Added some additional info about packaging and dep management options

Author: ginic

README.md

@@ -9,7 +9,7 @@ This template draws a lot of inspiration from [Cookiecutter Data Science](https:
 # Getting Started
 ## Installing Dependencies and Packages
 Use these steps for setting up a development environment to install and work with code in this template:
-1) Set up a Python 3 virtual environment using [Conda](https://docs.conda.io/projects/conda/en/latest/user-guide/install/index.html#) or [Virtualenv](https://virtualenv.pypa.io/en/latest/index.html). Read [Python Virtual Environments: A Primer](https://realpython.com/python-virtual-environments-a-primer/#the-virtualenv-project) for details on how to get started with virtual environments and why you need them.
+1) Set up a Python 3 virtual environment using [Conda](https://docs.conda.io/projects/conda/en/latest/user-guide/install/index.html#) or [Virtualenv](https://virtualenv.pypa.io/en/latest/index.html). Read [Python Virtual Environments: A Primer](https://realpython.com/python-virtual-environments-a-primer/#the-virtualenv-project) for details on how to get started with virtual environments and why you need them. For a _really detailed_ explanation, see [An unbiased evaluation of environment management and packaging tools](https://alpopkes.com/posts/python/packaging_tools/). 
 2) Activate your virtual environment.
 
 3) Install the package.
@@ -51,11 +51,14 @@ Collecting numpy
 
 ## Specifying Requirements
 In order for users to install your package and all the libraries it depends on by running `pip install`, you need to provide a `pyproject.toml` file. This has two important sections:
-- `project`: List project metadata and version information and all library requirements/dependencies, including for testing or development environments. This is the main file you will work with and add requirements to.
-- `build-system`: Define the build tool that is used to package and distribute your code. For this project, we use [SetupTools](https://setuptools.pypa.io/en/latest/userguide/quickstart.html), but we also recommend [Poetry](https://python-poetry.org/docs/).
+- `project`: List project metadata and version information and all library requirements/dependencies, including for testing or development environments. This is the main file you will work with and add requirements to. Some dependencies 
+- `build-system`: Define the build tool that is used to package and distribute your code. For this project, we use [SetupTools](https://setuptools.pypa.io/en/latest/userguide/quickstart.html).
 
 If you'd like to learn more about python packaging, refer to [the Python Packaging User Guide](https://packaging.python.org/en/latest/) or [PEP 517](https://peps.python.org/pep-0517/#build-requirements).
 
+### Requirements via conda environment files
+[Anaconda](https://www.anaconda.com/download/) and its bare bones counterpart, [Miniconda](https://docs.anaconda.com/free/miniconda/index.html), are especially useful if your project depends on libraries that are difficult to install in the standard pythonic way, such as [GPU libraries](https://docs.anaconda.com/free/working-with-conda/packages/gpu-packages/). If this is the case, you should also share a [Conda environment file](https://docs.conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html#creating-an-environment-file-manually) with your code. The conda virtual environment will need to be created and activated before any `pip install` steps. Installations with conda dependencies are usually a little more complicated, so make sure you include step-by-step instructions in documentation. 
+
 
 ## Directory Structure
 So what does each file in this repository do?