Mimesis VS FauxFactory

Compare Mimesis vs FauxFactory and see what are their differences.

Mimesis

Mimesis is a powerful Python library that empowers developers to generate massive amounts of synthetic data efficiently. (by lk-geimfari)

FauxFactory

Generates random data for your tests. (by omaciel)
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Mimesis FauxFactory
3 -
4,300 37
- -
9.1 2.6
3 days ago over 1 year ago
Python Python
MIT License Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

Mimesis

Posts with mentions or reviews of Mimesis. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-04-12.

FauxFactory

Posts with mentions or reviews of FauxFactory. We have used some of these posts to build our list of alternatives and similar projects.

We haven't tracked posts mentioning FauxFactory yet.
Tracking mentions began in Dec 2020.

What are some alternatives?

When comparing Mimesis and FauxFactory you can also consider the following projects:

faker - Faker is a Python package that generates fake data for you.

fake2db - create custom test databases that are populated with fake data

picka - pip install picka - Picka is a python based data generation and randomization module which aims to increase coverage by increasing the amount of tests you _dont_ have to write by hand.

radar

callee - Argument matchers for unittest.mock

aiounittest - Test python asyncio-based code with ease.

pytest-fastapi-deps - This library allows you to easily replace FastAPI dependencies in your tests. Regular mocking techniques do not work due to the inner working of FastAPI.