Assigned Study Material

Outline

Part 1. Functions and the doc syntax
- Functions associated with python list
- Functions associated with python dictionary
Part 2. Logical operators
Part 3. More about loops
- Nested loops
- Break and continue loops
Part 4. JSON data format
Part 5. Comment your code

Part 1. Function and the doc syntax

Function is a block of code which runs when it is called.

You can think of the functions as “incantations” in the magic world. In the magical world, whenever you need to use a magic, you will use the “incantation” to make it happen. Similarly, in the programming world, whenever you need to let python does something for you, you call functions to make it happen. For example, we have seen how to use functions to let python import packages and modules, open files we wanted to process, print out information for inspection.

There are three types of functions in Python:

Built-in functions, such as help() to ask for help, min() to get the minimum value, print() to print an object to the terminal,… You can find an overview with more of these functions here.
User-Defined Functions (UDFs), which are functions that users create to help them out; And
Anonymous functions, which are also called lambda functions because they are not declared with the standard def keyword.

In this module, we will focus on built-in functions.

1.1. Functions associated with python list

In python, everything is an object. (For now, it is ok if you don’t understand the concept of object . Later in this semester, we will spend a whole week to learn about this concept.) Python list is an object, dictionary is another object. For functions associated with an object, we call them via the doc syntax.

Let's take python list as an example and take a closer look. As we have learned, list can contain certain values we assigned to it. In addition, a list object also has functions associate with it. We can call the functions via the doc-syntax to interact with data in the list.

Let's say I have a list contain ten different names.

In[1]:

boys = ['James','Kelly','Andy','Nick','Mike','Eric','Bob','Chris','Danny','Frank']

If I wanted to sort the names alphabetically, I can use the .sort() function associate with the list to do so.

In[2]:

boys.sort()

Out[2]:

boys = ['Andy','Bob','Chris','Danny','Eric','Frank','James','Kelly','Mike','Nick']

In some cases, we may wanted to know the specific position of a value. For instance, in the sorted list, where is the name "Frank" positioned at? The .index() function associated with list object can be useful to solve this.

In[3]:

boys.index('Frank')

Out[3]:

One thing we need to always be careful about is that python starts indexing from zero. In the above example, if you count the number of people from the beginning of the list until "Frank", the intuitive answer is 6. However, when python count the numbers, it starts from zero. i.e., Andy--0, Bob--1, Chris--2, and so on.

Sometimes we need to "pick" and then removes the element at the specific position using index. Think of the name list as a customers' order list in a fast food restaurant. As the programmer, I wanted to "pick" the customer on the top of the list, complete the order, and remove his name from the list. the .pop() function is an effective way to help us complete this task:

In[4]:

print(boys)
now_serving = boys.pop(0)
print(now_serving)
print(boys)

Out[4]:

['Andy','Bob','Chris','Danny','Eric','Frank','James','Kelly','Mike','Nick']
Andy
['Bob','Chris','Danny','Eric','Frank','James','Kelly','Mike','Nick']

In the above example, the .pop() function picked the name at position 0 (which is Andy) out of the list, assigned it to a new variable now_serving, and then removed it from the original list.

Suppose another customer is coming in, we wanted to add a new name to the existing list, we can use the .append() function.Suppose the new customer's name is "Peter" , to add him into the list, we can do:

In[5]:

print(boys)
boys.append('Peter')
print(boys)

Out[5]:

['Bob','Chris','Danny','Eric','Frank','James','Kelly','Mike','Nick']
['Bob','Chris','Danny','Eric','Frank','James','Kelly','Mike','Nick','Peter']

Sometimes we wanted to create a copy of the existing list to play with. The .copy() function associate with list object can help us do this.

In[4]:

new_list = boys.copy()
print (new_list)

Out[4]:

 ['Andy','Bob','Chris','Danny','Eric','Frank','James','Kelly','Mike','Nick']

If you have some previous programming experience before, you may wonder if the .copy() function is really necessary. Why don't just do this by assigning values? This is a potential issue that can cause programming mistakes. Let's look at the following example:

In[5]:

boys1 =  ['Andy','Bob','Chris','Danny','Eric','Frank','James','Kelly','Mike','Nick']
boys2 = boys1
boys1.remove('Andy')
print(boys1)
print(boys2)

Out[5]:

 ['Bob','Chris','Danny','Eric','Frank','James','Kelly','Mike','Nick']
 ['Bob','Chris','Danny','Eric','Frank','James','Kelly','Mike','Nick']

This is what just happened: although the two list boys1 and boys2 are different in names, but they bot point to the same, identical list (i.e., the list with 10 names). As soon as you remove a name using boys1.remove('Andy') , this command will change the content in both names of the list. If you only wanted to change one list, and keep they other unchanged, do the following:

In[6]:

boys1 =  ['Andy','Bob','Chris','Danny','Eric','Frank','James','Kelly','Mike','Nick']
boys2 = boys1.copy()
boys1.remove('Andy')
print(boys1)
print(boys2)

Out[6]:

 ['Bob','Chris','Danny','Eric','Frank','James','Kelly','Mike','Nick']
 ['Andy','Bob','Chris','Danny','Eric','Frank','James','Kelly','Mike','Nick']

Above are some examples of list methods. To see all the functions (and examples) associated with python list, please go to this website.

