feat: polars prototype

.github/actions/test/action.yml

@@ -4,7 +4,6 @@ inputs:
   python-version:
     description: "Which Python version to run on"
     required: true
-    default: "3.9"
 
 runs:
   using: "composite"

.github/actions/test_tutorials/action.yml

@@ -4,7 +4,6 @@ inputs:
   python-version:
     description: "Which Python version to run on"
     required: true
-    default: "3.9"
 runs:
   using: "composite"
   steps:

.github/workflows/main_test_and_release.yml

@@ -20,7 +20,7 @@ jobs:
     strategy:
       matrix:
         os: [ubuntu-latest]
-        python-version: ["3.8", "3.9", "3.10", "3.11"]
+        python-version: [ "3.10", "3.11", "3.12"]
 
     env:
       python-version: ${{ matrix.python-version }}
@@ -37,7 +37,7 @@ jobs:
   jupyter-tutorials:
     runs-on: ${{ matrix.os }}
     env:
-      python-version: "3.9"
+      python-version: "3.10"
 
     strategy:
       matrix:

.github/workflows/static_type_checks.yml

@@ -29,7 +29,7 @@ jobs:
         uses: actions/setup-python@v4
         id: setup_python
         with:
-          python-version: "3.9"
+          python-version: "3.10"
 
       - name: Install dependencies
         shell: bash

.gitignore

@@ -167,4 +167,5 @@ poetry.lock
 **/tmp/
 **/.tmp/
 
-*nbconvert*
+*nbconvert*
+.testmondata

.pre-commit-config.yaml

@@ -1,13 +1,8 @@
 default_stages: [commit]
 
 repos:
-  - repo: https://github.com/psf/black
-    rev: 22.8.0
-    hooks:
-      - id: black
-
   - repo: https://github.com/charliermarsh/ruff-pre-commit
-    rev: v0.0.254
+    rev: v0.2.1
     hooks:
       - id: ruff
         args:
@@ -19,6 +14,9 @@ repos:
             "--fix",
             "--exit-non-zero-on-fix",
           ]
+        types_or: [ python, pyi, jupyter ]
+      - id: ruff-format
+        types_or: [ python, pyi, jupyter ]
 
   - repo: https://github.com/pre-commit/pre-commit-hooks
     rev: v2.3.0

Dockerfile

@@ -1,4 +1,4 @@
-FROM python:3.9
+FROM python:3.10
 
 RUN apt-get update && apt-get install -y curl
 

docs/conf.py

@@ -68,10 +68,7 @@
 html_show_sourcelink = True
 
 
-source_suffix = {
-    ".rst": "restructuredtext",
-    ".md": "markdown",
-}
+source_suffix = {".rst": "restructuredtext", ".md": "markdown"}
 
 html_static_path = ["_static"]
 html_favicon = "_static/favicon.ico"
@@ -98,21 +95,15 @@
                 </svg>
             """,
             "class": "",
-        },
+        }
     ],
     "source_repository": repo_url,
     "source_branch": "main",
     "source_directory": "docs/",
     "light_logo": "icon.png",
     "dark_logo": "icon_dark.png",
-    "light_css_variables": {
-        "color-brand-primary": "#ff5454",
-        "color-brand-content": "#ff7575",
-    },
-    "dark_css_variables": {
-        "color-brand-primary": "#ff8f8f",
-        "color-brand-content": "#ff8f8f",
-    },
+    "light_css_variables": {"color-brand-primary": "#ff5454", "color-brand-content": "#ff7575"},
+    "dark_css_variables": {"color-brand-primary": "#ff8f8f", "color-brand-content": "#ff8f8f"},
     "sidebar_hide_name": False,
     "navigation_with_keys": True,
 }

docs/tutorials/01_basic.ipynb

@@ -890,9 +890,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from timeseriesflattener.feature_specs.single_specs import OutcomeSpec\n",
-    "from timeseriesflattener.aggregation_fns import maximum\n",
     "import pandas as pd\n",
+    "from timeseriesflattener.aggregation_fns import maximum\n",
+    "from timeseriesflattener.feature_specs.single_specs import OutcomeSpec\n",
     "\n",
     "test_df = pd.DataFrame()\n",
     "\n",
@@ -944,9 +944,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from timeseriesflattener.feature_specs.single_specs import PredictorSpec, StaticSpec\n",
-    "from timeseriesflattener.aggregation_fns import mean\n",
     "import numpy as np\n",
+    "from timeseriesflattener.aggregation_fns import mean\n",
+    "from timeseriesflattener.feature_specs.single_specs import PredictorSpec, StaticSpec\n",
     "\n",
     "temporal_predictor_spec = PredictorSpec(\n",
     "    timeseries_df=df_synth_predictors,\n",
@@ -1116,9 +1116,7 @@
    ],
    "source": [
     "sex_predictor_spec = StaticSpec(\n",
-    "    timeseries_df=df_synth_sex,\n",
-    "    feature_base_name=\"female\",\n",
-    "    prefix=\"pred\",\n",
+    "    timeseries_df=df_synth_sex, feature_base_name=\"female\", prefix=\"pred\"\n",
     ")\n",
     "\n",
     "df_synth_sex"
@@ -1185,7 +1183,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "ts_flattener.add_spec([sex_predictor_spec, temporal_predictor_spec, temporal_interval_predictor_spec, outcome_spec])"
+    "ts_flattener.add_spec(\n",
+    "    [sex_predictor_spec, temporal_predictor_spec, temporal_interval_predictor_spec, outcome_spec]\n",
+    ")"
    ]
   },
   {