Help needed with respect to the zipline ingest data

[YP]

Hi All,

I am using Anaconda to install zipline in my environment.

My environment uses the following:

python                    3.9.2

zipline-reloaded          2.1.1            py39he6999da_0    ml4t

I am trying to ingest quandl bundle using the api key I have.

Upon executing the following command:

zipline ingest -b quandl

I am getting the following error:

C:\MachineLearning\ZeroToMastery\Development\workspace1\sample_project2\env\lib\site-packages\zipline\data\bcolz_daily_bars.py:366: UserWarning: Ignoring 1 values because they are out of bounds for uint32:             open  high   low  close        volume  ex_dividend  split_ratio
2011-04-11  1.79  1.84  1.55    1.7  6.674913e+09          0.0          1.0
  winsorise_uint32(raw_data, invalid_data_behavior, "volume", *OHLC)
Merging daily equity files:  [####################################]
[2022-04-13 00:33:17.180427] INFO: zipline.data.bundles.quandl: Parsing split data.
[2022-04-13 00:33:17.444717] INFO: zipline.data.bundles.quandl: Parsing dividend data.
Traceback (most recent call last):
  File "C:\MachineLearning\ZeroToMastery\Development\workspace1\sample_project2\env\lib\site-packages\pandas\core\construction.py", line 600, in _try_cast
    subarr = construct_1d_ndarray_preserving_na(subarr, dtype, copy=copy)
  File "C:\MachineLearning\ZeroToMastery\Development\workspace1\sample_project2\env\lib\site-packages\pandas\core\dtypes\cast.py", line 1672, in construct_1d_ndarray_preserving_na
    subarr = np.array(values, dtype=dtype, copy=copy)
ValueError: invalid __array_struct__

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "C:\MachineLearning\ZeroToMastery\Development\workspace1\sample_project2\env\Scripts\zipline-script.py", line 10, in <module>
    sys.exit(main())
  File "C:\MachineLearning\ZeroToMastery\Development\workspace1\sample_project2\env\lib\site-packages\click\core.py", line 1130, in __call__
    return self.main(*args, **kwargs)
  File "C:\MachineLearning\ZeroToMastery\Development\workspace1\sample_project2\env\lib\site-packages\click\core.py", line 1055, in main
    rv = self.invoke(ctx)
  File "C:\MachineLearning\ZeroToMastery\Development\workspace1\sample_project2\env\lib\site-packages\click\core.py", line 1657, in invoke
    return _process_result(sub_ctx.command.invoke(sub_ctx))
  File "C:\MachineLearning\ZeroToMastery\Development\workspace1\sample_project2\env\lib\site-packages\click\core.py", line 1404, in invoke
    return ctx.invoke(self.callback, **ctx.params)
  File "C:\MachineLearning\ZeroToMastery\Development\workspace1\sample_project2\env\lib\site-packages\click\core.py", line 760, in invoke
    return __callback(*args, **kwargs)
  File "C:\MachineLearning\ZeroToMastery\Development\workspace1\sample_project2\env\lib\site-packages\zipline\__main__.py", line 389, in ingest
    bundles_module.ingest(
  File "C:\MachineLearning\ZeroToMastery\Development\workspace1\sample_project2\env\lib\site-packages\zipline\data\bundles\core.py", line 445, in ingest
    bundle.ingest(
  File "C:\MachineLearning\ZeroToMastery\Development\workspace1\sample_project2\env\lib\site-packages\zipline\data\bundles\quandl.py", line 207, in quandl_bundle
    adjustment_writer.write(
  File "C:\MachineLearning\ZeroToMastery\Development\workspace1\sample_project2\env\lib\site-packages\zipline\data\adjustments.py", line 689, in write
    self.write_frame("mergers", mergers)
  File "C:\MachineLearning\ZeroToMastery\Development\workspace1\sample_project2\env\lib\site-packages\zipline\data\adjustments.py", line 444, in write_frame
    return self._write(
  File "C:\MachineLearning\ZeroToMastery\Development\workspace1\sample_project2\env\lib\site-packages\zipline\data\adjustments.py", line 393, in _write
    frame = pd.DataFrame(expected_dtypes, index=[])
  File "C:\MachineLearning\ZeroToMastery\Development\workspace1\sample_project2\env\lib\site-packages\pandas\core\frame.py", line 529, in __init__
    mgr = init_dict(data, index, columns, dtype=dtype)
  File "C:\MachineLearning\ZeroToMastery\Development\workspace1\sample_project2\env\lib\site-packages\pandas\core\internals\construction.py", line 287, in init_dict
    return arrays_to_mgr(arrays, data_names, index, columns, dtype=dtype)
  File "C:\MachineLearning\ZeroToMastery\Development\workspace1\sample_project2\env\lib\site-packages\pandas\core\internals\construction.py", line 85, in arrays_to_mgr
    arrays = _homogenize(arrays, index, dtype)
  File "C:\MachineLearning\ZeroToMastery\Development\workspace1\sample_project2\env\lib\site-packages\pandas\core\internals\construction.py", line 355, in _homogenize
    val = sanitize_array(
  File "C:\MachineLearning\ZeroToMastery\Development\workspace1\sample_project2\env\lib\site-packages\pandas\core\construction.py", line 496, in sanitize_array
    subarr = _try_cast(data, dtype, copy, raise_cast_failure)
  File "C:\MachineLearning\ZeroToMastery\Development\workspace1\sample_project2\env\lib\site-packages\pandas\core\construction.py", line 608, in _try_cast
    subarr = np.array(arr, dtype=object, copy=copy)
ValueError: invalid __array_struct__

Can someone help with this.

Regards,

YP