Fix datestring warning and index sorting in timeseries parsing

pyproject.toml

@@ -56,6 +56,7 @@ docs = [
 
 test = [
   "pytest>=7.0",
+  "pandas>=2.0",
 ]
 
 dev = [

solarfarmer/models/energy_calculation_results.py

@@ -1721,9 +1721,8 @@ def _handle_losstree_results(
         if _PANDAS:
             with io.StringIO(loss_tree_results_text) as g:
                 data = pd.read_csv(g, sep="\t", skiprows=[0, 1])
-                data["Start of period"] = pd.to_datetime(data["Start of period"])
-                data.set_index("Start of period", inplace=True)
-                data.index = data.index.sort_values()
+            data["Start of period"] = pd.to_datetime(data["Start of period"])
+            data = data.set_index("Start of period").sort_index()
             return data
         else:
             warnings.warn(
@@ -1776,9 +1775,9 @@ def _handle_pvsyst_results(
         if _PANDAS:
             with io.StringIO(pvsyst_results_text) as g:
                 data = pd.read_csv(g, sep=";", skiprows=[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 11, 12])
-            data["date"] = pd.to_datetime(data["date"], utc=True).dt.tz_localize(None)
-            data.set_index("date", inplace=True)
-            data.index = data.index.sort_values()
+            # Timestamps are site-local time as returned by the SF API.
+            data["date"] = pd.to_datetime(data["date"], format="%d/%m/%y %H:%M")
+            data = data.set_index("date").sort_index()
             return data
         else:
             warnings.warn(

