Python for loop
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The document discusses for loops in Python. It explains that for loops are used to iterate over sequences like lists, tuples, and strings. There are two types of for loops: 1) Getting each element of the sequence, and 2) Using the range() function to generate a sequence of numbers to use as indexes. The document provides examples of iterating over lists and strings using for loops, and using break and continue statements to control loop behavior. It also explains how to use the range() function to generate a sequence of numbers for iteration.
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turtle.backward(distance) – Same as forward but it moves in the opposite direction the turtle is facing
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turtle.pendown() – Places the pen back down to the turtle can continue leaving lines when forward and
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turtle.pencolor(color string) – Changes the color of the lines left by the turtle to whatever color string
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turtle.bgcolor(color string) – Changes the background color for the window that the turtle draws in.
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1
2 Functions and Parameters
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def square(side_length):
’’’
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’’’
turtle.forward(side_length)
turtle.right(90)
turtle.forward(side_length)
turtle.right(90)
turtle.forward(side_length)
turtle.right(90)
turtle.forward(side_length)
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return
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square(100) # This would give side_length the value of 100
print side_length # This will give an error because side_length
# only exists inside the function!
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COSC 2336 Data Structures
Objectives
• Practice writing functions
• Practice writing recursive functions.
• Learn about Analysis of algorithms and O(n log n) sorts
Description
In this assignment we will be implementing one of the most popular sorting
algorithms used in libraries (like the C++ STL library, and the UNIX qsort
function) to provide basic sorting abilities, the Quicksort algorithm. I would
recommend that you at least read section 7.5 from our supplemental Shaffer
textbook on Quicksort, if not sections 7.1-7.5 talking about three well known
O(n log n) sorting algorithms, and the 3 O(n2) algorithms we discussed last
week.
Quicksort, when properly implemented, is very attractive because it pro-
vides a way to do a fast sort completely in-place (without having to allocate
additional memory to do the sort, beyond a single value needed when swap-
ping two values in the list being sorted). In the worst case, Quicksort is
actually O(n2), no better than bubble sort. But this worse case only occurs
when every pivot selected is the wort possible, and does not divide the list
at all. This is very unlikely to happen, unless you know how the pivot is
selected, and specifically design the input list to always choose the worst
possible pivot. On average the cost of Quicksort is O(n log n), and it is
usually very likely that average case performance will result when lists to be
sorted are relatively random.
The most direct implementation of Quicksort is as a recursive algorithm.
Quicksort is an example of a divide and conquer approach to solving the
problem of sorting the list. We are given a list of items, A and indexes left
1
and right that indicate a sub-portion of the list to be sorted. left and right
indicate the actual indexes, so if the list is a regular C array of integers, and
the array is of size 10
int left;
int right;
const inst SIZE = 10;
int A[size];
Then to sort the whole list we set left = 0 and right = 9 to initially
call the Quicksort function:
left = 0;
right = size-1;
quicksort(A, left, right);
Conceptually the steps of the Quicksort algorithm are as follows:
1. if list size is 0 or 1 (left <= right) return (lists of this size are sorted
by definition).
2. Choose a pivot value and swap the pivot value to the end of the list
swap(pivotIndex, right)
3. Partition the list. Partitioning means all values less than the pivot
value should end up on the left of the list, and all values greater will
be on the right. The first index k where a value >= to the pivot value
is at indicates the new left and right side sub-lists.
4. Swap the pivot value to its correct position k swap(k, right)
5. Recursively call Quicksort on the new left and right sub-lists
• quicksort(A, left, k-1)
• quicksort(A, k+1, right)
Most of the real work happens in the function/code to partition the list.
The partitioning of the list, for Quicksort to be an in-place sort, must work
by swapping values in-place in the list o.
Assg 05 QuicksortCOSC 2336 Data StructuresObjectives.docx
Assg 05 QuicksortCOSC 2336 Data StructuresObjectives.docxfestockton Assg 05: Quicksort
COSC 2336 Data Structures
Objectives
• Practice writing functions
• Practice writing recursive functions.
