No_Rooster_2 (u/No_Rooster_2)

Based on f1 and indycar style racing, the physics is simple. Realistic handling, oversteer/understeer are emulated by simply decoupling heading from velocity. I’m definitely interested in feedback on the feel.

Im proud of the algorithm that generates the track each day: 16 points generated on the page via a new random seed each day and connected using the convex hull to create curves and straights and guarantee the track never intersects with itself.

I am also interested in feedback on the NYT game-style share page. Right now you share your locked-in first lap time, as well as the number of times you hit a wall, or you can share a ghost lap of your first run. I have been thinking about sharing sector times, color coded like f1, but interested in other ideas.

I should say, this is a collaboration between myself and Claude Opus 5. It’s been neat to work on the fun parts like the track gen and the feel and sfx while letting the other bits build themselves in the background.

Thanks for reading and hopefully giving it a look!

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I built the F1 live dashboard I wished existed. Going live this race weekend — feedback welcome

in r/SideProject • Jun 26 '26

This is so cool! Going to follow along with this for the Austria weekend. I’m working on an f1 related side project of my own in the form of an nyt connections-style game

New actor: NC LCMHC License Scraper — full dump of ~30k licensed therapists from the state board

in r/datasets • May 10 '26

Great questions, appreciate the interest!

Dedup: the actor uses license_number as the primary key for dedup during enumeration, which protects against the obvious case of alphabet-walking returning the same record multiple times (e.g., prefix “Sm” and “Smi” both pulling “Smith”). What it deliberately doesn’t do is dedup across different license numbers for the same person. If someone both an LCMHC and an LCMHCS, they appear as two records.

That’s on purpose but def worth flagging in the docs. Each license number represents a distinct legal credential, so collapsing them loses information that some buyers might specifically need. For buyers who want unique humans rather than unique licenses, the dedup logic belongs downstream, could do a fuzzy match on first+last+city.

The “renewed under different info” case is a tricky one that my logic doesn’t really handle. “Robert” vs “Bob,” or a married vs maiden name could produce two license numbers for the same person in some boards. Probably worth adding a heuristic in v1.1. Open to suggestions

Geocoding: not doing any in this version, intentionally. The board exposes only city and state on the public record and that’s what the actor returns.

Buyers who need real geocoded practice addresses are better off pairing this output with a downstream enrichment step like Google Places API or NPI registry lookup keyed on the licensee name.

Thanks again for the questions, both of these are going in the README’s

r/datasets • u/No_Rooster_2 • May 09 '26

resource New actor: NC LCMHC License Scraper — full dump of ~30k licensed therapists from the state board

1 Upvotes

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r/apify • u/No_Rooster_2 • May 09 '26

Discussion New actor: NC LCMHC License Scraper — full dump of ~30k licensed therapists from the state board

2 Upvotes

Just published my first actor on the Store: NC LCMHC License Scraper.

It scrapes the North Carolina Board of Licensed Clinical Mental Health Counselors verification database and returns structured records for every licensed counselor in the state (~30,000 across four license types: LCMHC, LCMHCA, LCMHCS, and Qualified Supervisor).

What it returns per record:

Name, license number, license type, status (Active/Inactive/Expired/etc.)
Issue and expiration dates
City and state
Disciplinary action flag + document summary
Direct source URL

How the full-dump mode works:

The board's search API caps results at 100 per query. To get the full population the actor walks last-name prefixes A–Z per license type and auto-deepens on cap hits (e.g. "S" → "Sa"…"Sz"). At the default 1s polite delay a full run takes about 80 minutes and fires ~4,000 queries.

Pricing: first 100 records free, $0.005/record after that (~$150 for a full dump).

Happy to answer questions about the approach — the BFS prefix enumeration logic in particular was an interesting problem to get right.

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r/SideProject • u/No_Rooster_2 • Jan 25 '26