Initial commit

API UBS NEO.py

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+# -*- coding: utf-8 -*-
+"""
+Created on Wed Oct 22 15:15:02 2025
+
+@author: Federico
+"""
+
+import os
+from datetime import date, timedelta
+
+import pandas as pd
+import requests
+
+# === Lettura token da file ===
+with open("token.txt", "r") as f:
+    token = f.read().strip()
+
+# === Parametri ===
+isin = "DE000UP32UU0"
+url = f"https://neo.ubs.com/api/ged-amc/external/report/v1/valuation/{isin}"
+headers = {"Authorization": f"Bearer {token}"}
+
+# === Intervallo management fee ===
+management_from = date(2025, 11, 1)
+management_to = date.today() - timedelta(days=1)
+management_url = (
+    "https://neo.ubs.com/api/ged-amc/external/fee/v1/management/"
+    f"{isin}?fromDate={management_from:%Y-%m-%d}&toDate={management_to:%Y-%m-%d}"
+)
+performance_url = (
+    "https://neo.ubs.com/api/ged-amc/external/fee/v1/performance/"
+    f"{isin}?fromDate={management_from:%Y-%m-%d}&toDate={management_to:%Y-%m-%d}"
+)
+
+
+# Helper per trasformare il payload JSON in DataFrame pronti per Excel
+def build_tables_from_payload(payload, base_name="MANAGEMENT_FEE"):
+    tables = {}
+
+    def normalize(obj):
+        return pd.json_normalize(obj, sep=".")
+
+    if isinstance(payload, list):
+        tables[base_name] = normalize(payload)
+        return tables
+
+    if isinstance(payload, dict):
+        if "content" in payload and isinstance(payload["content"], list):
+            tables[base_name] = normalize(payload["content"])
+
+        for key, val in payload.items():
+            if key == "content":
+                continue
+            if isinstance(val, list):
+                sheet_name = f"{base_name}_{key}".upper()[:31]
+                tables[sheet_name] = normalize(val)
+
+        if not tables:
+            tables[base_name] = normalize(payload)
+
+    return tables
+
+
+# === Richiesta API valuation ===
+response = requests.get(url, headers=headers)
+print("Status code:", response.status_code)
+
+if response.status_code == 200:
+    data = response.json()
+
+    # === Info generali del certificato ===
+    amc_info = data.get("amc", {})
+    print("\n--- INFO CERTIFICATO ---")
+    print("ISIN:", amc_info.get("isin"))
+    print("Descrizione:", amc_info.get("description"))
+    print("AUM:", amc_info.get("aum"))
+
+    # === Estraggo le varie asset class ===
+    constituents = data.get("constituents", {})
+    dfs = {k: pd.DataFrame(v) for k, v in constituents.items()}
+
+    # === Richiesta management fee ===
+    management_response = requests.get(management_url, headers=headers)
+    print("Management fee status code:", management_response.status_code)
+    management_tables = {}
+
+    if management_response.status_code == 200:
+        management_payload = management_response.json()
+        management_tables = build_tables_from_payload(management_payload)
+    else:
+        print("Errore nella richiesta management fee:", management_response.status_code)
+        print(management_response.text)
+
+    # === Richiesta performance fee ===
+    performance_response = requests.get(performance_url, headers=headers)
+    print("Performance fee status code:", performance_response.status_code)
+    performance_tables = {}
+
+    if performance_response.status_code == 200:
+        performance_payload = performance_response.json()
+        performance_tables = build_tables_from_payload(performance_payload, base_name="PERFORMANCE_FEE")
+    else:
+        print("Errore nella richiesta performance fee:", performance_response.status_code)
+        print(performance_response.text)
+
+    # === Salvataggio in Excel ===
+    output_file = f"Valuation_{isin}.xlsx"
+    with pd.ExcelWriter(output_file, engine="openpyxl") as writer:
+        # Salva anche info generali in un foglio
+        pd.DataFrame([amc_info]).to_excel(writer, sheet_name="AMC_INFO", index=False)
+        for name, df in dfs.items():
+            if not df.empty:
+                df.to_excel(writer, sheet_name=name[:31], index=False)
+        for name, df in management_tables.items():
+            if not df.empty:
+                df.to_excel(writer, sheet_name=name[:31], index=False)
+        for name, df in performance_tables.items():
+            if not df.empty:
+                df.to_excel(writer, sheet_name=name[:31], index=False)
+
+    print(f"\nFile salvato con successo: {os.path.abspath(output_file)}")
+
+    # Esempio: mostra i primi record di EQUITY
+    if "EQUITY" in dfs and not dfs["EQUITY"].empty:
+        print("\n--- EQUITY ---")
+        print(dfs["EQUITY"].head())
+
+else:
+    print("Errore nella richiesta:", response.status_code)
+    print(response.text)

Token.txt

@@ -0,0 +1 @@
+eyJ0eXAiOiJKV1QiLCJhbGciOiJSUzI1NiJ9.eyJhdWQiOiIvZ2VkLWFtYy9leHRlcm5hbCIsInN1YiI6IlRDQ2JmZjU4MGYyZDE1MDQ2MDZiYzIwZTRkZDUzZWViYjY4IiwiaXNzIjoiTmVvIFBsYXRmb3JtIEpXVCBBdXRob3JpemF0aW9uIFNlcnZpY2UiLCJleHAiOjE3NjkwNDAwMDAsImlhdCI6MTc2MTEzNDU0NCwianRpIjoiMzYwN2NhNGItZjQzMi00NzI1LTliMDEtMDFkMzk3NmEzOTM1In0.l7XVhPvKvEeu7wM7EQTyiDKmQ9YcmgEzmtN0rW9d0G9waB8AE3hjOPq8xgWAdDkqcyEWuwqPEZoPEzx4mT6P4E8pXLZkTvfq7VzY3UZ_CdawHL7LmtwoXGeCpORHJe4m_6yDuxcr8FdOQsApVZDL_Dhq3uRCcIPe-zUcY440ZdND5oyGJQIELvomsIbNW7pgCW2P_MTW0ELWTKH4RWQkvc1DNC4XIlY8EJCWLU8Icn_iGav4J7mO2h8yLZTOIDywOd6s27GQMUAn4E46n9rVRVGrPwKbV1KjgI8Z3SsK8vMHorotZAaruaOT3lV3P5zrxwOpafJMrDFsXOGgd97VfA