improve hint readability

src/litdata/imports.py

@@ -97,7 +97,7 @@ def _check_requirement(self) -> None:
             self.message = f"Requirement {self.requirement!r} met"
         except Exception as ex:
             self.available = False
-            self.message = f"{ex.__class__.__name__}: {ex}. HINT: Try running `pip install -U {self.requirement!r}`"
+            self.message = f"{ex.__class__.__name__}: {ex}.\n HINT: Try running `pip install -U {self.requirement!r}`"
             requirement_contains_version_specifier = any(c in self.requirement for c in "=<>")
             if not requirement_contains_version_specifier or self.module is not None:
                 module = self.requirement if self.module is None else self.module

src/litdata/processing/functions.py

@@ -254,7 +254,7 @@ def map(
         if _output_dir.url and "cloudspaces" in _output_dir.url:
             raise ValueError(
                 f"The provided `output_dir` isn't valid. Found {_output_dir.path if _output_dir else None}."
-                " HINT: You can either use `/teamspace/s3_connections/...` or `/teamspace/datasets/...`."
+                "\n HINT: You can either use `/teamspace/s3_connections/...` or `/teamspace/datasets/...`."
             )
 
         if error_when_not_empty:
@@ -400,7 +400,7 @@ def optimize(
         if _output_dir.url is not None and "cloudspaces" in _output_dir.url:
             raise ValueError(
                 f"The provided `output_dir` isn't valid. Found {_output_dir.path}."
-                " HINT: You can either use `/teamspace/s3_connections/...` or `/teamspace/datasets/...`."
+                "\n HINT: You can either use `/teamspace/s3_connections/...` or `/teamspace/datasets/...`."
             )
 
         _assert_dir_has_index_file(_output_dir, mode=mode, use_checkpoint=use_checkpoint)

src/litdata/processing/utilities.py

@@ -46,7 +46,7 @@ def _create_dataset(
     project_id = os.getenv("LIGHTNING_CLOUD_PROJECT_ID", None)
     cluster_id = os.getenv("LIGHTNING_CLUSTER_ID", None)
     user_id = os.getenv("LIGHTNING_USER_ID", None)
-    cloud_space_id = os.getenv("LIGHTNING_CLOUD_SPACE_ID", None)
+    studio_id = os.getenv("LIGHTNING_CLOUD_SPACE_ID", None)
     lightning_app_id = os.getenv("LIGHTNING_CLOUD_APP_ID", None)
 
     if project_id is None:
@@ -64,7 +64,7 @@ def _create_dataset(
     try:
         client.dataset_service_create_dataset(
             body=ProjectIdDatasetsBody(
-                cloud_space_id=cloud_space_id if lightning_app_id is None else None,
+                cloud_space_id=studio_id if lightning_app_id is None else None,
                 cluster_id=cluster_id,
                 creator_id=user_id,
                 empty=empty,

src/litdata/streaming/dataloader.py

@@ -103,7 +103,7 @@ def __getitem__(self, index: int) -> Any:
                 if not _equal_items(data_1, data2):
                     raise ValueError(
                         f"Your dataset items aren't deterministic. Found {data_1} and {data2} for index {index}."
-                        " HINT: Use the `litdata.cache.Cache` directly within your dataset."
+                        "\n HINT: Use the `litdata.cache.Cache` directly within your dataset."
                     )
                 self._is_deterministic = True
             self._cache[index] = data_1
@@ -115,7 +115,7 @@ class CacheCollateFn:
 
     During the chunking phase, there is no need to return any data from the DataLoader reducing some time.
 
-    Additionally, if the user makes their __getitem__ asynchronous, the collate executes them in parallel.
+    Additionally, if the user makes their __getitem__ asynchronous, collate executes them in parallel.
 
     """
 

src/litdata/streaming/dataset.py

@@ -177,7 +177,7 @@ def _create_cache(self, worker_env: _WorkerEnv) -> Cache:
         if not cache.filled:
             raise ValueError(
                 f"The provided dataset `{self.input_dir}` doesn't contain any {_INDEX_FILENAME} file."
-                " HINT: Did you successfully optimize a dataset to the provided `input_dir`?"
+                "\n HINT: Did you successfully optimize a dataset to the provided `input_dir`?"
             )
 
         return cache

src/litdata/streaming/resolver.py

@@ -108,10 +108,10 @@ def _resolve_studio(dir_path: str, target_name: Optional[str], target_id: Option
     project_id = os.getenv("LIGHTNING_CLOUD_PROJECT_ID", None)
 
     if cluster_id is None:
-        raise RuntimeError("The `cluster_id` couldn't be found from the environment variables.")
+        raise RuntimeError("The `LIGHTNING_CLUSTER_ID` couldn't be found from the environment variables.")
 
