1 files changed, 54 insertions, 61 deletions
diff --git a/python/load_bbh_reports.py b/python/load_bbh_reports.py
index a433a050..3dacc44c 100644
--- a/python/load_bbh_reports.py
+++ b/python/load_bbh_reports.py
@@ -1,82 +1,75 @@
 import datetime
 import pandas as pd
+from env import DAILY_DIR
 from utils.db import dbengine
 
 
 def pnl_report(f):
-    df = pd.read_csv(f, thousands=",")
-    column_list = [
-        "Accounting Date",
-        "Security ID",
-        "Custody Head Account Number",
-        "Issue Name",
-        "Local Currency",
-        "Base Market Value",
-        "Base Change Income",
-        "Base Change FX Realized Gain Loss",
-        "Base Change FX Unrealized Gain Loss",
-        "Base Change Unrealized Gain Loss",
-        "Base Change Realized Gain Loss",
-        "Base Change Miscellaneous Income",
-        "Base Change Expense",
-        "Base Change Total",
-        "Sub Security Type Code",
-        "Source",
-    ]
-    df = df[column_list]
-    df.columns = (
-        df.columns.str.strip()
-        .str.lower()
-        .str.replace(" ", "_")
-        .str.replace("(", "")
-        .str.replace(")", "")
+    df = pd.read_csv(
+        f,
+        thousands=",",
+        usecols=[
+            "Accounting Date",
+            "Security ID",
+            "Custody Head Account Number",
+            "Issue Name",
+            "Local Currency",
+            "Base Market Value",
+            "Base Change Income",
+            "Base Change FX Realized Gain Loss",
+            "Base Change FX Unrealized Gain Loss",
+            "Base Change Unrealized Gain Loss",
+            "Base Change Realized Gain Loss",
+            "Base Change Miscellaneous Income",
+            "Base Change Expense",
+            "Base Change Total",
+            "Sub Security Type Code",
+            "Source",
+        ],
     )
+    df.columns = df.columns.str.lower().str.replace(" ", "_")
     df["row"] = df.index
     df.to_sql("bbh_pnl", dbengine("dawndb"), if_exists="append", index=False)
 
 
 def val_report(f):
-    df = pd.read_csv(f, thousands=",")
-    df = df.apply(lambda x: x.str.strip() if x.dtype == "object" else x)
-    column_list = [
-        "Accounting Date",
-        "Custody Head Account Number",
-        "Security ID",
-        "Security Description",
-        "Asset Currency",
-        "Original Face",
-        "Base Price",
-        "Local Unit Cost",
-        "Base Unit Cost",
-        "Local Market Value",
-        "Base Market Value",
-        "Security ID Type",
-        "Sub Security Type Code",
-        "Source",
-        "Investment Type Code",
-        "Investment Type Description",
-        "Security Long Description",
-        "Security Type Code",
-        "Total Current Assets",
-        "Total Current Liabilities",
-        "Total Net Assets",
-    ]
-    df = df[column_list]
-    df.columns = (
-        df.columns.str.strip()
-        .str.lower()
-        .str.replace(" ", "_")
-        .str.replace("(", "")
-        .str.replace(")", "")
+    df = pd.read_csv(
+        f,
+        thousands=",",
+        usecols=[
+            "Accounting Date",
+            "Custody Head Account Number",
+            "Security ID",
+            "Security Description",
+            "Asset Currency",
+            "Original Face",
+            "Base Price",
+            "Local Unit Cost",
+            "Base Unit Cost",
+            "Local Market Value",
+            "Base Market Value",
+            "Security ID Type",
+            "Sub Security Type Code",
+            "Source",
+            "Investment Type Code",
+            "Investment Type Description",
+            "Security Long Description",
+            "Security Type Code",
+            "Total Current Assets",
+            "Total Current Liabilities",
+            "Total Net Assets",
+        ],
     )
+    for col in df.select_dtypes(include="object"):
+        df[col] = df[col].str.strip()
     df["row"] = df.index
     df.to_sql("bbh_val", dbengine("dawndb"), if_exists="append", index=False)
 
 
 def load_reports(date=datetime.date.today()):
-    f = "/home/serenitas/Daily/" + date.strftime("%Y-%m-%d") + "/Reports/BBH"
-    pnl_report(f + "_PNL.csv")
-    val_report(f + "_VAL.csv")
+    path = DAILY_DIR / str(date) / "Reports"
+    pnl_report(path / "BBH_PNL.csv")
+    val_report(path / "BBH_VAL.csv")
 
 
 if __name__ == "__main__":