more tests and fixes

environment-dev.yml

@@ -21,6 +21,7 @@ dependencies:
   - netCDF4
   - numcodecs
   - numpy >=1.24
+  - openpyxl
   - pandas >=2.2
   - parse
   - pyyaml

environment.yml

@@ -21,6 +21,7 @@ dependencies:
   - netCDF4
   - numcodecs
   - numpy >=1.24
+  - openpyxl
   - pandas >=2.2
   - parse
   - pyyaml

pyproject.toml

@@ -54,6 +54,7 @@ dependencies = [
   "netCDF4",
   "numcodecs",
   "numpy >=1.24",
+  "openpyxl",
   "pandas >=2.2",
   "parse",
   # Used when opening catalogs.

src/xscen/io.py

@@ -454,7 +454,8 @@ def save_to_zarr(  # noqa: C901
         if 'o', removes the existing variables.
         if 'a', skip existing variables, writes the others.
     encoding : dict, optional
-        If given, skipped variables are popped in place.
+        If given here instead of 'zarr_kwargs', encoding will only be applied to the variables that are being written,
+        skipping those that are already in the zarr.
     bitround : bool or int or dict
         If not False, float variables are bit-rounded by dropping a certain number of bits from their mantissa,
         allowing for a much better compression.
@@ -512,17 +513,29 @@ def _skip(var):
             return False
 
         if mode == "a":
+            # In all cases, we need to skip the encoding of existing variables.
+            if exists:
+                if encoding:
+                    encoding.pop(var, None)
+
+            # If we are not appending, we need to skip the writing of existing variables.
             if "append_dim" not in zarr_kwargs:
                 return exists
+
+            # If we are appending, we need to raise an error if there are new variables.
+            elif exists is False:
+                raise ValueError(
+                    f"When 'append_dim' is set in zarr_kwargs, all variables must already exist in the dataset."
+                )
+
             return False
 
     for var in list(ds.data_vars.keys()):
         if _skip(var):
             msg = f"Skipping {var} in {path}."
             logger.info(msg)
             ds = ds.drop_vars(var)
-            if encoding:
-                encoding.pop(var)
+            continue
         if keepbits := _get_keepbits(bitround, var, ds[var].dtype):
             ds = ds.assign({var: round_bits(ds[var], keepbits)})
         # Remove original_shape from encoding, since it can cause issues with some engines.
@@ -773,7 +786,6 @@ def make_toc(ds: xr.Dataset | xr.DataArray, loc: str | None = None) -> pd.DataFr
             for vv, da in ds.data_vars.items()
         ],
     ).set_index(_("Variable"))
-    toc.attrs["name"] = _("Content")
 
     # Add global attributes by using a fake variable and description
     if len(ds.attrs) > 0:
@@ -793,28 +805,29 @@ def make_toc(ds: xr.Dataset | xr.DataArray, loc: str | None = None) -> pd.DataFr
         toc = pd.concat([toc, pd.DataFrame(index=[""])])
         toc = pd.concat([toc, pd.DataFrame(index=[_("Global attributes")])])
         toc = pd.concat([toc, globattr])
+    toc.attrs["name"] = _("Content")
 
     return toc
 
 
 TABLE_FORMATS = {".csv": "csv", ".xls": "excel", ".xlsx": "excel"}
 
 
-def save_to_table(
+def save_to_table(  # noqa: C901
     ds: xr.Dataset | xr.DataArray,
     filename: str | os.PathLike,
     output_format: str | None = None,
     *,
     row: str | Sequence[str] | None = None,
-    column: None | str | Sequence[str] = "variable",
+    column: None | str | Sequence[str] = None,
     sheet: str | Sequence[str] | None = None,
     coords: bool | Sequence[str] = True,
     col_sep: str = "_",
     row_sep: str | None = None,
     add_toc: bool | pd.DataFrame = False,
     **kwargs,
 ):
-    """Save the dataset to a tabular file (csv, excel, ...).
+    r"""Save the dataset to a tabular file (csv, excel, ...).
 
     This function will trigger a computation of the dataset.
 
@@ -835,7 +848,8 @@ def save_to_table(
       Default is all data dimensions.
     column : str or sequence of str, optional
       Name of the dimension(s) to use as columns.
-      Default is "variable", i.e. the name of the variable(s).
+      When using a Dataset with more than 1 variable, default is "variable", i.e. the name of the variable(s).
+      When using a DataArray, default is None.
     sheet : str or sequence of str, optional
       Name of the dimension(s) to use as sheet names.
       Only valid if the output format is excel.
@@ -851,7 +865,7 @@ def save_to_table(
       A table of content to add as the first sheet. Only valid if the output format is excel.
       If True, :py:func:`make_toc` is used to generate the toc.
       The sheet name of the toc can be given through the "name" attribute of the DataFrame, otherwise "Content" is used.
-    kwargs:
+    \*\*kwargs:
       Other arguments passed to the pandas function.
       If the output format is excel, kwargs to :py:class:`pandas.ExcelWriter` can be given here as well.
     """
@@ -864,6 +878,9 @@ def save_to_table(
             f"Output format could not be inferred from filename {filename.name}. Please pass `output_format`."
         )
 
+    if column is None and isinstance(ds, xr.Dataset) and len(ds.data_vars) > 1:
+        column = "variable"
+
     if sheet is not None and output_format != "excel":
         raise ValueError(
             f"Argument `sheet` is only valid with excel as the output format. Got {output_format}."
@@ -882,15 +899,22 @@ def save_to_table(
             add_toc = make_toc(ds)
         out = {(add_toc.attrs.get("name", "Content"),): add_toc, **out}
 
-    if sheet or (add_toc is not False):
+    # Get engine_kwargs
+    if output_format == "excel":
         engine_kwargs = {}  # Extract engine kwargs
         for arg in signature(pd.ExcelWriter).parameters:
             if arg in kwargs:
                 engine_kwargs[arg] = kwargs.pop(arg)
+    else:
+        engine_kwargs = {}
 
+    if sheet or (add_toc is not False):
         with pd.ExcelWriter(filename, **engine_kwargs) as writer:
             for sheet_name, df in out.items():
                 df.to_excel(writer, sheet_name=col_sep.join(sheet_name), **kwargs)
+    elif len(engine_kwargs) > 0:
+        with pd.ExcelWriter(filename, **engine_kwargs) as writer:
+            out.to_excel(writer, **kwargs)
     else:
         if output_format != "excel" and isinstance(out.columns, pd.MultiIndex):
             out.columns = out.columns.map(lambda lvls: col_sep.join(map(str, lvls)))