Update README.md

README.md

@@ -1,4 +1,61 @@
 ---
 license: odbl
 ---
-Weekly snapshots of Models, Datasets and Papers on the HF Hub
+Weekly snapshots of Models, Datasets and Papers on the HF Hub
+
+## Sample code
+
+To query the dataset to see which snapshots are observable, use e.g.:
+```python
+import json
+
+from datasets import load_dataset
+from huggingface_hub import HfApi
+
+REPO_ID = "hfmlsoc/hub_weekly_snapshots"
+
+hf_api = HfApi()
+all_files = hf_api.list_repo_files(repo_id=REPO_ID, repo_type="dataset")
+
+repo_type_to_snapshots = {}
+for repo_fpath in all_files:
+    if ".parquet" in repo_fpath:
+        repo_type = repo_fpath.split("/")[0]
+        repo_type_to_snapshots[repo_type] = repo_type_to_snapshots.get(repo_type, []) + [repo_fpath]
+
+for repo_type in repo_type_to_snapshots:
+    repo_type_to_snapshots[repo_type] = sorted(repo_type_to_snapshots[repo_type], key=lambda x:x.split("/")[1])
+
+repo_type_to_snapshots
+```
+
+You can then load a specific snapshot as e.g.:
+```python
+date = "2025-01-01"
+snapshot = load_dataset(REPO_ID, data_files={date.replace("-",""): f"datasets/{date}/datasets.parquet"})
+snapshot
+```
+
+Returning:
+```
+DatasetDict({
+    20250101: Dataset({
+        features: ['_id', 'id', 'author', 'cardData', 'disabled', 'gated', 'lastModified', 'likes', 'trendingScore', 'private', 'sha', 'description', 'downloads', 'tags', 'createdAt', 'key', 'paperswithcode_id', 'citation'],
+        num_rows: 276421
+    })
+})
+```
+
+### Sample analysis of top datasets
+
+To look at the 10 most liked datasets as of January 1st 2025, you can then run:
+```python
+[{
+    "id": row['id'],
+    "tags": json.loads(row["cardData"]).get("tags", []),
+    "tasks": json.loads(row["cardData"]).get("task_categories", []),
+    "likes": row['likes'],
+} for row in snapshot["20250101"].sort("likes", reverse=True).select(range(10))]
+```
+
+Most of the user-maintained metadata for Hub repositories is stored in the cardData field, which is saved as a JSON-formated string