Datasets:

---

P2SAMAPA

/

p2-etf-erl-results

like 1

Error code:   DatasetGenerationError
Exception:    ArrowInvalid
Message:      Schema at index 1 was different: 
date: timestamp[s]
generated_at: string
basis: string
pick: string
conviction: double
rationale: string
pick_source: string
classifier_probs: struct<TLT: double, LQD: double, HYG: double, VNQ: double, GLD: double, SLV: double, QQQ: double, XLK: double, XLF: double, XLE: double, XLV: double, XLI: double, XLY: double, XLP: double, XLU: double, XME: double, IWF: double, XSD: double, XBI: double, GDX: double, IWM: double>
regime: int64
regime_name: string
crisis_prob: double
transition_entropy: double
hmm_probs: struct<0: double, 1: double, 2: double, 3: double, 4: double, 5: double, 6: double, 7: double>
raw_weights: struct<TLT: double, LQD: double, HYG: double, VNQ: double, GLD: double, SLV: double, QQQ: double, XLK: double, XLF: double, XLE: double, XLV: double, XLI: double, XLY: double, XLP: double, XLU: double, XME: double, IWF: double, XSD: double, XBI: double, GDX: double, IWM: double, CASH: double>
gate_A: double
gate_B: double
gate_C: double
rolling_sharpe: double
n_active_rules: int64
active_rule_summary: list<item: string>
portfolio_return: null
benchmark_return: null
excess_return: null
scored: bool
vs
n_scored: int64
first_date: timestamp[s]
last_date: timestamp[s]
computed_at: string
ann_portfolio_return: double
ann_benchmark_return: double
ann_excess_return: double
portfolio_sharpe: double
excess_sharpe: double
max_drawdown: double
win_rate_vs_bench: double
total_excess_return: double
rolling_20d_return: double
rolling_20d_excess: double
rolling_20d_sharpe: double
regime_performance: struct<Low Vol Expansion: struct<n_days: int64, mean_excess: double, win_rate: double>, Curve Flattening: struct<n_days: int64, mean_excess: double, win_rate: double>, Acute Crisis: struct<n_days: int64, mean_excess: double, win_rate: double>, Recovery: struct<n_days: int64, mean_excess: double, win_rate: double>, Late Cycle: struct<n_days: int64, mean_excess: double, win_rate: double>, Mid Cycle Growth: struct<n_days: int64, mean_excess: double, win_rate: double>>
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1800, in _prepare_split_single
                  writer.write_table(table)
                File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 764, in write_table
                  self.write_rows_on_file()  # in case there are buffered rows to write first
                  ^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 662, in write_rows_on_file
                  table = pa.concat_tables(self.current_rows)
                          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "pyarrow/table.pxi", line 6319, in pyarrow.lib.concat_tables
                File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
                File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
              pyarrow.lib.ArrowInvalid: Schema at index 1 was different: 
              date: timestamp[s]
              generated_at: string
              basis: string
              pick: string
              conviction: double
              rationale: string
              pick_source: string
              classifier_probs: struct<TLT: double, LQD: double, HYG: double, VNQ: double, GLD: double, SLV: double, QQQ: double, XLK: double, XLF: double, XLE: double, XLV: double, XLI: double, XLY: double, XLP: double, XLU: double, XME: double, IWF: double, XSD: double, XBI: double, GDX: double, IWM: double>
              regime: int64
              regime_name: string
              crisis_prob: double
              transition_entropy: double
              hmm_probs: struct<0: double, 1: double, 2: double, 3: double, 4: double, 5: double, 6: double, 7: double>
              raw_weights: struct<TLT: double, LQD: double, HYG: double, VNQ: double, GLD: double, SLV: double, QQQ: double, XLK: double, XLF: double, XLE: double, XLV: double, XLI: double, XLY: double, XLP: double, XLU: double, XME: double, IWF: double, XSD: double, XBI: double, GDX: double, IWM: double, CASH: double>
              gate_A: double
              gate_B: double
              gate_C: double
              rolling_sharpe: double
              n_active_rules: int64
              active_rule_summary: list<item: string>
              portfolio_return: null
              benchmark_return: null
              excess_return: null
              scored: bool
              vs
              n_scored: int64
              first_date: timestamp[s]
              last_date: timestamp[s]
              computed_at: string
              ann_portfolio_return: double
              ann_benchmark_return: double
              ann_excess_return: double
              portfolio_sharpe: double
              excess_sharpe: double
              max_drawdown: double
              win_rate_vs_bench: double
              total_excess_return: double
              rolling_20d_return: double
              rolling_20d_excess: double
