Add etna.datasets.load_dataset to public API (#484)

etna-team · Oct 4, 2024 · f24c94a · f24c94a
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diff --git a/CHANGELOG.md b/CHANGELOG.md
@@ -7,7 +7,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ## Unreleased
 ### Added
-- 
+- Add `load_dataset` to public API ([#484](https://github.com/etna-team/etna/pull/484))
 - 
 - 
 - 

diff --git a/docs/source/api_reference/datasets.rst b/docs/source/api_reference/datasets.rst
@@ -45,3 +45,11 @@ Utilities for data manipulation:
    infer_alignment
    apply_alignment
    make_timestamp_df_from_alignment
+
+Utilities for working with internal datasets:
+
+.. autosummary::
+   :toctree: api/
+   :template: base.rst
+
+   load_dataset
diff --git a/docs/source/internal_datasets.rst b/docs/source/internal_datasets.rst
@@ -15,7 +15,8 @@ models. To load them you choose dataset name and use the following code:
 
 The first time, it will take some time to download and save the dataset locally, the next times the data will be read from a file.
 In the example above, we load ``tourism`` dataset with monthly frequency. We also use ``parts="full"``, which means that we load
-the full dataset (each dataset has predefined parts to load).
+the full dataset (each dataset has predefined parts to load). For more details you can check 
+:py:func:`etna.datasets.load_dataset` API reference.
 
 List of internal datasets
 -------------------------

diff --git a/etna/datasets/internal_datasets.py b/etna/datasets/internal_datasets.py
@@ -108,14 +108,14 @@ def load_dataset(
     parts: Union[str, Tuple[str, ...]] = "full",
 ) -> Union[TSDataset, List[TSDataset]]:
     """
-    Load internal dataset.
+    Load internal dataset. Full list of available datasets you can see on :ref:`internal datasets page <internal_datasets>`.
 
     Parameters
     ----------
     name:
         Name of the dataset.
     download_path:
-        The path for saving dataset locally.
+        The path for saving dataset locally. By default it is directory "~/.etna/internal_datasets".
     rebuild_dataset:
         Whether to rebuild the dataset from the original source. If ``rebuild_dataset=False`` and the dataset was saved
         locally, then it would be loaded from disk. If ``rebuild_dataset=True``, then the dataset will be downloaded and