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Hello everyone, I am looking for guidance on how to check the compatibility of libraries when using Streamlit on CDF. When migrating Streamlit apps from local environments or web servers (other than Pyodide) to CDF, I find it a bit challenging to confirm whether the libraries used in the app will work on Streamlit on CDF.Currently, I check if the libraries are included in the built-in packages of Pyodide and verify if they are pure Python 3 wheels on PyPI. However, I am wondering if there are any recommended methods for checking compatibility more efficiently. Any suggestions or best practices would be greatly appreciated. Thanks

I need to use a private package from our Azure DevOps Feed. We use Cognite UI to upload zip file which contains handler.py and requirements.txt. If I deploy using cognite-sdk then I get additional arguments like in this link : https://docs.cognite.com/cdf/functions/#additional-argumentswhich I can use in client.functions.create()So I have options: index_url (string): A URL pointing to a different package repository. It supports basic HTTP authentication. extra_index_urls (list): A list of URLs pointing to additional python package repositories. Supports basic HTTP authentication.Using any of these approach I can point to my azure feed(however I am not sure about authentication part. how to provide PAT)However, when I am using Cognite UI to deploy functions via zip files I dont get options to provide index_urls So I tried including whl file of our private package within zipped folder and deploy the function. But I got this error: Message: Function deployment failed.Trace:Failed to publi

We are using Pygen to generate Python SDK for our Data Model. Pygen has given us good set of classes and methods which are really helpful. However, descriptions added in this generated SDK are very generic and not that useful. I think the only way to add descriptions and examples are manually doing changes to each classes and methods.We are planning to use Pygen to create SDK and may generate SDK multiple times based on data model versions. If we put our own descriptions and examples manually then each time new SDK will generated we will loose the descriptions and examples.Here, descriptions should be applied to all classes, methods, arguments etc.I believe there should be way to create SDK with relevant descriptions and examples.Please suggest what needs to be done.

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".

Greetings. I wanted to reach out in this Document Parser [Early Adopter] group to request access to the Document Parser Tool in our Project. I was hoping to test the tool for a business use case. Additionally, the documentation explains using the Document Parser on data ingested in the DMS. Will this tool also be available for data ingested in an asset-centric model? Thanks,Gabriel

I’m using the Cognite SDK to create files on CDF but I’m not able to find this file under the dataset on data Explorer UI. Where will this files be stored and how can I make sure that they are visible?  fileMetadata = FileMetadataWrite( name=fileName, external_id=fileName, overwrite=True, data_set_id=dataSetId, mime_type="application/json", ) new_file = client.files.create(fileMetadata) 

I'm using python sdk and wanted to query instances based on a condition using “data_modeling.instances.query” method. i have a view “TimeseriesProperty” and it has a direct relation/reference to "TimeseriesPropertyType" view. Is it possible to have a distinct filter on the result, because multiple “TimeseriesProperty” instances can have the same "TimeseriesPropertyType"  instances , we don't want duplicated "TimeseriesPropertyType"  instances coming in response for below query: view_id= ViewId(space="slb-pdm-dm-governed", external_id="TimeseriesProperty",version="2_0")v_id_2_PROP = ViewId(space="slb-pdm-dm-governed", external_id="TimeseriesPropertyType",version="2_0")query= Query( with_= { "TimeseriesProperty":NodeResultSetExpression( limit=10, filter= HasData(views=[view_id])), "TimeseriesPropertyType":NodeResultSetExpression( limit=10000, direction="outwards",

Hi, As mentioned below, which group to sign up for early adopters of DirectQuery in Power BI? https://docs.cognite.com/cdf/dashboards/guides/powerbi/dq_whyI can’t find relevant group from what I see from here https://hub.cognite.com/groupsAny tips ? :)Thanks, 

We have customers using InfluxDB as a local on-prem storage mechanism. What’s the best extractor to use to push this data to CDF? I’ve heard OPC-UA is the way to do it, but what I find online are ways to store OPC-UA data into Influx, but not ways to get InfluxDB data into a OPC-UA server so I could use the OPC-UA extractor to get it into CDF.

Our team is handling 3D models in various file formats and applying colors to different models before importing them into CDF. Additionally, we are applying textures to models using Navisworks Simulate and exporting them in .nwd or .fbx formats. All related files are zipped before uploading them in CDF.According to the Cognite 3D documentation, this should be possible. However, when we import the models, the colors do not appear as expected. Could you provide guidance on the correct procedure to ensure that colors and textures are retained? Is there a specific workflow or setting we should follow?

