def test_data_object_generation(dataframe: pd.DataFrame) -> None:
data_object = DataGrid.generate_data_object(dataframe, "ipydguuid", "key")
expected_output = {
"data": [
{"key": "One", "A": 1, "B": 4, "ipydguuid": 0},
{"key": "Two", "A": 2, "B": 5, "ipydguuid": 1},
{"key": "Three", "A": 3, "B": 6, "ipydguuid": 2},
],
"schema": {
"fields": [
{"name": "key", "type": "string"},
{"name": "A", "type": "integer"},
{"name": "B", "type": "integer"},
{"name": "ipydguuid", "type": "integer"},
],
"primaryKey": ["key", "ipydguuid"],
"pandas_version": "0.20.0",
"primaryKeyUuid": "ipydguuid",
},
"fields": [
{"key": None},
{"A": None},
{"B": None},
{"ipydguuid": None},
],
}
assert data_object == expected_output
def test_default_dataframe_index(dataframe):
# Setting a custom index name
grid = DataGrid(dataframe)
# Making sure index_name is set
assert grid._index_name is None
# Generate primary key schema object
index_key = grid.get_dataframe_index(dataframe)
data_obj = grid.generate_data_object(dataframe, "ipydguuid", index_key)
# Default and unused keys should not be in schema
assert "key" in data_obj["schema"]["primaryKey"]
def test_user_defined_index_name(dataframe):
# Setting a custom index name
dataframe.index.name = "unused_index"
grid = DataGrid(dataframe, index_name="custom_index")
# Making sure index_name is set
assert grid._index_name is not None
# Checking index name matches DataFrame retrieved from grid
index_key = grid.get_dataframe_index(dataframe)
data_obj = grid.generate_data_object(dataframe, "ipydguuid", index_key)
# Default and unused keys should not be in schema
assert "key" not in data_obj["schema"]["primaryKey"]
assert "unused_index" not in data_obj["schema"]["primaryKey"]
# User defined key should be in primary key schema
assert "custom_index" in data_obj["schema"]["primaryKey"]
def data_object(dataframe) -> None:
return DataGrid.generate_data_object(dataframe, "ipydguuid", "key")
