README.md

@@ -1,10 +1 @@
-## Overview
+**Hello world!!!**
-This block (`block.py`) is responsible for assigning grade for the passed in probability.
-
-## Key Inputs & Outputs
-- **Request**: Refer to `request_schema.json` for detailed input fields and validation rules.  
-- **Response**: Refer to `response_schema.json` for the returned structure and data types.
-
-## Implementation Details
-- All core logic resides in `block.py` within the `__main__` function.
-- Example usage and validation are demonstrated in `test_block.py`.

block.py

@@ -1,44 +1,21 @@
-import logging
+@flowx_block
+def example_function(request: dict) -> dict:
 
-# Configure logging
+  # Processing logic here...
-logging.basicConfig(
-    level=logging.INFO,
-    format="%(asctime)s [%(levelname)s] %(name)s - %(message)s",
-)
-logger = logging.getLogger(__name__)
 
-def __main__(probability:float):
+  return {
-    logger.info("Received input: probability=%.8f", float(probability))
+    "meta_info": [
-    
+      {
-    if not isinstance(probability, (int, float)):
+        "name": "created_date",
-        logger.error("Invalid input type: probability=%s", type(probability).__name__)
+        "type": "string",
-        raise ValueError("Input probability must be a number (int or float)")
+        "value": "2024-11-05"
-    
+      }
-    if probability <= 0.3200099998:
+    ],
-        bin =  "1"
+    "fields": [
-    elif 0.3200099998 < probability <= 0.4459999998:
+      {
-        bin =  "2"
+        "name": "",
-    elif 0.4459999998 < probability <= 0.5394999999:
+        "type": "",
-        bin =  "3"
+        "value": ""
-    elif 0.5394999999 < probability <= 0.6186978508:
+      }
-        bin =  "4"
+    ]
-    elif 0.6186978508 < probability <= 0.6350320994:
+  }
-        bin =  "5"
-    elif 0.6350320994 < probability <= 0.6553314835:
-        bin =  "6"
-    elif 0.6553314835 < probability <= 0.6759955555:
-        bin =  "7"
-    elif 0.6759955555 < probability <= 0.7399999999:
-        bin =  "8"
-    elif 0.7399999999 < probability <= 0.7899992753:
-        bin =  "9"
-    elif 0.7899992753 < probability <= 0.8199900001:
-        bin =  "10"
-    elif 0.8199900001 < probability <= 0.8400000009:
-        bin =  "11"
-    else:
-        bin =  "12"
-
-    logger.info(f"Repeat V1 Bin: {bin}")
-    
-    return {"bin":bin}

request_schema.json

@@ -1,11 +1 @@
-{
+{}
-  "$schema": "http://json-schema.org/draft-07/schema#",
-  "type": "object",
-  "properties": {
-    "probability": {
-      "type": "number",
-      "description": "Model predicted score."
-    }
-  },
-  "required": []
-}

requirements.txt

@@ -1 +1 @@
-jsonschema==4.23.0
+{}

response_schema.json

@@ -1,10 +1 @@
-{
+{}
-    "$schema": "http://json-schema.org/draft-07/schema#",
-    "type": "object",
-    "properties": {
-      "bin": {
-        "type": "string",
-        "description": "Bin for the given input float."
-      }
-    }
-  }

test_block.py

@@ -1,15 +0,0 @@
-import unittest
-from block import __main__
-
-class TestBlock(unittest.TestCase):
-
-    def test_main_success(self):
-        result = __main__(probability=0.2707298696)
-        self.assertEqual(result, {"bin": "1"})
-
-    def test_main_invalid_input(self):
-        with self.assertRaises(ValueError):
-            __main__(probability="0.27")  # Invalid input type (string)
-
-if __name__ == "__main__":
-    unittest.main()