— chars

— bytes (utf-8)

— words

— lines

— unique chars

— entropy (bits/char)

character frequency

paste or type text…


              curl -sX POST 'https://api.whittly.dev/v1/string/inspect' \
  -H 'Authorization: Bearer $WHITTLY_API_KEY' \
  -H 'Content-Type: application/json' \
  -d '{"input":"hello, world!"}'


              const res = await fetch('https://api.whittly.dev/v1/string/inspect', {
  method: 'POST',
  headers: {
    'Authorization': 'Bearer ' + apiKey,
    'Content-Type': 'application/json',
  },
  body: JSON.stringify({ input: "hello, world!" }),
});
const data = await res.json();


              const { data } = await axios.post(
  'https://api.whittly.dev/v1/string/inspect',
  { input: "hello, world!" },
  { headers: { Authorization: 'Bearer ' + apiKey } }
);

// prohistory syncpro·bulk analysis via APIproupgrade →

// about this tool

Text is more complex than it appears — a string's byte length differs from its character count when it contains multi-byte Unicode characters (emoji, CJK characters, accented letters). Shannon entropy measures the information density of the string and can detect patterns or randomness.

// when to use

Check if a string fits within a database column's byte limit
Detect high-entropy (random) strings like tokens or passwords
Analyze character distribution in text data
Find invisible characters or zero-width spaces in a string

// faq

Why is the byte count different from the character count?

UTF-8 encoding uses 1 byte for ASCII characters, 2 bytes for Latin Extended and Greek, 3 bytes for most CJK characters and emoji, and 4 bytes for supplementary emoji. A single emoji like 🔥 is 1 character but 4 bytes.

What is Shannon entropy?

Shannon entropy measures the average information per character. A string of all identical characters has 0 entropy. A random string of bytes has ~8 bits of entropy. Passwords should have high entropy; natural language text is typically around 4–5 bits per character.

// related tools

// about this tool

// when to use

// faq