Dataset size on CLI (#345)

* init

* lint

* fix

* lint

* lint

* rm print stmt

* Update dataset_utils.py

prompt2model/dataset_retriever/description_dataset_retriever.py

@@ -13,6 +13,7 @@
 from prompt2model.dataset_retriever.base import DatasetInfo, DatasetRetriever
 from prompt2model.prompt_parser import PromptSpec
 from prompt2model.utils import encode_text, retrieve_objects
+from prompt2model.utils.dataset_utils import get_dataset_size
 
 datasets.utils.logging.disable_progress_bar()
 logger = logging.getLogger(__name__)
@@ -115,10 +116,12 @@ def choose_dataset_by_cli(self, top_datasets: list[DatasetInfo]) -> str | None:
         """
         self._print_divider()
         print("Here are the datasets I've retrieved for you:")
-        print("#\tName\tDescription")
+        print("#\tName\tSize[MB]\tDescription")
         for i, d in enumerate(top_datasets):
-            description_no_spaces = d.description.replace("\n", " ")
-            print(f"{i+1}):\t{d.name}\t{description_no_spaces}")
+            description_no_space = d.description.replace("\n", " ")
+            print(
+                f"{i+1}):\t{d.name}\t{get_dataset_size(d.name)}\t{description_no_space}"
+            )
 
         self._print_divider()
         print(

prompt2model/utils/dataset_utils.py

@@ -0,0 +1,33 @@
+"""Util functions for datasets."""
+
+import requests
+
+from prompt2model.utils.logging_utils import get_formatted_logger
+
+logger = get_formatted_logger("dataset_utils")
+
+
+def query(API_URL):
+    """Returns a response json for a URL."""
+    try:
+        response = requests.get(API_URL)
+        if response.status_code == 200:
+            return response.json()
+        else:
+            logger.error(f"Error occurred in fetching size: {response.status_code}")
+    except requests.exceptions.RequestException as e:
+        logger.error("Error occurred in making the request: " + str(e))
+
+    return {}
+
+
+def get_dataset_size(dataset_name):
+    """Fetches dataset size for a dataset in MB from hugging face API."""
+    API_URL = f"https://datasets-server.huggingface.co/size?dataset={dataset_name}"
+    data = query(API_URL)
+    size_dict = data.get("size", {})
+    return (
+        "NA"
+        if size_dict is {}
+        else "{:.2f}".format(size_dict["dataset"]["num_bytes_memory"] / 1024 / 1024)
+    )

prompt2model/utils/dataset_utils_test.py

@@ -0,0 +1,64 @@
+"""Testing dataset utility functions."""
+from unittest.mock import patch
+
+from prompt2model.utils import dataset_utils
+
+
+@patch("prompt2model.utils.dataset_utils.query")
+def test_get_dataset_size(mock_request):
+    """Test function for get_dataset_size."""
+    mock_request.return_value = {
+        "size": {
+            "dataset": {
+                "dataset": "rotten_tomatoes",
+                "num_bytes_original_files": 487770,
+                "num_bytes_parquet_files": 881052,
+                "num_bytes_memory": 1345449,
+                "num_rows": 10662,
+            },
+            "configs": [
+                {
+                    "dataset": "rotten_tomatoes",
+                    "config": "default",
+                    "num_bytes_original_files": 487770,
+                    "num_bytes_parquet_files": 881052,
+                    "num_bytes_memory": 1345449,
+                    "num_rows": 10662,
+                    "num_columns": 2,
+                }
+            ],
+            "splits": [
+                {
+                    "dataset": "rotten_tomatoes",
+                    "config": "default",
+                    "split": "train",
+                    "num_bytes_parquet_files": 698845,
+                    "num_bytes_memory": 1074806,
+                    "num_rows": 8530,
+                    "num_columns": 2,
+                },
+                {
+                    "dataset": "rotten_tomatoes",
+                    "config": "default",
+                    "split": "validation",
+                    "num_bytes_parquet_files": 90001,
+                    "num_bytes_memory": 134675,
+                    "num_rows": 1066,
+                    "num_columns": 2,
+                },
+                {
+                    "dataset": "rotten_tomatoes",
+                    "config": "default",
+                    "split": "test",
+                    "num_bytes_parquet_files": 92206,
+                    "num_bytes_memory": 135968,
+                    "num_rows": 1066,
+                    "num_columns": 2,
+                },
+            ],
+        },
+        "pending": [],
+        "failed": [],
+        "partial": False,
+    }
+    assert dataset_utils.get_dataset_size("rotten_tomatoes") == "1.28"