pointblank VS strict

Compare pointblank vs strict and see what are their differences.

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pointblank strict
3 2
826 224
1.3% -
9.4 -
about 1 month ago over 3 years ago
R R
GNU General Public License v3.0 or later -
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.

pointblank

Posts with mentions or reviews of pointblank. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-03-02.

strict

Posts with mentions or reviews of strict. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-03-02.
  • R: Introduction to Data Science
    4 projects | news.ycombinator.com | 2 Mar 2024
    (1) You might want to check out https://github.com/t-kalinowski/Rapp by my colleague Tomasz

    (2) I think part of that is in scope for strict (https://github.com/hadley/strict). You might also be well served by adopting some more data validation tooling, e.g. pointblank (https://rstudio.github.io/pointblank/).

What are some alternatives?

When comparing pointblank and strict you can also consider the following projects:

pandera - A light-weight, flexible, and expressive statistical data testing library

allure-environment-writer - Java library which allows to write environment.xml file into allure-results directory.

allure-docker-service - This docker container allows you to see up to date reports simply mounting your "allure-results" directory in the container (for a Single Project) or your "projects" directory (for Multiple Projects). Every time appears new results (generated for your tests), Allure Docker Service will detect those changes and it will generate a new report automatically (optional: send results / generate report through API), what you will see refreshing your browser.

soda-core - :zap: Data quality testing for the modern data stack (SQL, Spark, and Pandas) https://www.soda.io

piperider - Code review for data in dbt

DataProfiler - What's in your data? Extract schema, statistics and entities from datasets