1.2. Functions associated with python dictionary

Similar to list, a dictionary object also has functions associate with it. Let's look at some examples.

There are several ways to create a dictionary, but the most straightforward way is to explicitly define the key:value pairs.

In[1]:

mycar = {
    "brand":"Subaru",
    "model":"Forester",
    "year":2005,
    "color":"green"
}
print(mycar)

Out[1]:

{'brand': 'Subaru', 'model': 'Forester', 'year': 2005, 'color': 'green'}

To access items in a dictionary, you can refer to its key name, inside square brackets:

In[2]:

x = mycar['color']
print(x)

Out[2]:

green

Alternatively, you can also call the .get() function to access the item in the dictionary:

In[3]:

x = mycar.get("color")
print(x)

Out[3]:

green

We can loop through a dictionary by using a for loop. When looping through a dictionary, the return value are the keys of the dictionary. But we can certainly figure out ways to return the values as well: the .values() function will return values of a dictionary.

In[3]:

for x in mycar:
    print(x)

Out[3]:

brand
model
year
color

In[4]:

for x in mycar.values():
    print(x)

Out[4]:

Subaru
Forester
2005
green

We can also loop through both keys and values by using the .items() function.

In[5]:

for x, y in mycar.items():
    print(x, y)

Out[5]:

brand Subaru
model Forester
year 2005
color green

To add an item to the dictionary, we can create a new index key and assigning a value to it:

In[6]:

mycar['miles'] = 72000
print(mycar)

Out[6]:

{'brand': 'Subaru', 'model': 'Forester', 'year': 2005, 'color': 'green', 'miles': 72000}

Alternatively, we can also call the .update() function associated with dictionary object to insert the specific items.

In[7]:

mycar.update({'register':'Connecticut'})
print(mycar)

Out[7]:

{'brand': 'Subaru', 'model': 'Forester', 'year': 2005, 'color': 'green', 'miles': 72000, 'register': 'Connecticut'}

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Part 2. Logic Operators

As we have learned, conditions are nice way to make decisions by asking if something equals True or False. Sometimes, we may want to test several different conditions or even combine the conditions together to make a decision. Logical operators are used to combine conditional statements.

There are three commonly used logical operators, and, or, not. Let’s look at each of them.

When use and, it returns True if both statements are true

In[1]:

x = 5
(x > 3 and x < 10)
# the above two lines will returns True, because BOTH conditions are True.

Out[1]:

True

When use or, it returns true if one of the statements is true.

In[2]:

x = 5
(x > 3 or x < 4)
# the above two lines will returns True, 
# because one of the conditions (x > 3) is True

Out[2]:

True

The not operator has two common use cases:

Case 1. it reverse the result. i.e., it returns False if the result is True

In[3]:

x = 5
not (x > 3 and x < 10)
# returns False, because it reverse the result inside the parentheses.

Out[3]:

False

Case 2. it can be used to check if a data structure (i.e., list, dictionary, set, tuple) is empty. If the data structure is empty, it returns true, otherwise it returns False.

In[4]:

empty_list = [ ]
not empty_list
# returns True, because there is no element inside the empty_list

Out[4]:

True

In[5]:

list1 = [1,2,3]
not list1
# returns False, because list1 has elements in it, it is not empty.

Out[5]:

False

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Part 3. More about loops

In the previous week, we studied how to use loops to perform iterations in Python. In this section, we extend the discussion to nested loops (i.e., loops inside loops). We will learn about how to use the break and continue statements to control the loops behavior. The ultimatum goal is to master the magic of nested loops and use them to complete conditional, repeated tasks.

3.1. Nested loops

Let's take while loop as an example and look at the following code:

In[1]:

i, j = 1, 5
while i < 4:
    while j < 8:
        print("now running the inner loop")
        print(i, ",", j)
        j = j + 1   
    print("now running the outer loop") 
    print(i, ",", j)
    i = i+1

Out[1]:

    now running the inner loop
    1 , 5
    now running the inner loop
    1 , 6
    now running the inner loop
    1 , 7
    now running the outer loop
    1 , 8
    now running the outer loop
    2 , 8
    now running the outer loop
    3 , 8

In the above example, we see two while-loops nested together. The "outer loop" check the condition i<4 before every iteration, the "inner loop" check the condition j<8 before every iteration. When we run the block of code, here is what happened:

We first assign two variable i=1 and j=5;
Then python will start with check if i<4 (i.e., the outer loop condition) is True,
- when i<4 is True, python will move forward to the inner loop, and check if the condition j<8 is True;
  - when j<8 is True, python will then execute the command inside the inner loop.
  - After the first iteration, we will have i=1, j=6
  - then python will go back to the top of the inner loop, and check the condition j<8 again.
  - the inner iteration will keep running until j<8 become False
- When the condition j<8 become False, python will jump out of the outer loop, and execute the commands below the inner loop.
- When it reaches the bottom of the code, python will go back to the top of the outer loop, check the condition i<4 again, and determine if to start the next iteration.
The whole process ends when the condition i<4 become False.