              rolling_20d_sharpe: double
              regime_performance: struct<Low Vol Expansion: struct<n_days: int64, mean_excess: double, win_rate: double>, Curve Flattening: struct<n_days: int64, mean_excess: double, win_rate: double>, Acute Crisis: struct<n_days: int64, mean_excess: double, win_rate: double>, Recovery: struct<n_days: int64, mean_excess: double, win_rate: double>, Late Cycle: struct<n_days: int64, mean_excess: double, win_rate: double>, Mid Cycle Growth: struct<n_days: int64, mean_excess: double, win_rate: double>>
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1821, in _prepare_split_single
                  num_examples, num_bytes = writer.finalize()
                                            ^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 781, in finalize
                  self.write_rows_on_file()
                File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 662, in write_rows_on_file
                  table = pa.concat_tables(self.current_rows)
                          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "pyarrow/table.pxi", line 6319, in pyarrow.lib.concat_tables
                File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
                File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
              pyarrow.lib.ArrowInvalid: Schema at index 1 was different: 
              date: timestamp[s]
              generated_at: string
              basis: string
              pick: string
              conviction: double
              rationale: string
              pick_source: string
              classifier_probs: struct<TLT: double, LQD: double, HYG: double, VNQ: double, GLD: double, SLV: double, QQQ: double, XLK: double, XLF: double, XLE: double, XLV: double, XLI: double, XLY: double, XLP: double, XLU: double, XME: double, IWF: double, XSD: double, XBI: double, GDX: double, IWM: double>
              regime: int64
              regime_name: string
              crisis_prob: double
              transition_entropy: double
              hmm_probs: struct<0: double, 1: double, 2: double, 3: double, 4: double, 5: double, 6: double, 7: double>
              raw_weights: struct<TLT: double, LQD: double, HYG: double, VNQ: double, GLD: double, SLV: double, QQQ: double, XLK: double, XLF: double, XLE: double, XLV: double, XLI: double, XLY: double, XLP: double, XLU: double, XME: double, IWF: double, XSD: double, XBI: double, GDX: double, IWM: double, CASH: double>
              gate_A: double
              gate_B: double
              gate_C: double
              rolling_sharpe: double
              n_active_rules: int64
              active_rule_summary: list<item: string>
              portfolio_return: null
              benchmark_return: null
              excess_return: null
              scored: bool
              vs
              n_scored: int64
              first_date: timestamp[s]
              last_date: timestamp[s]
              computed_at: string
              ann_portfolio_return: double
              ann_benchmark_return: double
              ann_excess_return: double
              portfolio_sharpe: double
              excess_sharpe: double
              max_drawdown: double
              win_rate_vs_bench: double
              total_excess_return: double
              rolling_20d_return: double
              rolling_20d_excess: double
              rolling_20d_sharpe: double
              regime_performance: struct<Low Vol Expansion: struct<n_days: int64, mean_excess: double, win_rate: double>, Curve Flattening: struct<n_days: int64, mean_excess: double, win_rate: double>, Acute Crisis: struct<n_days: int64, mean_excess: double, win_rate: double>, Recovery: struct<n_days: int64, mean_excess: double, win_rate: double>, Late Cycle: struct<n_days: int64, mean_excess: double, win_rate: double>, Mid Cycle Growth: struct<n_days: int64, mean_excess: double, win_rate: double>>
              
              The above exception was the direct cause of the following exception:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1347, in compute_config_parquet_and_info_response
                  parquet_operations = convert_to_parquet(builder)
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 980, in convert_to_parquet
                  builder.download_and_prepare(
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 882, in download_and_prepare
                  self._download_and_prepare(
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 943, in _download_and_prepare
                  self._prepare_split(split_generator, **prepare_split_kwargs)
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1646, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1832, in _prepare_split_single
                  raise DatasetGenerationError("An error occurred while generating the dataset") from e
              datasets.exceptions.DatasetGenerationError: An error occurred while generating the dataset