Use context manager for reading Excel file (#818)

* Use context manager for reading Excel file

* Update RELEASE_NOTES.md

* Apply black

* Update pytest workflow

* Pin ixmp4 to fix failing test

.github/workflows/pytest.yml

@@ -25,12 +25,12 @@ jobs:
 
     runs-on: ${{ matrix.os }}
     name: ${{ matrix.os }} py${{ matrix.python-version }}
-  
+
     steps:
-    - uses: actions/checkout@v3
+    - uses: actions/checkout@v4
 
     - name: Set up Python ${{ matrix.python-version }}
-      uses: actions/setup-python@v4
+      uses: actions/setup-python@v5
       with:
         python-version: ${{ matrix.python-version }}
 

RELEASE_NOTES.md

@@ -1,5 +1,6 @@
 # Next release
 
+- [#818](https://github.com/IAMconsortium/pyam/pull/818) Use context manager for reading Excel file
 - [#813](https://github.com/IAMconsortium/pyam/pull/813) Fix a corner case in region-aggregation with missing data
 - [#797](https://github.com/IAMconsortium/pyam/pull/797) Add `to_ixmp4()` method to write to an **ixmp4** platform
 

pyam/utils.py

@@ -98,9 +98,7 @@ def read_pandas(path, sheet_name=["data*", "Data*"], *args, **kwargs):
     if isinstance(path, Path) and path.suffix == ".csv":
         return pd.read_csv(path, *args, **kwargs)
 
-    else:
-        xl = path if isinstance(path, pd.ExcelFile) else pd.ExcelFile(path)
-
+    with pd.ExcelFile(path) as xl:
         # reading multiple sheets
         sheet_names = pd.Series(xl.sheet_names)
         if len(sheet_names) > 1:
@@ -116,18 +114,18 @@ def read_pandas(path, sheet_name=["data*", "Data*"], *args, **kwargs):
         else:
             df = pd.read_excel(xl, *args, **kwargs)
 
-        # remove unnamed and empty columns, and rows were all values are nan
-        def is_empty(name, s):
-            if str(name).startswith("Unnamed: "):
-                try:
-                    if len(s) == 0 or all(np.isnan(s)):
-                        return True
-                except TypeError:
-                    pass
-            return False
+    # remove unnamed and empty columns, and rows were all values are nan
+    def is_empty(name, s):
+        if str(name).startswith("Unnamed: "):
+            try:
+                if len(s) == 0 or all(np.isnan(s)):
+                    return True
+            except TypeError:
+                pass
+        return False
 
-        empty_cols = [c for c in df.columns if is_empty(c, df[c])]
-        return df.drop(columns=empty_cols).dropna(axis=0, how="all")
+    empty_cols = [c for c in df.columns if is_empty(c, df[c])]
+    return df.drop(columns=empty_cols).dropna(axis=0, how="all")
 
 
 def read_file(path, *args, **kwargs):

setup.cfg

@@ -27,7 +27,7 @@ python_requires = >=3.10, <3.12
 # Please also add a section "Dependency changes" to the release notes
 install_requires =
     iam-units >= 2020.4.21
-    ixmp4 >= 0.6.0
+    ixmp4 == 0.6.0
     numpy >= 1.23.0, < 1.24
 #    requests  included via ixmp4
 #    httpx[http2] included via ixmp4