Add Validoopsie example

Author: rich-iannone

docs/blog/survey-validation-libs/index.qmd

@@ -82,6 +82,7 @@ look like rather than writing imperative validation logic. The schema acts as bo
 as a validation contract. Notice how multiple checks can be applied to a single column (here, the
 `age` column receives two checks), and the validation either succeeds completely or provides
 error information about what failed.
+
 ## 2. Patito: Pydantic-Style Data Models for DataFrames
 
 Patito brings Pydantic's well-received model-based validation approach to DataFrame validation,
@@ -150,3 +151,46 @@ of validation logic from modular, testable components that can be combined in fl
 create complex validation workflows. Like Pointblank, Validoopsie had Polars support from the very
 first release (early-2025).
 
+```{python}
+from validoopsie import Validate
+from narwhals.dtypes import Int64, Float64, String
+
+# Composable validation checks using our standard dataset
+validation = (
+    Validate(user_data)
+    .ValuesValidation.ColumnValuesToBeBetween(
+        column="user_id",
+        min_value=0
+    )
+    .ValuesValidation.ColumnValuesToBeBetween(
+        column="age",
+        min_value=18,
+        max_value=80
+    )
+    .StringValidation.PatternMatch(
+        column="email",
+        pattern=r"^[^@]+@[^@]+\.[^@]+$"
+    )
+    .ValuesValidation.ColumnValuesToBeBetween(
+        column="score",
+        min_value=0,
+        max_value=100
+    )
+    .TypeValidation.TypeCheck(
+        frame_schema_definition={
+            "user_id": Int64,
+            "age": Int64,
+            "email": String,
+            "score": Float64
+        }
+    )
+)
+
+# Check if validation passed
+try:
+    validation.validate()
+    print("Validation successful!")
+except Exception as e:
+    print(f"Validation failed: {e}")
+```
+