Setup CI

.devcontainer/devcontainer.json

@@ -3,16 +3,19 @@
 {
 	"name": "Python 3",
 	// Or use a Dockerfile or Docker Compose file. More info: https://containers.dev/guide/dockerfile
-	"image": "mcr.microsoft.com/devcontainers/python:0-3.9",
+	"image": "mcr.microsoft.com/devcontainers/python:0-3.10",
 
 	// Features to add to the dev container. More info: https://containers.dev/features.
-	// "features": {},
+	"features": {
+		"ghcr.io/jsburckhardt/devcontainer-features/uv:1": {},
+		"ghcr.io/jsburckhardt/devcontainer-features/ruff:1": {}
+	},
 
 	// Use 'forwardPorts' to make a list of ports inside the container available locally.
 	// "forwardPorts": [],
 
 	// Use 'postCreateCommand' to run commands after the container is created.
-	"postCreateCommand": "pip3 install --user -r requirements-dev.txt; pre-commit install",
+	"postCreateCommand": "uv pip install --prefix ~/.local -r requirements-dev.txt && prek install",
 
 	// Configure tool-specific properties.
 	"customizations": {

.github/ISSUE_TEMPLATE/bug.yml

@@ -22,7 +22,7 @@ body:
     id: environment
     attributes:
       label: Environment
-      description: Please provide environment details that will help us reproduce the issue e.g. operating system and tubular/scikit-learn/pandas versions.
+      description: Please provide environment details that will help us reproduce the issue e.g. operating system and numpy/shap/xgboost-cpu versions.
     validations:
       required: true    
   - type: textarea

.github/workflows/python-package.yml

@@ -2,6 +2,9 @@
 
 name: Python package build and test
 
+permissions:
+  contents: read
+
 on:
   push:
   pull_request:
@@ -42,9 +45,9 @@ jobs:
 
       - name: Upload coverage pytest html test results to github
         if: always()
-        uses: actions/upload-artifact@v3
+        uses: actions/upload-artifact@v4
         with:
-          name: coverage-html-pytest-results
+          name: coverage-html-pytest-results-${{ matrix.python-version }}
           path: htmlcov
 
   lint:
@@ -56,27 +59,37 @@ jobs:
     steps:
         - uses: actions/checkout@v3
 
-        - name: Set up Python 3.9
+        - name: Set up Python ${{ matrix.python-version }}
           uses: actions/setup-python@v4
           with:
-            python-version: 3.9
+            python-version: ${{ matrix.python-version }}
 
-        - name: Install ruff
+        - name: Install linters
           run: |
             python -m pip install uv
-            uv venv -p 3.9 ruff
-            source ruff/bin/activate
+            uv venv -p ${{ matrix.python-version }} $HOME/lints
+            source $HOME/lints/bin/activate
             uv pip install -r requirements-dev.txt
 
         - name: Lint with ruff
           run: |
-            source ruff/bin/activate
+            source $HOME/lints/bin/activate
             ruff --version
             ruff check --output-format github .
 
-        - name: Check formatting with ruff
+        - name: Check for typos with codespell
           run: |
-            source ruff/bin/activate
-            ruff --version
-            ruff format --diff .
-            ruff format --check .
+            source $HOME/lints/bin/activate
+            codespell --version
+            codespell .
+
+        - name: Check for typos with typos
+          run: |
+            source $HOME/lints/bin/activate
+            typos --version
+            typos .
+
+        - name: lint code examples in docs
+          run: |
+            source $HOME/lints/bin/activate
+            prek run blacken-docs --all-files

.pre-commit-config.yaml

@@ -1,12 +1,31 @@
-repos: 
- -  repo: https://github.com/ambv/black
-    rev: 22.3.0
-    hooks:
-    - id: black
-      language_version: python3
-
- -  repo: https://github.com/pycqa/bandit
-    rev: 1.7.4
-    hooks:
-    - id: bandit
-
+repos:
+-   repo: https://github.com/astral-sh/ruff-pre-commit
+    # Ruff version.
+    rev: v0.14.0
+    hooks:
+      # Run the linter.
+      - id: ruff
+        args: [ --fix, --exit-non-zero-on-fix ]
+      # Run the formatter.
+      - id: ruff-format
+-   repo: https://github.com/MarcoGorelli/auto-walrus
+    rev: 0.3.4
+    hooks:
+    -   id: auto-walrus
+-   repo: https://github.com/codespell-project/codespell
+    rev: 'v2.4.1'
+    hooks:
+      - id: codespell
+        additional_dependencies:
+          - tomli
+-   repo: https://github.com/crate-ci/typos
+    rev: 'v1.39.0'
+    hooks:
+      - id: typos
+-   repo: https://github.com/adamchainz/blacken-docs
+    rev: "1.20.0" 
+    hooks:
+    -   id: blacken-docs
+        args: [--skip-errors]
+        additional_dependencies:
+        - black==22.12.0

