Replace FeatureLabs Github URLs with alteryx (#1224)

* replace github org urls

* update release notes

Makefile

@@ -31,4 +31,4 @@ installdeps:
 .PHONY: checkdeps
 checkdeps:
 	$(eval allow_list='scipy|numpy|pandas|tqdm|pyyaml|cloudpickle|distributed|dask|psutil|click|pyspark|koalas')
-	pip freeze | grep -v "FeatureLabs/featuretools.git" | grep -E $(allow_list) > $(OUTPUT_PATH)
+	pip freeze | grep -v "alteryx/featuretools.git" | grep -E $(allow_list) > $(OUTPUT_PATH)

README.md

@@ -8,8 +8,8 @@
 
 
 
-[![Circle CI](https://circleci.com/gh/FeatureLabs/featuretools.svg?maxAge=2592000&style=shield)](https://circleci.com/gh/FeatureLabs/featuretools)
-[![Coverage Status](https://codecov.io/gh/FeatureLabs/featuretools/branch/main/graph/badge.svg)](https://codecov.io/gh/FeatureLabs/featuretools)
+[![Circle CI](https://circleci.com/gh/alteryx/featuretools.svg?maxAge=2592000&style=shield)](https://circleci.com/gh/alteryx/featuretools)
+[![Coverage Status](https://codecov.io/gh/alteryx/featuretools/branch/main/graph/badge.svg)](https://codecov.io/gh/alteryx/featuretools)
 [![PyPI version](https://badge.fury.io/py/featuretools.svg?maxAge=2592000)](https://badge.fury.io/py/featuretools)
 [![Anaconda-Server Badge](https://anaconda.org/conda-forge/featuretools/badges/version.svg)](https://anaconda.org/conda-forge/featuretools)
 [![StackOverflow](http://img.shields.io/badge/questions-on_stackoverflow-blue.svg)](https://stackoverflow.com/questions/tagged/featuretools)
@@ -61,7 +61,7 @@ Below is an example of using Deep Feature Synthesis (DFS) to perform automated f
 >> es.plot()
 ```
 
-<img src="https://github.com/FeatureLabs/featuretools/blob/main/docs/source/_static/images/entity_set.png?raw=true" width="350">
+<img src="https://github.com/alteryx/featuretools/blob/main/docs/source/_static/images/entity_set.png?raw=true" width="350">
 
 Featuretools can automatically create a single table of features for any "target entity"
 ```python
@@ -101,7 +101,7 @@ The Featuretools community welcomes pull requests. Instructions for testing and
 The Featuretools community is happy to provide support to users of Featuretools. Project support can be found in four places depending on the type of question:
 
 1. For usage questions, use [Stack Overflow](https://stackoverflow.com/questions/tagged/featuretools) with the `featuretools` tag.
-2. For bugs, issues, or feature requests start a [Github issue](https://github.com/FeatureLabs/featuretools/issues).
+2. For bugs, issues, or feature requests start a [Github issue](https://github.com/alteryx/featuretools/issues).
 3. For discussion regarding development on the core library, use [Slack](https://join.slack.com/t/featuretools/shared_invite/enQtNTEwODEzOTEwMjg4LTQ1MjZlOWFmZDk2YzAwMjEzNTkwZTZkN2NmOGFjOGI4YzE5OGMyMGM5NGIxNTE4NjkzYWI3OWEwZjkyZGExYmQ).
 4. For everything else, the core developers can be reached by email at help@featuretools.com.
 

contributing.md

@@ -9,7 +9,7 @@ There are many ways to contribute to Featuretools, with the most common ones bei
 **To contribute, you can:**
 1. Help users on our [Slack channel](https://join.slack.com/t/featuretools/shared_invite/enQtNTEwODEzOTEwMjg4LTQ1MjZlOWFmZDk2YzAwMjEzNTkwZTZkN2NmOGFjOGI4YzE5OGMyMGM5NGIxNTE4NjkzYWI3OWEwZjkyZGExYmQ). Answer questions under the featuretools tag on [Stack Overflow](https://stackoverflow.com/questions/tagged/featuretools)
 
-2. Submit a pull request for one of [Good First Issues](https://github.com/FeatureLabs/featuretools/issues?q=is%3Aopen+is%3Aissue+label%3A%22Good+First+Issue%22)
+2. Submit a pull request for one of [Good First Issues](https://github.com/alteryx/featuretools/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).
 
@@ -18,7 +18,7 @@ There are many ways to contribute to Featuretools, with the most common ones bei
 5. [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.
 
