@Quantalabs

All the time I currently have was from when I was working on this for Unfold (which was discontinued before anyone finished). That thread is visible here.

In summary, I’ve been using the data from the University of Richmond’s Mapping Inequality site to get the HOLC grades of each census tract, and then fetching present-day data using the US Census ACS API. Since ACS data is only getting changed once a year, I fetch all that data and store it server-side so the entire website can be served as a static site.

I also plan on adding aggregate and general statistics aside from the main map, such as the number of tracts in each grade for different income levels, % of green space, etc.

The most recent comment on the development from my slack thread:
I’ll add more data from the Census (sorting through ACS docs takes really long…) later, along with more visualizations so people can understand some clearer trends in the city as a whole. I should note that I’ve scaled down to just SF because I didn’t want to rate limit when I was fetching data from the census API, but I’ll add more cities slowly as time goes on. It’s also decently fast because I’m not making any API calls except for the Geoapify map in the background. The GeoJSON for the redlining and the the JSON that has all the census data is all stored, since they don’t change other than every 5 or so years. That means that the site is pretty much static, so I removed all the server-side JS. I have a python script to refresh the data or fetch any extra census data if I add more features. I also switched from the larger neighborhood regions that the original HOLC maps had to 2020 Census Tracts, since these were the regions that the Census uses, so I can get population data.

All the time I currently have was from when I was working on this for Unfold (which was discontinued before anyone finished). That thread is visible here.

In summary, I’ve been using the data from the University of Richmond’s Mapping Inequality site to get the HOLC grades of each census tract, and then fetching present-day data using the US Census ACS API. Since ACS data is only getting changed once a year, I fetch all that data and store it server-side so the entire website can be served as a static site.

I also plan on adding aggregate and general statistics aside from the main map, such as the number of tracts in each grade for different income levels, % of green space, etc.

The most recent comment on the development from my slack thread:
I’ll add more data from the Census (sorting through ACS docs takes really long…) later, along with more visualizations so people can understand some clearer trends in the city as a whole. I should note that I’ve scaled down to just SF because I didn’t want to rate limit when I was fetching data from the census API, but I’ll add more cities slowly as time goes on. It’s also decently fast because I’m not making any API calls except for the Geoapify map in the background. The GeoJSON for the redlining and the the JSON that has all the census data is all stored, since they don’t change other than every 5 or so years. That means that the site is pretty much static, so I removed all the server-side JS. I have a python script to refresh the data or fetch any extra census data if I add more features. I also switched from the larger neighborhood regions that the original HOLC maps had to 2020 Census Tracts, since these were the regions that the Census uses, so I can get population data.

I designed the stepper mount for the axis module in Flora. It’s using the Nema 17 17HS4401 as the stepper motor, which I’ll connect to a lead screw with a 5mm to 8mm flex shaft coupler. The small box on the side is for the connectors to the base, but I need to design the board that will connect there to control the stepper board. I also spent a fair amount of time moving variables to a global variable studio for variables that I’m repeatedly using.

After the design of the board, we can move on to the toolhead, then the bed, and then the design should be complete!

BOM Development

Created a blockout Cad and did research on different parts that would be needed

So I got something like a MVP working. Essentially I’m spamming MusicBrainz with requests for each artist and what MusicBrainz categorizes as “relationships”. Those relationships, however, only include things like familial relationships or if someone was a member of a band or something like that. I need to add collaborations, features, etc.

Since requests need to be sent to MusicBrainz for every artist (which rate limits at 1/sec), I’m planning on implementing caching to speed up the processing with some artists. Additionally, I would like to be able to “score” artists in a certain way such that certain artists are favored based on the number of collaborations, genre, etc. Right now, distant requests take an insanely long time to process, since 1 query/sec prevents the app from getting through the collaborations quickly.

I made some updates to the schematic and then designed the PCB. I found footprints to Adafruits magnetic pogo pins, which I think I’ll be using to attach components and keep it modular. The PSU will be wired to the terminal on the PCB, and the 24V outputs will go to 2 XT30U connectors (not on the PCB). The case will expose the connectors and pogo pins, so new components can be added onto it.

A rough BOM:

• LCP300-24D5 PSU
• RPi Zero 2W
• Wemos D1 Mini
• 2x XT30U connectors
• 5mm pitch 2-pin screw terminal
• 2x 5-pin Magnetic Pogo Pin connectors
• IEC 320 C14 Power Socket

I had a lot of issues when deploying, mainly because the server took too long to respond. So, I added a cache file that just stores gpa and private/public school data for each school, so that the app doesn’t need to send thousands of requests for a valid school. Now, response times are down to a couple seconds at most, but usually <1 second, which I’m okay with for now.

Added actual filtering functionality using collegedata.fyi to get CDS data. I’m having issues distinguishing between public and private, so I may remove that functionality or try and distinguish schools by if they charge different in- and out-of-state tuition.

(yes i did create an object that has all 50 states split among 5 different regions)

I setup the express project and landing page so far. I used the MD.css retro framework to style the website. I added a bit of other CSS to make the form look a bit better. I currently have a couple criteria by which users can filter schools (the actual filtering functionality will be implemented soon)

Completed the initial schematic for the base. I’m not completely sure this will even work as is. I have AC power from any wall outlet going into the PSU (likely a LCP300-24D5), and I use the 5V output to power the RPi and ESP board. I plan on using an I2C bus to communicate between the modules and the RPi, and UARC to communicate between the ESP and RPi, which I think I wired correctly? Then I have the 24V outputs from the PSU that I need to use, which will eventually be powering the motors. I need to add a switch between the PSU and receptacle so that you can turn the printer off and some XT30U connectors so the modules can get 24V power.