Generate realistic-looking fake data for your Prisma models

Hacker News

At work, we're migrating from Mongoose to Prisma + PostgreSQL. When we started migrating the integration tests, I noticed that we were spending a lot of time creating fake objects to populate the database before the tests. Previously, our factory methods were all untyped (they were created before our migration to TS), so it was hard to make them work with Prisma. Also, every time we add or remove a field, the factories would break. That's when I decided to investigate if there was a better way. `prisma-generator-fake-data` allows you to easily generate realistic fake data that you can use for testing, prototyping, or anything in between. If you're using JSON fields in Prisma, it allows you to provide your own fake data generator function. Let me know what you think!

Visit product View on Hacker NewsMar 27, 2023

Share card

Actual performance

2points

Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →

Product HuntOn track for Day 1 leaderboard · Strong signals: model, models, using · Missing: mac, agents, macos

70%70% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Indie HackersFits the IH revenue-focused audience · Strong signals: created, started · Missing: supports, reddit linkedin, podcasting

63%63% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive

52%52% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released

46%46% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRLess likely to generate early MRR · Strong signals: way · Missing: mobile apps, ios, personal

41%41% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

19%19% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

Similar products

Schematic Ipsum - generate realistic fake JSON data65%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Schematic Ipsum - generate realistic fake JSON data

Hacker News3

Fakid – generate fake identities58%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Fakid – generate fake identities

Hacker News10

I made a website to generate 1000s of rows of fake data56%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

I made a website to generate 1000s of rows of fake data

Hacker News1

Plait.py – a fake data modeler49%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Plait.py – a fake data modeler

Hacker News85

Glassdoor without fake data: KnowYourWorth64%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Glassdoor without fake data: KnowYourWorth

Hacker News11

FakerFill62%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Fill web forms instantly with realistic fake data

Indie Hackers1programming

Look Busy – Realistic-Looking Fake Calendar Events54%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Look Busy – Realistic-Looking Fake Calendar Events

Hacker News8

Temply.in – Fake Email Generator53%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Generate realistic fake emails for testing and privacy in 1

Indie Hackers1email-marketing

Faker.jl: generator of fake data for julia58%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Faker.jl: generator of fake data for julia

Hacker News2

Faker – Struct Data Fake Generator in Go58%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Faker – Struct Data Fake Generator in Go

Hacker News34

Browse all products Analyze your launch