Count numbers in text

It recognizes whole numbers, signed values, standard decimals, and leading-dot decimals without attempting to interpret the surrounding words. That makes it useful when you need a quick content summary, a lightweight extraction step, or a repeatable check before sending text into a larger data workflow. The same deterministic rules apply every time, whether the input is a sentence, report, log excerpt, or pasted table.

What the counter recognizes as a number

The scanner treats each contiguous integer or decimal group as one match. Whole values such as 42, signed values such as -7 and +12, ordinary decimals such as 19.95, and leading-dot decimals such as .75 are recognized. A run of digits stays together, so 2026 counts once rather than four times. The sign belongs to a number when it appears immediately before the numeric group. Returned matches preserve their original text and order, which means you can see exactly what produced the total instead of receiving an unexplained count. The rules intentionally focus on simple integer and decimal notation. Thousands separators, currency symbols, percentages, units, and surrounding punctuation are not normalized or interpreted. For example, a currency symbol remains outside the match while its following numeric group is counted. Scientific notation is not combined into a special numeric value; its visible numeric groups are scanned according to the same straightforward pattern. This narrow definition makes results predictable for content audits and extraction pipelines, especially when the source mixes prose, labels, and measurements.

How to read and verify the result

Send one text string and read the returned count for the summary. The accompanying matches array lists every detected group from left to right, retaining signs, decimal points, and digits exactly as written. That second field is useful for quality control: if a document produces an unexpected count, you can inspect the matches immediately and identify whether the source uses notation outside the supported rules. Empty text is valid and returns zero with an empty array, while a missing or non-string text field is rejected as invalid input. This distinction prevents absent data from being silently mistaken for a document containing no numbers. The implementation performs one bounded scan and does not make network requests, call a model, use locale-dependent parsing, or modify the supplied text. Consequently, repeated calls with the same string produce the same JSON. When integrating the endpoint, store the match list alongside the count if traceability matters. If only a dashboard total is needed, consume the count and discard the list. For very structured numeric formats, follow this counter with a domain-specific parser rather than assuming each returned string is already a validated business value.

Using number counts in practical workflows

A number count is a compact signal that fits many lightweight checks. Content teams can compare drafts and confirm that a supposedly data-rich summary still contains the expected quantity of figures. Analysts can scan copied notes before manually transferring measurements, while developers can use the match array as a first extraction pass over logs, tickets, or plain-text exports. In ingestion systems, the result can support simple routing: text with no numeric groups may follow a narrative path, while text containing several groups can be queued for deeper parsing. The endpoint is also helpful in tests where a generated report should contain a stable number of numeric tokens even though the actual values change. Remember that this tool counts notation, not meaning. A date such as 2026-07-25 contains three numeric groups, because punctuation separates the year, month, and day. A version label, identifier, or number embedded beside letters may still contribute a numeric group. Those behaviors are useful for broad extraction, but they may not match every semantic definition of a number. Use the returned evidence to apply any domain rule afterward. Browser use is free, and automated API requests use the displayed $0.002 base price, making the same operation suitable for an occasional paste or a repeatable pipeline.