add support for search v2

tests/test_integration.py

@@ -163,8 +163,8 @@ def test_fetch_account_activity_by_period(self, ig_service: IGService):
         assert isinstance(response, pd.DataFrame)
 
     def test_fetch_account_activity_by_date(self, ig_service: IGService):
-        to_date = datetime.now()
-        from_date = to_date - timedelta(days=7)
+        to_date = datetime.now() - timedelta(days=30)
+        from_date = to_date - timedelta(days=60)
         response = ig_service.fetch_account_activity_by_date(from_date, to_date)
         assert isinstance(response, pd.DataFrame)
 
@@ -174,32 +174,32 @@ def test_fetch_account_activity_v2_span(self, ig_service: IGService):
         assert isinstance(response, pd.DataFrame)
 
     def test_fetch_account_activity_v2_dates(self, ig_service):
-        to_date = datetime(2021, 7, 31)
-        from_date = to_date - timedelta(days=7)
+        to_date = datetime.now() - timedelta(days=30)
+        from_date = to_date - timedelta(days=60)
         response = ig_service.fetch_account_activity_v2(
             from_date=from_date, to_date=to_date
         )
         assert isinstance(response, pd.DataFrame)
 
     def test_fetch_account_activity_from(self, ig_service: IGService):
-        to_date = datetime.now() - timedelta(days=3)
-        from_date = to_date - timedelta(days=7)
+        to_date = datetime.now() - timedelta(days=30)
+        from_date = to_date - timedelta(days=60)
         response = ig_service.fetch_account_activity(from_date=from_date)
         assert isinstance(response, pd.DataFrame)
         assert response.shape[1] == 9
 
     def test_fetch_account_activity_from_to(self, ig_service: IGService):
-        to_date = datetime(2023, 7, 18)
-        from_date = to_date - timedelta(days=7)
+        to_date = datetime.now() - timedelta(days=30)
+        from_date = to_date - timedelta(days=60)
         response = ig_service.fetch_account_activity(
             from_date=from_date, to_date=to_date
         )
         assert isinstance(response, pd.DataFrame)
         assert response.shape[1] == 9
 
     def test_fetch_account_activity_detailed(self, ig_service):
-        to_date = datetime(2023, 7, 18)
-        from_date = to_date - timedelta(days=7)
+        to_date = datetime.now() - timedelta(days=30)
+        from_date = to_date - timedelta(days=60)
         response = ig_service.fetch_account_activity(
             from_date=from_date, to_date=to_date, detailed=True
         )
@@ -208,16 +208,16 @@ def test_fetch_account_activity_detailed(self, ig_service):
 
     def test_fetch_account_activity_old(self, ig_service: IGService):
         from_date = datetime(1970, 1, 1)
-        to_date = from_date + timedelta(days=7)
+        to_date = from_date + timedelta(days=60)
         response = ig_service.fetch_account_activity(
             from_date=from_date, to_date=to_date
         )
         assert isinstance(response, pd.DataFrame)
         assert response.shape[0] == 0
 
     def test_fetch_account_activity_fiql(self, ig_service: IGService):
-        to_date = datetime(2023, 7, 18)
-        from_date = to_date - timedelta(days=30)
+        to_date = datetime.now() - timedelta(days=30)
+        from_date = to_date - timedelta(days=60)
         response = ig_service.fetch_account_activity(
             from_date=from_date, to_date=to_date, fiql_filter="channel==PUBLIC_WEB_API"
         )
@@ -461,6 +461,11 @@ def test_search_markets(self, ig_service: IGService):
         response = ig_service.search_markets(search_term)
         assert isinstance(response, pd.DataFrame)
 
+    def test_search_markets_v2(self, ig_service: IGService):
+        epics = "CS.D.GBPUSD.TODAY.IP"
+        response = ig_service.search_markets_v2(epics)
+        assert isinstance(response, pd.DataFrame)
+
     def test_fetch_historical_prices_by_epic_and_numpoints(self, ig_service: IGService):
         response = ig_service.fetch_historical_prices_by_epic_and_num_points(
             "CS.D.EURUSD.MINI.IP", "h", 4

trading_ig/rest.py

@@ -1569,6 +1569,19 @@ def search_markets(self, search_term, session=None):
             data = pd.DataFrame(data["markets"])
         return data
 
+    def search_markets_v2(self, epics, session=None):
+        """Returns all markets matching the epics"""
+        self.non_trading_rate_limit_pause_or_pass()
+        version = "2"
+        endpoint = "/markets"
+        params = {"epics": epics}
+        action = "read"
+        response = self._req(action, endpoint, params, session, version)
+        data = self.parse_response(response.text)
+        if self.return_dataframe:
+            data = pd.DataFrame(data["marketDetails"])
+        return data
+
     def format_prices(self, prices, version, flag_calc_spread=False):
         """
         Format prices data as a DataFrame with hierarchical columns