feat: refactor to FastAPI architecture v2.0

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

app/core/validator.py

@@ -0,0 +1,69 @@
+"""
+Validation logic for Scenar Creator.
+Extracted from scenar/core.py — validate_inputs, validate_excel_template, overlap detection.
+"""
+
+import pandas as pd
+from datetime import datetime
+import logging
+
+logger = logging.getLogger(__name__)
+
+DEFAULT_COLOR = "#ffffff"
+MAX_FILE_SIZE_MB = 10
+REQUIRED_COLUMNS = ["Datum", "Zacatek", "Konec", "Program", "Typ", "Garant", "Poznamka"]
+
+
+class ScenarsError(Exception):
+    """Base exception for Scenar Creator."""
+    pass
+
+
+class ValidationError(ScenarsError):
+    """Raised when input validation fails."""
+    pass
+
+
+class TemplateError(ScenarsError):
+    """Raised when Excel template is invalid."""
+    pass
+
+
+def validate_inputs(title: str, detail: str, file_size: int) -> None:
+    """Validate user inputs for security and sanity."""
+    if not title or not isinstance(title, str):
+        raise ValidationError("Title is required and must be a string")
+    if len(title.strip()) == 0:
+        raise ValidationError("Title cannot be empty")
+    if len(title) > 200:
+        raise ValidationError("Title is too long (max 200 characters)")
+
+    if not detail or not isinstance(detail, str):
+        raise ValidationError("Detail is required and must be a string")
+    if len(detail.strip()) == 0:
+        raise ValidationError("Detail cannot be empty")
+    if len(detail) > 500:
+        raise ValidationError("Detail is too long (max 500 characters)")
+
+    if file_size > MAX_FILE_SIZE_MB * 1024 * 1024:
+        raise ValidationError(f"File size exceeds {MAX_FILE_SIZE_MB} MB limit")
+
+
+def normalize_time(time_str: str):
+    """Parse time string in formats %H:%M or %H:%M:%S."""
+    for fmt in ('%H:%M', '%H:%M:%S'):
+        try:
+            return datetime.strptime(time_str, fmt).time()
+        except ValueError:
+            continue
+    return None
+
+
+def validate_excel_template(df: pd.DataFrame) -> None:
+    """Validate that Excel has required columns."""
+    missing_cols = set(REQUIRED_COLUMNS) - set(df.columns)
+    if missing_cols:
+        raise TemplateError(
+            f"Excel template missing required columns: {', '.join(missing_cols)}. "
+            f"Expected: {', '.join(REQUIRED_COLUMNS)}"
+        )