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Hello, we are facing an SSL issue while trying to connect to cognite even if we’re disabling SSL verification.Could you please help ?from cognite.client import ClientConfig, CogniteClientfrom cognite.client.credentials import OAuthClientCredentialsfrom cognite.client.config import global_configglobal_config.disable_ssl = Truecreds = OAuthClientCredentials( **{ "client_id": "", "client_secret": "", "token_url": "", "scopes": ["https://westeurope-1.cognitedata.com/.default"], } )def get_cognite_client(project: str) -> CogniteClient: return CogniteClient( ClientConfig( client_name="Python-jupyter", project=project, credentials=creds, base_url="https://westeurope-1.cognitedata.com", ) )client = get_cognite_client("totalenergies-sandbox")res = client.units.list().to_pandas()------------------------------------------------------------------------------------

Hi all, looking for guidance on two issues we hit with CDF related to timeseries visibility and datamodel queries.403 error leaking timeseries externalIds:when a user without access requests a timeseries resource, a 403 error is returned as expected, but the error body contains the externalIds of the timeseries. Those externalIds are sensitive and should not be exposed to users who don’t have access.Is it expected behavior that externalIds are included in 403 error messages? If not, is there a setting / configuration / log-level that controls whether identifiers are returned in errors? Any recommended mitigation or planned fix? Datamodel query returns datapoints from unauthorized timeseriesSetup: Created dataset_1 and dataset_2 Created two timeseries, TS_A in dataset_1 and TS_B in dataset_2 Attached both TS_A and TS_B to a datamodel Granted the user only timeseries:READ scope:dataset_2 (so they should see TS_B only) Observed behavior: querying the datamodel returns datapoints for T

Hi,I understand that we can define properties on edges, but it isn’t clear from the documentation how these properties are populated. I am trying to implement the following modelAnd defined the data model using DML as follows How can I add a UserActivity edge with properties start_time and stop_time, that I can read while listing all the activities that a User has performed?Thank you

Hello experts,We want to achieve the following workflow:Once a new instance is created/added in our datamodel container Another workflow must be triggered immediately We do not want to create a scheduled based polling to invoke our workflow since our workflow is time sensitive and high importanceCould you please let us know if CDF supports this functionality? Or suggest a way to achieve it.I have explored the CDF in my limited knowledge, I found that subscription is available on Data Model, but it is not enabled in our environment.Could you please help me in this.Thanks,Pranjul Singh  ​​​​​​​    

Hello,I’m looking to compute the standard deviation of a timeseries on the fly with synthetic timeseries.I expected to use this pseudocode formula : sqrt(avg(pow(TS{externalid}-avg(TS{externalid}),2))) with endpoint :client.time_series.data.synthetic.query(    expressions=expression,    start="2w-ago",    end="now")Unfortunately, avg expect at least 2 inputs, I try to switch to aggregate feature but I found it available only for timeseries, not synthetic timeseries.expression = '''sqrt( avg( pow( ts{ID} - ts{ID, aggregate="average", granularity="14d"}, 2 ) ))'''Do you have any tips or workaround to compute this value when “start” value changes ? Dont hesitate to explain I'm open to any opportunity to calculate this metric using another method.Thanks in advance,Pierre edit : I find this function in additionnal library : Rolling standard deviation of data points time delta — indsl 8.7.0 documentation but i’m looking for a answer without additionn

Use CaseI am building a dashboard in Power BI that will visualize Events from CDF (about one million events per year). So to make the solution scale I want to use incremental refresh of the semantic model so I only refresh the model with the newest Events since the last refresh.I have followed your tutorial on Incremental refresh (which seems copy/paste of Microsoft’s tutorial), but I still have questions:What happens if the StartTime attribute of an Event is a date/time/zone when loaded into the model? The attribute needs to be a date/time type, which means I need to convert the type first. How will the incremental refresh work if the model needs to load the data in order to convert the type, and then apply the RangeStart/RangeEnd filters? Can I use Incremental refersh with the new REST API Connector? When I load events with the new connector I get the start times as number of milliseconds since epoch. So the type conversion from above also applies here. Thanks for your help!Anders

How much time does it really take to build a full solution?We deployed a complete solution using Cognite CDF, Cursor, and Anthropic Claude Opus 4.6, powered heavily by Gen AI in just 4 hours.This was not just a prototype screen. It was a fully deployed solution for demo purpose.And here’s the most interesting part:All of the following steps were done using Gen AI:1️⃣ Creation of the data model in Cognite Data Fusion and the Terraform2️⃣ Deployment of the model in Cognite3️⃣ Data generation and ingestion into the Cognite Data Platform4️⃣ Development of a React application on top of Cognite using the Cognite SDK5️⃣ Creation of: Asset Map, KPIs, Production Time Series Dashboardand Well Intervention viewFrom data modeling to frontend application — accelerated with AI.This is not about replacing engineers.It’s about dramatically increasing speed, experimentation, and delivery capacity. The question is no longer “Can we build it?”It’s “How fast can we build it?”Post here!  

