alteryx · gsheni · Aug 19, 2021
diff --git a/categorical_encoding/primitives/binary_enc.py b/categorical_encoding/primitives/binary_enc.py
@@ -2,7 +2,8 @@
 from featuretools.primitives.base.transform_primitive_base import (
     TransformPrimitive
 )
-from featuretools.variable_types import Categorical, Numeric
+from woodwork.column_schema import ColumnSchema
+from woodwork.logical_types import Categorical, Integer
 
 
 class BinaryEnc(TransformPrimitive):
@@ -25,8 +26,8 @@ class BinaryEnc(TransformPrimitive):
          [0, 1, 1, 1]]
     """
     name = "binary_enc"
-    input_types = [Categorical]
-    return_type = [Numeric]
+    input_types = [ColumnSchema(logical_type=Categorical)]
+    return_type = ColumnSchema(semantic_tags={'numeric'})
 
     def __init__(self, fitted_encoder, category):
         self.mapping, self.mapping_ord = fitted_encoder.get_mapping(category)

diff --git a/categorical_encoding/primitives/hashing_enc.py b/categorical_encoding/primitives/hashing_enc.py
@@ -3,7 +3,8 @@
 from featuretools.primitives.base.transform_primitive_base import (
     TransformPrimitive
 )
-from featuretools.variable_types import Categorical, Numeric
+from woodwork.column_schema import ColumnSchema
+from woodwork.logical_types import Categorical, Integer
 
 
 class HashingEnc(TransformPrimitive):
@@ -28,8 +29,8 @@ class HashingEnc(TransformPrimitive):
          [0, 0, 0, 0]]
     """
     name = "hashing_enc"
-    input_types = [Categorical]
-    return_type = [Numeric]
+    input_types = [ColumnSchema(logical_type=Categorical)]
+    return_type = [ColumnSchema(logical_type=Integer, semantic_tags={'numeric'})]
 
     def __init__(self, fitted_encoder):
         self.hash_method = fitted_encoder.get_hash_method()

diff --git a/categorical_encoding/primitives/leave_one_out_enc.py b/categorical_encoding/primitives/leave_one_out_enc.py
@@ -1,8 +1,8 @@
 from featuretools.primitives.base.transform_primitive_base import (
     TransformPrimitive
 )
-from featuretools.variable_types import Categorical, Numeric
-
+from woodwork.column_schema import ColumnSchema
+from woodwork.logical_types import Categorical, Integer
 
 class LeaveOneOutEnc(TransformPrimitive):
     """Applies a fitted LeaveOneOut Encoder to the values.
@@ -23,8 +23,8 @@ class LeaveOneOutEnc(TransformPrimitive):
         [2, 3, 1, 1]
     """
     name = "leave_one_out"
-    input_types = [Categorical]
-    return_type = Numeric
+    input_types = [ColumnSchema(logical_type=Categorical)]
+    return_type = [ColumnSchema(logical_type=Integer, semantic_tags={'numeric'})]
 
     def __init__(self, fitted_encoder, category):
         self.mapping = fitted_encoder.get_mapping(category)

diff --git a/categorical_encoding/primitives/one_hot_enc.py b/categorical_encoding/primitives/one_hot_enc.py
@@ -2,8 +2,8 @@
 from featuretools.primitives.base.transform_primitive_base import (
     TransformPrimitive
 )
-from featuretools.variable_types import Categorical, Numeric
-
+from woodwork.column_schema import ColumnSchema
+from woodwork.logical_types import Categorical, Integer
 
 class OneHotEnc(TransformPrimitive):
     """Applies one hot encoding for the specific category value to the column.
@@ -20,8 +20,8 @@ class OneHotEnc(TransformPrimitive):
         [0, 0, 1, 1]
     """
     name = "one_hot_enc"
-    input_types = [Categorical]
-    return_type = [Numeric]
+    input_types = [ColumnSchema(logical_type=Categorical)]
+    return_type = [ColumnSchema(logical_type=Integer, semantic_tags={'numeric'})]
 
     def __init__(self, value=None):
         self.value = value

diff --git a/categorical_encoding/primitives/ordinal_enc.py b/categorical_encoding/primitives/ordinal_enc.py
@@ -1,8 +1,8 @@
 from featuretools.primitives.base.transform_primitive_base import (
     TransformPrimitive
 )
-from featuretools.variable_types import Categorical, Ordinal
-
+from woodwork.column_schema import ColumnSchema
+from woodwork.logical_types import Categorical, Integer
 
 class OrdinalEnc(TransformPrimitive):
     """Applies a fitted Ordinal Encoder to the values.
@@ -23,8 +23,8 @@ class OrdinalEnc(TransformPrimitive):
         [2, 3, 1, 1]
     """
     name = "ordinal_enc"
-    input_types = [Categorical]
-    return_type = Ordinal
+    input_types = [ColumnSchema(logical_type=Categorical)]
+    return_type = [ColumnSchema(logical_type=Integer, semantic_tags={'numeric'})]
 
     def __init__(self, fitted_encoder, category):
         self.mapping = fitted_encoder.get_mapping(category)

diff --git a/categorical_encoding/primitives/target_enc.py b/categorical_encoding/primitives/target_enc.py
@@ -1,8 +1,8 @@
 from featuretools.primitives.base.transform_primitive_base import (
     TransformPrimitive
 )
-from featuretools.variable_types import Categorical, Numeric
-
+from woodwork.column_schema import ColumnSchema
+from woodwork.logical_types import Categorical, Integer
 
 class TargetEnc(TransformPrimitive):
     """Applies a fitted Target Encoder to the values.
@@ -23,8 +23,8 @@ class TargetEnc(TransformPrimitive):
         [2, 3, 1, 1]
     """
     name = "target_enc"
-    input_types = [Categorical]
-    return_type = Numeric
+    input_types = [ColumnSchema(logical_type=Categorical)]
+    return_type = [ColumnSchema(logical_type=Integer, semantic_tags={'numeric'})]
 
