factory_boy
faker
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factory_boy | faker | |
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3 | 9 | |
3,395 | 17,064 | |
1.0% | - | |
6.9 | 9.4 | |
8 days ago | 6 days ago | |
Python | Python | |
MIT License | MIT License |
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.
factory_boy
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Embracing Modern Python for Web Development
Factory Boy doesn't currently support asynchronous operations, but there is an async-factory-boy extension with enough async support for most use cases. There is also an open pull request in Factory Boy with recent updates (July 2023) that will hopefully be merged soon.
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Testing files in Python like a pro
You can use it with Faker and factory_boy (for ORM integration).
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Five Easy to Miss PostgreSQL Query Performance Bottlenecks
When releasing a new application (or feature) I've always loaded each table in my development environments database with a few million rows. Tools like Python's Factory Boy [1] or Ruby's Factory Bot [2] make this trivial.
After the data is loaded up, start navigating through the application and it will become evident where improvements need to be made. Tools like Django Debug Toolbar [3] help expose where the bad ORM calls are or also by tailing Postgres log files.
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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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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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
What are some alternatives?
Mimesis - Mimesis is a powerful Python library that empowers developers to generate massive amounts of synthetic data efficiently.
mixer - Mixer -- Is a fixtures replacement. Supported Django, Flask, SqlAlchemy and custom python objects.
model_mommy
FauxFactory - Generates random data for your tests.
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.
PyRestTest - Python Rest Testing
callee - Argument matchers for unittest.mock
Selenium Wire - Extends Selenium's Python bindings to give you the ability to inspect requests made by the browser.
radar
mqtt-explorer - MQTT Explorer - MQTT Subscriber client to explore topic hierarchies