April 2021 meeting notes¶

2021-04-26¶

Ghislaine: wireframes & roadmap update
- Went well
- Discovered a lot of things while making wireframes
- Need to agree on what we’ll cover in wireframes, and what we’ll do in later steps
  - See questions in notes
Brent:
- Library splitting done
- Code moving over from prototype - in progress
  - Crucial method in SQLAlchemy deprecated (meant to be internal method)
- Doing a better job of testing the Mathesar db library (someday could be pip installable on its own)
- Setup Mathesar to work with existing Postgres DB.
Kriti:
- Everything is now moved to the wiki
- Collections -> tables, Applications -> schemas
- Read-only APIs (APIs ongoing, CRUD and records API pending)
Pavish:
- Set up his CCI account
- Started discussion re: front-end framework and repo structure
- Finalized Svelte/Django templates + monorepo

Ghislaine:
- Wireframes for data explorer
- Move current work to wiki
Brent:
- Finish moving code over from the prototype
- Types:
  - String
  - Email
  - Number types
  - Datetime types
Kriti:
- Update roadmap based on current work
- Finish API work
- Sync database tables and webapp tables
- Import TSVs as well as CSVs
Pavish:
- Set up frontend repo
- Set up workflows required for client
- Set up Docker

License
- Hopefully finalized next week
Ticket creation
- Depends on wireframes/roadmap finalization, at least a couple of weeks away
Other community building ideas?
- Too early

How to install Mathesar?
- Use docker for now
- Installation instructions for deployment, we’ll figure this out as its own task:
  - see wiki.js as an example https://docs.requarks.io/install
How to handle large amounts of data?
- Two approaches: canvas vs. replace data in elements

Everyone to create tickets for their work
Deferred to later discussion
- Should we create an issue template for internal feature tickets? (existing templates only cover external feature requests)
- When should we start creating tickets in advance for the next sprint or for contributors?

Standups
Weekly meeting
- Agenda: planning for the next week (sprint)
Sprint cadence
- Weekly
- Tool: GitHub Project with Backlog column
Informal collaboration
- Impromptu chat, video call encouraged
- Chats are async, don’t feel pressure to reply
Notes location
- Public docs
- Private notes (strategy, competitors, funding) etc. will live in mathesar-notes repo
- Semi-public notes (e.g. user interview notes) - we’ll figure out later
- Technical discussions/decisions that we might want to go back to should go in GitHub Discussions
  - https://github.com/centerofci/mathesar/discussions
Todos
- Kriti will invite Ghislaine and Brent to Miro
- Kriti will set up a GitHub Project
- Kriti to figure out first issue templates
- In a couple of weeks, we’ll talk about the process with collaborating with the community
  - Brent: think about “create a type” issue template

Two candidates in the pipeline
Perhaps Ghislaine would like to talk to the Frontend Engineer
- TODO: Share interview notes with Ghislaine
- TODO: Prepare Interview Questions

Goals
Timeline
- Will be decided after we agree on MVP goals
Ghislaine’s research/questions:
- How people use Airtable
  - Sharing forms is a big use case, unlike SurveyMonkey etc., you don’t need to connect to a Google sheet
    - from a table
    - This is opposed to bulk importing data
  - Automation
    - Zapier is a bit disconnected, Airtable pulls it all together
    - Improve the quality of data collection
- Some industries need to automate processes for cost savings
  - for example, see librarians transitioning in the 70s
  - we could get some user journeys here
Process for further iteration
- Ghislaine will do some research and write up user journey
- Then we’ll measure roadmap against it and refine roadmap

Book collection inventory
- would be great to support barcode scanning that looks up books
DVD/Bluray collection inventory
Food inventory + grocery list creation
Health data tracking
- would be great to be able to upload Apple Health exports, Migraine Buddy exports, MyFitnessPal exports etc. and find patterns in data, correlate different types of data
Track lectures/courses that I want to watch, have already watched, etc.