 6. Spread the word: reference Featuretools from your blog and articles, link to it from your website, or simply star it in GitHub to say "I use it".
-    * If you would like to be featured on [ecosystem page](https://docs.featuretools.com/en/stable/ecosystem.html), you can submit a [pull request](https://github.com/FeatureLabs/featuretools).
+    * If you would like to be featured on [ecosystem page](https://docs.featuretools.com/en/stable/ecosystem.html), you can submit a [pull request](https://github.com/alteryx/featuretools).
 
 ## Contributing to the Codebase
 
@@ -28,7 +28,7 @@ Before starting major work, you should touch base with the maintainers of Featur
 * 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/FeatureLabs/featuretools.git
+  git clone https://github.com/alteryx/featuretools.git
   cd featuretools
   virtualenv venv
   source venv/bin/activate

docs/source/conf.py

@@ -151,7 +151,7 @@
 # further.  For a list of options available for each theme, see the
 # documentation.
 html_theme_options = {
-    "github_url": "https://github.com/FeatureLabs/featuretools",
+    "github_url": "https://github.com/alteryx/featuretools",
     "twitter_url": "https://twitter.com/featuretools_py"
 }
 
@@ -329,8 +329,8 @@
 nbsphinx_execute = 'auto'
 
 extlinks = {
-    'issue': ('https://github.com/FeatureLabs/featuretools/issues/%s', 'GH#'),
-    'pr': ('https://github.com/FeatureLabs/featuretools/pull/%s', 'GH#'),
+    'issue': ('https://github.com/alteryx/featuretools/issues/%s', 'GH#'),
+    'pr': ('https://github.com/alteryx/featuretools/pull/%s', 'GH#'),
     'user': ('https://github.com/%s', '@')
 }
 

docs/source/guides/performance.rst

@@ -24,7 +24,7 @@ Computation with Dask and Koalas EntitySets (BETA)
 .. note::
     Support for Dask EntitySets and Koalas EntitySets is still in Beta. While the key functionality has been implemented, development is ongoing to add the remaining functionality.
 
-    All planned improvements to the Featuretools/Dask and Featuretools/Koalas integration are documented on Github (`Dask issues <https://github.com/FeatureLabs/featuretools/issues?q=is%3Aopen+is%3Aissue+label%3ADask>`_, `Koalas issues <https://github.com/FeatureLabs/featuretools/issues?q=is%3Aopen+is%3Aissue+label%3AKoalas>`_). If you see an open issue that is important for your application, please let us know by upvoting or commenting on the issue. If you encounter any errors using Dask or Koalas entities, or find missing functionality that does not yet have an open issue, please create a `new issue on Github <https://github.com/FeatureLabs/featuretools/issues>`_.
+    All planned improvements to the Featuretools/Dask and Featuretools/Koalas integration are documented on Github (`Dask issues <https://github.com/alteryx/featuretools/issues?q=is%3Aopen+is%3Aissue+label%3ADask>`_, `Koalas issues <https://github.com/alteryx/featuretools/issues?q=is%3Aopen+is%3Aissue+label%3AKoalas>`_). If you see an open issue that is important for your application, please let us know by upvoting or commenting on the issue. If you encounter any errors using Dask or Koalas entities, or find missing functionality that does not yet have an open issue, please create a `new issue on Github <https://github.com/alteryx/featuretools/issues>`_.
 
 Dask or Koalas can be used with Featuretools to perform parallel feature computation with virtually no changes to the workflow required. Featuretools supports creating an ``EntitySet`` directly from Dask or Koalas dataframes instead of using pandas dataframes, enabling the parallel and distributed computation capabilities of Dask or Spark to be used. By creating an ``EntitySet`` directly from Dask or Koalas dataframes, Featuretools can be used to generate a larger-than-memory feature matrix, something that may be difficult with other approaches. When computing a feature matrix from an ``EntitySet`` created from Dask or Koalas dataframes, the resulting feature matrix will be returned as a Dask or Koalas dataframe depending on which type was used.
 

docs/source/guides/using_dask_entitysets.rst

@@ -3,7 +3,7 @@ Using Dask EntitySets (BETA)
 .. note::
     Support for Dask EntitySets is still in Beta. While the key functionality has been implemented, development is ongoing to add the remaining functionality.
 
-    All planned improvements to the Featuretools/Dask integration are `documented on Github <https://github.com/FeatureLabs/featuretools/issues?q=is%3Aopen+is%3Aissue+label%3ADask>`_. If you see an open issue that is important for your application, please let us know by upvoting or commenting on the issue. If you encounter any errors using Dask entities, or find missing functionality that does not yet have an open issue, please create a `new issue on Github <https://github.com/FeatureLabs/featuretools/issues>`_.
+    All planned improvements to the Featuretools/Dask integration are `documented on Github <https://github.com/alteryx/featuretools/issues?q=is%3Aopen+is%3Aissue+label%3ADask>`_. If you see an open issue that is important for your application, please let us know by upvoting or commenting on the issue. If you encounter any errors using Dask entities, or find missing functionality that does not yet have an open issue, please create a `new issue on Github <https://github.com/alteryx/featuretools/issues>`_.
 
