namegender for R

client <- namegender(Sys.getenv("NAMEGENDER_API_KEY"))
result <- ng_name(client, "Ayşe", country = "TR")
result$gender
result$sample_size

Options and response

ng_name(), ng_email(), ng_username() and ng_bulk() pass extra arguments to the API, such as ai_fallback = TRUE and best_guess = TRUE:

ng_name(client, "Andrea", country = "IT", best_guess = TRUE)

A result carries query, name, first_name, middle_name, last_name, name_type, gender, country, probability, sample_size, took_ms, source, confidence and matched_as, alongside credits_charged, credits_remaining, data_version and request_id. Success is the HTTP status: a non-2xx response stops with the API’s message.

Country hints

Without a country, pass what you know about your end user and the API picks the country from it: locale (a language tag such as "it-IT" or "pt_BR"; a tag without a region, such as "en", sets no country) or ip (the user’s IP address, not stored by the API). The priority is country > locale > ip.

result <- ng_name(client, "Andrea", locale = "it-IT", ip = "203.0.113.7")
result$country_source   # "country", "locale", "ip", or NULL when none applied

ng_email(), ng_username() and ng_bulk() take the same arguments. For ng_bulk(), country_source is on the response envelope (next to took_ms), not on each row of results. File jobs and ng_countries() do not take them.

Country distribution

Which countries a name is recorded in. This is not a country-of-origin or ethnicity inference: registrations is counted volume, comparable only among the countries that publish counted birth statistics, and attested_in is presence with no weight attached. Show basis$note next to any percentage.

dist <- ng_countries(client, "Mehmet", limit = 10)
dist$registrations[, c("country", "share")]
dist$attested_in

Salutation

A ready-to-use salutation for a letter or an email, in en, de, fr, es, it, pt, nl, tr, pl or ja (and regional variants such as de-AT or pt-BR). Without language it follows locale, then the country, then English.

result <- ng_salutation(client, "Dr. Anna Müller", language = "de")
result$salutation$formal     # "Sehr geehrte Frau Dr. Müller,"
result$salutation$informal   # "Liebe Anna,"

ng_salutation(client, "Ahmet Yılmaz", language = "tr")$salutation$formal   # "Sayın Ahmet Bey,"

# Names stored in separate fields are used as they are, not parsed:
ng_salutation(client, first_name = "Anna", last_name = "Müller", title = "Dr.", language = "de")

bulk <- ng_salutation_bulk(client, c("Dr. Anna Müller", "Müller GmbH"), language = "de")
bulk$results$salutation$formal
bulk$summary   # total, gendered, neutral, organization

One credit per name. When the gender is not certain enough (min_probability, default 90), you get the neutral form rather than a guess: form is "gendered", "neutral" or "organization", and reason says why it is not gendered ("gender_unknown", "below_min_probability", …). best_guess does not apply here. If you already know the gender, pass gender = "female", "male" or "neutral". ng_salutation_bulk() takes up to 100 names and returns results in input order. An unsupported language is a namegender_error with status 422 and body$supported.

Name check

Whether a name typed into a form looks like a real person’s name, with the reasons. It never calls a name fake: use it to flag records for a closer look, not to reject people automatically.

result <- ng_name_check(client, "asdf qwerty")
result$assessment   # "implausible"
result$score        # 0 (0-100)
result$signals      # data frame: code, severity, part, value

ng_name_check(client, "Jennifer Null")$assessment   # "plausible"

# Names stored in separate fields are used as they are, not parsed:
ng_name_check(client, first_name = "Jennifer", last_name = "Null", country = "US")

bulk <- ng_name_check_bulk(client, c("Jennifer Null", "asdf qwerty"))
bulk$results[, c("query", "assessment", "score")]
bulk$summary   # total, plausible, suspicious, implausible

One credit per name. assessment is "plausible", "suspicious" or "implausible"; each signal has code, severity (high, medium, low, info, positive), part and value (either can be NA). evidence says whether the first name is counted, attested or not found. Surnames are judged by their shape only. It takes country, locale and ip, not best_guess or ai_fallback. ng_name_check_bulk() takes up to 100 names and returns results in input order.

File jobs

Upload a CSV or XLSX file (up to 100 MB and 1,000,000 rows) and get it back with gender columns added. One credit per row, charged only if the job completes.

job <- ng_batch_create(client, "customers.csv",
  name_column = "first_name",   # required to start
  country_column = "country"    # optional: a country code per row
)

done <- ng_batch_wait(client, job$id, on_progress = function(j) message(j$progress, "%"))
if (done$status == "failed") stop(done$error$code)

ng_batch_download(client, done$id, "customers-gender.csv")
result <- read.csv("customers-gender.csv", fileEncoding = "UTF-8-BOM")

name_column is required to start: a guessed column that turns out to be wrong would spend credits on the wrong data. To see the columns and the cost first, upload with start = FALSE, read job$inspection, then call ng_batch_start(client, job$id, name_column = ...).

ng_batch_create() sends an Idempotency-Key and retries connection errors and 502/503/504 with the same key, so a retry never opens a second job. Pass your own idempotency_key to keep that guarantee across your own retries.

ng_batch_wait() returns a failed job rather than stopping; branch on job$error$code. ng_batch_cancel() returns the credit of a job that has not started, and deletes a finished one. ng_batch_list(client, limit =, page =) includes jobs started from the dashboard. Up to three jobs can be queued or running at once; a fourth is refused with 429 too_many_batches.

An API error is a condition of class namegender_error carrying status and body (error, message, request_id, docs). Branch on body$error, not on the message:

tryCatch(
  ng_batch_create(client, "customers.csv", name_column = "ad"),
  namegender_error = function(e) if (identical(e$body$error, "invalid_input")) print(e$body$columns) else stop(e)
)

The result appends gender, probability, sample_size, country, source, matched_as, first_name, middle_name, last_name and name_type to every row. A CSV result starts with a UTF-8 byte order mark; read it with fileEncoding = "UTF-8-BOM". ng_batch_download() without a path returns the file as a raw vector.

Webhooks

Add an endpoint under Webhooks in the dashboard, and NameGender sends a signed POST to it when a file job completes or fails, and when credits are about to run out (credits.low) or have run out (credits.depleted, checked hourly). ng_webhook_verify() checks the signature and the timestamp, and returns the event.

# plumber.R
#* @post /namegender
#* @serializer unboxedJSON
function(req, res) {
  event <- tryCatch(
    namegender::ng_webhook_verify(
      req$bodyRaw,                      # the raw bytes, not the parsed body
      req$HTTP_NAMEGENDER_SIGNATURE,
      Sys.getenv("NAMEGENDER_WEBHOOK_SECRET")
    ),
    namegender_webhook_error = function(e) NULL
  )
  if (is.null(event)) {
    res$status <- 400
    return(list())
  }

  if (event$type == "batch.completed") {
    job <- event$data$object   # the job, as ng_batch_get() returns it
    # ...
  }
  res$status <- 204
  list()
}

Answer quickly and do slow work afterwards. Anything other than a 2xx within 10 seconds is retried, up to 8 attempts over about 45 hours. Use event$id (also the NameGender-Event-Id header) to ignore a delivery you have already handled: a retry carries the same id, and order is not guaranteed.