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Hello, I am trying to use “Filter time series” or “List time series” endpoints. However, because of 1000 limit, I need to parallelize these calls as I would like to retrieve thousands of timeseries. The challenge I am facing is the pagination used in these endpoints which is based on id of timeseries. Is there a way to use index as pagination? 

Hello,I have a question regarding the post-bootcamp exercise. Task says:MainOil would like to improve their maintenance monitoring and decisionsupport at their oil platform named Stella by using Cognite Data Fusion. They would like toleverage their data to get a better overview of their maintenance operations and improvecollaboration between their maintenance and operations teams.For those, who are not into oil&gas industry so much, what exactly is required to do, i.e. what is the desired data and calculations that need to be implemented?

Hi,To apply a startWith filter on a property, we can do:prop_view = client.data_modeling.views.retrieve(('myspace', 'myview'))filters.Prefix(prop_view[0].as_id().as_property_ref("myPropertyName"),"xxx")This is working fine. However, as the externalId is not a property so the code below doesn’t work:filters.Prefix(prop_view[0].as_id().as_property_ref("externalId"),"xxx")and the error message is: “Invalid prefix filter with property reference [myspace, myview/94b12855a09cf4, externalId]. View myspace:myview/94b12855a09cf4 does not have property externalId.” Could you help find out how to apply a startWith filter on externalId in python sdk? Regards,Xiaofeng

Is the data persist both on staging and the contextualized layer(destination layer after transformation as per target data model)? Or only on staging layer? If only on the staging layer, is the data pulled from staging layer during the API calls and presented as per the target model? RegardsVikash

How do I log errors and activities while working with the Cognite SDK. I need to keep track of what the code is doing, diagnose issues, and improve the overall reliability of the application. If I am designing a function, how to handle all these logging in my code to better log errors and validations within the application. Please advise. Also share practical code samples from SDK   

  Getting above error whenever trying to reach documentation

I have implemented block-updates to work with CDF Files. This by itself works quite well, as documented here.However, for very large files there are some problems. After some time, typically around 4 minutes, one of the block updates fail, with a simple `ReadError`. There’s no response from the API.Some logs from our application:DEBUG:odp.odcat.storage.cdffs.async_spec:Uploaded 133120 bytes to https://westeurope-1.cognitedata.com/api/v1/files/storage/cognite/6723545981847516/7406155183547467/wod_gld_2013.nc?sig=REDACTED&rsct=application%2Foctet-stream&sp=cw&sr=bDEBUG:odp.odcat.storage.cdffs.async_spec:Total bytes uploaded: 2660989807DEBUG:odp.odcat.storage.cdffs.async_spec:Data: len=5376000, MD5=6a0c0db1b66dac18ee28e8b082830667DEBUG:odp.odcat.storage.cdffs.async_spec:Buffer cursors: start=0, end=5242880, final=FalseDEBUG:httpx._client:HTTP Request: PUT https://westeurope-1.cognitedata.com/api/v1/files/storage/cognite/6723545981847516/7406155183547467/wod_gld_2013.nc?sig=RED

We have some requirements to use DB in built extractors and how can we setup Extraction pipeline configuration. 

While going through CDF fundamental course and working with the hands-on exercise, I came across the transformation SQL which uses _cdf database and I have seen 2 different tables (assets and timeseries) used in 2 different transformations. Can someone please help a bit more on this _cdf database? What is it’s content, what all tables it contains, how is it created, to which all datasets this DB will be related to etc.

I am looking for a way to update the extraction.id-prefix field inside the OPC-UA extractor config file after partially starting data extraction. Basically, I need to be able to store data in CDF raw with External ID prefix set to a particular tag value coming from the OPC server. So I would need to read the timeseries value of that particular tag from the OPC server and set this value as id-prefix in the extractor config file before pushing subsequent data to CDF raw.Since the pre-built OPC-UA extractor works well for our use case, I am looking for ways to use it as is without having to implement a custom extractor. What would be the best way to implement the functionality mentioned above using the OPC-UA extractor?(Attn. @Jatin Sablok )

Hi. I’m using the Cognite Data Source for Grafana. For numerical time series I can retrieve properties like {{name}}, {{description}}, etc. But for some reason I cannot for string time series. The only difference between the two panels below is the External Id of the time series it points to: one is a string time series, the other numerical. Both time series have a name specified in CDF. 

I have some views with simple array properties (arrays of primitives) and others with arrays of relationships to views (edges).Location viewI can filter the simple arrays with the “containsAll” or “containsAny” methods.But there seems to not be a filter avaiable for the edges in the Graphql API. How can I filter by these properties via the GraphQL API?

