Datasets:

Modalities:
Tabular
Text
Formats:
parquet
ArXiv:
Libraries:
Datasets
pandas
License:
tytskiy commited on
Commit
7ec4728
·
verified ·
1 Parent(s): 9b63850

Update README.md

Browse files
Files changed (1) hide show
  1. README.md +17 -18
README.md CHANGED
@@ -178,51 +178,50 @@ from datasets import load_dataset
178
  ds = load_dataset("yandex/yambda", data_dir="flat/50m", data_files="likes.parquet")
179
  ```
180
 
181
- Also, we provide simple wrapper for convenient
182
- usage
183
  ```python
184
  from typing import Literal
185
-
186
  from datasets import Dataset, DatasetDict, load_dataset
187
 
188
-
189
  class YambdaDataset:
190
- INTERACTIONS = frozenset(["likes", "listens", "multi_event", "dislikes", "unlikes", "undislikes"])
 
 
191
 
192
  def __init__(
193
- self, dataset_type: Literal["flat", "sequential"] = "flat", dataset_size: Literal["50m", "500m", "5b"] = "50m"
 
 
194
  ):
195
  assert dataset_type in {"flat", "sequential"}
196
  assert dataset_size in {"50m", "500m", "5b"}
197
-
198
  self.dataset_type = dataset_type
199
  self.dataset_size = dataset_size
200
 
201
- def interaction(
202
- self, type: Literal["likes", "listens", "multi_event", "dislikes", "unlikes", "undislikes"]
203
- ) -> Dataset:
204
- assert type in YambdaDataset.INTERACTIONS
205
-
206
- return YambdaDataset._download(f"{self.dataset_type}/{self.dataset_size}", type)
207
 
208
  def audio_embeddings(self) -> Dataset:
209
- return YambdaDataset._download("", "embeddings")
210
 
211
  def album_item_mapping(self) -> Dataset:
212
- return YambdaDataset._download("", "album_item_mapping")
213
 
214
  def artist_item_mapping(self) -> Dataset:
215
- return YambdaDataset._download("", "artist_item_mapping")
216
 
217
  @staticmethod
218
  def _download(data_dir: str, file: str) -> Dataset:
219
  data = load_dataset("yandex/yambda", data_dir=data_dir, data_files=f"{file}.parquet")
 
220
  assert isinstance(data, DatasetDict)
221
  return data["train"]
222
 
223
  dataset = YambdaDataset("flat", "50m")
224
-
225
- likes = dataset.interaction("likes")
226
  ```
227
 
228
  ## FAQ
 
178
  ds = load_dataset("yandex/yambda", data_dir="flat/50m", data_files="likes.parquet")
179
  ```
180
 
181
+ Also, we provide simple wrapper for convenient usage:
 
182
  ```python
183
  from typing import Literal
 
184
  from datasets import Dataset, DatasetDict, load_dataset
185
 
 
186
  class YambdaDataset:
187
+ INTERACTIONS = frozenset([
188
+ "likes", "listens", "multi_event", "dislikes", "unlikes", "undislikes"
189
+ ])
190
 
191
  def __init__(
192
+ self,
193
+ dataset_type: Literal["flat", "sequential"] = "flat",
194
+ dataset_size: Literal["50m", "500m", "5b"] = "50m"
195
  ):
196
  assert dataset_type in {"flat", "sequential"}
197
  assert dataset_size in {"50m", "500m", "5b"}
 
198
  self.dataset_type = dataset_type
199
  self.dataset_size = dataset_size
200
 
201
+ def interaction(self, event_type: Literal[
202
+ "likes", "listens", "multi_event", "dislikes", "unlikes", "undislikes"
203
+ ]) -> Dataset:
204
+ assert event_type in YambdaDataset.INTERACTIONS
205
+ return self._download(f"{self.dataset_type}/{self.dataset_size}", event_type)
 
206
 
207
  def audio_embeddings(self) -> Dataset:
208
+ return self._download("", "embeddings")
209
 
210
  def album_item_mapping(self) -> Dataset:
211
+ return self._download("", "album_item_mapping")
212
 
213
  def artist_item_mapping(self) -> Dataset:
214
+ return self._download("", "artist_item_mapping")
215
 
216
  @staticmethod
217
  def _download(data_dir: str, file: str) -> Dataset:
218
  data = load_dataset("yandex/yambda", data_dir=data_dir, data_files=f"{file}.parquet")
219
+ # Returns DatasetDict; extracting the only split
220
  assert isinstance(data, DatasetDict)
221
  return data["train"]
222
 
223
  dataset = YambdaDataset("flat", "50m")
224
+ likes = dataset.interaction("likes") # returns a HuggingFace Dataset
 
225
  ```
226
 
227
  ## FAQ