out across all CDF backend APIs, and details of these limits will be provided in their respective resource type descriptions.For any existing client applications that are calling more than 10 partitions, the
Welcome to the Time Series Subscriptions community group for Early Adopters!Time series subscriptions are aimed at data engineers who need to monitor changes to Time Series datapoints / write only the updated datapoints to their application storage etc. This feature negates the need for consumers to download an entire time series again, just to get the changes. The feature is now available in public beta (including Python SDK support), and customers are encouraged to try it out.This group is staffed by the product team and we are available for Q&A, providing support and receiving feedback on the feature.To get started, please take a look at the user guide, the API specification.User guide: https://developer.cognite.com/dev/concepts/data_point_subscriptions/ API documentation: https://developer.cognite.com/api/?version=20230101-beta#tag/Data-point-subscriptions/ Python SDK: https://cognite-sdk-python.readthedocs-hosted.com/en/latest/core_data_model.html#data-point-subscriptionsWe
We are pleased to announce an update to the Search, Filtering and Aggregations documentation, detailing enhanced search, filtering and aggregation capabilities for our Assets, Documents, Events, Sequences and Time Series APIs.These additional features are already implemented in the April 2023 update to Data Explorer and are available to use natively within the service APIs. The documentation provides guidance on how to implement advanced filtering, sorting, search and aggregation functionality (which is available on both the standard fields and metadata), so that application users can use much more powerful and expressive search queries to find exactly the data they are looking for.Use is recommended for existing, mature projects, and apply to use cases for the Assets, Documents, Events, Sequences and Time Series APIs. For new projects and use cases, customers are recommended to work with the newer Data Modelling APIs.The updated documentation may be found here Tell us what you think
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