Hello, As per the docuementaiton Pygen exposes a `graphql_query` method. However, I’m not able to find it. Could you please help? version used:  cognite-pygen==1.2.1Thanks

Hello, While testing data gouvernance feature per space in the data model service, we noticed that it does work on the instance level but not on the data models level. Here are the tests conducted: Test 1:We tested giving access to users to only instances that are in a specific space but applying the following ACL :  - dataModelInstancesAcl: actions: - READ scope: spaceIdScope: { spaceIds: ['test'] }When requesting the data model, only instances in the test space are returned. ACL works on instance level. Perfect!Test 2: When applying a similar ACL on the data model level :  - dataModelsAcl: actions: - READ scope: spaceIdScope: { spaceIds: ['not_that_important_data_models'] }In this case, we notice that we get revoked access to all data models, even data model in not_that_important_data_models space.  We expected that we would be able to access only data models in not_that_important_data_models. Could you please check ?  Thanks

Hi!Is there a way to enable cascading deletes for instances for both direct relations and edges? Edit: I posted in the wrong group, but i don’t think i can delete. 

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'

In Cognite Academy Fundamentals : Working With CDF: Contextualize, I have followed all of the instructions several times for Entity Matching and, in all instances, get “No matches found”, so there is nothing to confirm or write to CDF.  What am I missing here?

Using PBI Desktop and Cognites Rest API Connector betaWhen configuring the GraphQL parameters of Space, Datamodel, version and queryThere is a problem when pasting a query that was copied from the Query Explorer or even notepad into the query input boxIt is truncating the query string at the first carriage return CR and or Line Feed LFIf all CR and LF are removed from the query string, it will paste properly and run properly.   

I am new bee for this mammal, to Setup the Cognite file extractor for the local file upload to CDF, how to I config the environment variable in the yaml?according to the example-local.yaml I need to read:COGNITE_BASE_URLCOGNITE_PROJECTCOGNITE_CLIENT_IDCOGNITE_TOKEN_URLCOGNITE_CLIENT_SECRETI am little confuse, should I create a .env file to have all of those environment variables in that file and put it in the same folder as the yaml config file or can I inject those variables in the configuration file itself, if so any example?  need someone lighting me up.

got 401 "Unauthorized" error when using Postman and also  sometimes a bad request error while I did everything  as they did in the course. please help it took a lot of time from me.

Hi there,I know there’s a lot happening in NEAT right now, and we're doing our best to keep up with the changes and learn from all the improvements. That said, I have a question regarding the documentation.The docs refer to core_data_model, which doesn’t seem to exist. Should we be using the example to load the core data model instead?For example, the documentation shows:neat.read.cdf.core_data_model( ["CogniteAsset", "CogniteEquipment", "CogniteTimeSeries", "CogniteActivity", "CogniteDescribable"])But in our case, we’re currently using:#extend the core data model through examplesneat.read.examples.core_data_model()neat.subset.data_model(["CogniteAsset", "CogniteEquipment", "CogniteTimeSeries", "CogniteActivity"]) 

How can we configure the OPCUA data node (in string) as event in Cognite instead of timeseries (by default)?P.S. The existing OPCUA Server does not support to configure it as Event.

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 

so in the Learn to Use the Cognite Python SDK  in the data engineer course , I got stuck on the hands on test.as   in the readme file after I created a dataset and a root assets I just do not know how can I  do this section : - Read the `all_countries.csv` file as a dataframe and list all the unique regions in the world.- For each geographical region, create a corresponding CDF asset that is under the "global" root asset and is associated with the "world_info" data set.- Next, create country-level assets using the data from the CSV and link them to their corresponding region-level assets. 

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

When I am trying to runcdf deployorcdf deploy --dry-run In both cases I am getting this errorERROR (AuthorizationError): Don't have correct access rights to clean spaces.Missing:DataModelsAcl(actions=[<DataModelsAcl Action.Read: 'READ'>], scope=AllScope())Please click here to visit the documentation and ensure that you have setupauthentication for the CDF toolkit correctlyPlease note that I am using toolkit in azure devops pipeline so its CLI and I dont see any documentation link there as mentioned in the error. What are required access for deploy (with or without dry run)?

In CDF, does “Domain Data model” provided out of the box by the product or it needs to be configured? My understanding is, source data is firstly staged on staging/raw layer, then mapped to “domain data model” and then each customer can derive “Solution data model” out of “Domain data model”. Most probably “Domain data model” should be 3NF. Can someone validate my understanding please.