     if project_id is None:
-        raise RuntimeError("The `project_id` couldn't be found from the environment variables.")
+        raise RuntimeError("The `LIGHTNING_CLOUD_PROJECT_ID` couldn't be found from the environment variables.")
 
     clusters = client.cluster_service_list_project_clusters(project_id).clusters
 
@@ -147,7 +147,7 @@ def _resolve_s3_connections(dir_path: str) -> Dir:
     # Get the ids from env variables
     project_id = os.getenv("LIGHTNING_CLOUD_PROJECT_ID", None)
     if project_id is None:
-        raise RuntimeError("The `project_id` couldn't be found from the environment variables.")
+        raise RuntimeError("The `LIGHTNING_CLOUD_PROJECT_ID` couldn't be found from the environment variables.")
 
     target_name = dir_path.split("/")[3]
 
@@ -169,16 +169,16 @@ def _resolve_datasets(dir_path: str) -> Dir:
     # Get the ids from env variables
     cluster_id = os.getenv("LIGHTNING_CLUSTER_ID", None)
     project_id = os.getenv("LIGHTNING_CLOUD_PROJECT_ID", None)
-    cloud_space_id = os.getenv("LIGHTNING_CLOUD_SPACE_ID", None)
+    studio_id = os.getenv("LIGHTNING_CLOUD_SPACE_ID", None)
 
     if cluster_id is None:
-        raise RuntimeError("The `cluster_id` couldn't be found from the environment variables.")
+        raise RuntimeError("The `LIGHTNING_CLUSTER_ID` couldn't be found from the environment variables.")
 
     if project_id is None:
-        raise RuntimeError("The `project_id` couldn't be found from the environment variables.")
+        raise RuntimeError("The `LIGHTNING_CLOUD_PROJECT_ID` couldn't be found from the environment variables.")
 
-    if cloud_space_id is None:
-        raise RuntimeError("The `cloud_space_id` couldn't be found from the environment variables.")
+    if studio_id is None:
+        raise RuntimeError("The `LIGHTNING_CLOUD_SPACE_ID` couldn't be found from the environment variables.")
 
     clusters = client.cluster_service_list_project_clusters(project_id).clusters
 
@@ -187,17 +187,17 @@ def _resolve_datasets(dir_path: str) -> Dir:
         for cloudspace in client.cloud_space_service_list_cloud_spaces(
             project_id=project_id, cluster_id=cluster_id
         ).cloudspaces
-        if cloudspace.id == cloud_space_id
+        if cloudspace.id == studio_id
     ]
 
     if not target_cloud_space:
-        raise ValueError(f"We didn't find any matching Studio for the provided id `{cloud_space_id}`.")
+        raise ValueError(f"We didn't find any matching Studio for the provided id `{studio_id}`.")
 
     target_cluster = [cluster for cluster in clusters if cluster.id == target_cloud_space[0].cluster_id]
 
     if not target_cluster:
         raise ValueError(
-            f"We didn't find a matching cluster associated with the id {target_cloud_space[0].cluster_id}."
+            f"We didn't find a matching cluster associated with the id `{target_cloud_space[0].cluster_id}`."
         )
 
     return Dir(
@@ -211,7 +211,7 @@ def _resolve_datasets(dir_path: str) -> Dir:
 
 def _assert_dir_is_empty(output_dir: Dir, append: bool = False, overwrite: bool = False) -> None:
     if not isinstance(output_dir, Dir):
-        raise ValueError("The provided output_dir isn't a Dir Object.")
+        raise ValueError("The provided output_dir isn't a `Dir` Object.")
 
     if output_dir.url is None:
         return
@@ -234,7 +234,7 @@ def _assert_dir_is_empty(output_dir: Dir, append: bool = False, overwrite: bool
     if objects["KeyCount"] > 0:
         raise RuntimeError(
             f"The provided output_dir `{output_dir.path}` already contains data and datasets are meant to be immutable."
-            " HINT: Did you consider changing the `output_dir` with your own versioning as a suffix?"
+            "\n HINT: Did you consider changing the `output_dir` with your own versioning as a suffix?"
         )
 
 
@@ -261,8 +261,8 @@ def _assert_dir_has_index_file(
             if os.path.exists(index_file) and mode is None:
                 raise RuntimeError(
                     f"The provided output_dir `{output_dir.path}` already contains an optimized immutable datasets."
-                    " HINT: Did you consider changing the `output_dir` with your own versioning as a suffix?"
-                    " HINT: If you want to append/overwrite to the existing dataset, use `mode='append | overwrite'`."
+                    "\n HINT: Did you consider changing the `output_dir` with your own versioning as a suffix?"
+                    "\n HINT: If you want to append/overwrite to the existing dataset, use `mode='append | overwrite'`."
                 )
 
