Add example in sub-chapter about how to read in sas7bdat-files on Dapla:

import pandas as pd

from dapla import FileClient

 

fs = FileClient.get_gcs_file_system()

 

sti = "gs://ssb-prod-eksempelbotte-data-produkt/undermappe/fil.sas7bdat"

 

with fs.open(sti) as sas:

    df = pd.read_sas(sas,

                     format='sas7bdat',

                     encoding='latin7'

                    )

Use console instead of terminal when installing

https://manual.dapla.ssb.no/pakke-install.html#installering-1

Need to specify what a user, who has not made the basic git-configuration and wnats to build someone elses ssb-project, has to do.. Just refer to to git-chapter

The book should explain:

• How to list pre-installed packages from base-image? Both R and Python
• How to get a package installed from other sources than Cran or PyPI? Like Github, internal, etc.

Page on transfer services (https://manual.dapla.ssb.no/overf%C3%B8ring-av-data.html) is missing description on how to set up inter-bucket transfer jobs. How one sets up such a service is obvious if one has read the page, but seeing as a description of how this is done is missing many people might not be aware this is possible.

Needs explanation since its changed a little bit compared to the old Jupyter-environment

See: https://quarto.org/docs/authoring/language.html

Links 2, 4 and 5 in the highlighted text do not work

https://github.com/statisticsnorway/dapla-manual/blob/2aaac1cdba23e4adeef6d337572457567062baf4/dapla-manual/navnestandard-datalagring.qmd#L10C1-L20C36

Some explanation of Maskinporten-guardian and use of it with a code example would be highly appreciated in the future. Maybe team skatt can help here.

Add explanations for:

• how to give write access to repo
• • Recommend using AD-groups, and how to set it up (Settings, Collaborators and teams, Create team, add to AD-groupo under Identity Provider Groups, Select Groups)

The page https://manual.dapla.ssb.no/datatilstander.html sends readers to a document outside the dapla manual. The page should instead (or in addition) define and describe these.

Presisere når (og hvorfor) man må kjøre ssb-project build i kapittel 17.5 eller annet egnet sted

New manual will include embedded notebooks.
Example-notebooks must therefore be created. For instance notebooks on GCS file-system, klass and statbank. Feel free to add more suggestions for embedded notebooks

Her står det at renv ikke håndtereing versjonering av selv R men det gjøre det: https://manual.dapla.ssb.no/nytt-ssbproject.html#hva-med-r. Versjonen ar r er i lock-filen. Men foreløpig hjelper det ikke nå vi kun har en versjon av R tilgjengelig, men det er en annen sak. Manual bør endres men kanksje vi kan se på hvordan å integrere R i ssb-prosject første?

The manual should describe how a user can restart the server from jupyter. This is often necessary to get new versions in the instance.

Update datatilstander reference to latest version (2nd edition).

Latest version can be found here
https://ssbno.sharepoint.com/sites/Internedokumenter/Delte%20dokumenter/Forms/AllItems.aspx?id=%2Fsites%2FInternedokumenter%2FDelte%20dokumenter%2FInterne%20dokumenter%202023%2F2023%2D14%20Datatilstander%20i%20SSB%2Epdf&parent=%2Fsites%2FInternedokumenter%2FDelte%20dokumenter%2FInterne%20dokumenter%202023

Information on how one configures automation script to be triggered by any new file in the bucket is missing.
If one sets folder_prefix to an empty string in config.yaml the automation script is applied to the whole bucket. Would be nice to have this in the manual.

Jeg savner fortsatt en litt nærmere forklaring av terminalen/linux/operativsystemet til JupyterLab Dapla. Jeg forstår at det er Linux operativsystem, men hvor foreligger denne? den er vel en del av Dapla på en eller annen måte?
Blant seksjonene hører jeg noen kaller det "Linux i adminsonen" og noen sier "Dapla-Linux". Kanskje greit å få dette svart på hvitt så det ikke blir noen misforståelser her. adminsone kan jo tolkes som om det er på bakken, slik som linux i prodsone er, så hvor foreligger denne linux delen til JupyterLab Dapla seg?

Explain what packages is necessary for building dashboard with Dash in JupyterLab.

Add example of how to use the argument repo_privacy in ssb-project create

Should describe that a user needs to run atlantis apply again if the make changes to config.yaml of an existing job.

Måten å opprette mapper på Google Cloud Storage som står i daplamanualen fungerer ikke (https://manual.dapla.ssb.no/jobbe-med-data.html)

Jeg fulgte denne veiledningen:

from dapla import FileClient
fs = FileClient.get_gcs_file_system()

Example of how you can use gcsfs and dapla-toolbelt together

fs.mkdir("gs://ssb-prod-arbmark-skjema-data-produkt/ledstill/klargjorte-data/sesongjustering/p2023k2")