Efficient token use

The API is metered in tokens: one per returned row, minimum one per request, and 10 per isochrone contour. Tokens are rows, so spending well is mostly about not asking for rows you will throw away.

Free queries

Metadata queries are free and keyless: $modes(), $destination_types(), $vintage(), $places(), $isochrone_meta(), $last_updated(), and $health(). Do your lookups before you spend a token.

Revalidation is free too. Keep a reply’s etag and pass it back as if_none_match; an unchanged response returns a free 304. Read output = "raw" when you want the etag:

close$output <- "raw"
first <- close$block_summary(geoid = "440070008001068", mode = "walk")
again <- close$block_summary(
  geoid = "440070008001068",
  mode = "walk",
  if_none_match = first$etag
)
again$not_modified   # TRUE, and nothing was charged

The big levers

The rows a query returns multiply out as modes times types times blocks:

Pass mode. Omitting it returns all three modes, so three times the rows.
Filter by type. The POI and areal routes take a destination type, so ask the server for only the category you want rather than fetching everything and filtering in R. Look the id up in $destination_types().
Request leaf types, not parents. A parent type expands to its leaves, so a single leaf id is a fraction of the rows of a parent like parks.
Shrink the area. Cost grows with the square of radius_m, so halving the radius is roughly a quarter of the tokens.
Use max_minutes. It drops rows you would filter out anyway.

Isochrones are the cheap reach primitive

An isochrone is 10 tokens per contour regardless of area, and format = "blocks" returns every reachable block with its minutes. A whole walkshed for 10 tokens, where a catchment or block query charges per block:

shed <- close$isochrone(
  block = "440070008001068",
  minutes = 30,
  mode = "walk",
  format = "blocks"
)

Watch what you spend

Every metered reply carries the token counts. In the frame output modes they are attached as attributes; in output = "raw" they are on the reply. Here the type filter asks only for supermarkets, so you pay for a handful of rows, not every POI in the radius:

close$output <- "tabular"
types <- close$destination_types()
supermarket_dest_type <- types[types$label == "grocery_stores", ]$dest_type_id

supermarkets <- close$pois_search(
  lat = 41.823,
  lon = -71.412,
  radius_m = 1200,
  type = supermarket_dest_type
)
attr(supermarkets, "tokens_charged")
attr(supermarkets, "tokens_remaining")

When you only want the numbers, output = "tabular" skips the block-boundary download entirely. The block boundaries the spatial mode joins are cached locally, so re-running a script costs time, not tokens; pass a block_geometry frame you already have to skip even that.