 Creating a feature matrix from a very large dataset can be problematic if the underlying pandas dataframes that make up the entities cannot easily fit in memory. To help get around this issue, Featuretools supports creating ``Entity`` and ``EntitySet`` objects from Dask dataframes. A Dask ``EntitySet`` can then be passed to ``featuretools.dfs`` or ``featuretools.calculate_feature_matrix`` to create a feature matrix, which will be returned as a Dask dataframe. In addition to working on larger than memory datasets, this approach also allows users to take advantage of the parallel and distributed processing capabilities offered by Dask.
 

docs/source/guides/using_koalas_entitysets.rst

@@ -3,7 +3,7 @@ Using Koalas EntitySets (BETA)
 .. note::
     Support for Koalas EntitySets is still in Beta. While the key functionality has been implemented, development is ongoing to add the remaining functionality.
 
-    All planned improvements to the Featuretools/Koalas integration are `documented on Github <https://github.com/FeatureLabs/featuretools/issues?q=is%3Aopen+is%3Aissue+label%3AKoalas>`_. If you see an open issue that is important for your application, please let us know by upvoting or commenting on the issue. If you encounter any errors using Koalas entities, or find missing functionality that does not yet have an open issue, please create a `new issue on Github <https://github.com/FeatureLabs/featuretools/issues>`_.
+    All planned improvements to the Featuretools/Koalas integration are `documented on Github <https://github.com/alteryx/featuretools/issues?q=is%3Aopen+is%3Aissue+label%3AKoalas>`_. If you see an open issue that is important for your application, please let us know by upvoting or commenting on the issue. If you encounter any errors using Koalas entities, or find missing functionality that does not yet have an open issue, please create a `new issue on Github <https://github.com/alteryx/featuretools/issues>`_.
 
 Creating a feature matrix from a very large dataset can be problematic if the underlying pandas dataframes that make up the entities cannot easily fit in memory. To help get around this issue, Featuretools supports creating ``Entity`` and ``EntitySet`` objects from Koalas dataframes. A Koalas ``EntitySet`` can then be passed to ``featuretools.dfs`` or ``featuretools.calculate_feature_matrix`` to create a feature matrix, which will be returned as a Koalas dataframe. In addition to working on larger than memory datasets, this approach also allows users to take advantage of the parallel and distributed processing capabilities offered by Koalas and Spark.
 

docs/source/install.rst

@@ -79,9 +79,9 @@ Install from Source
 -------------------
 
 To install featuretools from source, clone the repository from `github
-<https://github.com/FeatureLabs/featuretools>`_::
+<https://github.com/alteryx/featuretools>`_::
 
-    git clone https://github.com/FeatureLabs/featuretools.git
+    git clone https://github.com/alteryx/featuretools.git
     cd featuretools
     python setup.py install
 
@@ -96,7 +96,7 @@ of ``setup.py``.
 
 Development
 -----------
-Before making contributing to the codebase, please follow the guidelines `here <https://github.com/FeatureLabs/featuretools/blob/main/contributing.md>`_
+Before making contributing to the codebase, please follow the guidelines `here <https://github.com/alteryx/featuretools/blob/main/contributing.md>`_
 
