Change package name to recommenders

NEWS.md

@@ -6,7 +6,7 @@ We have a new release [Recommenders 0.6.0](https://github.com/microsoft/recommen
 
 Recommenders is now on PyPI and can be installed using pip! In addition there are lots of bug fixes and utilities improvements.
 
-Here you can find the PyPi page: https://pypi.org/project/ms-recommenders/
+Here you can find the PyPi page: https://pypi.org/project/recommenders/
 
 Here you can find the package documentation: https://microsoft-recommenders.readthedocs.io/en/latest/
 

README.md

@@ -8,7 +8,7 @@ We have a new release [Recommenders 0.6.0](https://github.com/microsoft/recommen
 
 Recommenders is now on PyPI and can be installed using pip! In addition there are lots of bug fixes and utilities improvements.
 
-Here you can find the PyPi page: https://pypi.org/project/ms-recommenders/
+Here you can find the PyPi page: https://pypi.org/project/recommenders/
 
 Here you can find the package documentation: https://microsoft-recommenders.readthedocs.io/en/latest/
 
@@ -48,7 +48,7 @@ On Windows you will need [Microsoft C++ Build Tools](https://visualstudio.micros
 ```bash
 conda create -n my_environment_name python=3.6
 pip install --upgrade pip
-pip install ms-recommenders[examples]
+pip install recommenders[examples]
 ```
 
 3. Register your (conda or virtual) environment with Jupyter:

SETUP.md

@@ -51,7 +51,7 @@ conda update conda -n root
 conda update anaconda        # use 'conda install anaconda' if the package is not installed
 ```
 
-There are different ways one may use the recommenders utilities. The most convenient one is probably by installing the `ms-recommenders` package from [PyPI](https://pypi.org). For instructions on how to do these, see [this guide](reco_utils/README.md).
+There are different ways one may use the recommenders utilities. The most convenient one is probably by installing the `recommenders` package from [PyPI](https://pypi.org). For instructions on how to do these, see [this guide](reco_utils/README.md).
 
 An alternative is to run all the recommender utilities directly from a local copy of the source code. This requires installing all the necessary dependencies from Anaconda and PyPI. For instructions on how to do this, see [this guide](conda.md)
 
@@ -190,7 +190,7 @@ An example of how to create an Azure Databricks workspace and an Apache Spark cl
 
 ### Installation from PyPI
 
-The `ms-recommenders` package can be installed with core dependencies for utilities and CPU-based algorithms.
+The `recommenders` package can be installed with core dependencies for utilities and CPU-based algorithms.
 This is done from the _Libraries_ link at the cluster, selecting the option to import a library and selecting _PyPI_ in the menu.  
 For installations with more dependencies, see the steps below.
 
@@ -352,4 +352,4 @@ First make sure that the tag that you want to add, e.g. `0.6.0`, is added in [re
 generates a wheel and a tar.gz which are uploaded to a [GitHub draft release](https://github.com/microsoft/recommenders/releases).
 1. Fill up the draft release with all the recent changes in the code.
 1. Download the wheel and tar.gz locally, these files shouldn't have any bug, since they passed all the tests.
-1. Publish the wheel and tar.gz to pypi: `twine upload ms_recommenders*`
+1. Publish the wheel and tar.gz to pypi: `twine upload recommenders*`

reco_utils/README.md

@@ -19,12 +19,12 @@ For more details about the software requirements that must be pre-installed on e
 To install core utilities, CPU-based algorithms, and dependencies
 ```bash
 pip install --upgrade pip
-pip install ms-recommenders
+pip install recommenders
 ```
 
 ## Optional Dependencies
 
-By default `ms-recommenders` does not install all dependencies used throughout the code and the notebook examples in this repo. Instead we require a bare minimum set of dependencies needed to execute functionality in the `ms-recommenders` package (excluding Spark and GPU functionality). We also allow the user to specify which groups of dependencies are needed at installation time (or later if updating the pip installation). The following groups are provided:
+By default `recommenders` does not install all dependencies used throughout the code and the notebook examples in this repo. Instead we require a bare minimum set of dependencies needed to execute functionality in the `recommenders` package (excluding Spark and GPU functionality). We also allow the user to specify which groups of dependencies are needed at installation time (or later if updating the pip installation). The following groups are provided:
 
 - examples: dependencies needed to run [example notebooks](https://github.com/microsoft/recommenders/tree/main/examples)
 - gpu: dependencies to enable GPU functionality (PyTorch & TensorFlow)
@@ -38,10 +38,10 @@ Note that, currently, NNI and Vowpal Wabbit are in the experimental group.
 These groups can be installed alone or in combination:
 ```bash
 # install recommenders with core requirements and support for CPU-based recommender algorithms and notebooks
-pip install ms-recommenders[examples]
+pip install recommenders[examples]
 
 # add support for running example notebooks and GPU functionality
-pip install ms-recommenders[examples,gpu]
+pip install recommenders[examples,gpu]
 ```
 
 ## GPU Support
@@ -55,7 +55,7 @@ For manual installation of the necessary requirements see [TensorFlow](https://w
 
 When installing with GPU support you will need to point to the PyTorch index to ensure you are downloading a version of PyTorch compiled with CUDA support. This can be done using the --find-links or -f option below.
 
-`pip install ms-recommenders[gpu] -f https://download.pytorch.org/whl/cu100/torch_stable.html`
+`pip install recommenders[gpu] -f https://download.pytorch.org/whl/cu100/torch_stable.html`
 
 ## Experimental dependencies
 

setup.py

@@ -21,8 +21,6 @@
 if HASH is not None:
     version += ".post" + str(int(time.time()))
 
-name = environ.get("LIBRARY_NAME", "ms_recommenders")
-
 install_requires = [
     "numpy>=1.14",
     "pandas>1.0.3,<2",
@@ -88,7 +86,7 @@
 
 
 setup(
-    name=name,
+    name="recommenders",
     version=version,
     description="Microsoft Recommenders - Python utilities for building recommender systems",
     long_description=LONG_DESCRIPTION,

tests/ci/azure_pipeline_test/dsvm_linux_template.yml

@@ -65,7 +65,7 @@ jobs:
         python setup.py sdist bdist_wheel --plat-name=$PLATFORM || exit -1
 
         echo "   --- INSTALLING WHEEL ---"
-        pip install dist/ms_recommenders-$RELEASE_VERSION-py3-none-$PLATFORM.whl${{ parameters.pip_opts }} || exit -1
+        pip install dist/recommenders-$RELEASE_VERSION-py3-none-$PLATFORM.whl${{ parameters.pip_opts }} || exit -1
       else
         echo "   --- INSTALLING LATEST CODE ---"
         pip install .${{ parameters.pip_opts }} || exit -1
@@ -128,7 +128,7 @@ jobs:
     condition: and(succeeded(), eq('${{ parameters.install }}', 'release'), eq('${{ parameters.package }}', 'publish'))
     inputs:
       targetPath: $(System.DefaultWorkingDirectory)/dist
-      patterns: 'ms_recommenders*'
+      patterns: 'recommenders*'
       artifactName: PackageAssets
 
   - script: |