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zentraR is an R client for the ZENTRA Cloud v5 API. It gets you
from “I have an API key” to “I have a tidy, up-to-date data
frame of my sensor readings” in a few lines — handling
authentication, pagination, rate limits, and reshaping so you can get
straight to analysis.
zc_list_devices()
lists every device your key can access.zc_get_readings()
returns one row per measurement, ready for dplyr /
ggplot2, with a zc_pivot_wider() helper for a
spreadsheet layout.zc_sync() fetches only what’s new and appends it to your
store of choice: native R files (zc_store_rds()), plain CSV
(zc_store_csv()), or nothing at all (return-only, for
loading into your own database).zc_sync() on
file open, daily, or weekly. See the Scheduling automatic syncs
vignette.Install from the METER Group public packages group on GitLab:
# install.packages("remotes")
remotes::install_gitlab("meter-group-inc/pubpackages/zentraR")Alternatively, download the package file
(zentraR_0.1.0.tar.gz) from the
Installation section of the Getting
Started with zentraR guide and install it locally:
install.packages(c("httr2", "cli", "rlang", "tibble", "tidyr", "vctrs"))
install.packages("zentraR_0.1.0.tar.gz", repos = NULL, type = "source")Get your API key from ZENTRA Cloud: User Account →
Integrations → Show Token (https://app.zentracloud.io/profile/integrations). Then
either set it for the session, or save it to your .Renviron
so it’s always available:
library(zentraR)
zc_set_key("your-api-key") # this session only
zc_set_key("your-api-key", install = TRUE) # persist across sessionslibrary(zentraR)
# 1. What devices can I see?
devices <- zc_list_devices(expand = "max_min_timestamp")
devices
# 2. Pull the last week of readings for one device (tidy long format).
readings <- zc_get_readings("z6-00930", start = Sys.Date() - 7)
readings
# 3. Reshape to one column per measurement.
zc_pivot_wider(readings)
# 4. Add human-readable quality flags.
zc_label_errors(readings)zc_sync() remembers what you already have and fetches
only newer readings, so you can run it on a routine. Pick where the data
lives:
# Persist as CSV (accessible to non-R tools):
store <- zc_store_csv("data/zentra")
# First run backfills history; later runs fetch only what's new:
zc_sync("z6-00930", store = store, start = Sys.Date() - 30)
zc_sync("z6-00930", store = store) # incremental
# Sync every device your key can access:
zc_sync(store = store)
# Read your accumulated data back:
zc_store_read(store)Prefer native R objects for an RStudio project? Use
zc_store_rds("data/zentra"). Piping into your own database?
Pass store = NULL and zc_sync() simply returns
the new readings.
The v5 API is limited per key: roughly a 5-request burst, then about
one request per minute. zentraR respects this automatically
(pacing and retrying), but very large historical backfills will take
time. Because zc_sync() is incremental and resumable,
routine top-ups stay well within the limit.
Built-in vignettes:
vignette("getting-started", package = "zentraR")
vignette("working-with-data", package = "zentraR")
vignette("scheduling", package = "zentraR")Online (kept current with the API) on ZENTRA Cloud:
MIT © METER Group, Inc.
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.