Release/1.3.1

.github/CODEOWNERS

@@ -1 +1,2 @@
 /rialto/ @MDobransky
+/rialto/ @vvancak

.github/workflows/release.yml

@@ -10,17 +10,12 @@ env:
 
 jobs:
   publish:
-    environment: jfrog
+    environment: pypi
     runs-on: ubuntu-20.04
     steps:
       - name: Checkout Rialto
         uses: actions/checkout@v3
 
-      - name: Install system dependencies
-        run: |
-          apt-get update
-          apt-get install -y openssl libssl-dev wget
-
       - uses: actions/setup-python@v4
         with:
           python-version: "3.10.6"
@@ -37,4 +32,4 @@ jobs:
       - name: Build and publish the wheel to jfrog
         run: |
           poetry build
-#          poetry publish
+          twine upload dist/*

README.md

@@ -7,15 +7,14 @@ Rialto is a framework for building and deploying machine learning features in a
 The name Rialto is a reference to the Rialto Bridge in Venice, Italy. The Rialto Bridge was a major marketplace for goods and ideas the Middle Ages.
 Rialto is intended to be a foundation of a similar marketplace for machine learning features, where users and find and share reusable features.
 
-Sphinx-Generated autodocs pages available **[here]()**.
+Sphinx-Generated autodocs pages available **[here](https://absaoss.github.io/rialto/)**.
 
 # Contents
-1. [Instalatlion](#install)
+1. [Installation](#install)
 2. [Library Overview](#overview)
 3. [Contributing](#contributing)
 
 # <a id="install"></a> 1. Installation
-The packages is not yet available in public pip
 ```bash
 pip install rialto
 ```
@@ -151,7 +150,12 @@ Sequential feature generation can be simply interpreted as appending a new colum
 from rialto.maker import FeatureMaker
 from my_features import simple_features
 
-features, metadata = FeatureMaker.make(df=input_data, key="KEY", make_date=run_date, features_module=simple_features, keep_preexisting=True)
+features, metadata = FeatureMaker.make(
+    df=input_data,
+    key="KEY",
+    make_date=run_date,
+    features_module=simple_features,
+    keep_preexisting=True)
 ```
 
 #### Aggregated
@@ -161,7 +165,11 @@ In aggregated generation, the source dataframe is grouped by the key or keys and
 from rialto.maker import FeatureMaker
 from my_features import agg_features
 
-features, metadata = FeatureMaker.make_aggregated(df=input_data, key="KEY", make_date=run_date, features_module=agg_features)
+features, metadata = FeatureMaker.make_aggregated(
+    df=input_data,
+    key="KEY",
+    make_date=run_date,
+    features_module=agg_features)
 ```
 
 There are also **make_single_feature** and **make_single_agg_feature** available, intended to be used in tests. (See full documentation)

pyproject.toml

@@ -1,16 +1,30 @@
 [tool.poetry]
 name = "rialto"
 
-version = "1.3.0"
+version = "1.3.1"
 
 packages = [
     { include = "rialto" },
 ]
+classifiers = [
+    "Programming Language :: Python :: 3",
+    "License :: OSI Approved :: Apache Software License",
+    "Operating System :: OS Independent",
+]
+description = "Rialto is a framework for building and deploying machine learning features in a scalable and reusable way. It provides a set of tools that make it easy to define and deploy features and models, and it provides a way to orchestrate the execution of these features and models."
+authors = ["Marek Dobransky <[email protected]>", "Vladislav Vancak <[email protected]>"]
 
-description = "Rialto"
-authors = ["Marek Dobransky <[email protected]>"]
+[project]
+name = "rialto"
+readme = "README.md"
+description = "Rialto is a framework for building and deploying machine learning features in a scalable and reusable way. It provides a set of tools that make it easy to define and deploy features and models, and it provides a way to orchestrate the execution of these features and models."
+authors = ["Marek Dobransky <[email protected]>", "Vladislav Vancak <[email protected]>"]
 keywords = ["feature", "featureslib", "featuremaker", "metadata", "featureloader", "loader"]
 
+[project.urls]
+Documentation = "https://absaoss.github.io/rialto/"
+Repository = "https://github.com/AbsaOSS/rialto"
+
 [tool.poetry.dependencies]
 python = ">=3.10,<4.0"
 pydantic = "^2.2.1"