Dragon Finance Corpus
Collection
A balanced corpus of public financial data across product classes. • 10 items • Updated
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The dataset generation failed
Error code: DatasetGenerationError
Exception: TypeError
Message: int() argument must be a string, a bytes-like object or a real number, not 'NoneType'
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1539, in _prepare_split_single
for key, record in generator:
^^^^^^^^^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 621, in wrapped
for item in generator(*args, **kwargs):
~~~~~~~~~^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 131, in _generate_examples
for example_idx, example in enumerate(self._get_pipeline_from_tar(tar_path, tar_iterator)):
~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 32, in _get_pipeline_from_tar
for filename, f in tar_iterator:
^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/utils/track.py", line 49, in __iter__
for x in self.generator(*self.args):
~~~~~~~~~~~~~~^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/utils/file_utils.py", line 1419, in _iter_from_urlpath
with xopen(urlpath, "rb", download_config=download_config, block_size=0) as f:
~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/utils/file_utils.py", line 976, in xopen
file_obj = fs.open(paths[0], mode)
File "<string>", line 3, in open
File "/usr/local/lib/python3.14/unittest/mock.py", line 1176, in __call__
return self._mock_call(*args, **kwargs)
~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/unittest/mock.py", line 1180, in _mock_call
return self._execute_mock_call(*args, **kwargs)
~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/unittest/mock.py", line 1247, in _execute_mock_call
result = effect(*args, **kwargs)
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 794, in wrapped
tracker.files[urlpath] = {"read": 0, "size": int(f.size)}
~~~^^^^^^^^
TypeError: int() argument must be a string, a bytes-like object or a real number, not 'NoneType'
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 1379, in compute_config_parquet_and_info_response
parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
~~~~~~~~~~~~~~~~~~~~~~~~~^
builder, max_dataset_size_bytes=max_dataset_size_bytes
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 956, in stream_convert_to_parquet
builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1401, in _prepare_split
for job_id, done, content in self._prepare_split_single(
~~~~~~~~~~~~~~~~~~~~~~~~~~^
gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
):
^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1579, in _prepare_split_single
raise DatasetGenerationError("An error occurred while generating the dataset") from e
datasets.exceptions.DatasetGenerationError: An error occurred while generating the datasetNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
__key__ string | __url__ string | csv_id_DEXCAUS unknown | csv_id_DEXCHUS unknown | csv_id_DEXJPUS unknown | csv_id_DEXMXUS unknown | csv_id_DEXSZUS unknown | csv_id_DEXUSAL unknown | csv_id_DEXUSEU unknown | csv_id_DEXUSUK unknown | csv_id_DTWEXAFEGS unknown | csv_id_DTWEXBGS unknown |
|---|---|---|---|---|---|---|---|---|---|---|---|
./fredgraph | "hf://datasets/dragonlimited/Dragon-Finance-FX@a83de93d10eafad21980aa05400b52159184b141/federalreser(...TRUNCATED) | "b2JzZXJ2YXRpb25fZGF0ZSxERVhDQVVTCjE5NzEtMDEtMDQsMS4wMTA5CjE5NzEtMDEtMDUsMS4wMTAyCjE5NzEtMDEtMDYsMS4(...TRUNCATED) | "b2JzZXJ2YXRpb25fZGF0ZSxERVhDSFVTCjE5ODEtMDEtMDIsMS41MzQxCjE5ODEtMDEtMDUsMS41NDE4CjE5ODEtMDEtMDYsMS4(...TRUNCATED) | "b2JzZXJ2YXRpb25fZGF0ZSxERVhKUFVTCjE5NzEtMDEtMDQsMzU3LjczCjE5NzEtMDEtMDUsMzU3LjgxCjE5NzEtMDEtMDYsMzU(...TRUNCATED) | "b2JzZXJ2YXRpb25fZGF0ZSxERVhNWFVTCjE5OTMtMTEtMDgsMy4xNTIwCjE5OTMtMTEtMDksMy4yNDAwCjE5OTMtMTEtMTAsMy4(...TRUNCATED) | "b2JzZXJ2YXRpb25fZGF0ZSxERVhTWlVTCjE5NzEtMDEtMDQsNC4zMTgwCjE5NzEtMDEtMDUsNC4zMTE3CjE5NzEtMDEtMDYsNC4(...TRUNCATED) | "b2JzZXJ2YXRpb25fZGF0ZSxERVhVU0FMCjE5NzEtMDEtMDQsMS4xMTI3CjE5NzEtMDEtMDUsMS4xMTMyCjE5NzEtMDEtMDYsMS4(...TRUNCATED) | "b2JzZXJ2YXRpb25fZGF0ZSxERVhVU0VVCjE5OTktMDEtMDQsMS4xODEyCjE5OTktMDEtMDUsMS4xNzYwCjE5OTktMDEtMDYsMS4(...TRUNCATED) | "b2JzZXJ2YXRpb25fZGF0ZSxERVhVU1VLCjE5NzEtMDEtMDQsMi4zOTM4CjE5NzEtMDEtMDUsMi4zOTQ5CjE5NzEtMDEtMDYsMi4(...TRUNCATED) | "b2JzZXJ2YXRpb25fZGF0ZSxEVFdFWEFGRUdTCjIwMDYtMDEtMDIsMTAxLjc4NTcKMjAwNi0wMS0wMywxMDAuNjk2NwoyMDA2LTA(...TRUNCATED) | "b2JzZXJ2YXRpb25fZGF0ZSxEVFdFWEJHUwoyMDA2LTAxLTAyLDEwMS40MTU1CjIwMDYtMDEtMDMsMTAwLjc1NTgKMjAwNi0wMS0(...TRUNCATED) |
Dragon Finance — fx
Foreign exchange — official US reference rates.
Part of the Dragon Finance Corpus — US public financial data from federal and official sources only. Nothing licensed, paywalled or registration-only.
Coverage
| Reference rates | Federal Reserve H.10: EUR, JPY, GBP, CNY, CAD, MXN, CHF, AUD and more |
| Trade-weighted | broad and AFE dollar indices |
Size
| metric | value |
|---|---|
| stored | 2.03 MB |
| shards | 2 |
Sources present
| source | jurisdiction | data | licence |
|---|---|---|---|
| Federal Reserve | US | Z.1 accounts, SCF, DFA | public |
What you can do with it
- Build FX panels from official rates
- Convert and deflate cross-border figures
For engineers
Data is stored as tar shards (the hub caps a directory at 10,000 files and these tiers run to millions). Members keep their original names and relative paths.
import tarfile
with tarfile.open("0000.tar") as tf:
print(tf.getnames()[:5])
tf.extractall("out/")
| shard | size |
|---|---|
README.md |
1.5 KB |
federalreserve/h10/0000.tar |
2.03 MB |
Every shard records its sha256 in the pipeline ledgers; shards are append-only, so a resumed run re-uploads only what changed. A shard with a failed member is never marked complete, so missed files are retried rather than dropped.
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