Okay, let's see if we can set some ground rules and pick up a couple of 0:00 theoretical concepts before we get into the nitty gritty of writing code. 0:03 The first two are pretty straightforward. 0:07 Computation is the evaluation of functions. 0:09 This means that we do our work computing values and outcomes all in functions. 0:13 We'll try to keep as much of our work inside of discrete functions as possible. 0:17 To me, this is easiest to think of as math. 0:22 When we're just talking about it, we take two and combine it with another two, and 0:24 we get four. 0:27 But in programming we'd be using an add function that takes 0:28 at least two arguments. 0:31 That function then sends back the four. 0:33 So our computation was done by evaluating the add function. 0:35 This ties neatly into our next rule. 0:39 Programming is done with expressions. 0:41 We do our work by using expressions, 0:43 passing the output of one function into another, either through chaining or 0:46 by assigning the output to a variable and then using that variable. 0:50 Again, we can go back to math. 0:54 If we have an equation of 5 minus 3 times 2, that of course has subtraction and 0:55 multiplication in it. 1:00 And according to the order of operations in math, we do the multiplication and 1:02 use its resulting value in the subtraction to get us our answer of minus 1. 1:06 And just like doing the same math problem over and over again will 1:09 always get you the same answer, we should have no side effects from computation. 1:12 We don't want to change values that are outside of our function's scope. 1:18 We have to be careful with this when we're using mutable types like lists and 1:22 dictionaries. 1:26 Eliminating side effects means that we can run a function with the same 1:27 inputs multiple times and nothing else, no other inputs or 1:30 values anywhere in the stack will change. 1:33 It also means that we can more easily predict the state of the entire program 1:35 at any point in time. 1:39 Functions are first-class citizens. 1:40 In Python, functions can be provided as an argument to a function call or 1:44 returned from a function. 1:47 Since functions are usable as values just like variables are, 1:49 they're considered to be first-class. 1:52 To get the most out of functional programming, 1:55 a language needs to be able to do more with functions than just call them. 1:57 Being able to chain functions together, take functions as arguments, and 2:00 return functions as values gives us some fluidity to how we solve a problem. 2:04 Functions should be limited in scope and functionality. 2:08 We want to make sure our functions have a well-defined purpose. 2:12 We want them to achieve a single task and then give us the answer from that task. 2:15 By limiting the scope, or amount of data that a function has, and 2:19 the functionality of the function, we can keep our code clean, small, and 2:23 effective, all great things. 2:27 Okay, the next video will actually get us some practice 2:30 to go along with all this theory. 2:32 I'll see you there in a bit. 2:34