CHANGELOG.rst

@@ -16,13 +16,23 @@ Subsections for each version can be one of the following;
 
 Each individual change should have a link to the pull request after the description of the change.
 
+1.0.1 (unreleased)
+------------------
+
+Changed
+^^^^^^^
+- Reactivated CI and added PR approval guardrails (https://github.com/azukds/model_interpreter/pull/8)
+- Updated CI configuration to follow tubular's python-package.yml (https://github.com/azukds/model_interpreter/pull/8)
+- Switched to prek for pre-commit checks (https://github.com/azukds/model_interpreter/pull/8)
+- Fixed spelling mistakes and removed stale tubular references (https://github.com/azukds/model_interpreter/pull/8)
+
 1.0.0 (2024-08-06)
 -------------------
 
 Added
 ^^^^^
 - Moved config to pyproject.toml approach
-- Updated envs and impacted logic (e.g to accomodate new shap behaviour)
+- Updated envs and impacted logic (e.g to accommodate new shap behaviour)
 - Setup devcontainer config for codespaces
 - Updated build pipeline
 

CONTRIBUTING.rst

@@ -1,7 +1,7 @@
 Contributing
 ============
 
-Thanks for your interest in contributing to this package! No contibution is too small! We're hoping it can be made even better through community contributions.
+Thanks for your interest in contributing to this package! No contribution is too small! We're hoping it can be made even better through community contributions.
 
 Requests and feedback
 ---------------------
@@ -24,7 +24,7 @@ Then clone the fork (or this repository if internal);
      git clone https://github.com/lvgig/model_interpreter.git
      cd model_interpreter
 
-Then install tubular and dependencies for development;
+Then install model_interpreter and dependencies for development;
 
    .. code::
 

README.md

@@ -27,10 +27,12 @@ from model_interpreter.interpreter import ModelInterpreter
 
 # generate a classification dataset
 X, y = make_classification(
-n_samples=1000, 
-n_features=4, n_informative=2,
- n_redundant=0, random_state=0, 
-shuffle=False
+    n_samples=1000,
+    n_features=4,
+    n_informative=2,
+    n_redundant=0,
+    random_state=0,
+    shuffle=False,
 )
 
 # fit a model
@@ -45,11 +47,10 @@ model_interpreter.fit(clf)
 # return feature contribution importances for a single row
 single_row = X.head(1)
 contribution_list = single_model_contribution.transform(
-single_row, return_type="name_value_dicts"
+    single_row, return_type="name_value_dicts"
 )
 