Getting above error whenever trying to reach documentation

Hi I have a final computed dataframe that looks like this. sample set alone listed here (15 rows) There are 570 records. I need to create timeseries for sumprod and derivedYields columns as per the value in Yieldcode. I have written the code and it is running and timeseries is getting created. But it is running slow. How to make it get done faster?Any best method? Please advise     sumprod Yieldcode Rank Group derivedYields MBBLD Vol LP-Class 1 532 0.009636 VBALFG1 1 VBAL 0.009636 3.524946 FG1 2 533 0 VBALLP1 2 VBAL 0 0 LP1 3 534 0.210269 VBALFN1 3 VBAL 0.218807 80.0382 FN1 4 535 0.037774 VBALLW1 4 VBAL 0 0 LW1 5 536 0.048263 VBALSK1 5 VBAL 0.094867 34.70158 SK1 6 537 0.017368 VBALHK1 6 VBAL 0 0 HK1 7 538 0.128149 VBALSR1 7 VBAL 0.142624 52.17094 SR1 8 539 0.014722 VBALDS1 8 VBAL 0 0 DS1 9 540 0.034342 VBALAG1 9 VBAL 0.0345

I have been working on this for some time now. It was all running fine till now but suddenly it is failing now, and it is giving an error for this function. Is there something that has been changed in the platform/library?DB name and table name are all accurate and was running fine till today.  lp_df_input = client.raw.rows.retrieve_dataframe(db_name="Eashwar_MOTDB-db",table_name="lp_input",limit=None,columns=None)Error: ---------------------------------------------------------------------------MissingSchema Traceback (most recent call last)Cell In[30], line 1----> 1 lp_df_input = client.raw.rows.retrieve_dataframe(db_name="Eashwar_MOTDB-db",table_name="lp_input",limit=None,columns=None)File /lib/python3.11/site-packages/cognite/client/_api/raw.py:613, in RawRowsAPI.retrieve_dataframe(self, db_name, table_name, min_last_updated_time, max_last_updated_time, columns, limit) 589 """`Retrieve rows in a table as a pandas dataframe. <https://developer.cog

When I run connection.py it tells me that https://westeurope-1.cognitedata.com/login/status is not accessible. Other resources are accessible.

Hi,I need to connect to CDF with Power BI and when trying to load the table, I get this error:It only loads a limited rows of data (probably those rows have no errors) and I cannot change the format of the fields in PBI.I already whent thru the documentation , but the solution provided there does not work in this case (there is no option to change the data format).For other datasets (other data sources), where Power BI encounters errors, the data is still loaded (with errors), but in this case, the data is not loaded and the import is stopped by the error. This is also keeping for saving the report or using the data source.The behavior needed is that PowerBI is loading the entire dataset with errors and to change the field format before importing the data.Thank you!

https://docs.cognite.com/cdf/integration/guides/contextualization/interactive_diagrams How to create engineering diagram, and How get label name in diagram “23-LAHH-96138” through JavaScript.

I’m facing the above issue while running the demo cognite custom extractor

I am looking forward to a solution for reading a csv files that has 100 columns and 200 rows. It is stored in CDF as ‘Files’. How do I read the file and then use pandas to convert the file as a dataframe?diet_f= (client.files.list(name='diet_daily.csv'))[0]diet_daily_transformed = pd.read_csv(diet_f.name)diet_daily_transformedThis isnt working and throwing an error. Please advise the best means to perform this task. 

I have a helper function that returns a CogniteClient via interactive OAuth authentication. This worked literally yesterday, but gives me an error today.This is my function definition import osfrom cognite.client import CogniteClient, ClientConfigfrom cognite.client.credentials import OAuthInteractivefrom typing import Uniondef authenticate_to_cognite_oauth( project: str="akerbp", client_name: str="Employee", client_id: Union[str, type(None)]=None, tenant_id: Union[str, type(None)]=None, base_url: str="https://api.cognitedata.com" ) -> CogniteClient: """Authenticate to Cognite via OAuth interactive login. Return cognite.client.CogniteClient.""" if client_id is None: client_id = os.getenv("CDF_CLIENT_ID") if tenant_id is None: tenant_id = os.getenv("CDF_TENANT_ID") authority_url = f"https://login.microsoftonline.com/{tenant_id}" scopes = [f"{base_url}/.default"] creds = OAuthInteractive( authority_url=authority_u

I want to create a cognite function that will do lot of computations and finally attach the derived output to a timeseries. Is there some production-ready sample code snippet that can be shared to see how to attach a derived value from cognite function to a timseries?

Hi Team, We are working on a POC , where we need to create unit test cases where we are facing different issues .For reference we are using code from Cognite HubBelow attaching our code and output expectations .Please help with the approach to resolve this issue ts_retrieved = [    TimeSeries(    id= 3973245479016710,    external_id= "Brazil:3W:Well-Bore-19B_target_throughput",    name= "Brazil:3W:Well-Bore-19B_target_throughput",    is_string= False,    metadata= {},    unit= "Barrel",    asset_id= 3332326574821917,    is_step= False,    description= "target volume for a oil well bore",    security_categories= [],    data_set_id= 8739280581150161,    created_time= "2023-05-02 09:37:04.944000",    last_updated_time= "2023-05-02 09:37:04.944000")]@pytest.fixturedef cognite_client_mock():    with monkeypatch_cognite_client() as client:          client.assets.retrieve().time_series().get().return_value = ts_retrieved        return client   Method code          ts_data = c.assets.retrieve(

Please share Cognite deployment architecture diagram. How storage is maintained on public cloud in various regions?

Getting OSError: [Errno 22] Invalid argument while I am running a query while other queries are running.And also this query is running in SQL server only giving error of invalid argument while ingesting timeseries data in extractor.