support polars 1.0

Author: jmoralez

environment.yml

@@ -30,7 +30,7 @@ dependencies:
     - fugue[ray]
     - lightgbm_ray
     - nbdev
-    - polars
+    - polars[numpy]>=0.0.0rc0
     - ray<2.8
     - triad==0.9.1
     - utilsforecast>=0.0.27

local_environment.yml

@@ -24,5 +24,5 @@ dependencies:
   - pip:
     - datasetsforecast
     - nbdev
-    - polars
+    - polars[numpy]>=0.0.0rc0
     - utilsforecast>=0.0.27

mlforecast/utils.py

@@ -71,11 +71,18 @@ def generate_daily_series(
             "id_" + series["unique_id"].astype(str).str.rjust(n_digits, "0")
         ).astype("category")
     else:
-        series = series.with_columns(
-            ("id_" + pl.col("unique_id").cast(pl.Utf8).str.rjust(n_digits, "0"))
-            .alias("unique_id")
-            .cast(pl.Categorical)
-        )
+        try:
+            series = series.with_columns(
+                ("id_" + pl.col("unique_id").cast(pl.Utf8).str.pad_start(n_digits, "0"))
+                .alias("unique_id")
+                .cast(pl.Categorical)
+            )
+        except AttributeError:
+            series = series.with_columns(
+                ("id_" + pl.col("unique_id").cast(pl.Utf8).str.rjust(n_digits, "0"))
+                .alias("unique_id")
+                .cast(pl.Categorical)
+            )
     return series
 
 # %% ../nbs/utils.ipynb 16

nbs/utils.ipynb

@@ -118,11 +118,18 @@
     "            'id_' + series['unique_id'].astype(str).str.rjust(n_digits, '0')\n",
     "        ).astype('category')\n",
     "    else:\n",
-    "        series = series.with_columns(\n",
-    "            ('id_' + pl.col('unique_id').cast(pl.Utf8).str.rjust(n_digits, '0'))\n",
-    "            .alias('unique_id')\n",
-    "            .cast(pl.Categorical)\n",
-    "        )\n",
+    "        try:\n",
+    "            series = series.with_columns(\n",
+    "                ('id_' + pl.col('unique_id').cast(pl.Utf8).str.pad_start(n_digits, '0'))\n",
+    "                .alias('unique_id')\n",
+    "                .cast(pl.Categorical)\n",
+    "            )\n",
+    "        except AttributeError:\n",
+    "            series = series.with_columns(\n",
+    "                ('id_' + pl.col('unique_id').cast(pl.Utf8).str.rjust(n_digits, '0'))\n",
+    "                .alias('unique_id')\n",
+    "                .cast(pl.Categorical)\n",
+    "            )\n",
     "    return series"
    ]
   },
@@ -136,6 +143,8 @@
       "text/markdown": [
        "---\n",
        "\n",
+       "[source](https://github.com/Nixtla/mlforecast/blob/main/mlforecast/utils.py#L16){target=\"_blank\" style=\"float:right; font-size:smaller\"}\n",
+       "\n",
        "### generate_daily_series\n",
        "\n",
        ">      generate_daily_series (n_series:int, min_length:int=50,\n",
@@ -163,6 +172,8 @@
       "text/plain": [
        "---\n",
        "\n",
+       "[source](https://github.com/Nixtla/mlforecast/blob/main/mlforecast/utils.py#L16){target=\"_blank\" style=\"float:right; font-size:smaller\"}\n",
+       "\n",
        "### generate_daily_series\n",
        "\n",
        ">      generate_daily_series (n_series:int, min_length:int=50,\n",

settings.ini

@@ -22,7 +22,7 @@ spark_requirements = fugue pyspark>=3.3 lightgbm xgboost
 aws_requirements = fsspec[s3]
 gcp_requirements = fsspec[gcs]
 azure_requirements = fsspec[adl]
-dev_requirements = black datasetsforecast matplotlib mypy nbdev polars prophet pyarrow ruff shap statsmodels
+dev_requirements = black datasetsforecast matplotlib mypy nbdev polars[numpy]>=0.0.0rc0 prophet pyarrow ruff shap statsmodels
 nbs_path = nbs
 doc_path = _docs
 recursive = True