def test_get_display_value_self_describing_object():
"""Check that SelfDescribingObject is displayed correctly."""
json_object = json.loads("{\"schema\" : \"Integer\", \"value\": 23}")
assert _parse_json_with_schema('SelfDescribing', json_object) == 23
json_object = json.loads("{\"schema\" : \"Integer\"}")
assert _parse_json_with_schema('SelfDescribing', json_object) is None
def test_get_display_value_self_describing_object():
"""Check that SelfDescribingObject is displayed correctly."""
json_object = json.loads('{"schema" : "Integer", "value": 23}')
assert _parse_json_with_schema("SelfDescribing", json_object) == 23
json_object = json.loads('{"schema" : "Integer"}')
assert _parse_json_with_schema("SelfDescribing", json_object) is None
def test_trace_tree_list_deserialization():
raw_trace_tree_list = [
{
"traceElement": {
"fragments": [{
"class": TEXT_FRAGMENT,
"text": "aaa"
}]
}
},
{
"traceElement": {
"fragments": [{
"class": TEXT_FRAGMENT,
"text": "bbb"
}]
}
},
]
trace_tree_list = _parse_json_with_schema("List<TraceTree>",
raw_trace_tree_list)
assert len(trace_tree_list) == 2
assert trace_tree_list[0] == TraceTree(TraceElement([TextFragment("aaa")]),
[])
assert trace_tree_list[1] == TraceTree(TraceElement([TextFragment("bbb")]),
[])
def _rows_to_frame(table_metadata, rows):
# type: (TableMetadata, List[Row]) -> pandas.DataFrame
return pandas.DataFrame.from_records(
[[
_parse_json_with_schema(cm.schema, row.get(cm.name))
for cm in table_metadata.column_metadata
] for row in rows],
columns=table_metadata.get_column_names())
def test_trace_tree_list_representation():
raw_trace_tree_list = [
{
"traceElement": {"fragments": [{"class": TEXT_FRAGMENT, "text": "aaa"}]},
"children": [
{
"traceElement": {
"fragments": [{"class": TEXT_FRAGMENT, "text": "bbb"}]
},
"children": [
{
"traceElement": {
"fragments": [{"class": TEXT_FRAGMENT, "text": "ccc"}]
}
}
],
},
{
"traceElement": {
"fragments": [{"class": TEXT_FRAGMENT, "text": "ddd"}]
}
},
],
},
{
"traceElement": {"fragments": [{"class": TEXT_FRAGMENT, "text": "eee"}]},
"children": [
{
"traceElement": {
"fragments": [{"class": TEXT_FRAGMENT, "text": "fff"}]
}
}
],
},
]
trace_tree_list = _parse_json_with_schema("List<TraceTree>", raw_trace_tree_list)
assert str(trace_tree_list) == "\n".join(
["- aaa", " - bbb", " - ccc", " - ddd", "- eee", " - fff"]
)
html_text = trace_tree_list._repr_html_().replace(" ", "").replace("\n", "")
assert html_text == "".join(
[
"<ul>",
"<li>aaa<ul>",
"<li>bbb<ul>",
"<li>ccc</li></ul></li>",
"<li>ddd</li></ul></li>",
"<li>eee<ul>",
"<li>fff</li></ul></li>",
"</ul>",
]
)
def _rows_to_frame(table_metadata, rows):
# type: (TableMetadata, List[Row]) -> pandas.DataFrame
row_based = [[_parse_json_with_schema(cm.schema, row.get(cm.name))
for cm in table_metadata.column_metadata]
for row in rows]
column_names = table_metadata.get_column_names()
# convert data to column format and force dtype=object on Series
# This gets us consistent `None` values across columns -- no columns
# are treated as numeric.
col_based = {column_names[i]: pandas.Series(column, dtype='object')
for i, column in enumerate(zip(*row_based))}
df = pandas.DataFrame.from_dict(col_based, orient='columns',
dtype='object')
# Re-index to:
# 1. Force ordering of columns
# 2. Set columns even if the dataframe is empty
return df.reindex(labels=column_names, axis='columns')
def test_get_display_value_unknown_schema():
"""Check that Integer values are extracted correctly."""
assert _parse_json_with_schema('bogus', None) is None
json_object = json.loads("{\"foo\" : 23}")
assert _parse_json_with_schema('bogus', json_object) == json_object
def test_get_display_value_integer():
"""Check that Integer values are extracted correctly."""
assert _parse_json_with_schema('Integer', "0") == 0
assert _parse_json_with_schema('Integer', 0) == 0
assert _parse_json_with_schema('Integer', -1) == -1
assert _parse_json_with_schema('Integer', "-1") == -1
