[Feature] Adds timeseries display (#313)

Adds a way to input/display timeseries data to the additional information

Reviewed-on: enviPath/enviPy#313
Reviewed-by: jebus <lorsbach@envipath.com>
Co-authored-by: Tobias O <tobias.olenyi@envipath.com>
Co-committed-by: Tobias O <tobias.olenyi@envipath.com>

epapi/utils/validation_errors.py

@@ -0,0 +1,82 @@
+"""Shared utilities for handling Pydantic validation errors."""
+
+import json
+from pydantic import ValidationError
+from pydantic_core import ErrorDetails
+from ninja.errors import HttpError
+
+
+def format_validation_error(error: ErrorDetails) -> str:
+    """Format a Pydantic validation error into a user-friendly message.
+
+    Args:
+        error: A Pydantic error details dictionary containing 'msg', 'type', 'ctx', etc.
+
+    Returns:
+        A user-friendly error message string.
+    """
+    msg = error.get("msg") or "Invalid value"
+    error_type = error.get("type") or ""
+
+    # Handle common validation types with friendly messages
+    if error_type == "enum":
+        ctx = error.get("ctx", {})
+        expected = ctx.get("expected", "") if ctx else ""
+        return f"Please select a valid option{': ' + expected if expected else ''}"
+    elif error_type == "literal_error":
+        # Literal errors (like Literal["active", "inactive"])
+        return msg.replace("Input should be ", "Please enter ")
+    elif error_type == "missing":
+        return "This field is required"
+    elif error_type == "string_type":
+        return "Please enter a valid string"
+    elif error_type == "int_type":
+        return "Please enter a valid int"
+    elif error_type == "int_parsing":
+        return "Please enter a valid int"
+    elif error_type == "float_type":
+        return "Please enter a valid float"
+    elif error_type == "float_parsing":
+        return "Please enter a valid float"
+    elif error_type == "value_error":
+        # Strip "Value error, " prefix from custom validator messages
+        return msg.replace("Value error, ", "")
+    else:
+        # Default: use the message from Pydantic but clean it up
+        return msg.replace("Input should be ", "Please enter ").replace("Value error, ", "")
+
+
+def handle_validation_error(e: ValidationError) -> None:
+    """Convert a Pydantic ValidationError into a structured HttpError.
+
+    This function transforms Pydantic validation errors into a JSON structure
+    that the frontend expects for displaying field-level errors.
+
+    Args:
+        e: The Pydantic ValidationError to handle.
+
+    Raises:
+        HttpError: Always raises a 400 error with structured JSON containing
+                   type, field_errors, and message fields.
+    """
+    # Transform Pydantic validation errors into user-friendly format
+    field_errors: dict[str, list[str]] = {}
+    for error in e.errors():
+        # Get the field name from location tuple
+        loc = error.get("loc", ())
+        field = str(loc[-1]) if loc else "root"
+
+        # Format the error message
+        friendly_msg = format_validation_error(error)
+
+        if field not in field_errors:
+            field_errors[field] = []
+        field_errors[field].append(friendly_msg)
+
+    # Return structured error for frontend parsing
+    error_response = {
+        "type": "validation_error",
+        "field_errors": field_errors,
+        "message": "Please correct the errors below",
+    }
+    raise HttpError(400, json.dumps(error_response))