Implement nasdaq api preprocessor

stocklake/nasdaqapi/preprocessor.py

@@ -1,11 +1,23 @@
 from typing import List
 
 from stocklake.core.base_preprocessor import BasePreprocessor
-from stocklake.nasdaqapi.entities import RawNasdaqApiSymbolData
+from stocklake.nasdaqapi.entities import NasdaqApiSymbolData, RawNasdaqApiSymbolData
 
 
 class NASDAQSymbolsPreprocessor(BasePreprocessor):
-    def process(
-        self, data: List[RawNasdaqApiSymbolData]
-    ) -> List[RawNasdaqApiSymbolData]:
-        return data
+    def process(self, data: List[RawNasdaqApiSymbolData]) -> List[NasdaqApiSymbolData]:
+        processed_data: List[NasdaqApiSymbolData] = []
+        for data_dic in data:
+            _data: NasdaqApiSymbolData = {
+                "symbol": data_dic["symbol"],
+                "name": data_dic["name"],
+                "lastsale": float(
+                    data_dic["lastsale"].replace("$", "").replace(",", "")
+                ),
+                "netchange": float(data_dic["netchange"]),
+                "pctchange": float(data_dic["pctchange"].replace("%", "")),
+                "marketCap": float(data_dic["marketCap"].replace(",", "")),
+                "url": data_dic["url"],
+            }
+            processed_data.append(_data)
+        return processed_data

tests/nasdaqapi/test_preprocessor.py

@@ -0,0 +1,17 @@
+import json
+
+from stocklake.nasdaqapi.preprocessor import NASDAQSymbolsPreprocessor
+
+with open("./tests/nasdaqapi/sample_response.json") as f:
+    mock_raw_data = json.load(f)["data"]["rows"]
+
+
+def test_process():
+    preprocessor = NASDAQSymbolsPreprocessor()
+    data = preprocessor.process(mock_raw_data)
+    for data_dic in data:
+        for key, val in data_dic.items():
+            if key in ["lastsale", "netchange", "pctchange", "marketCap"]:
+                assert isinstance(val, float)
+            else:
+                assert isinstance(val, str)