Add toggle to tfdoc to remove type hints (#3842)
* Add toggle to tfdoc to remove type hints * Update all readmes * Fix python formatting
This commit is contained in:
Julio Castillo
@@ -461,18 +461,18 @@ module "dataplex-datascan" {
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| name | description | type | required | default |
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|---|---|:---:|:---:|:---:|
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| [data](variables.tf#L17) | The data source for DataScan. The source can be either a Dataplex `entity` or a BigQuery `resource`. | <code title="object({ entity = optional(string) resource = optional(string) })">object({…})</code> | ✓ | |
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| [data](variables.tf#L17) | The data source for DataScan. The source can be either a Dataplex `entity` or a BigQuery `resource`. | <code>object({…})</code> | ✓ | |
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| [name](variables.tf#L122) | Name of Dataplex Scan. | <code>string</code> | ✓ | |
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| [project_id](variables.tf#L133) | The ID of the project where the Dataplex DataScan will be created. | <code>string</code> | ✓ | |
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| [region](variables.tf#L138) | Region for the Dataplex DataScan. | <code>string</code> | ✓ | |
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| [data_profile_spec](variables.tf#L29) | DataProfileScan related setting. Variable descriptions are provided in https://cloud.google.com/dataplex/docs/reference/rest/v1/DataProfileSpec. | <code title="object({ sampling_percent = optional(number) row_filter = optional(string) })">object({…})</code> | | <code>null</code> |
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| [data_quality_spec](variables.tf#L38) | DataQualityScan related setting. Variable descriptions are provided in https://cloud.google.com/dataplex/docs/reference/rest/v1/DataQualitySpec. | <code title="object({ sampling_percent = optional(number) row_filter = optional(string) post_scan_actions = optional(object({ bigquery_export = optional(object({ results_table = optional(string) })) })) rules = list(object({ column = optional(string) ignore_null = optional(bool, null) dimension = string threshold = optional(number) non_null_expectation = optional(object({})) range_expectation = optional(object({ min_value = optional(number) max_value = optional(number) strict_min_enabled = optional(bool) strict_max_enabled = optional(bool) })) regex_expectation = optional(object({ regex = string })) set_expectation = optional(object({ values = list(string) })) uniqueness_expectation = optional(object({})) statistic_range_expectation = optional(object({ statistic = string min_value = optional(number) max_value = optional(number) strict_min_enabled = optional(bool) strict_max_enabled = optional(bool) })) row_condition_expectation = optional(object({ sql_expression = string })) table_condition_expectation = optional(object({ sql_expression = string })) sql_assertion = optional(object({ sql_statement = string })) })) })">object({…})</code> | | <code>null</code> |
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| [data_profile_spec](variables.tf#L29) | DataProfileScan related setting. Variable descriptions are provided in https://cloud.google.com/dataplex/docs/reference/rest/v1/DataProfileSpec. | <code>object({…})</code> | | <code>null</code> |
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| [data_quality_spec](variables.tf#L38) | DataQualityScan related setting. Variable descriptions are provided in https://cloud.google.com/dataplex/docs/reference/rest/v1/DataQualitySpec. | <code>object({…})</code> | | <code>null</code> |
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| [description](variables.tf#L88) | Custom description for DataScan. | <code>string</code> | | <code>null</code> |
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| [execution_schedule](variables.tf#L94) | Schedule DataScan to run periodically based on a cron schedule expression. If not specified, the DataScan is created with `on_demand` schedule, which means it will not run until the user calls `dataScans.run` API. | <code>string</code> | | <code>null</code> |
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| [factories_config](variables.tf#L100) | Paths to data files and folders that enable factory functionality. | <code title="object({ data_quality_spec = optional(string) })">object({…})</code> | | <code>{}</code> |
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| [factories_config](variables.tf#L100) | Paths to data files and folders that enable factory functionality. | <code>object({…})</code> | | <code>{}</code> |
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| [iam](variables-iam.tf#L24) | Dataplex DataScan IAM bindings in {ROLE => [MEMBERS]} format. | <code>map(list(string))</code> | | <code>{}</code> |
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| [iam_bindings](variables-iam.tf#L31) | Authoritative IAM bindings in {KEY => {role = ROLE, members = [], condition = {}}}. Keys are arbitrary. | <code title="map(object({ members = list(string) role = string condition = optional(object({ expression = string title = string description = optional(string) })) }))">map(object({…}))</code> | | <code>{}</code> |
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| [iam_bindings_additive](variables-iam.tf#L46) | Individual additive IAM bindings. Keys are arbitrary. | <code title="map(object({ member = string role = string condition = optional(object({ expression = string title = string description = optional(string) })) }))">map(object({…}))</code> | | <code>{}</code> |
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| [iam_bindings](variables-iam.tf#L31) | Authoritative IAM bindings in {KEY => {role = ROLE, members = [], condition = {}}}. Keys are arbitrary. | <code>map(object({…}))</code> | | <code>{}</code> |
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| [iam_bindings_additive](variables-iam.tf#L46) | Individual additive IAM bindings. Keys are arbitrary. | <code>map(object({…}))</code> | | <code>{}</code> |
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| [iam_by_principals](variables-iam.tf#L17) | Authoritative IAM binding in {PRINCIPAL => [ROLES]} format. Principals need to be statically defined to avoid cycle errors. Merged internally with the `iam` variable. | <code>map(list(string))</code> | | <code>{}</code> |
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| [incremental_field](variables.tf#L109) | The unnested field (of type Date or Timestamp) that contains values which monotonically increase over time. If not specified, a data scan will run for all data in the table. | <code>string</code> | | <code>null</code> |
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| [labels](variables.tf#L115) | Resource labels. | <code>map(string)</code> | | <code>{}</code> |
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