84 add some more examples of package managers

episodes/04-software_package_management.md

@@ -22,11 +22,13 @@ exercises: 0
 
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-Virtual environments are a useful tool for isolating and managing the software packages you use. Doing this enables you to track the packages you use for your work (enabling you to create reproducable environments, so that others can also use your code). It also allows you to use packages which might have conflicting requirements (or even different versions of the same package) without the hassle of haveing to install and uninstall these each time.
+Virtual environments are a useful tool for isolating and managing the software packages you use. Doing this enables you to track the packages you use for your work, letting you create reproducable environments so that others can use your code. It also allows you to use packages which might have conflicting requirements (or even different versions of the same package) without the hassle of having to install and uninstall these each time.
 
-Python has a built in tools for managing virtual environments ([venv](https://docs.python.org/3/tutorial/venv.html)) and packages ([pip](https://pypi.org/project/pip/)). However we will not cover these tools today. While venv and pip are very useful for managing pure python packages, they are not very flexible when we want to use packages which are built on other languages (or perhaps do not use python at all). Another tool, conda, has been built to extend their functionality to cover these mixed-language packages, for a wide range of computing platforms, and it is this which we will cover today. More details on the differences between conda and pip are given in this [summary](https://www.anaconda.com/blog/understanding-conda-and-pip).
+Python has built in tools for managing virtual environments ([venv](https://docs.python.org/3/tutorial/venv.html)) and packages ([pip](https://pypi.org/project/pip/)). However, we will not cover these tools today. While venv and pip are very useful for managing pure python packages, they are not very flexible when we want to use packages which are built on other languages (or perhaps do not use python at all). Another tool, [conda](https://docs.conda.io/en/latest/index.html), has been built to extend their functionality to cover these mixed-language packages for a wide range of computing platforms, and it is this which we will cover today.
 
-The lesson below is not conducted using a python interpreter, but instead using the unix shell. When you are asked to type in code below, please do this in a terminal window and not in this browser.
+More details on the differences between conda and pip are given in this [summary](https://www.anaconda.com/blog/understanding-conda-and-pip). Other tools for package management exist as well as conda - popular ones include [uv](https://docs.astral.sh/uv/) and [poetry](https://python-poetry.org/). See here for a full list of [packaging projects](https://packaging.python.org/en/latest/key_projects/).
+
+The lesson below is not conducted using a Python interpreter, but instead using the unix shell. When you are asked to type in code below, please do this in a terminal window and not in a Jupyter notebook or other Python interpreter.
 
 ## Installing Conda