def test_table_answer_element_excluded_rows():
"""Check deserialization creates empty table when no rows are present."""
answer = {
"answerElements": [{
"metadata": {
"columnMetadata":
[
{
"name": "col1",
"schema": "String"
}
]
},
"excludedRows": [{
"exclusionName": "myEx",
"rows": [{
"col1": "stringValue"
}]
}]
}]
}
table = TableAnswer(answer)
assert len(table.excluded_rows) == 1
assert len(table.excluded_rows["myEx"]) == 1
assert table.excluded_frame("myEx").size == 1
def test_table_answer_element_deser():
"""Check proper deserialization for a valid table answer."""
answer = {
"answerElements": [{
"metadata": {
"columnMetadata": [
{
"name": "col1",
"schema": "String"
},
{
"name": "col2",
"schema": "String"
},
]
},
"rows": [{
"col1": "value1",
"col2": "value2"
}],
}]
}
table = TableAnswer(answer)
assert len(table.metadata.column_metadata) == 2
assert table.metadata.column_metadata[0].name == "col1"
assert len(table.rows) == 1
assert table.rows[0].get("col1") == "value1"
assert table.rows[0].get("col2") == "value2"
assert not table.frame().empty
def test_table_answer_element_no_metadata():
"""Exception is raised when metadata field is not present."""
answer = {"answerElements": [{"nometadata": {}}]}
with pytest.raises(ValueError):
TableAnswer(answer)
answer = {"answerElements": [{}]}
with pytest.raises(ValueError):
TableAnswer(answer)
def test_table_answer_immutable_lists():
answer = {
"answerElements": [{
"metadata": {
"columnMetadata": [{
"name": "col1",
"schema": "List<String>"
}]
},
"rows": [{
"col1": ["e1", "e2", "e3"]
}],
}]
}
table = TableAnswer(answer)
assert isinstance(table.frame().loc[0]["col1"], ListWrapper)
def test_table_answer_element_deser_no_rows():
"""Check deserialization creates empty table when no rows are present."""
answer = {
"answerElements": [{
"metadata": {
"columnMetadata": [{
"name": "col1",
"schema": "Node"
}]
}
}]
}
table = TableAnswer(answer)
assert len(table.metadata.column_metadata) == 1
assert table.metadata.column_metadata[0].name == "col1"
assert len(table.rows) == 0
assert table.frame().empty
def from_string(json_string):
# type: (str) -> Answer
"""Take a string representing a Batfish answer, return answer object.
:returns either an old :py:class:`Answer`
or new :py:class:`TableAnswer` class.
"""
o = json.loads(json_string)
if "answerElements" in o and "metadata" in o["answerElements"][0]:
return TableAnswer(o)
else:
return Answer(o)
def bf_str_answer(answer_json):
"""Convert the Json answer to a string."""
try:
if "answerElements" in answer_json and "metadata" in \
answer_json["answerElements"][0]:
table_answer = TableAnswer(answer_json)
return table_answer.table_data.to_string()
else:
return get_answer_text(answer_json)
except Exception as error:
return "Error getting answer text: {}\n Original Json:\n {}".format(
error, json.dumps(answer_json, indent=2))
def test_table_answer_dtype_object():
"""
Ensure table answer frames have dtype of object.
This also means converting missing values to None (and not ``numpy.nan``)
"""
answer = {
"answerElements": [{
"metadata": {
"columnMetadata": [
{
"name": "col1",
"schema": "String"
},
{
"name": "col2",
"schema": "Integer"
},
]
},
"rows": [
{
"col1": "v1",
"col2": 1
},
{
"col1": "v2",
"col2": None
},
{
"col1": "v3",
"col2": -1
},
{
"col1": "v4",
"col2": "-1"
},
],
}]
}
df = TableAnswer(answer).frame()
assert df["col1"].dtype == "object"
assert df["col2"].dtype == "object"
assert df["col2"][1] is None
assert str(df["col2"][1]) == "None"
def test_table_answer_no_answer_elements():
"""Exception is raised when answer elements are empty or not present."""
with pytest.raises(ValueError):
TableAnswer({})
with pytest.raises(ValueError):
TableAnswer({"answerElements": []})