Troubleshooting Save/Load TraceDataset in Python: Common Errors

---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
Cell In[56], line 4
      2 allspans=px.active_session().get_spans_dataframe()
      3 #allspans=px.active_session().get_trace_dataset()
----> 4 dataset = TraceDataset.from_spans(allspans)

File ~\AppData\Local\anaconda3\envs\testdir\Lib\site-packages\phoenix\trace\trace_dataset.py:139, in TraceDataset.from_spans(cls, spans)
    128 @classmethod
    129 def from_spans(cls, spans: List[Span]) -> "TraceDataset":
    130     """Creates a TraceDataset from a list of spans.
    131 
    132     Args:
   (...)
    136         TraceDataset: A TraceDataset containing the spans.
    137     """
    138     return cls(
--> 139         pd.json_normalize(
    140             (json.loads(span_to_json(span)) for span in spans),  # type: ignore
    141             max_level=1,
    142         )
    143     )

File ~\AppData\Local\anaconda3\envs\testdir\Lib\site-packages\pandas\io\json\_normalize.py:461, in _json_normalize(data, record_path, meta, meta_prefix, record_prefix, errors, sep, max_level)
    458     return DataFrame(_simple_json_normalize(data, sep=sep))
    460 if record_path is None:
--> 461     if any([isinstance(x, dict) for x in y.values()] for y in data):
    462         # naive normalization, this is idempotent for flat records
    463         # and potentially will inflate the data considerably for
    464         # deeply nested structures:
    465         #  {VeryLong: { b: 1,c:2}} -> {VeryLong.b:1 ,VeryLong.c:@}
    466         #
    467         # TODO: handle record value which are lists, at least error
    468         #       reasonably
    469         data = nested_to_record(data, sep=sep, max_level=max_level)
    470     return DataFrame(data)

File ~\AppData\Local\anaconda3\envs\testdir\Lib\site-packages\pandas\io\json\_normalize.py:461, in <genexpr>(.0)
    458     return DataFrame(_simple_json_normalize(data, sep=sep))
    460 if record_path is None:
--> 461     if any([isinstance(x, dict) for x in y.values()] for y in data):
    462         # naive normalization, this is idempotent for flat records
    463         # and potentially will inflate the data considerably for
    464         # deeply nested structures:
    465         #  {VeryLong: { b: 1,c:2}} -> {VeryLong.b:1 ,VeryLong.c:@}
    466         #
    467         # TODO: handle record value which are lists, at least error
    468         #       reasonably
    469         data = nested_to_record(data, sep=sep, max_level=max_level)
    470     return DataFrame(data)

AttributeError: 'str' object has no attribute 'values'

---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
Cell In[57], line 3
      1 from phoenix.trace import TraceDataset
      2 #allspans=px.active_session().get_spans_dataframe()
----> 3 allspans=px.active_session().get_trace_dataset()
      4 dataset = TraceDataset.from_spans(allspans)

AttributeError: 'ThreadSession' object has no attribute 'get_trace_dataset'

Name: arize-phoenix
Version: 2.7.0
Summary: ML Observability in your notebook

---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
Cell In[5], line 4
      2 from phoenix.trace import TraceDataset
----> 3 allspans=px.active_session().get_trace_dataset()
      4 dataset = TraceDataset.from_spans(allspans)

AttributeError: 'NoneType' object has no attribute 'get_trace_dataset'

import phoenix as px

# run your app here to collect traces

dataset = px.active_session().get_trace_dataset()