• Learn about Analysis of algorithms and O(n log n) sorts
Description
In this assignment we will be implementing one of the most popular sorting
algorithms used in libraries (like the C++ STL library, and the UNIX qsort
function) to provide basic sorting abilities, the Quicksort algorithm. I would
recommend that you at least read section 7.5 from our supplemental Shaffer
textbook on Quicksort, if not sections 7.1-7.5 talking about three well known
O(n log n) sorting algorithms, and the 3 O(n2) algorithms we discussed last
week.
Quicksort, when properly implemented, is very attractive because it pro-
vides a way to do a fast sort completely in-place (without having to allocate
additional memory to do the sort, beyond a single value needed when swap-
ping two values in the list being sorted). In the worst case, Quicksort is
actually O(n2), no better than bubble sort. But this worse case only occurs
when every pivot selected is the wort possible, and does not divide the list
at all. This is very unlikely to happen, unless you know how the pivot is
selected, and specifically design the input list to always choose the worst
possible pivot. On average the cost of Quicksort is O(n log n), and it is
usually very likely that average case performance will result when lists to be
sorted are relatively random.
The most direct implementation of Quicksort is as a recursive algorithm.
Quicksort is an example of a divide and conquer approach to solving the
problem of sorting the list. We are given a list of items, A and indexes left
1
and right that indicate a sub-portion of the list to be sorted. left and right
indicate the actual indexes, so if the list is a regular C array of integers, and
the array is of size 10
int left;
int right;
const inst SIZE = 10;
int A[size];
Then to sort the whole list we set left = 0 and right = 9 to initially
call the Quicksort function:
left = 0;
right = size-1;
quicksort(A, left, right);
Conceptually the steps of the Quicksort algorithm are as follows:
1. if list size is 0 or 1 (left <= right) return (lists of this size are sorted
by definition).
2. Choose a pivot value and swap the pivot value to the end of the list
swap(pivotIndex, right)
3. Partition the list. Partitioning means all values less than the pivot
value should end up on the left of the list, and all values greater will
be on the right. The first index k where a value >= to the pivot value
is at indicates the new left and right side sub-lists.
4. Swap the pivot value to its correct position k swap(k, right)
5. Recursively call Quicksort on the new left and right sub-lists
• quicksort(A, left, k-1)
• quicksort(A, k+1, right)
Most of the real work happens in the function/code to partition the list.
The partitioning of the list, for Quicksort to be an in-place sort, must work
by swapping values in-place in the list o ...
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Python for loop
- 2. Quick revision What is a list? Difference between list and a variable Can list store data of multiple types? What is used to iterate over a list? How to calculate length of list? Are strings stored as lists in python?
- 3. What is for loop??? The for loop in Python is used to iterate over a sequence (list, tuple, string) or other iterable objects. Iterating over a sequence is called traversal.
- 4. 2 types of writing for loops 1.Getting each element of the sequence 2.Range (): By generating range of numbers and use these numbers as indexes to access sequences.
- 5. Lets dive in type 1 of for loop
- 6. Syntax of for loop
- 7. Example
- 8. Flowchart of for loop
- 10. Example 2:For loop to calculate sum of elements in a list
- 11. The break statement Exit the loop when x is "banana", but this time the break comes before the print:
- 12. Continue keyword With the continue statement we can stop the current iteration of the loop, and continue with the next:
- 13. Type 2 of for loop
- 14. The range() function We can generate a sequence of numbers using range() function. range(10) will generate numbers from 0 to 9 (10 numbers). We can also define the start, stop and step size as range(start,stop,step size). step size defaults to 1 if not provided. To force this function to output all the items, we can use the function list().
- 15. Example
- 16. Example to use range() in for loop
- 17. Syntax : range(start index, end index, step size)
- 18. Sample problems Print elements of a 1 dimensional list. Print elements of 2 dimensional list. Print even elements in a list.
- 19. This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 Unported License. It makes use of the works of Mateus Machado Luna.