1.2. Break and Continue

When we use loops to perform iteration, another useful skill is to stop the iteration when certain condition is met. Typically there are two ways to stop a running loop: the break statement and continue statement.

The break statement is used to terminate the current iteration and exist the loop immediately. If the break statement is inside a nested loop, the break statement will terminate the innermost loop. Let's look at an example:

In[1]:

name_list = ['Mary','Diana','Dorothy','Jessica','Esther','Valerie',
'Brenda','Alfreda','Martha','Cari']
while name_list:    #This is a pythonic way to say "while name_list is not empty"
    name = name_list.pop(0)
    if name !='Dorothy':   
        print("current name is %s." %(name))
    else:
        print("Break the loop when see the name Dorothy")
        break  # terminate the loop
print(name_list)  #Let's see who are still in the name list

In this example, we first create a name_list with 10 names in it. Then we use a while loop to pop the names and print them out one by one. During the iterations, we want python to stop the loop whenever the name "Dorothy" appears. Below is the output when running the above bock of code.

Out[1]:

current name is Mary.
current name is Diana.
Break the loop when see the name Dorothy.
['Jessica', 'Esther', 'Valerie', 'Brenda', 'Alfreda', 'Martha', 'Cari']

The continue statement are similar to the break statement. The continue statement is used to skip the rest of the code inside a loop ONLY for the current iteration. It will not terminate the loop, but continues on with the next iteration. Still using the above example:

In[1]:

name_list = ['Mary','Diana','Dorothy','Jessica','Esther','Valerie',
'Brenda','Alfreda','Martha','Cari']
while name_list:    #This is a pythonic way to say "while name_list is not empty"
    name = name_list.pop(0)
    if name !='Dorothy':   
        print("current name is %s." %(name))
    else:
        print("skip one")
        continue. # continue on to the next iteration
print(name_list)  #Let's see who are still in the name list

Out[1]:

current name is Mary.
current name is Diana.
skip one
current name is Jessica.
current name is Esther.
current name is Valerie.
current name is Brenda.
current name is Alfreda.
current name is Martha.
current name is Cari.
[]

As the result, the continue statement only skipped the name "Dorothy", and then continued on to the next iteration. Below are the flowchart of break statement and continue statement in python.

The Break Statement	The Continue Statement

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Part 4. JSON data format

In brief, JSON (JavaScript Object Notation) is one of the most popular ways for data storage and exchange, which is accomplished through its syntax, and is used in many web applications. It can be easily used to store and communicate information to other products. Many programming languages, including python, support the JSON data format.

In python, there is a built-in package ‘json’ that can be used to read json file and convert a JSON string into a python object. Since JSON file store information based on key:value pairs, which is very similar to python dictionary It is the most convenient to convert JSON file to python dictionary. Here is an example.

In our weekly project, you will need to import a json file I provided and then start play with it. Here is how it works:

In[1]:

import json
# import the datasets
with open('project2_data.json') as f:
    preference = json.load(f)

The above block of code will load the 'project2_data.josn' file I provided, and store it in a python dictionary named as 'preference'. ==========================================================================================================

Part 5. Comment your code

When writing your code in python, it’s important to make sure that your code can be easily understood by others and by yourself. Giving variables obvious names, defining explicit functions, and organizing your code are all great ways to do this. Another awesome and easy way to increase the readability of your code is by using comments. In addition, comments can also be used to prevent execution when testing the code.

Programmers forget what their own code does all the time, especially if the code was written a long time ago or under pressure. Writing comments as you go is a great way to keep your memory fresh. It will also push yourself to think about if your code make sense and keep improve it. Using proper comments throughout your code can also help others understand how it all works very quickly. This is very important when collaborating with others.

When you need to make a comment, simply put a hash mark # before the line you wanted to comment. Let’s look at this example:

In[1]:

# this line is a comment, python won't run it.
print('this sentence will be printed out in you terminal.')  #you can insert comments anywhere
# python ignores everything AFTER the hash mark and UP TO the end of the line.
# If you wanted to write a long comment that may take more than one line,
# just put a hash mark on each subsequent line.
print('Good luck with the weekly project.')
# now I think you got the idea. let's run this block of code and see what will happen.

Out[1]:

this sentence will be printed out in your terminal.
Good luck with the weekly project.

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