     def __init__(self, fitted_encoder, category):
         self.mapping, self.mapping_ord = fitted_encoder.get_mapping(category)

diff --git a/contributing.md b/contributing.md
@@ -0,0 +1,68 @@
+# Contributing to Categorical Encoding
+
+:+1::tada: First off, thank you for taking the time to contribute! :tada::+1:
+
+Whether you are a novice or experienced software developer, all contributions and suggestions are welcome!
+
+There are many ways to contribute to Categorical Encoding, with the most common ones being contribution of code or documentation to the project.
+
+**To contribute, you can:**
+1. Help users on our [Slack channel](https://join.slack.com/t/featuretools/shared_invite/enQtNTEwODEzOTEwMjg4LTQ1MjZlOWFmZDk2YzAwMjEzNTkwZTZkN2NmOGFjOGI4YzE5OGMyMGM5NGIxNTE4NjkzYWI3OWEwZjkyZGExYmQ). 
+
+2. Submit a pull request for one of [Good First Issues](https://github.com/alteryx/categorical_encoding/issues?q=is%3Aopen+is%3Aissue+label%3A%22good+first+issue%22)
+
+3. Make changes to the codebase, see [Contributing to the codebase](#Contributing-to-the-Codebase).
+
+4. [Report issues](#Report-issues) you're facing, and give a "thumbs up" on issues that others reported and that are relevant to you. Issues should be used for bugs, and feature requests only.
+
+## Contributing to the Codebase
+
+#### 1. Clone repo
+* The code is hosted on GitHub, so you will need to use Git to clone the project and make changes to the codebase. Once you have obtained a copy of the code, you should create a development environment that is separate from your existing Python environment so that you can make and test changes without compromising your own work environment.
+* You can run the following steps to clone the code, create a separate virtual environment, and install featuretools in editable mode. 
+  ```bash
+  git clone https://github.com/alteryx/categorical_encoding.git
+  python -m venv venv
+  source venv/bin/activate
+  python -m pip install -e .
+  python -m pip install -r dev-requirements.txt
+  ```
+#### 2. Implement your Pull Request
+
+* Implement your pull request. If needed, add new tests or update the documentation.
+* Before submitting to GitHub, verify the tests run and the code lints properly
+  ```bash
+  # runs test
+  make test
+
+  # runs linting
+
+
+  # will fix some common linting issues automatically
+  make lint-fix
+  ```
+* If you made changes to the documentation, build the documentation locally.
+  ```bash
+  # go to docs and build
+  cd docs
+  make html
+
+  # view docs locally
+  open build/html/index.html
+  ```
+
+#### 3. Submit your Pull Request
+
+* Once your changes are ready to be submitted, make sure to push your changes to GitHub before creating a pull request. Create a pull request, and our continuous integration will run automatically.
+* Update the "Future Release" section of the release notes (`docs/source/release_notes.rst`) to include your pull request and add your github username to the list of contributors.  Add a description of your PR to the subsection that most closely matches your contribution:
+    * Enhancements: new features or additions to Featuretools.
+    * Fixes: things like bugfixes or adding more descriptive error messages.
+    * Changes: modifications to an existing part of Featuretools.
+    * Documentation Changes
+    * Testing Changes
+
+   Documentation or testing changes rarely warrant an individual release notes entry; the PR number can be added to their respective "Miscellaneous changes" entries.
+* We will review your changes, and you will most likely be asked to make additional changes before it is finally ready to merge. However, once it's reviewed by a maintainer of Featuretools, passes continuous integration, we will merge it, and you will have successfully contributed to Featuretools!
+
+## Report issues
+When reporting issues please include as much detail as possible about your operating system, featuretools version and python version. Whenever possible, please also include a brief, self-contained code example that demonstrates the problem.
diff --git a/dev-requirements.txt b/dev-requirements.txt
@@ -1,5 +1,5 @@
 -r test-requirements.txt
-codecov==2.0.15
-flake8==3.7.0
-autopep8==1.4.3
-isort==4.3.4
+codecov==2.1.8
+flake8==3.7.8
+autopep8==1.4.4
+isort==4.3.21
diff --git a/docs/source/changelog.rst b/docs/source/changelog.rst
diff --git a/docs/source/release_notes.rst b/docs/source/release_notes.rst
@@ -0,0 +1,33 @@
+.. _release_notes:
+
+Release Notes
+-------------
+.. Future Release
+  ==============
+    * Enhancements
+    * Fixes
+    * Changes
+    * Documentation Changes
+    * Testing Changes
+
+.. Thanks to the following people for contributing to this release:
+
+
+v0.4.1 Apr 27, 2020
+===================
+    * Fix conflicting jupyter and nbconvert requirement
+    * Removed unused requirements (jupyter, nbconvert, nbsphinx)
+    * Pinned category_encoders to 2.0.0 
+
+v0.2.0 Aug 13, 2019
+===================
+    * Supports Bayesian encoders: Target and LeaveOneOut
+    * Encoder class independent of primitives
+
+v0.1.0 Aug 12, 2019
+===================
+    * Supports all 4 Classic encoders: OneHotEncoder, OrdinalEncoder, HashingEncoder, BinaryEncoder
+
+v0.0.0 Aug 7, 2019
+==================
+    * Initial Release
diff --git a/test-requirements.txt b/test-requirements.txt
@@ -1,3 +1,3 @@
-pytest==4.4.1
-pytest-xdist==1.26.1
-pytest-cov==2.6.1
+pytest>=5.2.0
+pytest-xdist>=1.26.1
+pytest-cov>=2.6.1