Free Boolean Generator

01 · Definition

What is boolean generator?

A boolean generator creates synthetic true or false values for tests, demos and fixture files. It is useful when flags, toggles, checkbox states and validation branches need realistic variation without copying production state into lower-control environments.

The tool above sends your count, locale, seed, method and true-probability option to the Spotzee Extended API, then renders returned datatypes[] records. The upstream datatype endpoint currently supports the boolean method, with optional probability control from 0 to 1. Read the in-depth boolean generator guide for endpoint options, response fields and fixture design notes.

02 · Process

How it works

1. 1Enter a count.Type the number of boolean records to generate, from 1 to 100.
2. 2Choose the method.Use boolean, the only method exposed by the upstream datatype generator today.
3. 3Set probability.Leave probability blank for the default distribution, or send a value from 0 to 1 with up to two decimal places.
4. 4Generate records.The server validates the count, seed and probability, forwards a form-encoded request to /generic/data/generate/datatype and renders the returned boolean records.

03 · Risk

Why it matters

Boolean fields drive feature flags, opt-in states, validation branches, import toggles and UI variants. Tests often need a controlled mix of true and false values, including all-false and all-true edge cases.

Synthetic boolean data gives QA and engineering teams repeatable branch coverage without storing production state in fixture files. Probability control lets you bias output when a workflow needs mostly enabled, mostly disabled or balanced samples.

04 · Use cases

Common ways to use this tool

• Feature-flag testing. Use it as a boolean generator to create true or false values for enabled and disabled branches.
• Toggle-state fixtures. Use the random boolean generator output for switches, checkboxes and preference states.
• Import validation. Use the boolean test data generator output to test CSV, JSON and form parsers that expect boolean fields.
• Probability-biased branches. Set probability to 0, 1 or a decimal such as 0.75 when tests need a specific true rate.
• Repeatable QA datasets. Set a numeric seed so the same data generator output can be reproduced after failures.

05 · Interpretation

What to check in the result

• Count outside 1 to 100. The API accepts up to 100 boolean records per request. For larger datasets, call the endpoint multiple times.
• Probability outside 0 to 1. Use 0, 1 or a decimal such as 0.25; values above 1 are rejected.
• Too many decimal places. Probability supports up to two decimal places, so use 0.75 rather than 0.755.
• Unseeded snapshots. Set a numeric seed when tests assert exact true/false sequences or snapshot output.
• Assuming production state. Generated boolean values are synthetic sample data. Do not treat them as real customer, feature or consent states.