Testing

.github/workflows/python-tests.yml

@@ -0,0 +1,41 @@
+name: Python Tests
+
+on:
+  push
+
+jobs:
+  test:
+    runs-on: ${{ matrix.os }}
+    strategy:
+      fail-fast: false
+      matrix:
+        os: [ubuntu-latest, macos-latest, windows-latest]
+        python-version: ['3.10', '3.11', '3.12', '3.13']
+
+    steps:
+    - uses: actions/checkout@v4
+
+    - name: Set up Python ${{ matrix.python-version }}
+      uses: actions/setup-python@v5
+      with:
+        python-version: ${{ matrix.python-version }}
+
+    - name: Install dependencies
+      run: |
+        python -m pip install --upgrade pip
+        python -m pip install pytest
+        pip install -r requirements.txt
+        pip install -e .
+
+
+    - name: Test with pytest
+      run: |
+        python -m pip install pytest-html pytest-cov
+        pytest tests/ --html=test-report-${{ matrix.os }}-${{ matrix.python-version }}.html --self-contained-html
+
+    - name: Upload test report
+      if: always()
+      uses: actions/upload-artifact@v4
+      with:
+        name: test-report-${{ matrix.os }}-${{ matrix.python-version }}
+        path: test-report-${{ matrix.os }}-${{ matrix.python-version }}.html

.gitignore

@@ -11,7 +11,6 @@ dist
 quantstats.egg-info
 QuantStats.egg-info
 Icon
-/tests
 .vscode
 Icon
 QuantStats_Lumi.egg-info/*

quantstats_lumi/_plotting/core.py

@@ -354,12 +354,34 @@ def plot_timeseries(
 
     _plt.yscale("symlog" if log_scale else "linear")
 
+
     # Set y-axis limits to avoid blank space at the bottom and top
-    min_val = returns.min()
-    max_val = returns.max()
+    # At this stage returns are a frame!
+    min_val = -1
+    max_val = +1
+
+    if isinstance(returns, _pd.Series):
+        # todo: this case can not be used. returns is always a frame
+        min_val = returns.min()
+        max_val = returns.max()
+
+    if isinstance(returns, _pd.DataFrame):
+        min_val = returns.min().min()
+        max_val = returns.max().max()
+
     if benchmark is not None:
-        min_val = min(min_val, benchmark.min())
-        max_val = max(max_val, benchmark.max())
+        bench_min = min_val
+        bench_max = max_val
+
+        if isinstance(benchmark, _pd.Series):
+            bench_min = benchmark.min()
+            bench_max = benchmark.max()
+        if isinstance(benchmark, _pd.DataFrame):
+            bench_min = benchmark.min().min()
+            bench_max = benchmark.max().max()
+
+        min_val = min(min_val, bench_min)
+        max_val = max(max_val, bench_max)
 
     # Handle cases where min_val or max_val might be NaN or Inf
     if not _np.isfinite(min_val) or not _np.isfinite(max_val) or min_val == max_val:

quantstats_lumi/utils.py

@@ -62,7 +62,7 @@ def multi_shift(df, shift=3):
     dfs = [df.shift(i) for i in _np.arange(shift)]
     for ix, dfi in enumerate(dfs[1:]):
         dfs[ix + 1].columns = [str(col) for col in dfi.columns + str(ix + 1)]
-    return _pd.concat(dfs, 1, sort=True)
+    return _pd.concat(dfs, axis=1, sort=True)
 
 
 def to_returns(prices, rf=0.0):

tests/__init__.py

@@ -0,0 +1 @@
+

tests/conftest.py

@@ -0,0 +1,42 @@
+"""global fixtures."""
+
+from __future__ import annotations
+
+from pathlib import Path
+
+import pandas as pd
+import pytest
+
+
+@pytest.fixture(scope="session", name="resource_dir")
+def resource_fixture():
+    """Resource fixture."""
+    return Path(__file__).parent / "resources"
+
+
+@pytest.fixture
+def returns(resource_dir) -> pd.DataFrame:
+    """Fixture that returns a Series with Meta returns.
+
+    Args:
+        resource_dir: The resource_dir fixture containing the path to test resources.
+
+    Returns:
+        pd.Series: A Series containing Meta returns.
+
+    """
+    return pd.read_csv(resource_dir / "meta.csv", index_col="Date", parse_dates=["Date"]).squeeze()
+
+
+@pytest.fixture
+def benchmark(resource_dir) -> pd.DataFrame:
+    """Fixture that returns a Series with benchmark returns.
+
+    Args:
+        resource_dir: The resource_dir fixture containing the path to test resources.
+
+    Returns:
+        pd.Series: A Series containing SPY benchmark returns.
+
+    """
+    return pd.read_csv(resource_dir / "benchmark.csv", index_col="Date", parse_dates=["Date"]).squeeze()