 So far we've got the basic pieces in place, so that if you want to jump into your very first Python program, you can. We have the command line, we have a text editor, we have Python installed. Now we're going to step through a couple of other tools that you may find very helpful. The first of these is called PIP. It's the Python package installer. It comes automatically with Python. You already have it on your machine. The way that you use it is you go to the command line and you type python-m pip install-U and then the name of the package that you'd like to install. In this case, NumPy. PIP here is the package installer that we're running, but we run it using python-m. What that does is it goes to the version of Python that that command is linked to. You might have more than one version on your machine, depending on its history, and this way we make sure to get the pip that is tied to your command line Python command. So python.m pip install. The name of the package is NumPy. The dash capital U says install it just for me, just for my username, instead of trying to install it for all of the users that might use this machine. That's optional. If this is a machine that you have root access to or are a master user on, you can leave off the dash U and install it for everyone. You'll just be asked to provide a password. But the dash U keeps it as simple and straightforward as possible. When you run it, what your computer does, pip goes out to the internet, pulls down a copy of this package, NumPy, downloads it, unzips it, installs it. Also there are other packages that NumPy uses called dependencies. And if it doesn't have any of those, if it's missing any of those, it goes out, pulls those down and unzips and installs those as well. This is like if you've ever watched Matrix, Neo is able to lay back, get jacked into the computer and download Kung Fu. And then he knows Kung Fu. He's got all of those tools at his disposal. This is the same way after pip installing NumPy, our Python installation like knows the Python version of Kung Fu, which is NumPy, how to work with arrays and numbers and do all kinds of crazy math things. If you want to see all of the packages that you have installed, you can type python-m pip list. And sure enough, we can see NumPy in the list right there. That's very good. If ever we wanted to upgrade a package that we already have installed, we can do exactly what we did to install it, but just add dash dash upgrade. And then if there is a newer version, it'll go pull that down as well. If we want to uninstall it, we can modify that same command and say python-m pip uninstall and the package name. And it'll wipe it. It'll take it out. All of these packages live at pypy.org. This is a website where people all over the world write packages. They write code in Python. They upload it and carefully structure it so that anytime someone sits at their computer and says pip install NumPy, it can download it to their computer. Anyone can write packages. Anyone can upload them and share them with anyone else through pypy.org. It's free. It's not owned by any company. And there are no restrictions on how much code you can upload and how broadly you can share it. It is an amazing open coding resource. At PyPy, you can look up, for instance, information on NumPy. You can get some more information about the project, the description. Here we see it's good for working with n-dimensional arrays. So one or two or three or four-dimensional arrays as high as we want to go. It's good at doing math, linear algebra, random numbers. A thing that we'll find very useful in future projects. So it's a great example here to practice pip installing things. And with that, you now have the capability to download kung fu, jujitsu, linear algebra, and whatever else your Python program needs to do what you want it to do.