adding validate_gantt tests file

Author: mashraf-222

tests/test_optional/test_figure_factory/test_validate_gantt.py

@@ -0,0 +1,215 @@
+import pytest
+
+from plotly import exceptions, optional_imports
+from plotly.figure_factory._gantt import validate_gantt
+
+pd = optional_imports.get_module("pandas")
+REQUIRED_GANTT_KEYS = ["Task", "Start", "Finish"]
+
+
+# --- BASIC TEST CASES ---
+
+def test_valid_list_of_dicts():
+    input_data = [
+        {"Task": "A", "Start": "2020-01-01", "Finish": "2020-01-02"},
+        {"Task": "B", "Start": "2020-01-03", "Finish": "2020-01-04"},
+    ]
+
+    result = validate_gantt(input_data)
+    assert result is input_data
+    assert len(result) == 2
+    assert all(isinstance(x, dict) for x in result)
+
+
+@pytest.mark.skipif(pd is None, reason="pandas is not available")
+def test_valid_dataframe():
+    df = pd.DataFrame(
+        [
+            {"Task": "A", "Start": "2020-01-01", "Finish": "2020-01-02"},
+            {"Task": "B", "Start": "2020-01-03", "Finish": "2020-01-04"},
+        ]
+    )
+    result = validate_gantt(df)
+    assert isinstance(result, list)
+    assert len(result) == 2
+    assert set(result[0].keys()) == set(df.columns)
+    assert result[0]["Task"] == "A"
+    assert result[1]["Finish"] == "2020-01-04"
+
+
+def test_valid_list_with_extra_keys():
+    input_data = [
+        {"Task": "A", "Start": "2020-01-01", "Finish": "2020-01-02", "Resource": "X"},
+        {"Task": "B", "Start": "2020-01-03", "Finish": "2020-01-04", "Resource": "Y"},
+    ]
+    result = validate_gantt(input_data)
+    assert result is input_data
+    assert all("Resource" in row for row in result)
+
+
+@pytest.mark.skipif(pd is None, reason="pandas is not available")
+def test_valid_dataframe_with_extra_keys():
+    df = pd.DataFrame(
+        [
+            {"Task": "A", "Start": "2020-01-01", "Finish": "2020-01-02", "Resource": "X"},
+            {"Task": "B", "Start": "2020-01-03", "Finish": "2020-01-04", "Resource": "Y"},
+        ]
+    )
+    result = validate_gantt(df)
+    assert len(result) == 2
+    assert set(result[0].keys()) == set(["Task", "Start", "Finish", "Resource"])
+
+
+# --- EDGE TEST CASES ---
+
+def test_missing_required_key_in_list():
+    input_data = [
+        {"Task": "A", "Start": "2020-01-01"},  # Missing "Finish"
+    ]
+    # Should NOT raise: list input is not validated for keys
+    result = validate_gantt(input_data)
+    assert result is input_data
+
+
+@pytest.mark.skipif(pd is None, reason="pandas is not available")
+def test_missing_required_key_in_dataframe():
+    df = pd.DataFrame([
+        {"Task": "A", "Start": "2020-01-01"},  # Missing "Finish"
+    ])
+    with pytest.raises(exceptions.PlotlyError):
+        validate_gantt(df)
+
+
+def test_empty_list():
+    with pytest.raises(exceptions.PlotlyError):
+        validate_gantt([])
+
+
+def test_input_is_not_list_or_dataframe():
+    with pytest.raises(exceptions.PlotlyError):
+        validate_gantt("Not a list or DataFrame")
+
+
+@pytest.mark.skipif(pd is None, reason="pandas is not available")
+def test_dataframe_with_no_rows():
+    df = pd.DataFrame(columns=["Task", "Start", "Finish"])
+    result = validate_gantt(df)
+    assert isinstance(result, list)
+    assert result == []
+
+
+@pytest.mark.skipif(pd is None, reason="pandas is not available")
+def test_dataframe_with_extra_rows_and_missing_keys():
+    df = pd.DataFrame(
+        [
+            {"Task": "A", "Start": "2020-01-01", "Resource": "X"},
