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Create optional automaitc sorting capabilites for entries (#461)

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* Fix sorting stability and add tie-break tests

* update schema

* formatting

* fix error with import

* fix failing test case
This commit is contained in:
Ian Holloway
2025-10-23 14:20:56 -04:00
committed by GitHub
parent 24f221827a
commit bebbf8d04c
7 changed files with 291 additions and 7 deletions
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155
tests/test_data.py
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@@ -999,3 +999,158 @@ def test_none_entries():
},
)
)
def _create_sorting_data_model(order: str) -> data.RenderCVDataModel:
entries = [
{
"company": "A",
"position": "P",
"start_date": "2020-01-01",
},
{
"company": "B",
"position": "P",
"start_date": "2022-01-01",
},
{
"company": "C",
"position": "P",
"date": "2021-05-01",
},
{
"company": "D",
"position": "P",
"date": "2022-01-01",
},
]
cv = data.CurriculumVitae(
name="John Doe",
sections={"exp": entries},
)
settings = data.RenderCVSettings(date="2024-01-01", sort_entries=order)
return data.RenderCVDataModel(cv=cv, rendercv_settings=settings)
@pytest.mark.parametrize(
("order", "expected"),
[
(
"reverse-chronological",
["B", "A", "D", "C"],
),
(
"chronological",
["C", "D", "A", "B"],
),
(
"none",
["A", "B", "C", "D"],
),
],
)
def test_sort_entries(order, expected):
data_model = _create_sorting_data_model(order)
entries = data_model.cv.sections[0].entries
companies = [e.company for e in entries]
assert companies == expected
def _create_sorting_data_model_with_ranges(order: str) -> data.RenderCVDataModel:
entries = [
{
"company": "A",
"position": "P",
"start_date": "2020-01-01",
"end_date": "2021-06-01",
},
{
"company": "B",
"position": "P",
"start_date": "2019-01-01",
"end_date": "2022-06-01",
},
{
"company": "C",
"position": "P",
"start_date": "2021-01-01",
"end_date": "2022-06-01",
},
{
"company": "D",
"position": "P",
"date": "2020-05-01",
},
]
cv = data.CurriculumVitae(
name="John Doe",
sections={"exp": entries},
)
settings = data.RenderCVSettings(date="2024-01-01", sort_entries=order)
return data.RenderCVDataModel(cv=cv, rendercv_settings=settings)
@pytest.mark.parametrize(
("order", "expected"),
[
(
"reverse-chronological",
["C", "B", "A", "D"],
),
(
"chronological",
["D", "A", "B", "C"],
),
],
)
def test_sort_entries_with_ranges(order, expected):
data_model = _create_sorting_data_model_with_ranges(order)
entries = data_model.cv.sections[0].entries
companies = [e.company for e in entries]
assert companies == expected
def _create_sorting_data_model_with_ties(order: str) -> data.RenderCVDataModel:
entries = [
{
"company": "A",
"position": "P",
"date": "2020-01-01",
},
{
"company": "B",
"position": "P",
"date": "2020-01-01",
},
{
"company": "C",
"position": "P",
"date": "2020-01-02",
},
]
cv = data.CurriculumVitae(
name="John Doe",
sections={"exp": entries},
)
settings = data.RenderCVSettings(date="2024-01-01", sort_entries=order)
return data.RenderCVDataModel(cv=cv, rendercv_settings=settings)
@pytest.mark.parametrize("order", ["reverse-chronological", "chronological"])
def test_sort_entries_tie_keeps_order(order):
data_model = _create_sorting_data_model_with_ties(order)
entries = data_model.cv.sections[0].entries
companies = [e.company for e in entries]
if order == "reverse-chronological":
assert companies == ["C", "A", "B"]
else:
assert companies == ["A", "B", "C"]