 Virtualenv
 ~~~~~~~~~~

docs/source/release_notes.rst

@@ -13,6 +13,7 @@ Release Notes
     * Documentation Changes
         * Removed link to unused feedback board (:pr:`1220`)
         * Update footer with Alteryx Innovation Labs (:pr:`1221`)
+        * Update links to repo in documentation to use alteryx org url (:pr:`1224`)
     * Testing Changes
         * Update release notes check to use new repo url (:pr:`1222`)
 

docs/source/resources/ecosystem.rst

@@ -6,7 +6,7 @@ Featuretools External Ecosystem
 
 New projects are regularly being built on top of Featuretools, highlighting the importance of automated feature engineering. On this page, we have a list of libraries, use cases / demos, and tutorials that leverage Featuretools. If you would like to add a project, please contact us or submit a pull request on `GitHub`_.
 
-.. _`GitHub`: https://github.com/FeatureLabs/featuretools
+.. _`GitHub`: https://github.com/alteryx/featuretools
 
 .. note::
 

docs/source/resources/frequently_asked_questions.ipynb

@@ -425,7 +425,7 @@
    "source": [
     "### Can I create an `EntitySet` using Dask or Koalas dataframes? (BETA)\n",
     "\n",
-    "Support for Dask EntitySets and Koalas EntitySets is still in Beta - if you encounter any errors using either of these approaches, please let us know by creating a [new issue on Github](https://github.com/FeatureLabs/featuretools/issues).\n",
+    "Support for Dask EntitySets and Koalas EntitySets is still in Beta - if you encounter any errors using either of these approaches, please let us know by creating a [new issue on Github](https://github.com/alteryx/featuretools/issues).\n",
     "\n",
     "Yes! Featuretools supports creating an `EntitySet` from Dask dataframes or from Koalas dataframes. You can simply follow the same process you would when creating an `EntitySet` from pandas dataframes.\n",
     "\n",
@@ -1560,7 +1560,7 @@
    "source": [
     "### What primitives can I use when creating a feature matrix from a Dask `EntitySet`? (BETA)\n",
     "\n",
-    "Support for Dask EntitySets is still in Beta - if you encounter any errors using this approach, please let us know by creating a [new issue on Github](https://github.com/FeatureLabs/featuretools/issues).\n",
+    "Support for Dask EntitySets is still in Beta - if you encounter any errors using this approach, please let us know by creating a [new issue on Github](https://github.com/alteryx/featuretools/issues).\n",
     "\n",
     "When creating a feature matrix from a Dask `EntitySet`, only certain primitives can be used. Computation of certain features is quite expensive in a distributed environment, and as a result only a subset of Featuretools primitives are currently supported when using a Dask `EntitySet`.\n",
     "\n",

docs/source/resources/help.rst

@@ -17,7 +17,7 @@ Conversation happens in the following places:
     Stack Overflow where answers are more searchable by other users.
 
 .. _`StackOverflow`: http://stackoverflow.com/questions/tagged/featuretools
-.. _`Github issue tracker`: https://github.com/FeatureLabs/featuretools/issues
+.. _`Github issue tracker`: https://github.com/alteryx/featuretools/issues
 .. _`Slack`: https://join.slack.com/t/featuretools/shared_invite/enQtNTEwODEzOTEwMjg4LTQ1MjZlOWFmZDk2YzAwMjEzNTkwZTZkN2NmOGFjOGI4YzE5OGMyMGM5NGIxNTE4NjkzYWI3OWEwZjkyZGExYmQ
 
 

docs/source/templates/layout.html

@@ -36,7 +36,7 @@
       <img class="footer-image-alteryx" src="{{ pathto('_static/images/alteryx_open_source.svg', 1) }}" alt="Alteryx Open Source">
     </div>
     <div class="footer-cell-2">
-      <a href="https://github.com/FeatureLabs/featuretools#readme" target="_blank">
+      <a href="https://github.com/alteryx/featuretools#readme" target="_blank">
         <img class="footer-image-github" src="{{ pathto('_static/images/github.svg', 1) }}" alt="GitHub">
       </a>
       <a href="https://twitter.com/featuretools_py?lang=en" target="_blank">

release.md

@@ -10,7 +10,7 @@ We need to upload a featuretools package to test with the conda recipe
     ```
 2. Update version number in `setup.py`, `featuretools/version.py`, `featuretools/tests/test_version.py` to v0.13.3.dev0 and push branch to repo
 3. Publish a new release of featuretools on Github.
-    1. Go to the [releases page](https://github.com/FeatureLabs/featuretools/releases/) on Github
+    1. Go to the [releases page](https://github.com/alteryx/featuretools/releases/) on Github
     2. Click "Draft a new release"
     3. For the target, choose the new branch (v0.13.3.dev)
     4. For the tag, use the new version number (v0.13.3.dev0)
@@ -124,10 +124,10 @@ Fields to update in `recipe/meta.yaml` of feedstock repo:
 
 
 #### Create Release PR
-A [release pr](https://github.com/FeatureLabs/featuretools/pull/856) should have the version number as the title and the release notes for that release as the PR body text. The contributors list is not necessary. The special sphinx docs syntax (:pr:\`547\`) needs to be changed to github link syntax (#547).
+A [release pr](https://github.com/alteryx/featuretools/pull/856) should have the version number as the title and the release notes for that release as the PR body text. The contributors list is not necessary. The special sphinx docs syntax (:pr:\`547\`) needs to be changed to github link syntax (#547).
 
 #### Create Github Release
-After the release pull request has been merged into the main branch, it is time draft the github release. [Example release](https://github.com/FeatureLabs/featuretools/releases/tag/v0.13.3)
+After the release pull request has been merged into the main branch, it is time draft the github release. [Example release](https://github.com/alteryx/featuretools/releases/tag/v0.13.3)
 * The target should be the main branch
 * The tag should be the version number with a v prefix (e.g. v0.13.3)
 * Release title is the same as the tag