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Sanman Mehta

Super Seeqer
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Everything posted by Sanman Mehta

  1. Hi Ehsan, That looks like a general SPy error and I would recommend filing a ticket with support@seeq.com so we can look into it further. Sanman
  2. Hi Eric, Apologies for late reply. It got lost in the shuffle. Yes this is doable. You can check out Workbooks Templates jupyter notebook in SPy Documentation. Also depending on details of the use case there maybe another method as well using spy.workbooks search -> pull -> save ->load -> push where push step includes map (csv file) of your Old ID and New ID column corresponding to asset tree old and new leaf respectively. Sanman
  3. Seeq has added Dark mode from user configuration in R60. So it is natively supported.
  4. In addition to what Kris said, some of the things can be accessed by referencing to this example:
  5. Hi SBC, you are most likely running into a known bug which is actively being worked on (34178). Can you send me an email with short video showing this in action so I can file it?
  6. When anything is deleted in Seeq, the Archived property gets set to "true". You can use API reference and POST Archived as "false" property. Check out this screenshot on how to do so. You can also do this programatically using SDK as shown in this post:https://www.seeq.org/index.php?/forums/topic/1291-how-to-use-the-seeq-apisdk-in-pythonseeq-data-lab/
  7. Hi SBC, Pls reach out with links and logs to support@seeq.com so we can look into specifics.
  8. Hi SBC, This is not friendly to pushing visuals. we can discuss more on our call later this week to discuss further.
  9. Oh ya these results don't have to be siloed in data-lab python environment. They can be used as time series signals in workbench as well as organizer topics for any type of visualizations or in further calculations by anyone within the organization.
  10. SBC, unless I am misinterpreting your message, the cache should behave in same performance. Please reach out to me directly if you are experiencing slowness in any case. Sanman
  11. Seeq stores all results in cache (most cases), so once you have done calculations once, they should not need recalculation for 10 years every time and resulting signal can be instantly used in further calculations. This should help alleviate calculation load from 2nd time onwards such that only new calculation would be for the last 1 day. You should not have to run scripts for 10 years everyday. Sanman
  12. Hi VpJ, You are on the right track. Schedule daily jobs by adding this code to your data lab project script spy.jobs.schedule("Every 1 Day") In a future release you will be able to create python visuals in qorkbench and just link it to organizer topic (same as you do with standard trends, tables, treemap views).
  13. Hi VpJ, If you build it out using any of the solutions mentioned above, it is relatively easy to make it available in all workbenches.
  14. yeah just shoot me an email with workbench link in which you had the worksheet.
  15. Hi SBC, This is by design. Although you can make the asset tree available in all workbenches by specifying “workbook”=None in your spy.push call near the bottom of the script. Add on tool is running script in background which you can find and update.
  16. The script is designed to only tag pi tag (not pi server). If searching pi tag in workbench results in one unique tag then the script will work. Otherwise please reach to me directly for support.
  17. Unfortunately not. It has been accepted in feature request. If you request via support@seeq.com we will make sure you get an email when it’s in product future release. Btw, there is a workaround using fragile method I would not want to advertise here as well so feel free to reach out to Seeq support.
  18. I have encountered this error but would need to see the specifics. Can you pls send details to support@seeq.com and Seeqers can help you.
  19. Check out the data lab script and video that walks through it to automate data pull->apply ml->push results to workbench in an efficient manner. Of course you can skin the cat many different ways however this gives a good way to do it in bulk. Use case details: Apply ML on Temperature signals across the whole Example Asset Tree on a weekly basis. For your case, you can build you own asset tree and filter the relevant attributes instead of Temperature and set spy.jobs.schedule frequency to whatever works for you. Let me know if there are any unanswered questions in my post or demo. Happy to update as needed. apply_ml_at_scale.mp4 Apply ML on Asset Tree Rev0.ipynb
  20. Yes, in Data Lab users can use spy.pull to get the data and then write it to S3. See attached notebook example written by @Chris Herrera that shows an example of how to write data to S3. Disclaimer: User will have to add their own credentials and unlimited performance is not a guarantee. Reach out to support@seeq.com if your use case is not performing up to your expectations. Publish to S3.ipynb
  21. Hi RMC, I have "been there done that!" Now there is an archive parameter which when set to True will only keep the items from your push the unwanted "append" will not occur. Instead it will give you exactly what you are pushing and archive the rest.
  22. Yes! You can deploy ipywidgets from jupyter notebooks in data lab. Widgets can be great for wrapping code in UI for No-code experience from workbench using Seeq Add-on tools for implementing Machine Learning models. Here is one example for datepicker. import ipywidgets as widgets #import the library widgets.DatePicker( description='Start:', style={'description_width': '150px'}, layout={'width': '300px'}) You can read more about various widgets here: https://ipywidgets.readthedocs.io/en/latest/examples/Widget List.html
  23. Hi Bharat, Check out Table Across Assets: https://seeq.atlassian.net/wiki/spaces/KB/pages/1617592515/Tables#Tables-across-Assets Regards, Sanman
  24. Hi John, The error is pointing to column name having a period (.) Can you try after removing any period from column name in csv file? If you can email me the csv file to (sanman.mehta@seeq.com) I can take a look as well.
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