             # delete index.json file and chunks
@@ -310,8 +310,8 @@ def _assert_dir_has_index_file(
     if has_index_file and mode is None:
         raise RuntimeError(
             f"The provided output_dir `{output_dir.path}` already contains an optimized immutable datasets."
-            " HINT: Did you consider changing the `output_dir` with your own versioning as a suffix?"
-            " HINT: If you want to append/overwrite to the existing dataset, use `mode='append | overwrite'`."
+            "\n HINT: Did you consider changing the `output_dir` with your own versioning as a suffix?"
+            "\n HINT: If you want to append/overwrite to the existing dataset, use `mode='append | overwrite'`."
         )
 
     # Delete all the files (including the index file in overwrite mode)

src/litdata/streaming/serializers.py

@@ -103,7 +103,8 @@ def serialize(self, item: Any) -> Tuple[bytes, Optional[str]]:
         if isinstance(item, JpegImageFile):
             if not hasattr(item, "filename"):
                 raise ValueError(
-                    "The JPEG Image's filename isn't defined. HINT: Open the image in your Dataset __getitem__ method."
+                    "The JPEG Image's filename isn't defined."
+                    "\n HINT: Open the image in your Dataset `__getitem__` method."
                 )
             if item.filename and os.path.isfile(item.filename):
                 # read the content of the file directly

src/litdata/utilities/dataset_utilities.py

@@ -64,7 +64,7 @@ def subsample_streaming_dataset(
     else:
         raise ValueError(
             f"The provided dataset `{input_dir.path}` doesn't contain any {_INDEX_FILENAME} file."
-            " HINT: Did you successfully optimize a dataset to the provided `input_dir`?"
+            "\n HINT: Did you successfully optimize a dataset to the provided `input_dir`?"
         )
 
     assert len(original_chunks) > 0, f"No chunks found in the `{input_dir}/index.json` file"

tests/streaming/test_resolver.py

@@ -23,7 +23,9 @@ def test_src_resolver_s3_connections(monkeypatch, lightning_cloud_mock):
     auth = login.Auth()
     auth.save(user_id="7c8455e3-7c5f-4697-8a6d-105971d6b9bd", api_key="e63fae57-2b50-498b-bc46-d6204cbf330e")
 
-    with pytest.raises(RuntimeError, match="`project_id` couldn't be found from the environment variables."):
+    with pytest.raises(
+        RuntimeError, match="`LIGHTNING_CLOUD_PROJECT_ID` couldn't be found from the environment variables."
+    ):
         resolver._resolve_dir("/teamspace/s3_connections/imagenet")
 
     monkeypatch.setenv("LIGHTNING_CLOUD_PROJECT_ID", "project_id")
@@ -60,12 +62,12 @@ def test_src_resolver_studios(monkeypatch, lightning_cloud_mock):
     auth = login.Auth()
     auth.save(user_id="7c8455e3-7c5f-4697-8a6d-105971d6b9bd", api_key="e63fae57-2b50-498b-bc46-d6204cbf330e")
 
-    with pytest.raises(RuntimeError, match="`cluster_id`"):
+    with pytest.raises(RuntimeError, match="`LIGHTNING_CLUSTER_ID`"):
         resolver._resolve_dir("/teamspace/studios/other_studio")
 
     monkeypatch.setenv("LIGHTNING_CLUSTER_ID", "cluster_id")
 
-    with pytest.raises(RuntimeError, match="`project_id`"):
+    with pytest.raises(RuntimeError, match="`LIGHTNING_CLOUD_PROJECT_ID`"):
         resolver._resolve_dir("/teamspace/studios/other_studio")
 
     monkeypatch.setenv("LIGHTNING_CLOUD_PROJECT_ID", "project_id")
@@ -138,17 +140,17 @@ def test_src_resolver_datasets(monkeypatch, lightning_cloud_mock):
 
     assert resolver._resolve_dir("s3://bucket_name").url == "s3://bucket_name"
 
-    with pytest.raises(RuntimeError, match="`cluster_id`"):
+    with pytest.raises(RuntimeError, match="`LIGHTNING_CLUSTER_ID`"):
         resolver._resolve_dir("/teamspace/datasets/imagenet")
 
     monkeypatch.setenv("LIGHTNING_CLUSTER_ID", "cluster_id")
 
-    with pytest.raises(RuntimeError, match="`project_id`"):
+    with pytest.raises(RuntimeError, match="`LIGHTNING_CLOUD_PROJECT_ID`"):
         resolver._resolve_dir("/teamspace/datasets/imagenet")
 
     monkeypatch.setenv("LIGHTNING_CLOUD_PROJECT_ID", "project_id")
 
-    with pytest.raises(RuntimeError, match="`cloud_space_id`"):
+    with pytest.raises(RuntimeError, match="`LIGHTNING_CLOUD_SPACE_ID`"):
         resolver._resolve_dir("/teamspace/datasets/imagenet")
 
     monkeypatch.setenv("LIGHTNING_CLOUD_SPACE_ID", "cloud_space_id")