I start work on AC-400 and feel lack of understanding what is asked to deliver.
This ticket request autocomplete form for ‘Concepts’. Currently Android client doesn’t use concepts except settings screen, that doesn’t bring much understanding of what it is and its business use case.
Search on talk.openmrs.com shows me two use cases:
- first one is tag of the symptom
- second one of raw data for height and with
Does anyone can provide links of docs\topics where I can learn more about this or explain by your own what it is and how it is used in the app? Particularly for Android.
Hi @gelassen , I also don’t have enough knowledge on the goal of AC-400 . It was for GSoC 2017, you might find useful info in the wiki page. Pinging the issue creator @raff
According to visit form on demo server it is diagnoses mentioned in the first point. The ticket asks to deliver provider and PoC for this (this PoC I think might be extend to the functional visi form)
Results I receive over /concept call with filter don’t match with what I see in the web version. Both returns concepts relevant to my search, but my call returns 9 results over 27 on the web form for the search on ‘fe’. Does openmrs have a place where I can chat about this with server side devs?
Are you paging the results?
For the chat, you can try the OpenMRS IRC channel: https://wiki.openmrs.org/display/IRC/Home
Thank you, yes, I do paging. I use the same way as it was done for caching data https://issues.openmrs.org/browse/AC-385, https://github.com/openmrs/openmrs-contrib-android-client/pull/358 – checking links for '‘next’ references. For that specific case there is a single page.
According to IRC, does telegram just mirror communication in IRC or community use it as well? (I tried to use both, but feel lack of feedback from community)
I find out both rest call and call to cache populated by logic that passed review contain the same results. It means they are both doesn’t fully match to what we have in the web version. Moreover, for query “se” results contains dataset not relevant for diagnosis dataset. It still has business value as it provides relevant diagnosis, but the issue requires more investigation on the backend.