README.Rmd

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output: github_document
---

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# tidyvalidate <a href="https://angelfelizr.github.io/tidyvalidate/"><img src="man/figures/logo.png" align="right" height="139" alt="tidyvalidate website" /></a>

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## Overview

tidyvalidate simplifies data validation in R by providing an intuitive interface to the powerful `validate` package. It helps ensure data quality by making it easy to:

- Write clear, expressive validation rules
- Check both column-level and row-level conditions
- Get detailed reports of validation failures
- Integrate validation checks into your data pipeline

The package streamlines common validation tasks while leveraging the robust foundation of the `validate` package and R's error handling system.

## Installation

You can install the development version of tidyvalidate from GitHub:

```r
# Install pak if you haven't already
# install.packages("pak")

# Install tidyvalidate
pak::pak("AngelFelizR/tidyvalidate")
```

## Quick Start

### Basic Validation

Let's validate some data from the built-in `mtcars` dataset:

```{r setup}
library(tidyvalidate)

# Define and run validations
validation_results <- validate_rules(
  mtcars,
  # Column type validations
  mpg_is_numeric = is.numeric(mpg),
  hp_is_numeric = is.numeric(hp),
  
  # Business rule validation
  mpg_minimum = mpg > 15
)

# View results
validation_results
```

The results show:
- A summary of all validations
- Detailed information about which rows failed the `mpg_minimum` check

### Taking Action on Validation Failures

You can automatically handle validation failures in two ways:

#### 1. Stop Execution on Failure

```{r}
try({
  validate_rules(mtcars,
    mpg_minimum = mpg > 15
  ) |>
    action_if_problem(
      "Critical: Found cars with MPG below minimum threshold"
    )
})
```

#### 2. Continue with Warning

```{r}
validation_results <- validate_rules(mtcars,
    mpg_minimum = mpg > 15
  ) |>
  action_if_problem(
    "Advisory: Some cars have low MPG values",
    problem_action = "warning"
  )
```

## Key Features

- **Simple Interface**: Write validation rules using familiar R syntax
- **Comprehensive Results**: Get both summary statistics and row-level details
- **Flexible Actions**: Choose between warnings and errors based on severity
- **Pipeline Integration**: Works seamlessly with the pipe operator
- **Detailed Reporting**: Identify exactly which rows failed validation

## Learn More

- Visit our [website](https://angelfelizr.github.io/tidyvalidate/) for full documentation
- Read the [Getting Started](https://angelfelizr.github.io/tidyvalidate/articles/tidyvalidate.html) guide
- Check out the [Reference](https://angelfelizr.github.io/tidyvalidate/reference/index.html) section for detailed function documentation