_quarto.yml

project:
  type: website

format:
  html:
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    toc: true
    grid:
      sidebar-width: 300px
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      margin-width: 300px
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website:
  title: pointblank
  site-url: https://rich-iannone.github.io/pointblank/
  description: "Find out if your data is what you think it is"
  page-navigation: true
  navbar:
    left:
      - text: Get Started
        file: get-started/index.qmd
      - text: Examples
        file: demos/index.qmd
      - href: reference/index.qmd
        text: Reference
    right:
      - icon: github
        href: https://github.com/rich-iannone/pointblank

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quartodoc:
  package: pointblank
  dir: reference
  title: API Reference
  style: pkgdown
  dynamic: true
  renderer:
    style: markdown
    table_style: description-list
  sections:
    - title: Validate
      desc: >
        When peforming data validation, you'll need the `Validate` class to get the process started.
        It's given the target table and you can optionally provide some metadata and/or failure
        thresholds (using the `Thresholds` class or through shorthands for this task). The
        `Validate` class has numerous methods for defining validation steps and for obtaining
        post-interrogation metrics and data.
      contents:
        - name: Validate
          members: []
        - name: Thresholds
        - name: Schema
          members: []
    - title: Validation Steps
      desc: >
        Validation steps can be thought of as sequential validations on the target data. We call
        `Validate`'s validation methods to build up a validation plan: a collection of steps that,
        in the aggregate, provides good validation coverage.
      contents:
        - name: Validate.col_vals_gt
        - name: Validate.col_vals_lt
        - name: Validate.col_vals_ge
        - name: Validate.col_vals_le
        - name: Validate.col_vals_eq
        - name: Validate.col_vals_ne
        - name: Validate.col_vals_between
        - name: Validate.col_vals_outside
        - name: Validate.col_vals_in_set
        - name: Validate.col_vals_not_in_set
        - name: Validate.col_vals_null
        - name: Validate.col_vals_not_null
        - name: Validate.col_vals_regex
        - name: Validate.col_vals_expr
        - name: Validate.col_exists
        - name: Validate.rows_distinct
        - name: Validate.col_schema_match
        - name: Validate.row_count_match
        - name: Validate.col_count_match
    - title: Column Selection
      desc: >
        A flexible way to select columns for validation is to use the `col()` function along with
        column selection helper functions. A combination of `col()` + `starts_with()`, `matches()`,
        etc., allows for the selection of multiple target columns (mapping a validation across many
        steps). Furthermore, the `col()` function can be used to declare a comparison column (e.g.,
        for the `value=` argument in many `col_vals_*()` methods) when you can't use a fixed value
        for comparison.
      contents:
        - name: col
        - name: starts_with
        - name: ends_with
        - name: contains
        - name: matches
        - name: everything
        - name: first_n
        - name: last_n
    - title: Interrogation and Reporting
      desc: >
        The validation plan is put into action when `interrogate()` is called. The workflow for
        performing a comprehensive validation is then: (1) `Validate()`, (2) adding validation
        steps, (3) `interrogate()`. After interrogation of the data, we can view a validation report
        table (by printing the object or using `get_tabular_report()`), extract key metrics, or we
        can split the data based on the validation results (with `get_sundered_data()`).
      contents:
        - name: Validate.interrogate
        - name: Validate.get_tabular_report
        - name: Validate.get_step_report
        - name: Validate.get_json_report
        - name: Validate.get_sundered_data
        - name: Validate.get_data_extracts
        - name: Validate.all_passed
        - name: Validate.n
        - name: Validate.n_passed
        - name: Validate.n_failed
        - name: Validate.f_passed
        - name: Validate.f_failed
        - name: Validate.warn
        - name: Validate.stop
        - name: Validate.notify
    - title: Utilities
      desc: >
        The utilities group contains functions that are helpful for the validation process. We can
        load datasets with `load_dataset()`, preview a table with `preview()`, and set global
        configuration parameters with `config()`.
      contents:
        - name: load_dataset
        - name: preview
        - name: get_column_count
        - name: get_row_count
        - name: config