From b2e80e48b2ec4b673f3626ed8bc2ff93a576b9d9 Mon Sep 17 00:00:00 2001 From: Christian Kolset Date: Tue, 28 Jan 2025 19:11:36 -0700 Subject: Added environment and package management sections --- tutorials/02_intro_to_anaconda.md | 29 ++++++++++++++++++++++++----- 1 file changed, 24 insertions(+), 5 deletions(-) (limited to 'tutorials') diff --git a/tutorials/02_intro_to_anaconda.md b/tutorials/02_intro_to_anaconda.md index 58ed250..75cea67 100644 --- a/tutorials/02_intro_to_anaconda.md +++ b/tutorials/02_intro_to_anaconda.md @@ -1,5 +1,4 @@ -# Intro to Anaconda Navigator -# +# Introduction to Anaconda Navigator Anaconda Navigator is a program that we will be using in this course to manage Python environments, libraries and launch programs to help us write our python code. @@ -15,12 +14,32 @@ Note to windows 10 users: Some installation instances do not allow users to sear Once Navigator starts, under *Home*, you'll see tiles of programs that come with anaconda. The tab allows you to launch the programs we will be using in this course. Before jumping straight into the programs we will first need to configure our Python instance. -The *Environment* tab allows us to install python a variety of libraries and configure our environements for different project, more on this in the next section. +The *Environment* page allows us to install a variety of libraries and configure our environements for different project, more on this in the next section. ## Environments -A Python environment is like a "container" where you can have all the tools, libraries, and dependencies your Python project needs without interfering with other projects. Think of it as a toolbox dedicated to a specific task. +A Python environment is like a "container" where you can have all the tools, libraries, and dependencies your Python project needs without interfering with other projects. Think of it as a toolbox dedicated to a specific task. Although the base enviroment comes with many libraries and programs pre-installed, it's recommended to create a dedicated environment for your projects. This protects the base environment from breaking due to complex dependency conflicts. -Let us go ahead and create a new environment for us to use +Let us go ahead and create a new environment for us to use. Click on the *Environments* page located on the left hand side. +![Environment page](https://docs.anaconda.com/_images/nav-env-labeled1.png) +At the bottom of the environments list, click *Create*. +![Create new environment](https://docs.anaconda.com/_images/nav-env-create1.png) +Select the python checkbox. +Select versions of python. For this tutorial we will be using version X.XX.X. +Choose an apropriate name for your project. We will be creating an environment for Spyder IDE so we'll call it "spyder-dev". +Click *Create*. + +For more information see [Anaconda Environments](https://docs.anaconda.com/working-with-conda/environments/) and [Managing environment](https://docs.anaconda.com/navigator/tutorials/manage-environments/). ## Package Management +Now that we have a clean environment let us install some library we will be using for this class. Navigate to the environment page and select the environment we just created in the previous section. + +![Select environment to manage](https://docs.anaconda.com/_images/nav-pkg-list1.png) + +Use the search bar in the top right corner to search for the following packages: +- **numpy**: Numerical Computation library. +- **scipy**: Scientific and techical computing. +- **pandas**: data manipulation and analysis. +- **matplotlib**: creating plots and visualizations. +- **sympy**: symbolic mathematics. +- **cython**: optimizing Python code and interfacing with C++ code. -- cgit v1.2.3