+            {"Task": "B", "Start": "2020-01-03", "Resource": "Y"},
+        ]
+    )
+    with pytest.raises(exceptions.PlotlyError):
+        validate_gantt(df)
+
+
+def test_list_with_dict_missing_all_keys():
+    input_data = [{"Resource": "X"}]
+    # Should NOT raise: list input is not validated for keys
+    result = validate_gantt(input_data)
+    assert result is input_data
+
+
+@pytest.mark.skipif(pd is None, reason="pandas is not available")
+def test_dataframe_with_only_required_keys():
+    df = pd.DataFrame([
+        {"Task": "A", "Start": "2020-01-01", "Finish": "2020-01-02"},
+    ])
+    result = validate_gantt(df)
+    assert len(result) == 1
+    assert set(result[0].keys()) == set(REQUIRED_GANTT_KEYS)
+
+
+# --- LARGE SCALE TEST CASES ---
+
+def test_large_list_of_dicts():
+    input_data = [
+        {"Task": f"Task{i}", "Start": f"2020-01-{i%30+1:02d}", "Finish": f"2020-02-{i%28+1:02d}"}
+        for i in range(1000)
+    ]
+    result = validate_gantt(input_data)
+    assert result is input_data
+    assert len(result) == 1000
+
+
+@pytest.mark.skipif(pd is None, reason="pandas is not available")
+def test_large_dataframe():
+    df = pd.DataFrame([
+        {"Task": f"Task{i}", "Start": f"2020-01-{i%30+1:02d}", "Finish": f"2020-02-{i%28+1:02d}"}
+        for i in range(1000)
+    ])
+    result = validate_gantt(df)
+    assert isinstance(result, list)
+    assert len(result) == 1000
+    assert set(result[0].keys()) == set(df.columns)
+
+
+@pytest.mark.skipif(pd is None, reason="pandas is not available")
+def test_large_dataframe_missing_key():
+    df = pd.DataFrame([
+        {"Task": f"Task{i}", "Start": f"2020-01-{i%30+1:02d}"}  # Missing "Finish"
+        for i in range(1000)
+    ])
+    with pytest.raises(exceptions.PlotlyError):
+        validate_gantt(df)
+
+
+def test_large_list_with_non_dict_first_element():
+    input_data = [
+        "Not a dict",
+        *[
+            {"Task": f"Task{i}", "Start": f"2020-01-{i%30+1:02d}", "Finish": f"2020-02-{i%28+1:02d}"}
+            for i in range(999)
+        ],
+    ]
+    with pytest.raises(exceptions.PlotlyError):
+        validate_gantt(input_data)
+
+
+def test_large_list_with_non_dict_later_element():
+    input_data = [
+        *[
+            {"Task": f"Task{i}", "Start": f"2020-01-{i%30+1:02d}", "Finish": f"2020-02-{i%28+1:02d}"}
+            for i in range(999)
+        ],
+        "Not a dict",
+    ]
+    # Should NOT raise: only first element is checked
+    result = validate_gantt(input_data)
+    assert result is input_data
+    assert len(result) == 1000
+
+
+# --- Additional determinism/robustness checks ---
+
+def test_determinism_multiple_calls_list():
+    input_data = [
+        {"Task": "A", "Start": "2023-01-01", "Finish": "2023-01-02"},
+        {"Task": "B", "Start": "2023-01-02", "Finish": "2023-01-03"},
+    ]
+    out1 = validate_gantt(input_data)
+    out2 = validate_gantt(input_data)
+    assert out1 is input_data
+    assert out2 is input_data
+
+
+@pytest.mark.skipif(pd is None, reason="pandas is not available")
+def test_dataframe_column_order_and_index():
+    df = pd.DataFrame([
+        {"Finish": "2023-01-02", "Start": "2023-01-01", "Task": "A"},
+        {"Finish": "2023-01-03", "Start": "2023-01-02", "Task": "B"},
+    ], index=["x", "y"])
+    result = validate_gantt(df)
+    assert len(result) == 2
+    # Ensure values preserved regardless of order/index
+    assert result[0]["Task"] == "A"
+    assert set(result[0].keys()) == set(["Task", "Start", "Finish"])
+
+