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nordstatExtras

Shared SQLite cache backend for the nordstat family of R packages: rKolada, rTrafa, and pixieweb.

Why

The three nordstat packages each ship a per-package .rds cache that works fine for single-user scripts but falls short in multi-user web applications:

• No concurrent-write safety
• Cache granularity is the whole query, not the individual value — two overlapping queries refetch the same cells
• Metadata is cached but actual data values (get_values(), get_data()) are not

nordstatExtras replaces this with a single SQLite database shared across processes. Values are stored at cell granularity, deduplicated across overlapping queries, and expire based on the age of the cell itself — a refresh by one query propagates to every query that references the same cell.

Install

# install.packages("devtools")
devtools::install_github("LCHansson/nordstatExtras")

Use

Open a cache once per deployment, then hand it to the source packages via their cache_location argument:

library(nordstatExtras)

handle <- nxt_open("cache.sqlite")

# rKolada
kolada_vals <- rKolada::get_values(
  kpi = c("N03700", "N03701"),
  municipality = c("0180", "1480"),
  period = 2020:2024,
  cache = TRUE,
  cache_location = handle
)

# rTrafa
trafa_vals <- rTrafa::get_data(
  "t10011", "itrfslut",
  ar = c("2023", "2024"),
  cache = TRUE,
  cache_location = handle
)

# pixieweb
scb <- pixieweb::px_api("scb")
px_vals <- pixieweb::get_data(
  scb, "BE0101N1",
  Region = c("0180", "1480"),
  Tid = px_top(5),
  cache = TRUE,
  cache_location = handle
)

nxt_close(handle)

All three calls store their data in the same SQLite file. On a cache hit the source package skips the HTTP fetch entirely; on a miss it fetches, normalizes to cell format, and UPSERTs.

Design

• Cells: the cells table stores one row per statistical datum with a composite UNIQUE key (source, api_alias, entity_id, variable, period, dims_hash, lang). Overlapping queries deduplicate.
• Dimensions: arbitrary package-specific dimensions live in a sidecar cell_dims table, keyed by a hash of the dimension vector.
• Queries: the queries table plus a query_cells junction lets the handler look up which cells a given call originally produced, so it can reconstruct the source package’s expected tibble shape on load.
• TTL (cell-level): a query is fresh iff every cell it expects is present and the oldest cell is younger than max_age (default 30 days). Cross-query refreshes propagate automatically.
• Async writes: optional mirai-backed background flushing via nxt_write_async() + nxt_flush(). Falls back to sync when mirai is not installed.
• Multi-process: SQLite runs in WAL mode with synchronous = NORMAL, safe for concurrent readers and serial writers.

Maintenance

handle <- nxt_open("cache.sqlite")

# Drop a source entirely
nxt_clear(handle, source = "kolada")

# Delete stale cells (default 30-day TTL)
nxt_gc(handle)

nxt_close(handle)

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.