 print(contribution_list)
-
 ```
 
 Which will return the following output:

examples/Random_Forest/binary_classification.ipynb

@@ -137,7 +137,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "A model interpreter object is created by specifiying the feature names in the same order as used for building the model."
+    "A model interpreter object is created by specifying the feature names in the same order as used for building the model."
    ]
   },
   {
@@ -357,7 +357,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "There are also three `sorting` options avaliable:\n",
+    "There are also three `sorting` options available:\n",
     "- `'abs'`,  which is the default used in the above examples sorts by the absolute value of the feature contribution\n",
     "- `'positive'`, which sorts the contributions in descending order\n",
     "- `'label'`, which sorts in a descending order if `pred_label > 0`, and ascending if `pred_label = 0`\n",

examples/Random_Forest/multiclass_classification.ipynb

@@ -139,7 +139,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "A model interpreter object is created by specifiying the feature names in the same order as used for building the model."
+    "A model interpreter object is created by specifying the feature names in the same order as used for building the model."
    ]
   },
   {
@@ -364,7 +364,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "There are also three `sorting` options avaliable:\n",
+    "There are also three `sorting` options available:\n",
     "- `'abs'`,  which is the default used in the above examples sorts by the absolute value of the feature contribution\n",
     "- `'positive'`, which sorts the contributions in descending order\n",
     "- `'label'`, which sorts in a descending order if `pred_label > 0`, and ascending if `pred_label = 0`\n",

examples/XGB/example.ipynb

@@ -184,7 +184,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "A model interpreter object is created by specifiying the feature names in the same order as used for building the model."
+    "A model interpreter object is created by specifying the feature names in the same order as used for building the model."
    ]
   },
   {
@@ -343,7 +343,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[{'Name': 'MedInc feature', 'Value': -0.7173248529}, {'Name': 'Lattitude of location', 'Value': -0.2954589427}, {'Name': 'Average occupation', 'Value': -0.2584415674}, {'Name': 'Longitude of location', 'Value': -0.194666937}, {'Name': 'Average number of rooms', 'Value': 0.0455645546}, {'Name': 'Age of house', 'Value': -0.0052499785}, {'Name': 'Average number of bedrooms', 'Value': -0.0039967196}, {'Name': 'Population feature', 'Value': -0.0015882736}]\n"
+      "[{'Name': 'MedInc feature', 'Value': -0.7173248529}, {'Name': 'Latitude of location', 'Value': -0.2954589427}, {'Name': 'Average occupation', 'Value': -0.2584415674}, {'Name': 'Longitude of location', 'Value': -0.194666937}, {'Name': 'Average number of rooms', 'Value': 0.0455645546}, {'Name': 'Age of house', 'Value': -0.0052499785}, {'Name': 'Average number of bedrooms', 'Value': -0.0039967196}, {'Name': 'Population feature', 'Value': -0.0015882736}]\n"
      ]
     }
    ],
@@ -355,7 +355,7 @@
     "    \"AveBedrms\": \"Average number of bedrooms\",\n",
     "    \"Population\": \"Population feature\",\n",
     "    \"AveOccup\": \"Average occupation\",\n",
-    "    \"Latitude\": \"Lattitude of location\",\n",
+    "    \"Latitude\": \"Latitude of location\",\n",
     "    \"Longitude\": \"Longitude of location\",\n",
     "}\n",
     "\n",
@@ -412,7 +412,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "There are also three `sorting` options avaliable:\n",
+    "There are also three `sorting` options available:\n",
     "- `'abs'`,  which is the default used in the above examples sorts by the absolute value of the feature contribution\n",
     "- `'positive'`, which sorts the contributions in descending order\n",
     "- `'label'`, which sorts in a descending order if `pred_label > 0`, and ascending if `pred_label = 0`\n",
@@ -436,7 +436,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[{'Name': 'MedInc feature', 'Value': -0.7173248529}, {'Name': 'Lattitude of location', 'Value': -0.2954589427}, {'Name': 'Average occupation', 'Value': -0.2584415674}, {'Name': 'Longitude of location', 'Value': -0.194666937}, {'Name': 'Average number of rooms', 'Value': 0.0455645546}]\n"
+      "[{'Name': 'MedInc feature', 'Value': -0.7173248529}, {'Name': 'Latitude of location', 'Value': -0.2954589427}, {'Name': 'Average occupation', 'Value': -0.2584415674}, {'Name': 'Longitude of location', 'Value': -0.194666937}, {'Name': 'Average number of rooms', 'Value': 0.0455645546}]\n"
      ]
     }
    ],
