["python","random","numpy"]
Consistently create same random numpy array

I am waiting for another developer to finish a piece of code that will return an np array of shape (100,2000) with values of either -1,0, or 1. In the meantime, I want to randomly create an array of the same characteristics so I can get a head start on my development and testing. The thing is that I want this randomly created array to be the same each time, so that I'm not testing against an array that keeps changing its value each time I re-run my process. I can create my array like this, but is there a way to create it so that it's the same each time. I can pickle the object and unpickle it, but wondering if there's another way. r = np.random.randint(3, size=(100, 2000)) - 1
Simply seed the random number generator with a fixed value, e.g. numpy.random.seed(42) This way, you'll always get the same random number sequence. This function will seed the global default random number generator, and any call to a function in numpy.random will use and alter its state. This is fine for many simple use cases, but it's a form of global state with all the problems global state brings. For a cleaner solution, see Robert Kern's answer below.