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https://api.github.com/repos/huggingface/datasets/issues/4 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4/comments | https://api.github.com/repos/huggingface/datasets/issues/4/events | https://github.com/huggingface/datasets/issues/4 | 600,185,417 | MDU6SXNzdWU2MDAxODU0MTc= | 4 | [Feature] Keep the list of labels of a dataset as metadata | {
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"Yes! I see mostly two options for this:\r\n- a `Feature` approach like currently (but we might deprecate features)\r\n- wrapping in a smart way the Dictionary arrays of Arrow: https://arrow.apache.org/docs/python/data.html?highlight=dictionary%20encode#dictionary-arrays",
"I would have a preference for the secon... | 1,586,945,830,000 | 1,594,227,586,000 | 1,588,572,717,000 | CONTRIBUTOR | null | It would be useful to keep the list of the labels of a dataset as metadata. Either directly in the `DatasetInfo` or in the Arrow metadata. | {
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https://api.github.com/repos/huggingface/datasets/issues/3 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3/comments | https://api.github.com/repos/huggingface/datasets/issues/3/events | https://github.com/huggingface/datasets/issues/3 | 600,180,050 | MDU6SXNzdWU2MDAxODAwNTA= | 3 | [Feature] More dataset outputs | {
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"Yes!\r\n- pandas will be a one-liner in `arrow_dataset`: https://arrow.apache.org/docs/python/generated/pyarrow.Table.html#pyarrow.Table.to_pandas\r\n- for Spark I have no idea. let's investigate that at some point",
"For Spark it looks to be pretty straightforward as well https://spark.apache.org/docs/latest/sq... | 1,586,945,294,000 | 1,588,572,747,000 | 1,588,572,747,000 | CONTRIBUTOR | null | Add the following dataset outputs:
- Spark
- Pandas | {
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https://api.github.com/repos/huggingface/datasets/issues/2 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2/comments | https://api.github.com/repos/huggingface/datasets/issues/2/events | https://github.com/huggingface/datasets/issues/2 | 599,767,671 | MDU6SXNzdWU1OTk3Njc2NzE= | 2 | Issue to read a local dataset | {
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"My first bug report ❤️\r\nLooking into this right now!",
"Ok, there are some news, most good than bad :laughing: \r\n\r\nThe dataset script now became:\r\n```python\r\nimport csv\r\n\r\nimport nlp\r\n\r\n\r\nclass Bbc(nlp.GeneratorBasedBuilder):\r\n VERSION = nlp.Version(\"1.0.0\")\r\n\r\n def __init__(sel... | 1,586,888,331,000 | 1,589,223,323,000 | 1,589,223,322,000 | CONTRIBUTOR | null | Hello,
As proposed by @thomwolf, I open an issue to explain what I'm trying to do without success. What I want to do is to create and load a local dataset, the script I have done is the following:
```python
import os
import csv
import nlp
class BbcConfig(nlp.BuilderConfig):
def __init__(self, **kwargs):
super(BbcConfig, self).__init__(**kwargs)
class Bbc(nlp.GeneratorBasedBuilder):
_DIR = "./data"
_DEV_FILE = "test.csv"
_TRAINING_FILE = "train.csv"
BUILDER_CONFIGS = [BbcConfig(name="bbc", version=nlp.Version("1.0.0"))]
def _info(self):
return nlp.DatasetInfo(builder=self, features=nlp.features.FeaturesDict({"id": nlp.string, "text": nlp.string, "label": nlp.string}))
def _split_generators(self, dl_manager):
files = {"train": os.path.join(self._DIR, self._TRAINING_FILE), "dev": os.path.join(self._DIR, self._DEV_FILE)}
return [nlp.SplitGenerator(name=nlp.Split.TRAIN, gen_kwargs={"filepath": files["train"]}),
nlp.SplitGenerator(name=nlp.Split.VALIDATION, gen_kwargs={"filepath": files["dev"]})]
def _generate_examples(self, filepath):
with open(filepath) as f:
reader = csv.reader(f, delimiter=',', quotechar="\"")
lines = list(reader)[1:]
for idx, line in enumerate(lines):
yield idx, {"idx": idx, "text": line[1], "label": line[0]}
```
The dataset is attached to this issue as well:
[data.zip](https://github.com/huggingface/datasets/files/4476928/data.zip)
Now the steps to reproduce what I would like to do:
1. unzip data locally (I know the nlp lib can detect and extract archives but I want to reduce and facilitate the reproduction as much as possible)
2. create the `bbc.py` script as above at the same location than the unziped `data` folder.
Now I try to load the dataset in three different ways and none works, the first one with the name of the dataset like I would do with TFDS:
```python
import nlp
from bbc import Bbc
dataset = nlp.load("bbc")
```
I get:
```
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/opt/anaconda3/envs/transformers/lib/python3.7/site-packages/nlp/load.py", line 280, in load
dbuilder: DatasetBuilder = builder(path, name, data_dir=data_dir, **builder_kwargs)
File "/opt/anaconda3/envs/transformers/lib/python3.7/site-packages/nlp/load.py", line 166, in builder
builder_cls = load_dataset(path, name=name, **builder_kwargs)
File "/opt/anaconda3/envs/transformers/lib/python3.7/site-packages/nlp/load.py", line 88, in load_dataset
local_files_only=local_files_only,
File "/opt/anaconda3/envs/transformers/lib/python3.7/site-packages/nlp/utils/file_utils.py", line 214, in cached_path
if not is_zipfile(output_path) and not tarfile.is_tarfile(output_path):
File "/opt/anaconda3/envs/transformers/lib/python3.7/zipfile.py", line 203, in is_zipfile
with open(filename, "rb") as fp:
TypeError: expected str, bytes or os.PathLike object, not NoneType
```
But @thomwolf told me that no need to import the script, just put the path of it, then I tried three different way to do:
```python
import nlp
dataset = nlp.load("bbc.py")
```
And
```python
import nlp
dataset = nlp.load("./bbc.py")
```
And
```python
import nlp
dataset = nlp.load("/absolute/path/to/bbc.py")
```
These three ways gives me:
```
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/opt/anaconda3/envs/transformers/lib/python3.7/site-packages/nlp/load.py", line 280, in load
dbuilder: DatasetBuilder = builder(path, name, data_dir=data_dir, **builder_kwargs)
File "/opt/anaconda3/envs/transformers/lib/python3.7/site-packages/nlp/load.py", line 166, in builder
builder_cls = load_dataset(path, name=name, **builder_kwargs)
File "/opt/anaconda3/envs/transformers/lib/python3.7/site-packages/nlp/load.py", line 124, in load_dataset
dataset_module = importlib.import_module(module_path)
File "/opt/anaconda3/envs/transformers/lib/python3.7/importlib/__init__.py", line 127, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "<frozen importlib._bootstrap>", line 1006, in _gcd_import
File "<frozen importlib._bootstrap>", line 983, in _find_and_load
File "<frozen importlib._bootstrap>", line 965, in _find_and_load_unlocked
ModuleNotFoundError: No module named 'nlp.datasets.2fd72627d92c328b3e9c4a3bf7ec932c48083caca09230cebe4c618da6e93688.bbc'
```
Any idea of what I'm missing? or I might have spot a bug :) | {
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https://api.github.com/repos/huggingface/datasets/issues/1 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1/comments | https://api.github.com/repos/huggingface/datasets/issues/1/events | https://github.com/huggingface/datasets/pull/1 | 599,457,467 | MDExOlB1bGxSZXF1ZXN0NDAzMDk1NDYw | 1 | changing nlp.bool to nlp.bool_ | {
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