@@ -461,7 +461,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[{'Name': 'Average number of rooms', 'Value': 0.0455645546}, {'Name': 'Population feature', 'Value': -0.0015882736}, {'Name': 'Average number of bedrooms', 'Value': -0.0039967196}, {'Name': 'Age of house', 'Value': -0.0052499785}, {'Name': 'Longitude of location', 'Value': -0.194666937}, {'Name': 'Average occupation', 'Value': -0.2584415674}, {'Name': 'Lattitude of location', 'Value': -0.2954589427}, {'Name': 'MedInc feature', 'Value': -0.7173248529}]\n"
+      "[{'Name': 'Average number of rooms', 'Value': 0.0455645546}, {'Name': 'Population feature', 'Value': -0.0015882736}, {'Name': 'Average number of bedrooms', 'Value': -0.0039967196}, {'Name': 'Age of house', 'Value': -0.0052499785}, {'Name': 'Longitude of location', 'Value': -0.194666937}, {'Name': 'Average occupation', 'Value': -0.2584415674}, {'Name': 'Latitude of location', 'Value': -0.2954589427}, {'Name': 'MedInc feature', 'Value': -0.7173248529}]\n"
      ]
     }
    ],
@@ -486,7 +486,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[{'Name': 'MedInc feature', 'Value': -0.7173248529}, {'Name': 'Lattitude of location', 'Value': -0.2954589427}, {'Name': 'Average occupation', 'Value': -0.2584415674}, {'Name': 'Longitude of location', 'Value': -0.194666937}, {'Name': 'Age of house', 'Value': -0.0052499785}, {'Name': 'Average number of bedrooms', 'Value': -0.0039967196}, {'Name': 'Population feature', 'Value': -0.0015882736}, {'Name': 'Average number of rooms', 'Value': 0.0455645546}]\n"
+      "[{'Name': 'MedInc feature', 'Value': -0.7173248529}, {'Name': 'Latitude of location', 'Value': -0.2954589427}, {'Name': 'Average occupation', 'Value': -0.2584415674}, {'Name': 'Longitude of location', 'Value': -0.194666937}, {'Name': 'Age of house', 'Value': -0.0052499785}, {'Name': 'Average number of bedrooms', 'Value': -0.0039967196}, {'Name': 'Population feature', 'Value': -0.0015882736}, {'Name': 'Average number of rooms', 'Value': 0.0455645546}]\n"
      ]
     }
    ],
@@ -518,7 +518,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "{'MedInc feature': -0.71732485, 'Lattitude of location': -0.29545894, 'Average occupation': -0.25844157, 'Longitude of location': -0.19466694, 'Average number of rooms': 0.045564555}\n"
+      "{'MedInc feature': -0.71732485, 'Latitude of location': -0.29545894, 'Average occupation': -0.25844157, 'Longitude of location': -0.19466694, 'Average number of rooms': 0.045564555}\n"
      ]
     }
    ],
@@ -543,7 +543,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[('MedInc feature', -0.71732485), ('Lattitude of location', -0.29545894), ('Average occupation', -0.25844157), ('Longitude of location', -0.19466694), ('Average number of rooms', 0.045564555)]\n"
+      "[('MedInc feature', -0.71732485), ('Latitude of location', -0.29545894), ('Average occupation', -0.25844157), ('Longitude of location', -0.19466694), ('Average number of rooms', 0.045564555)]\n"
      ]
     }
    ],

examples/XGB/example_ohe.ipynb

@@ -283,7 +283,7 @@
    "metadata": {},
    "source": [
     "\n",
-    "### Create catagorical variable"
+    "### Create categorical variable"
    ]
   },
   {

examples/non_standard_model.ipynb

@@ -239,7 +239,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "A model interpreter object is created by specifiying the feature names in the same order as used for building the model."
+    "A model interpreter object is created by specifying the feature names in the same order as used for building the model."
    ]
   },
   {

model_interpreter/interpreter.py

@@ -25,7 +25,7 @@ class ModelInterpreter:
         model features, if applicable. The one hot encoded feature names are
         automatically derived based on this list, otherwise they are treated
         normally. eg: passing ["colour"] will aggregate the contributions
-        of fields with a name beggining with "colour_" and then return the
+        of fields with a name beginning with "colour_" and then return the
         aggregated contributions for "colour"
 
     """
@@ -113,7 +113,7 @@ def _kernel_explainer_setup(self, model, X_train, is_classification, n_samples):
 
         if is_classification is None:
             raise ValueError(
-                f"is_classification input required to fit kernel explainer. True for a classification model, False for a regression model, recieved {is_classification}"
+                f"is_classification input required to fit kernel explainer. True for a classification model, False for a regression model, received {is_classification}"
             )
 
         elif (is_classification is True) and (not hasattr(model, "predict_proba")):
@@ -406,7 +406,7 @@ def transform(
 
             return_precision: int, default = 16
                 how many decimal places to round the shap values in the return
-                message to. Default is 16 which mantains the decimal places
+                message to. Default is 16 which maintains the decimal places
                 returned by shap explainers
 
         Return:

pyproject.toml

@@ -35,6 +35,9 @@ dev = [
     "pytest-mock",
     "pytest-cov",
     "pytest-benchmark",
+    "prek",
+    "codespell",
+    "typos",
     "hypothesis",
     "mypy",
     "ruff",