in the pylist we go from to add another element to maybe secondbut probably less than that that' nice speedup in our program after making this changethe pylist append method is given in sect efficient append class pylistdef __init__(self)self items [ the append method is used to add commands to the sequence def append(self,item)self items append(item commonly occurring computational complexities the algorithms we will study in this text will be of one of the complexities of ( ) (log ) ( log ) ( )or (cn graph of the shapes of these functions appears in fig most algorithms have one of these complexities corresponding to some factor of constant values added or multiplied to the terms in formula for measuring the time needed to complete computation do not affect the overall complexity of that operation computational complexity is only affected by the highest power term of the equation the complexities graphed in fig are of some power or the log of nexcept for the really awful exponential complexity of (cn )where is some constant value as you are reading the text and encounter algorithms with differing complexitiesthey will be one of the complexities shown in fig as alwaysthe variable represents the size of the data provided as input to the algorithm the time taken to process that data is the vertical axis in the graph while we don' care about the exact numbers in this graphwe do care about the overall shape of these functions the flatter the linethe lower the slopethe better the algorithm performs clearly an algorithm that has exponential complexity ( (cn )or -squared complexity ( ( )complexity will not perform very well except for very small values of if you know your algorithm will never be called for large values of then an inefficient algorithm might be acceptablebut you would have to be really sure that you knew that your data size would always be small typically we want to design algorithms that are as efficient as possible in subsequent you will encounter sorting algorithms that are ( and then you'll learn that we can do better and achieve ( log ncomplexity you'll see search algorithms that are (nand then learn how to achieve (log ncomplexity you'll also learn technique called hashing that will search in ( time the techniques you learn will help you deal with large amounts of data as efficiently this copy belongs to 'acha