tests/test_handle_timeseries_parsing.py

@@ -0,0 +1,155 @@
+import warnings
+
+import pandas as pd
+
+from solarfarmer.models.energy_calculation_results import (
+    _handle_losstree_results,
+    _handle_pvsyst_results,
+    _handle_timeseries_results,
+)
+from solarfarmer.models.model_chain_response import ModelChainResponse
+
+# --- Synthetic data matching SF-Core output formats ---
+
+# PVsyst CSV: 10 header rows skipped (indices 0-9), column row, units row
+# (index 11 skipped), blank row (index 12 skipped), then data.
+# Separator: semicolon. Date format: dd/MM/yy HH:mm
+PVSYST_CSV = (
+    "SF-Core 0.4.443\n"
+    "\n"
+    "\n"
+    "\n"
+    "\n"
+    "\n"
+    "Simulation date;;30/04/26 14h00\n"
+    "\n"
+    "\n"
+    "\n"
+    "date;GlobHor;T_Amb;WindVel\n"
+    "-;kWh/m2;deg. C;m/s\n"
+    "\n"
+    "01/06/24 06:00;0.15;18.3;2.1\n"
+    "15/06/24 12:00;0.85;25.1;3.0\n"
+    "01/01/24 00:00;0.0;-2.5;5.4\n"
+    "31/12/24 23:00;0.0;5.2;4.1\n"
+)
+
+# Loss tree TSV: 2 header rows (descriptive + blank), then column headers,
+# then data. Separator: tab. Date format: yyyy-MM-ddTHH:mm:sszzz (ISO 8601)
+LOSSTREE_TSV = (
+    "Loss tree results for each time-step. Each value is an energy in kWh"
+    " for a certain step in the calculation\n"
+    "\n"
+    "Start of period\tGHI\tGlobalEffective\tNetEnergy\n"
+    "2024-06-01T06:00:00+00:00\t0.150\t0.120\t0.100\n"
+    "2024-06-01T07:00:00+00:00\t0.450\t0.400\t0.380\n"
+    "2024-06-01T08:00:00+00:00\t0.720\t0.680\t0.650\n"
+)
+
+# Detailed TSV: single header row then data rows. Separator: tab.
+# First columns are StartOfPeriod and PeriodInMinutes.
+DETAILED_TSV = (
+    "StartOfPeriod\tPeriodInMinutes\tGHI\tDHI\tTAmb\n"
+    "2024-06-01T06:00:00+00:00\t60\t150\t80\t18.3\n"
+    "2024-06-01T07:00:00+00:00\t60\t450\t200\t19.1\n"
+    "2024-06-01T08:00:00+00:00\t60\t720\t300\t20.5\n"
+)
+
+
+class TestHandlePvsystResults:
+    """Tests for _handle_pvsyst_results with PVsyst-format CSV data."""
+
+    def test_parses_pvsyst_csv_to_dataframe(self, tmp_path):
+        """Parsing a valid PVsyst CSV returns a DataFrame with expected shape and columns."""
+        response = ModelChainResponse(PvSystFormatResultsFile=PVSYST_CSV)
+        df = _handle_pvsyst_results(response, tmp_path, save_outputs=False)
+
+        assert isinstance(df, pd.DataFrame)
+        assert len(df) == 4
+        assert list(df.columns) == ["GlobHor", "T_Amb", "WindVel"]
+
+    def test_dates_parsed_day_first(self, tmp_path):
+        """Date column uses dd/MM/yy format; 01/06 must be June 1st, not Jan 6th."""
+        response = ModelChainResponse(PvSystFormatResultsFile=PVSYST_CSV)
+        df = _handle_pvsyst_results(response, tmp_path, save_outputs=False)
+
+        # 01/06/24 must parse as June 1st, not January 6th
+        assert pd.Timestamp("2024-06-01 06:00:00") in df.index
+        # 31/12/24 would blow up with month=31 if parsed month-first
+        assert pd.Timestamp("2024-12-31 23:00:00") in df.index
+
+    def test_sort_preserves_data_alignment(self, tmp_path):
+        """Sorting the index must keep data rows aligned with their timestamps."""
+        response = ModelChainResponse(PvSystFormatResultsFile=PVSYST_CSV)
+        df = _handle_pvsyst_results(response, tmp_path, save_outputs=False)
+
+        # Input row "01/01/24 00:00" has GlobHor=0.0 and T_Amb=-2.5
+        jan_row = df.loc[pd.Timestamp("2024-01-01 00:00:00")]
+        assert jan_row["GlobHor"] == 0.0
+        assert jan_row["T_Amb"] == -2.5
+
+    def test_index_is_timezone_naive(self, tmp_path):
+        """Index must be tz-naive: the SF API returns site-local time."""
+        response = ModelChainResponse(PvSystFormatResultsFile=PVSYST_CSV)
+        df = _handle_pvsyst_results(response, tmp_path, save_outputs=False)
+
+        assert df.index.tz is None
+
+    def test_no_warning_emitted(self, tmp_path):
+        """Parsing must not emit UserWarning about dateutil fallback (SM-326)."""
+        response = ModelChainResponse(PvSystFormatResultsFile=PVSYST_CSV)
+        with warnings.catch_warnings():
+            warnings.simplefilter("error")
+            _handle_pvsyst_results(response, tmp_path, save_outputs=False)
+
+    def test_saves_file_when_requested(self, tmp_path):
+        """With save_outputs=True, the raw CSV is written to disk."""
+        response = ModelChainResponse(PvSystFormatResultsFile=PVSYST_CSV)
+        _handle_pvsyst_results(response, tmp_path, save_outputs=True)
+
+        saved = list(tmp_path.glob("*"))
+        assert len(saved) == 1
+        assert saved[0].name == "PVsystResults.csv"
+
+
+class TestHandleLosstreeResults:
+    """Tests for _handle_losstree_results with loss-tree TSV data."""
+
+    def test_parses_losstree_tsv_to_dataframe(self, tmp_path):
+        """Parsing a valid loss-tree TSV returns a DataFrame with expected shape."""
+        response = ModelChainResponse(LossTreeResults=LOSSTREE_TSV)
+        df = _handle_losstree_results(response, tmp_path, save_outputs=False)
+
+        assert isinstance(df, pd.DataFrame)
+        assert len(df) == 3
+        assert list(df.columns) == ["GHI", "GlobalEffective", "NetEnergy"]
+        assert df.index.name == "Start of period"
+
+    def test_iso_dates_parsed_correctly(self, tmp_path):
+        """ISO 8601 timestamps are parsed to correct datetime values."""
+        response = ModelChainResponse(LossTreeResults=LOSSTREE_TSV)
+        df = _handle_losstree_results(response, tmp_path, save_outputs=False)
+
+        assert df.index[0] == pd.Timestamp("2024-06-01 06:00:00", tz="UTC")
+
+    def test_sort_preserves_data_alignment(self, tmp_path):
+        """Sorting the index must keep data rows aligned with their timestamps."""
+        response = ModelChainResponse(LossTreeResults=LOSSTREE_TSV)
+        df = _handle_losstree_results(response, tmp_path, save_outputs=False)
+
+        # First row in sorted output should have GHI=0.150
+        assert df.iloc[0]["GHI"] == 0.150
+        assert df.index[0] == pd.Timestamp("2024-06-01 06:00:00", tz="UTC")
+
+
+class TestHandleTimeseriesResults:
+    """Tests for _handle_timeseries_results (detailed format) with TSV data."""
+
+    def test_parses_detailed_tsv_to_dataframe(self, tmp_path):
+        """Parsing a valid detailed TSV returns a DataFrame with expected columns."""
+        response = ModelChainResponse(ResultsFile=DETAILED_TSV)
+        df = _handle_timeseries_results(response, tmp_path, save_outputs=False)
+
+        assert isinstance(df, pd.DataFrame)
+        assert len(df) == 3
+        assert list(df.columns) == ["StartOfPeriod", "PeriodInMinutes", "GHI", "DHI", "TAmb"]