Initial publish of dbt_f2dq (f2dq) package v0.12.1.

Clean package repo for Gitea installs via packages.yml git URL.

Co-authored-by: Cursor <cursoragent@cursor.com>

macros/metrics/base/build_in/optional_column_metrics.sql

@@ -0,0 +1,104 @@
+{% macro f2dq_metric_regex_count(column_name, pattern) %}
+    coalesce(
+        sum(
+            case when {{ regex_match_expression(column_name, pattern) }}
+                then 1
+            else 0
+            end
+        ), 0
+    )
+{% endmacro %}
+
+{% macro f2dq_metric_match_regex(context) %}
+    {{ f2dq_metric_regex_count(context.column_name, context.config.regex) }}
+{% endmacro %}
+
+{% macro f2dq_metric_match_regex_percent(context) %}
+    {{ percentage_formula(f2dq_metric_match_regex(context), f2dq_metric_row_count()) }}
+{% endmacro %}
+
+{% macro f2dq_metric_not_match_regex(context) %}
+    {{ f2dq_metric_row_count() }} - {{ f2dq_metric_regex_count(context.column_name, context.config.regex) }}
+{% endmacro %}
+
+{% macro f2dq_metric_not_match_regex_percent(context) %}
+    {{ percentage_formula(f2dq_metric_not_match_regex(context), f2dq_metric_row_count()) }}
+{% endmacro %}
+
+{% macro f2dq_metric_distinct_values(context) %}
+    {{ distinct_values(context) }}
+{% endmacro %}
+
+{% macro distinct_values(context) %}
+    {{ adapter.dispatch('distinct_values', 'f2dq')(context) }}
+{% endmacro %}
+
+{% macro default__distinct_values(context) %}
+    coalesce(
+        count(distinct {{ context.column_name }} )
+    , 0)
+{% endmacro %}
+
+{% macro postgres__distinct_values(context) %}
+    {# /* In postgres, its faster to count distinct values in a column by selecting then counting in separate steps */ #}
+    with temp_table as (
+            select distinct {{ context.column_name }} from {{ context.table_name }}
+            where {{ in_time_window(context.time_filter) }}
+        )
+    select coalesce(count(*), 0) from temp_table
+{% endmacro %}
+
+{% macro f2dq_metric_approx_distinct_values(context) %}
+    {{ approx_distinct_values(context) }}
+{% endmacro %}
+
+{% macro approx_distinct_values(context) %}
+    {{ adapter.dispatch('approx_distinct_values', 'f2dq')(context) }}
+{% endmacro %}
+
+{% macro default__approx_distinct_values(context) %}
+    {# /* No approximate distinct count in postgres so we default to using a distinct count */ #}
+    {{ f2dq_metric_distinct_values(context) }}
+{% endmacro %}
+
+{% macro redshift__approx_distinct_values(context) %}
+    approximate {{ f2dq_metric_distinct_values(context.column_name) }}
+{% endmacro %}
+
+{% macro bigquery__approx_distinct_values(context) %}
+    approx_count_distinct({{ context.column_name }})
+{% endmacro %}
+
+{% macro snowflake__approx_distinct_values(context) %}
+    approx_count_distinct({{ context.column_name }})
+{% endmacro %}
+
+{% macro f2dq_metric_duplicate_values(context) %}
+        with temp_table as (
+            select {{ context.column_name }} from {{ context.table_name }}
+            where {{ in_time_window(context.time_filter) }}
+            group by {{ context.column_name }}
+            having count(1) > 1
+        )
+        select coalesce(count(*), 0) from temp_table
+{% endmacro %}
+
+{% macro f2dq_metric_duplicate_rows(context) %}
+        with temp_table as (
+            select {{ context.column_name }}, count(1) as row_count from {{ context.table_name }}
+            where {{ in_time_window(context.time_filter) }}
+            group by {{ context.column_name }}
+            having count(1) > 1
+        )
+        select coalesce(sum(row_count), 0) from temp_table
+{% endmacro %}
+
+{% macro f2dq_metric_unique_rows(context) %}
+        with temp_table as (
+            select {{ context.column_name }}, count(1) as row_count from {{ context.table_name }}
+            where {{ in_time_window(context.time_filter) }}
+            group by {{ context.column_name }}
+            having count(1) = 1
+        )
+        select coalesce(sum(row_count), 0) from temp_table
+{% endmacro %}