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Random Unix Timestamp Generator

Used by developers, writers, and creators worldwide.

A random Unix timestamp generator solves a tedious problem every backend developer hits: you need realistic epoch values fast, without writing a throwaway script or computing offsets by hand. This tool produces batches of timestamps across any date range you define, outputting values in seconds, milliseconds, or both formats at once, each paired with a human-readable date string so you can sanity-check results immediately. Set the start and end year, choose how many timestamps you need, and pick your format. Want 20 timestamps scattered between 2010 and 2020 for seeding a Postgres staging table? Done in one click. The output is ready to paste directly into a fixture file, seed script, or API mock.

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How to use

  1. Choose your options above
  2. Click Generate
  3. Copy your result

Detailed instructions

  1. Set the Count field to the number of timestamps you need, between 1 and however many your project requires.
  2. Enter a Start Year and End Year to define the date window the random timestamps will fall within.
  3. Choose an output format: seconds only, milliseconds only, or both columns side by side with a readable date.
  4. Click Generate to produce the batch; review the human-readable dates in the output to confirm the range looks correct.
  5. Copy the timestamp values directly into your database seed file, test fixture, or code — one per line, ready to use.

Use Cases

  • •Seeding created_at and updated_at columns in a Postgres or MySQL staging database
  • •Generating mock Kafka event messages with realistic, spread-out event times
  • •Testing JavaScript date-parsing functions that expect millisecond-precision epoch values
  • •Building sample time-series datasets in a Jupyter notebook for data science coursework
  • •Populating API reference docs with believable timestamp examples across multiple decades

Tips

  • →For PostgreSQL, use seconds format; for JavaScript or MongoDB, use milliseconds — mismatching causes silent date errors 50 years off.
  • →Generate 20% more timestamps than you need, then deduplicate in your import script to guarantee uniqueness without reruns.
  • →Narrow the year range to a single year when you want test data that mimics records from a real product launch or event.
  • →If your system logs store ISO 8601 strings, use the human-readable date column this generator outputs as a cross-check before import.
  • →To simulate realistic traffic spikes, generate two separate batches with different year ranges and combine them in your test dataset.
  • →Timestamps near 2038-01-19 are useful as boundary test cases for any system that still stores dates in a 32-bit signed integer field.

FAQ

seconds vs milliseconds unix timestamp — which should I use?

Seconds-based timestamps (10 digits) are the traditional Unix standard used by PostgreSQL, Python's time module, and most server-side languages. Milliseconds (13 digits) are the default in JavaScript's Date.now() and most browser APIs. If you're unsure, select 'both' in the format dropdown and copy whichever column matches what your code expects.

how do I convert a unix timestamp back to a readable date in code

In JavaScript, use new Date(ts).toISOString() for milliseconds or new Date(ts * 1000).toISOString() for seconds. In Python, call datetime.utcfromtimestamp(ts). This generator already displays the human-readable date next to every value so you can verify the range before copying the list into your project.

are randomly generated unix timestamps safe to use in production test data

Yes — they're just integers representing moments in time, containing no personal or sensitive information. The values are statistically unlikely to collide in small batches across a wide year range. If your schema requires strict uniqueness, generate a slightly larger batch and deduplicate before importing into your fixture or seed file.