Is there a way to delete the relationship between an instance and a container? Let’s say I have a view Foo in one data model and another view FooExtension in another data model. FooExtension implements Foo.I have an instance of externalId “FOO”, space: “FOO-DAT” that have data stored in both views/containers.If it was no longer necessary to store data in container FooExtension is there a way to just delete this relationship in a way that `hasData(FooExtension)` from the DMS Query doesn’t find this instance anymore without affecting the data stored in Foo and the instance itself? Since instance count is limited, it’s becoming more common in our project modeling things having the mindset of shared instance when they mean the same thing across data models but with different formats to present the data on different Apps. But sometimes we don’t want to have the data in the app anymore and virtual deletion (boolean flags) is not always an option specially when the data volume is big. 

At Aker BP we are currently using the Cognite file extractor, and have some bugs and improvement points to report. Some of the bugs here are a big concern for us using the extractor going forward:1. Missing‑as‑Deleted Flag Does Not Work as DocumentedWhen missing-as-deleted: true and delete-behavior: hard are configured, the extractor does not delete files that are absent from the source query. This contradicts the documented behaviour and makes it impossible to rely on the extractor to keep target datasets clean. Because the executable is closed‑source, the root cause is unclear. From a developer who configures the file extractor: This bug went undiscovered for some time because the previous extractor had to be replaced, and has different behavior from the new file extractor on full loads. (This seems to be a bug in the new extractor.) The previous deprecated Documentum Extractor would delete all files that it did not upload for that specific extraction. This also caused issues in the

What capabilities are required to run a transformation using client credentials? I have a client_id and client_secret that when I add to the transformation and hit ‘Test credentials’ it says ‘Credentials verified’. However when I run with client credentials I get an error: Transformation job could not be created. Error code: 403 API error: Invalid source/destination credentials: Token did not provide access to project kuraray-america. Request ID: eb5136ee-594d-971f-b27a-7be0d1a60b15these credentials are a part of a group that that has read and write capabilities to:transformations sessions datamodelinstances (that is what this particular trasformation is creating)Additionally I am part of the same groups as this client_id, and I am able to run the transformation using ‘run as current user’ successfully

 I am facing issue of jupyter notebook getting crashed frequently. Sharing the image for reference.

Hello Team,I am trying to check like how many edges(entities in my case) are null in the view(event) is there any specific way to do so? I am trying right now sdk query api like below, but not working. Please give your insights. {    "with": {        "Event": {            "nodes": {                "filter": {                    "hasData": [                        {                            "type": "view",                            "space": "slb-pdm-dm-governed",                            "externalId": "Event",                            "version": "1_7"                        }                    ]                },                "chain_to": "destination",                "direction": "outwards"            },            "limit": 10000        },        "Event_2_entities.Entity": {            "edges": {                "from": "Event",                "direction": "outwards",                "filter": {                    "and": [                        {                            "equ

Hello, We are using cdf toolkit to deploy our container, views and data models.We recently added many new views, these views are dependent. i.e: they reference each other in the properties through a source block or via implements block. Here an examples of these view dependencies:- externalId: View1 implements: [] name: View1 properties: test: container: externalId: Container1 space: some_space type: container containerPropertyIdentifier: Test name: test source: externalId: View2 space: some_space type: view version: v1 space: some_space version: v1- externalId: View2 implements: [] name: View2 properties: wow: container: externalId: Container2 space: some_space type: container containerPropertyIdentifier: Test name: wow space: some_space version: v1or - externalId: Country implements: - externalId: CountryAttributes space: '{{sp_dm_dap_knowledge_graph}}_wv'

Hi Experts, Need your help on Cognite Python sdk.My goalGet all linked timeseries of an AssetI am using Asset class object https://cognite-sdk-python.readthedocs-hosted.com/en/latest/assets.html#cognite.client.data_classes.assets.Asset time_series function​​  ProblemIt is only giving me  the ‘Directly linked timeseries’ , not all the ‘Linked timeseries.   Means in this case I only getting 13 timeseries objects , compared to 64 linked timeseries of the Asset. Appreciate your help on adopting the correct approach Thanks and RegardsSree

Hello,  We are using: Toolkit Version '0.5.20' We are having a file schedules.Function.yaml: - name: Run every 10 minutes to do some work functionExternalId: fn_name description: Run every 10 minutes to do some work cronExpression: "*/10 * * * *" data: extractionPipeline: "test"When deploying we have this error trace: Traceback (most recent call last): File "venv/bin/cdf-tk", line 8, in <module> sys.exit(app()) File "venv/lib/python3.10/site-packages/cognite_toolkit/_cdf.py", line 116, in app _app() File "venv/lib/python3.10/site-packages/typer/main.py", line 340, in __call__ raise e File "venv/lib/python3.10/site-packages/typer/main.py", line 323, in __call__ return get_command(self)(*args, **kwargs) File "venv/lib/python3.10/site-packages/click/core.py", line 1161, in __call__ return self.main(*args, **kwargs) File "venv/lib/python3.10/site-packages/typer/core.py", line 740, in main return _main( File "venv/lib/python3.10/site-packages/typer/core

We’ve setup an MQTT Hosted Extractor that is recieving a SparkPlug B payload which some times contains a couple of null values, this values cannot be removed from the SparkPlug B payload. We believe that whenever the message contains null values the transformation for the datapoints fails.No more information is provided on the Transform Error, only the “Failed to transform data: Missing required field value”, could the null values just be ignored so the other values be inserted in the time series? We’re getting several empty time series that were created via the hosted extractor.

