Release 2.9.0 (#471)

etna-team · Sep 6, 2024 · 7ad2e61 · 7ad2e61
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diff --git a/CHANGELOG.md b/CHANGELOG.md
@@ -7,13 +7,6 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ## Unreleased
 ### Added
-- Add `**kwargs` argument description for models based on `LinearRegression`, `ElasticNet` and `CatBoostRegressor` ([#454](https://github.com/etna-team/etna/pull/454))  
-- Add possibility to load pretrained embedding models ([#461](https://github.com/etna-team/etna/pull/461))
-- Add `is_freezed` parameter to `TS2VecEmbeddingModel` and `TSTCCEmbeddingModel` ([#461](https://github.com/etna-team/etna/pull/461))
-- 
-- 
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-- Add test on working without extras ([#463](https://github.com/etna-team/etna/pull/463))
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@@ -29,13 +22,6 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 - 
 
 ### Changed
-- Add support of property attributes in `__repr__` and `to_dict` of `BaseMixin` ([#469](https://github.com/etna-team/etna/pull/469))
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@@ -51,15 +37,6 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 - 
 
 ### Fixed
-- Fix `IForestOutlierTransform` failed with ignored `target` column ([#460](https://github.com/etna-team/etna/pull/460))
-- Add lower limit for `typing_extension` versions ([#458](https://github.com/etna-team/etna/pull/458))
-- Fix `ModelDecomposeTransform` import without `prophet` module ([#459](https://github.com/etna-team/etna/pull/459))
-- Convert `segment` to string during reading csv in `backtest` and `forecast` commands ([#470](https://github.com/etna-team/etna/pull/470))
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-- Fix holidays during loading datasets `traffic_2008_10T` and `traffic_2008_hourly` ([#462](https://github.com/etna-team/etna/pull/462))
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@@ -74,6 +51,23 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
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+## [2.9.0] - 2024-09-06
+### Added
+- Add `**kwargs` argument description for models based on `LinearRegression`, `ElasticNet` and `CatBoostRegressor` ([#454](https://github.com/etna-team/etna/pull/454))  
+- Add possibility to load pretrained embedding models ([#461](https://github.com/etna-team/etna/pull/461))
+- Add `is_freezed` parameter to `TS2VecEmbeddingModel` and `TSTCCEmbeddingModel` ([#461](https://github.com/etna-team/etna/pull/461))
+- Add test on working without extras ([#463](https://github.com/etna-team/etna/pull/463))
+
+### Changed
+- Add support of property attributes in `__repr__` and `to_dict` of `BaseMixin` ([#469](https://github.com/etna-team/etna/pull/469))
+
+### Fixed
+- Fix `IForestOutlierTransform` failed with ignored `target` column ([#460](https://github.com/etna-team/etna/pull/460))
+- Add lower limit for `typing_extension` versions ([#458](https://github.com/etna-team/etna/pull/458))
+- Fix `ModelDecomposeTransform` import without `prophet` module ([#459](https://github.com/etna-team/etna/pull/459))
+- Convert `segment` to string during reading csv in `backtest` and `forecast` commands ([#470](https://github.com/etna-team/etna/pull/470))
+- Fix holidays during loading datasets `traffic_2008_10T` and `traffic_2008_hourly` ([#462](https://github.com/etna-team/etna/pull/462))
+
 ## [2.8.0] - 2024-08-13
 ### Added
 - Add `get_anomalies_iqr` function for anomaly detection ([#374](https://github.com/etna-team/etna/pull/374))

diff --git a/docs/source/_static/switcher.json b/docs/source/_static/switcher.json
@@ -5,10 +5,15 @@
         "url": "https://docs.etna.ai/latest/"
     },
     {
-        "name": "2.8.0 (stable)",
-        "version": "2.8.0",
+        "name": "2.9.0 (stable)",
+        "version": "2.9.0",
         "url": "https://docs.etna.ai/stable/"
     },
+    {
+        "name": "2.8.0",
+        "version": "2.8.0",
+        "url": "https://docs.etna.ai/2.8.0/"
+    },
     {
         "name": "2.7.1",
         "version": "2.7.1",

diff --git a/pyproject.toml b/pyproject.toml
@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "etna"
-version = "2.8.0"
+version = "2.9.0"
 repository = "https://github.com/etna-team/etna"
 readme = "README.md"
 description = "ETNA is the first python open source framework of T-Bank AI Center. It is designed to make working with time series simple, productive, and fun."