Dragon Finance Corpus
Collection
▓▒░ A balanced corpus of public financial data across 12 classes — US and world official sources; every figure hub-measured. ░▒▓ • 13 items • Updated • 1
Dataset Preview
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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.
pdf unknown | __key__ string | __url__ string |
|---|---|---|
"JVBERi0xLjYNJeLjz9MNCjcyIDAgb2JqDTw8L01ldGFkYXRhIDY5IDAgUi9QYWdlTGF5b3V0L1NpbmdsZVBhZ2UvUGFnZXMgNjU(...TRUNCATED) | ./19801118material | "hf://datasets/dragonlimited/Dragon-Finance-Documents@7e75da5155e3cf965c4d6f12936f9e01c1854e42/fomc/(...TRUNCATED) |
"JVBERi0xLjYNJeLjz9MNCjIyNiAwIG9iag08PC9MaW5lYXJpemVkIDEvTCAzODAxOTk3L08gMjMwL0UgMjk3NTMvTiA1NS9UIDM(...TRUNCATED) | ./19801118meeting | "hf://datasets/dragonlimited/Dragon-Finance-Documents@7e75da5155e3cf965c4d6f12936f9e01c1854e42/fomc/(...TRUNCATED) |
"JVBERi0xLjYNJeLjz9MNCjMzMSAwIG9iag08PC9MaW5lYXJpemVkIDEvTCAzNzQ3NDI2L08gMzM1L0UgMzMwMzkvTiA4MS9UIDM(...TRUNCATED) | ./19970520meeting | "hf://datasets/dragonlimited/Dragon-Finance-Documents@7e75da5155e3cf965c4d6f12936f9e01c1854e42/fomc/(...TRUNCATED) |
"JVBERi0xLjUNJeLjz9MNCjI2MCAwIG9iag08PC9MaW5lYXJpemVkIDEvTCAxNDk0NjQvTyAyNjIvRSAyMzk5L04gNjEvVCAxNDg(...TRUNCATED) | ./BeigeBook_20131016 | "hf://datasets/dragonlimited/Dragon-Finance-Documents@7e75da5155e3cf965c4d6f12936f9e01c1854e42/fomc/(...TRUNCATED) |
"JVBERi0xLjUNCiW1tbW1DQoxIDAgb2JqDQo8PC9UeXBlL0NhdGFsb2cvUGFnZXMgMiAwIFIvTGFuZyhlbi1VUykgL1N0cnVjdFR(...TRUNCATED) | ./BeigeBook_20140416 | "hf://datasets/dragonlimited/Dragon-Finance-Documents@7e75da5155e3cf965c4d6f12936f9e01c1854e42/fomc/(...TRUNCATED) |
"JVBERi0xLjYNJeLjz9MNCjc4NyAwIG9iag08PC9MaW5lYXJpemVkIDEvTCAyNjU0NjYvTyA3ODkvRSAyOTM5OC9OIDUwL1QgMjY(...TRUNCATED) | ./BeigeBook_20140604 | "hf://datasets/dragonlimited/Dragon-Finance-Documents@7e75da5155e3cf965c4d6f12936f9e01c1854e42/fomc/(...TRUNCATED) |
"JVBERi0xLjYNJeLjz9MNCjYyOCAwIG9iag08PC9GaWx0ZXIvRmxhdGVEZWNvZGUvRmlyc3QgODUvTGVuZ3RoIDI1Ni9OIDExL1R(...TRUNCATED) | ./BeigeBook_20140903 | "hf://datasets/dragonlimited/Dragon-Finance-Documents@7e75da5155e3cf965c4d6f12936f9e01c1854e42/fomc/(...TRUNCATED) |
"JVBERi0xLjYNJeLjz9MNCjc3OSAwIG9iag08PC9MaW5lYXJpemVkIDEvTCAxNTk3MjA0L08gNzgxL0UgMzM0OC9OIDUwL1QgMTU(...TRUNCATED) | ./BeigeBook_20141015 | "hf://datasets/dragonlimited/Dragon-Finance-Documents@7e75da5155e3cf965c4d6f12936f9e01c1854e42/fomc/(...TRUNCATED) |
"JVBERi0xLjUNJeLjz9MNCjU1NyAwIG9iag08PC9MaW5lYXJpemVkIDEvTCAyMDUxMzgvTyA1NTkvRSAzNTA1L04gNDgvVCAyMDQ(...TRUNCATED) | ./BeigeBook_20141203 | "hf://datasets/dragonlimited/Dragon-Finance-Documents@7e75da5155e3cf965c4d6f12936f9e01c1854e42/fomc/(...TRUNCATED) |
"JVBERi0xLjQNJeLjz9MNCjE2MCAwIG9iag08PC9MaW5lYXJpemVkIDEvTCAyNDAwMzIvTyAxNjIvRSA4OTM4L04gNTAvVCAyMzk(...TRUNCATED) | ./BeigeBook_20150114 | "hf://datasets/dragonlimited/Dragon-Finance-Documents@7e75da5155e3cf965c4d6f12936f9e01c1854e42/fomc/(...TRUNCATED) |
End of preview.
Dragon Finance — documents
stored: 7.06 GB · shards: 6 · class: documents · sources: US + global official
Finance documents as text: central-bank minutes, transcripts, speeches and reports, extracted from PDF rather than stored unread.
Part of the Dragon Finance Corpus — public financial data from US federal agencies, world official institutions and public registries. Nothing licensed, paywalled or registration-only.
Front door: Dragon-Finance-Corpus
— every card, the chunked corpus and the derived artefacts, all measured from the hub;
collection
— this repo and its siblings.
Coverage
| US monetary policy | the Federal Reserve's FOMC archive - statements, minutes and historical transcripts back to 1936 |
| Format | PDF text-extracted with pdfminer, then chunked like any other document |
| Growing | further publication families are added one verified index page at a time |
Size
| metric | value |
|---|---|
| stored | 7.06 GB |
| shards | 6 |
| training-ready tokens | none yet - no text from this class is in the chunked corpus yet, so it has no training-ready tokens to count |
Training-ready text
Measured 2026-11-04 11:49 UTC over 44 of 44 shard(s), 1 counted before its latest append. Tokens use the one convention these cards share - chars / 4 over the chunked text - so each figure is reconcilable against the shards.
| source | chunks | text | tokens | share |
|---|---|---|---|---|
| (none yet - no text from this class is in the chunked corpus) |
Class attribution uses the shard path's first segment, so a tier that shares a segment with
another class (census, federalreserve, sec) is attributed to its dominant class.
Sources present
| source | jurisdiction | data | licence |
|---|---|---|---|
| Federal Reserve FOMC | US | statements, minutes, historical transcripts (PDF) | US public record |
What you can do with it
- Study monetary-policy language and how it changed over decades
- Ground policy analysis in the primary documents
- Search the historical record of decisions and their wording
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 |
6.4 KB |
fomc/0000.tar |
1.29 GB |
fomc/0001.tar |
1.66 GB |
fomc/0002.tar |
1.62 GB |
fomc/0003.tar |
1.75 GB |
fomc/0004.tar |
741.17 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.
Not advice, no warranty, no endorsement. Compiled from third-party public sources and provided 'as is': derived and model-generated content may be wrong, and source material is routinely restated, amended or superseded. No source agency, exchange or company has reviewed, approved or endorsed this dataset, and none is affiliated with its publisher. Do not use it to re-identify any person, to manipulate any market, or as the sole basis for any decision about any person, entity or instrument. Terms of use:
DISCLAIMER.md.
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