We’re using the client.documents.previews.download_page_as_png_bytes() function in the Python SDK to retrieve png previews of P&IDs in order to display them in a webapp (Streamlit).For some P&IDs, the dimensions of the returned png are distorted. The image is in the correct orientation but squashed to fit within a portrait envelope. The affected P&IDs are displayed correctly in both CDF Data Management and when downloaded and opened in a pdf viewer.Has anyone had this issue before and, if so, did you find a way to handle it? 

I need some help with the SDK (Python). I'm trying to list active sessions in Cognite using the following resource: client.iam.sessions.list(status="ACTIVE" However, I notice that even my client_id doesn't return in the listing (I'm logged in via browser with my user). Am I misunderstanding this feature?

Hi,I have a view called "Entity" in an existing model with mandatory properties "name", "description" and "isVirtual".Now, I have a new version of "Entity" in which I have decided to implement CogniteDescribable from CDM for name and description, where these fields are not mandatory.When I try to ingest data into the new version of this view, it gives me a non-writable error since the mandatory properties that I had created for the older version is not getting populated.Is there any way to overcome this?Can I map the mandatory container to the container used in CogniteDescribable, so that when I ingest data in the new version, it automatically ingests the mandatory container as well?If yes, can you please share a YAML example of the same to be deployed through toolkit?Please note that both the mandatory and non-mandatory containers have the same name "name".

This might be a basic question, but I often find myself uncertain about when to use CogniteDescribable in data modeling within Cognite Data Fusion.For example, let's say we have domain tables in our data model, such as MaterialType, which contains data from SAP and defines the types of materials we work with (e.g., code and description). In this case, would it be appropriate to implement CogniteDescribable to reuse common properties like name and description?What are the advantages of doing so? Does using CogniteDescribable provide any specific benefits—such as improved performance through indexing or partitioning—when used it containers?In summary, should I always use CogniteDescribable in these types of scenarios, or are there cases where it's better not to?

Hello, We are using cdf toolkit to deploy our data models. We have a relatively a big data models that uses 478 views. Each time we deploy a breaking change our data model architecture (well centric) obliges us to redeploy a new version for all views. We notice a huge deployment time at the dependencies resolution step: 2025-08-19T09:34:54+00:00 WARNING [LOW]: Failed to create 478 views: One or moreviews do not exist: 'sp_dm_mud_brines_for_ops_real_wview:Activity/0.10'.. Attempting to recover...The overall deployment time takes 35 mins, this way bigger than our standard CI/CD job duration where we try to keep it under 10min at worst. Is there a way to optimize this please?  Thank you!    

Hello,  We are heavely relying on transformations to transform our data from Raw (staging) service to Data Models. We notice that it has very high latency compared to a “simple” Spark job. As per our discussion with our Solution Architect we understood that the bottleneck is the Raw service. Any plans to improve this in the future? Thank you!

I am getting following error when ingesting files from SharePoint site to CDF. send_request_body.failed exception=LocalProtocolError('Too much data for declared Content-Length')Anything I need to specify in .yaml file to allow content-length? Also how do I trace which file is causing the problem. I changed Logger to DEBUG level but still don’t see the file name info.Thanks,Zuber

When running the following lines of code I get an error with Pydantic:from cognite.neat import NeatSessionneat = NeatSession(client)The error is as follows:---------------------------------------------------------------------------ImportError Traceback (most recent call last)Cell In[13], line 1----> 1 from cognite.neat import NeatSession 2 neat = NeatSession(client)File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\cognite\neat\__init__.py:4 1 from cognite.neat.core._utils.auth import get_cognite_client 3 from ._version import __version__----> 4 from .session import NeatSession 6 __all__ = ["NeatSession", "__version__", "get_cognite_client"]File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\cognite\neat\session\__init__.py:1----> 1 from ._base import NeatSession 3 __all__ = ["NeatSession"]File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\cognite\neat\session\_base.py:9 7 from

I am trying to use the CogniteSdk in c# to build my FDM model node and egde. I able to insert the node accordingly but having issue when trying to define the edge. As you can see below , to create an edge, it require the "Type" to be define. There is no error but when i check my UserDashboard model, it cannot link to my DashboardItem. Anyone know how we can insert Edge using C# SDK? FDM:type UserDashboard @view(version: "c3020ef716088a") { userId: String! createdDateTime: Timestamp lastUpdateDatetime: Timestamp dashboard: [DashboardItem]}type DashboardItem @view(version: "62c414860c7734") { userId: String! index: Int! id: Int!} UserDashboard DashboardItem