faker
Java Faker
faker | Java Faker | |
---|---|---|
9 | 13 | |
17,246 | 4,612 | |
- | 1.1% | |
9.5 | 0.0 | |
6 days ago | 4 days ago | |
Python | Java | |
MIT License | GNU General Public License v3.0 or later |
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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.
faker
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Leveling up your custom fake data with Faker.js
Faker was originally written in Perl and is also available as a library for Ruby, Java, and Python.
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The Uncreative Software Engineer's Compendium to Testing
Faker: a library that generates fake data that can be useful when you need data to test for various components.
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Exploring LLMs for Data Synthesizing & Anonymization: looking for Insights on Current & Future Solutions
Don't get me wrong, LLMs are awesome but totally unsuited for what you are describing. Classic data science tools like faker will be better for the task in pretty much every aspect. They can generate synthetic datasets and anonymize existing ones faster and far more reliable than any LLM.
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Undercover work
The Python package, Faker, is just what you're looking for!
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Is there a way to automate testing in python? In my case :
for datatypes like string/date and other stuff, there is a Python library called faker, which you can use. It can generate fake names, fake phone numbers, dates, and addresses. here is the link to the documentation. https://faker.readthedocs.io/ here is a link to a blog post explaining Faker. https://levelup.gitconnected.com/pythons-faker-library-your-go-to-solution-for-test-data-generation-3a070065cc04
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Testing files in Python like a pro
Then test cases became more complex. Primary data sources were often files. We needed to test pipelines. Faker still helped a lot, but it was not convenient to copy your last-best-approach for files and reinvent the wheel over and over with each project.
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Database automation challenges and how to solve them
For a cloud-based solution, one can write their own Terraform or CloudFormation for installation as soon as their RDS instance boots up with appropriate security and authentication details. For a local dev environment, one can rely on Faker to create mock database data for your database.
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How to create a 1M record table with a single query
Creating realistic fake data is useful in lower environments and for load testing. Outside of SQL I like faker: https://github.com/joke2k/faker
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DuckDB: an embedded DB for data wrangling
To test a database, first you need some data. So I created a python script and used Faker to create the following CSV files:
Java Faker
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Leveling up your custom fake data with Faker.js
Faker was originally written in Perl and is also available as a library for Ruby, Java, and Python.
- Built a library to help generate test pojos with relevant but random data. I’d love some feedback.
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Data Seeding With MongoDB
you can use faker java
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Favorite hidden gem library?
JavaFaker for generating random data https://github.com/DiUS/java-faker
- Estudo sobre HTTP2 e protocolos binários - parte 2
- Estudo sobre HTTP2 e protocolos binários - parte 1
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Datafaker: An Alternative to Using Production Data
I've been using https://github.com/DiUS/java-faker which seems to be much more popular. How is this one different?
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Cucumber java Cannot resolve symbol 'github' when adding Faker to project
I'm using 1.0.2 from this repository: https://github.com/DiUS/java-faker
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The right to delete: how faker.js exposed the fragile nature of open source culture, again
I'm Java developer. While we have had our fair share of shenanigans, if the people behind the Java equivalent of faker (https://github.com/DiUS/java-faker) went off the rails it wouldn't be anywhere near as much of an issue.
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Datafaker, an alternative to using Production Data
This has another bottleneck, each time you request something, it ends up with a IO call to open a file, as all fake data is stored in a file: https://github.com/datafaker-net/datafaker/blob/master/src/main/resources/en/dragon_ball.yml I recently filed a bug to javafaker that in some cases file descriptor was never closed, resulting in even worse performance and memory leaks, killing our service after millions of method calls.
What are some alternatives?
Mimesis - Mimesis is a robust data generator for Python that can produce a wide range of fake data in multiple languages.
datafaker - Generating fake data for the JVM (Java, Kotlin, Groovy) has never been easier!
FauxFactory - Generates random data for your tests.
instancio - A library that creates fully populated objects for your unit tests.
fake2db - create custom test databases that are populated with fake data
Deep Dive - Fluent assertions library for Java
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.
faker - A library for generating fake data such as names, addresses, and phone numbers. [Moved to: https://github.com/faker-ruby/faker]
PyRestTest - Python Rest Testing
avoid-random-string-utils - Example of the RandomStringUtils class vs JavaFaker to generate data
radar
fixture-monkey - Let Fixture Monkey generate test instances including edge cases automatically